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ANALYSIS OF INNOVATION DRIVERS AND BARRIERS IN SUPPORT OF BETTER POLICIES

Economic and Market Intelligence on Innovation

Social attitudes to innovation and entrepreneurship

Prepared for:

European Commission Directorate-General Enterprise Unit D1 Innovation Policy Development

Prepared by:

UNU-MERIT

Maastricht, 26 March 2012

Project consortium

• Austrian Institute of Economic Research, WIFO, Vienna (coordination).

• Fraunhofer Institut für System- und Innovationsforschung, ISI, Karlsruhe.

• Greenovate! Europe, Brussels.

• NIFU Step, Oslo.

• UNU-Merit, Maastricht.

• MCI Innsbruck, Innsbruck (subcontractor).

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Authors (in alphabetical order by institute)

Bianca Buligescu (UNU-MERIT)

Hugo Hollanders (UNU-MERIT)

Tina Saebi (UNU-MERIT)

Referees for this report

Tore Sandven (NIFU-STEP)

Brian MacAulay (Innovative Futures Research)

Note: The referees have provided highly valuable comments that have led to a substantial improvement of this report. The authors are responsible for any remaining mistakes.

Acknowledgements

The authors want to thank referees Tore Sandven and Brian MacAulay for extremely helpful comments. We also thank the participants at the expert meeting in Brussels 19 January 2012 for their comments on an earlier draft of the report. Their comments, as well as the discussions, guided us in writing a better report about the important topic of social attitudes to innovation and entrepreneurship. We wish to thank Nordine Es-Sadki for research assistance. We also thank the European Commission for making this project possible financially.

Suggested citation

Buligescu, B., Hollanders, H. and Saebi, T. (2012), “Social attitudes to innovation and entrepreneurship”. PRO INNO Europe: INNO Grips II report, Brussels: European Commission, DG Enterprise and Industry.

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Foreword "INNO-Grips" (short for "Global Review of Innovation Policy Studies") is supporting policy makers in adopting appropriate policy responses to emerging innovation needs, trends and phenomena. It analyses framework conditions, barriers and drivers to innovation and innovation policy and offers intelligence on international developments in these fields.

Over a period of three years (2010-2012) INNO-Grips will conduct studies and organise workshops to exchange views, ideas and best practices with innovation stakeholders in order to optimise innovation policy Europe-wide. These key activities will be complemented by a news service about international innovation policy developments, covering about 40 countries worldwide, and further dissemination activities such as newsletters. Target audiences are invited to discuss the results of studies and related issues in an interactive online environment (the INNO-Grips blog). INNO-Grips is thus a platform for all stakeholders involved in the practice of innovation and in innovation policy, in particular innovation policy makers at the EU, national and regional levels; innovation intermediaries such as innovation agencies and knowledge transfer centres; innovation practitioners and academia conducting research on innovation dynamics.

Technically, INNO-Grips consists of two lots. The first one –"Innovation policy research and intelligence"– gathers evidence on innovation policy developments worldwide and analyses specific aspects and trends in detail. The second lot –"Economic and market intelligence on innovation"– analyses framework conditions (e.g. implications of socio-economic trends), barriers and drivers to innovation at firm level. This report is the first in a series of six studies in the context of the second lot which will investigate the following topics:1

1. Barriers to internationalisation and growth of EU’s innovative companies

2. Socio-economic trends for innovation policy

3. Open innovation and other new forms of collaboration

4. Social attitudes to innovation and entrepreneurship

5. The role of multinational companies and supply chains in innovation

6. The new nature of innovation

These studies will be delivered in close coordination with the representatives of the European Commission and in close interaction with the service providers of the other PRO INNO Europe activities. All studies are of high relevance to the activities set in the context of the Flagship Initiative “Innovation Union” carried out as part of the new Strategy Europe 2020.

WIFO is the lead partner of the "Economic and market intelligence on innovation" studies and is also responsible for the coordination of activities with the European Commission. The partner institutions in this project are NIFU-Step based in Oslo, UNU-Merit based in Maastricht, the

1 See http://www.proinno-europe.eu/inno-grips-ii/page/studies for more details.

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Fraunhofer Institute for Systems and Innovation Research (ISI) based in Karlsruhe, and the Management Center Innsbruck. Greenovate! Europe will support all dissemination activities. Each study will be presented and discussed at workshops organised by the Consortium in close cooperation with the European Commission. The workshops will serve to present the findings and conclusions as well as the derived policy recommendations to a qualified audience of stakeholders, representatives of the business community, policy makers, and leading academics for external validation.

The present report focuses on the “Social attitudes to innovation and entrepreneurship”. The terms of reference established that this study shall cover at least the following topics:

• Identify the effect of social attitudes to entrepreneurship and demand for innovative products on innovation outcomes in Europe and in other major economies, including (depending on data availability) the United States, Japan, Canada, Australia, India, China, and Brazil.

• Identify and recommend public innovation policies to foster more entrepreneurship and demand for innovation within Europe.

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Executive summary Europe is faced with many challenges: global competition is increasing, Europe’s population is ageing and governments are facing increasing budgetary constraints. Europe’s 2020 strategy has emphasized the role of innovation for improving our competitiveness, standard of living and well-being. But innovation is not something which should be taken for granted; Europe not only needs to invest more resources to improve its innovativeness but it should also improve the framework conditions for innovation. The 2006 Aho report2 recommended “the need for Europe to provide an innovation friendly market for its businesses”. Rather than stressing innovation inputs such as R&D, the Aho Report stresses innovation demand and the myriad of socio-cultural factors that encourage innovation, such as entrepreneurship, risk taking, flexibility and adaptability, and mobility. These socio-cultural factors can be linked to differences between countries’ social attitudes to entrepreneurship and the demand for innovative products and services on and entrepreneurship. A better understanding of the differences in these social attitudes to innovation and entrepreneurship will guide better policy making.

Social attitudes to demand for innovation

There are four types of demand for innovation: there is a demand from consumers, businesses and governments for business innovation and there is a customer demand for government innovation. The most important challenge on the demand side for innovation is the adoption and diffusion of innovation by consumers (OECD, 2011) with the success of a new product or service depending on consumer acceptance. Consumer attitudes to innovative products and services explain differences in consumer acceptance between countries.

Social attitudes towards innovation are defined as consumers’ receptiveness to try and adopt innovative products and services. Results from the Innobarometer 2005 report show that consumers’ receptiveness for innovative products and services range from a ‘pro-innovation’ attitude (with 11% of Europeans enthusiastically accepting or promoting an innovation) to an ‘anti-innovation’ attitude (with 16% of Europeans resisting or even rejecting an innovation).

Differences in consumers’ attractiveness can be explained by differences in national cultural dimensions as identified by Hofstede (1980, 1991). Power distance measures the degree of social inequality accepted by a society. Individualism reflects the degree to which a society’s members identify themselves as individuals (as “I”) or as members of a group (as “we”). Masculinity is a measure of the degree to which a society is characterized by masculine features which are associated with assertiveness, authority, performance and success. Uncertainty avoidance reflects the degree to which a society tries to avoid uncertain or risky situation. Our results show that consumers in high power cultures and individualistic societies share a more positive attitude

2 http://ec.europa.eu/invest-in-research/action/2006_ahogroup_en.htm

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towards innovative products and services where consumers in masculine societies and societies with high risk avoidance share a more negative attitude towards innovative products and services.

Besides differences in these cultural values, our results also show that education, age, gender and living environment are powerful predictors of attractiveness to innovation. People with more years of education, people of younger age, people living in urban areas and men (as compared to women) feel, on average, more attracted to innovations.

Consumer resistance

Companies experience high rates of innovation failures (Moore, 2001) due to low consumer demand for innovative products and services. Besides social attitudes, also differences in consumer resistance to innovation contribute to an unfavourable demand. Consumer resistance is not simply the observe of adoption, in fact, there are three types of consumer resistance: (1) ‘postponement’, where consumers decide to adopt an innovation at a later point in time until circumstances are more suitable; (2) ‘rejection’ involving an active evaluation on the part of the consumer resulting in a strong reluctance to adopt the innovation; and (3) ‘opposition’ where consumers are convinced that the innovation is not suitable and they may even actively engage in public protests to prevent the launch of the innovation.

Risk plays an important role in explaining consumer resistance. Risk reduction strategies are crucial in diminishing consumer resistance towards innovation. While strategies to increase innovation adoption usually emphasize the benefits of the innovation, a strategy to reduce risk perception should not rely on emphasizing additional product benefits. The concerns and worries of consumers need to be taken seriously and be addressed appropriately. Given that different drivers have different effects on the resistance types, companies and policy makers need to develop specific strategies to deal with each type of consumer resistance.

Entrepreneurship

Entrepreneurship is an important driver of economic growth and innovation. There are significant differences between countries’ rates of entrepreneurship. Self-employment is high in countries like Greece, Italy and Turkey and low in e.g. Denmark and Norway. In all European countries more than half of those being self-employed do not employ others with an average share of 70% in the EU27. There are also significant differences in preferences to be self-employed with less than half of the EU27 population wanting to be self-employed as compared to more than 60% in the US.

The rate of entrepreneurship also differs significantly when it measured by the share of nascent entrepreneurs involved in setting up a new business activity or company and current company owners. Using data from the Global Entrepreneurship Monitor (GEM) the rate of entrepreneurship in Europe is lower as compared to Brazil, China, India, South Korea and the US. The US rate of entrepreneurship is also higher as that in Europe using data from the Eurobarometer Entrepreneurship Survey (ESS). Within Europe the highest rate of entrepreneurship are observed in Cyprus, Greece and Iceland.

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Social attitudes to entrepreneurship

Entrepreneurship involves individual attitudes to risk, opportunities that reduce risk, receptiveness to new ideas, access to sources of new ideas with commercial potential, and access to capital. There are different strands of research in entrepreneurship across disciplines. In psychology research there is a shift away from research on “traits” and personality towards behaviour and cognitive issues. In economics there has been a shift towards entrepreneurial choice models and individuals as agents of change. Sociology on the other hand emphasizes the role of the environment and environmental factors that affect firm formation.

An increasing number of scientists argue that entrepreneurial variations are best understood by considering the social environment in which the firm is created as entrepreneurship is essentially a social phenomenon which has a social and cultural dimension. The literature on social and cultural factors has expanded with Hofstede’s (1980) work on cultural values dimensions. In general researchers have hypothesised that entrepreneurship is facilitated by cultures that are high in individualism or masculinity or low in uncertainty avoidance or power distance.

This report has used scattered information from both the Global Entrepreneurship Monitor and Eurobarometer Entrepreneurship Survey to show differences in social attitudes to entrepreneurship. Starting a new business is seen as societal desirable career choice in many non-European countries. In the EU27 almost 60% of the people consider becoming an entrepreneur a desirable career choice as compared to about 58% in the US. Being successful at starting a new business receives a high level of status and respect from about two-thirds of European citizens, in particular from people in Ireland and Finland. Europeans also have more respect for successful entrepreneurs as Japanese, Russians or US citizens. There is less media attention to successful entrepreneurs in Europe than in non-European countries, in particular in Denmark, Hungary and Poland, reflecting a lesser preferential societal attitude to entrepreneurship in most European countries. Almost two-thirds of Europeans prefer to live in a country where there is an equal income distribution whereas more than half of the population prefer an unequal income distribution in among others Japan and the US. As entrepreneurship is associated with higher income and income differences the preference in Europe for more equal income distributions can be seen to reflect a lower positive societal attitude to entrepreneurship. Countries with more positive social attitudes to entrepreneurship also have higher rates entrepreneurship.

Improved monitoring in surveys

To some extent differences in entrepreneurship can be explained by differences in personal attitudes like risk taking, but also in differences in countries’ educational attainment levels, their industrial composition and institutional differences in setting up a new business or expanding an existing company. These and other explanatory factors have been studied in detail by scholars, using among others data from Global Entrepreneurship Monitor (GEM) and Eurobarometer Entrepreneurship Survey (EES). Studies trying to understand the role of social attitudes are less frequent as surveys as GEM and EES only include a few questions which could be interpreted as reflecting social attitudes to entrepreneurship.

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GEM includes four such questions and the strength of the GEM survey is that these questions have been asked in most survey rounds making it possible to compare results over time. EES also includes questions which can be interpreted as social attitudes. Unfortunately such questions have only been asked in the 2 most recent EES surveys. It is strongly recommended to include these questions in future versions of EES which, as GEM, should become available more regularly then once every 3 years (as has been the case for the latest 3 EES surveys).

EES also lacks reliable data on education and does not have any indication of personal or household income, or prior occupation and employment status. EES asks respondents for their age when they stopped full-time education. Problem with the EES question is that it does not give any information on respondents’ educational attainment and it cannot be linked to the International Standard Classification of Education (ISCED) which distinguishes between several defined levels of education. Better proxies for educational attainment could be calculated if EES would directly ask respondents for the highest level of education for which they graduated.

A limitation of the results based on the Innobarometer 2005 for measuring attitudes to innovative products and services is that a very powerful variable as income is also not available. Persons with a higher disposable income are more likely to be attracted to innovations as they can afford these more expensive products. It is recommended to include a question on personal or household income in any future survey aiming to better understand peoples’ attractiveness to innovations. It is also strongly recommended to repeat the Innobarometer survey as results based on 2005 data become outdated as peoples’ attitudes, income and educational attainment change over time, and perhaps even more so during the current financial and economic crisis. The Innobarometer 2005 set of questions on peoples’ attitudes to innovations could easily be included in the EES (on an annual basis). It is also recommended to include non-European countries as the United States, Japan, China and India, to enable comparisons with major competitors and emerging countries outside of Europe.

Policies

Over the past century, the theoretical framework to understand the innovation process and the design of innovation policies has been predominantly influenced by technology-push innovation theories. Supply-push policies generally use public investment through grants and subsidies to stimulate innovation in the EU and its Member States. Examples of supply-push policies include government-sponsored R&D, tax credits for firms to invest in R&D and support for education and training. A demand-pull perspective acknowledges the importance of producing innovations but at the same time emphasizes the need for market opportunity. Demand-side policies aim to boost demand and encourage suppliers to meet the expressed needs of consumers. Examples of demand-side policies include tax credits and rebates for consumers of new technologies, technology-oriented government procurement, technology mandates, and innovation-specific regulations and standards (Cunningham, 2009).

Demand subsidies can persuade consumers to buy innovative products by lowering the cost price. Subsidies on energy-saving products (e.g. insulation used in the construction of new houses) can trigger consumers to buy such products and thereby increasing the market potential for firms supplying such products. Subsidising innovative products (or technologies) should not be done on

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an ad-hoc and discontinuous basis but should be repeated for a longer period time as this will increase the possibility that consumers also become more aware of the positive product characteristics (e.g. ‘good for the environment’) and will thus be more willing to buy such products in the long-run even if the subsidies diminish or disappear. Unawareness with new innovative products will deter consumers from buying these products. Awareness building measures should reduce such unawareness by emphasising the benefits of innovations. The introduction of labels will also contribute to reducing unawareness as consumers will perceive these as guarantees of quality and potential use.

Adopting innovations often requires changes in consumers’ existing habits and to develop new ones. Innovation resistance appears therefore as a normal consumer response. Risk reduction strategies are crucial in diminishing consumer resistance towards innovation. While strategies to increase innovation adoption usually emphasize the benefits of the innovation, a strategy to reduce risk perception cannot rely on emphasizing additional product benefits. The concerns and worries of consumers need to be taken seriously and thus be addressed appropriately. Policies should emphasize that the innovation fits within the consumer’s current lifestyle. Testing of innovations by independent institutes is an effective strategy to reduce the perception of risks and overcome opposition (Yeung and Morris, 2001).

Social attitudes to entrepreneurship by shaping personal attitudes become important in understanding and explaining differences in entrepreneurship. In countries with a more favourable attitude to entrepreneurs we observe a higher rate of entrepreneurship and also positive media attention attributes to more entrepreneurship. Networks are also important: knowing other entrepreneurs has a positive impact on becoming an entrepreneur oneself. Education also matters, as education can provide the knowledge and skills required to start a business. But also previous entrepreneurial experience, even involving failed attempts trying to start a business, will have a positive impact on entrepreneurship.

Entrepreneurs are shaped by their family environment, by the knowledge, skills and attitudes gathered during their formal education, from their working experience, from their interactions with others in social groups and from their exposure to the media. Policy interventions in any of these will have a two-stage effect. The first is a direct effect, e.g. educational policies introducing entrepreneurship classes in schools, in which the individual’s attitudes are likely to be changed in the short-run. The second is an indirect effect in which the changes in the individual’s attitudes will shape social attitudes in the longer run thereby having a positive impact on the attitudes of future individuals. Policies will have no direct effect on family environment but the latter can be changed in the future as many young entrepreneurs will be parents in the near future. For governments educational policies and the role of mass media are of particular interest.

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Table of contents Foreword........................................................................................................................................... 3

Executive summary........................................................................................................................... 5

Table of contents ............................................................................................................................ 10

1 Introduction ................................................................................................................ 14

1.1 Demand and entrepreneurship as drivers of innovation ............................................ 14

1.2 Social attitudes to demand and entrepreneurship...................................................... 15

1.3 Structure of the report ................................................................................................ 17

2 Attitudes and consumer demand for innovation......................................................... 19

2.1 Introduction ................................................................................................................ 19

2.2 Factors influencing consumers’ attitudes and adoption of innovation........................ 20

2.2.1 Social influence on innovation adoption..................................................................... 21

2.2.2 The influence of personal innovativeness on innovation adoption............................. 23

2.2.3 Demographics and personal innovativeness ............................................................. 24

2.2.4 The influence of national culture on innovation adoption ........................................... 27

2.2.5 The conceptual model................................................................................................ 31

2.3 Methodology............................................................................................................... 33

2.3.1 Motivation................................................................................................................... 33

2.3.2 Use of data sources and indicators............................................................................ 33

2.3.3 Description of sample and variables .......................................................................... 36

2.3.4 Analytical techniques ................................................................................................. 39

2.4 Analysis and results ................................................................................................... 39

2.5 Attitudes to demand: conclusions and limitations ...................................................... 42

3 Consumer resistance ................................................................................................. 43

3.1 Introduction ................................................................................................................ 43

3.2 Drivers of consumer resistance.................................................................................. 43

3.3 Types of consumer resistance ................................................................................... 45

3.3.1 The resistance hierarchy............................................................................................ 45

3.3.2 Innovation resistance by mature versus younger consumers .................................... 47

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3.3.3 Innovation resistance among European citizens........................................................ 49

3.4 Consumer resistance: conclusions and implications.................................................. 50

4 Attitudes to entrepreneurship ..................................................................................... 52

4.1 The importance of entrepreneurship .......................................................................... 52

4.2 Factors influencing entrepreneurship and innovation ................................................ 57

4.3 Defining entrepreneurship.......................................................................................... 62

4.3.1 Entrepreneurship definitions in scientific literature..................................................... 62

4.3.2 Self-employment as a measure of entrepreneurship ................................................. 65

4.4.3 Preferences to being self-employment....................................................................... 69

4.4.4 Rate of entrepreneurship ........................................................................................... 71

4.4.5 Innovative entrepreneurs ........................................................................................... 74

4.4 Attitudes and entrepreneurship .................................................................................. 76

4.4.1 Introduction ................................................................................................................ 76

4.4.2 (Social) attitudes to entrepreneurship ........................................................................ 78

4.5 The conceptual model and methodology ................................................................... 85

4.6 Econometric results.................................................................................................... 91

4.7 Discussion and recommendations ............................................................................. 98

5 Conclusions and recommendations ......................................................................... 102

5.1 Summary.................................................................................................................. 102

5.2 Recommendations for improved monitoring in surveys ........................................... 105

5.3 Policy discussion...................................................................................................... 107

6 References............................................................................................................... 113

Annex 1: Innobarometer 2005 questions on being attracted to innovation ............................... 120

Annex 2: Differences in attitudes between (non) (innovative) entrepreneurs ........................... 121

Annex 3: A scoreboard of attitudes to innovation and entrepreneurship .................................. 125

Annex 4: A comparison of the Eurobarometer entrepreneurship questionnaires ..................... 173

Annex 5: Country abbreviations................................................................................................ 176

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List of Figures Figure 2-1: The role of social influence on attitudes towards innovation use.................................................. 23 Figure 2-2: The role of personal innovativeness on attitude towards innovation use ..................................... 24 Figure 2-3: Cultural values – degree of power distance.................................................................................. 28 Figure 2-4: Cultural values – degree of individualism ..................................................................................... 29 Figure 2-5: Cultural values – degree of masculinity ........................................................................................ 30 Figure 2-6: Cultural values – degree of uncertainty avoidance....................................................................... 31 Figure 2-7: Conceptual model on consumer attitudes..................................................................................... 32 Figure 2-8: Cultural values and attitude to innovation ..................................................................................... 35 Figure 3-1: The resistance hierarchy............................................................................................................... 46 Figure 3-2: Index of optimism about six technologies ..................................................................................... 49 Figure 4-1: Business ownership rates 1972-2009........................................................................................... 56 Figure 4-2: Self-employment types.................................................................................................................. 66 Figure 4-3: Self-employment types by employees .......................................................................................... 67 Figure 4-4: Entrepreneurship as a dynamic measure ..................................................................................... 68 Figure 4-5: Self-employment dynamics based on Eurobarometer 2004-2009................................................ 69 Figure 4-6: Preference for being self-employed .............................................................................................. 70 Figure 4-7: Rate of self-employment with and without employees.................................................................. 70 Figure 4-8: Preference for being self-employed .............................................................................................. 71 Figure 4-9: Rate of entrepreneurship (GEM)................................................................................................... 72 Figure 4-10: Rate of entrepreneurship (EES).................................................................................................. 73 Figure 4-11: Entrepreneurship out of opportunity or necessity ....................................................................... 73 Figure 4-12: Share of innovative companies................................................................................................... 74 Figure 4-13: Rate of innovative entrepreneurship (GEM) ............................................................................... 75 Figure 4-14: Social attitudes to and entrepreneurship (GEM)......................................................................... 81 Figure 4-15: Attitudes for different types of entrepreneurs.............................................................................. 83 Figure 4-16: Conceptual model ....................................................................................................................... 86 Figure 4-17: Entrepreneurial attitudes............................................................................................................. 94 Figure 4-18: Risk attitudes............................................................................................................................... 94 Figure 4-17: Factor scores of the quality of institutions................................................................................... 95 Figure A3-1: Composite indicator for attitudes to demand for innovation ..................................................... 126 Figure A3-2: Composite indicator for attitudes to entrepreneurship.............................................................. 126

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List of Tables Table 2-1: Consumer attitudes towards innovation across Europe................................................................. 26 Table 2-2: Cross tabulations............................................................................................................................ 37 Table 2-3: Descriptive statistics....................................................................................................................... 38 Table 2-4: Cross tabulations............................................................................................................................ 39 Table 2-5: Regression results, binary logistics................................................................................................ 40 Table 4-1: Competing interpretations of the term entrepreneur ...................................................................... 64 Table 4-2: Attitudes to entrepreneurship (GEM) ............................................................................................. 79 Table 4-3: Correlations between social attitudes to and entrepreneurship ..................................................... 82 Table 4-4: Correlations between social attitudes to and innovative entrepreneurship.................................... 82 Table 4-5: Attitudes to entrepreneurship ......................................................................................................... 84 Table 4-6: Operationalization of control........................................................................................................... 87 Table 4-7: Characteristics of non-entrepreneurs and entrepreneurs .............................................................. 90 Table 4-8: Capturing social attitudes by country dummies.............................................................................. 92 Table 4-9: Entrepreneurship............................................................................................................................ 95 Table 4-10: Entrepreneurship due to opportunity............................................................................................ 96 Table 4-11: Entrepreneurship due to necessity............................................................................................... 97 Table 4-12: Entrepreneurship due to opportunity and necessity..................................................................... 97 Table 4-13: ISCED defined levels of education............................................................................................... 99 Table 4-14: EES years of education by age.................................................................................................. 101 Table 5-1: Demand-oriented support measures............................................................................................ 109 Table A3-1: Innovation performance and attitudes to innovation and entrepreneurship .............................. 125 Table A3-2: Social attitudes and demand for innovation (Scoreboard data)................................................. 127 Table A3-3: Social attitudes and entrepreneurship (Scoreboard data) ......................................................... 129

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1 Introduction 1.1 Demand and entrepreneurship as drivers of innovation Europe is faced with many challenges: global competition is increasing, Europe’s population is ageing and governments are facing increasing budgetary constraints. Europe’s 2020 strategy has emphasized the role of innovation for improving our competitiveness, standard of living and well-being. But innovation is not something which should be taken for granted; Europe not only needs to invest more resources to improve its innovativeness but it should also improve the framework conditions for innovation. The 2006 Aho report summarizing the results of an expert group on how to reinforce European research and innovation performance recommended “the need for Europe to provide an ‘innovation friendly market for its businesses”. This would require policy actions on “regulation, standards, public procurement, intellectual property and fostering a culture which celebrates innovation”. Rather than stressing innovation inputs such as R&D, the Aho Report stresses innovation demand and the myriad of socio-cultural factors that encourage innovation, such as entrepreneurship, risk taking, flexibility and adaptability, and mobility (Arundel and Hollanders, 2006).

A substantive body of literature, starting with Porter in the early 1990s, argues that sophisticated domestic demand for innovative products is an essential driver of innovation, a fact underlined by the strong and significant correlation between the indicator on ‘sophisticated demand’3 from the Global Competitiveness Report (WEF, 2011) and innovation performance from the Innovation Union Scoreboard. Also government demand through government procurement and business demand are important drivers of demand for new innovative products.

Entrepreneurship is possibly one of the most important drivers of innovation and one of the most difficult to measure. It involves individual attitudes to risk, opportunities that reduce risk, receptiveness to new ideas, and access to capital. Most indicators of entrepreneurship either measure individual attitudes, such as the Flash Eurobarometer measure of attitudes to starting a financially risky business, or attitudes to self-employment. There are no indicators for entrepreneurship within existing firms, such as the rate of formation of new spin-off firms or the rate of introduction of new products. In addition, indicators of individual attitudes to entrepreneurship do not differentiate between establishing a ‘mom and pop’ shop and establishing a firm with an innovative business strategy (Arundel and Hollanders, 2006).

Over the past century, the theoretical framework to understand the innovation process and the design of innovation policies has been predominantly influenced by technology-push innovation theories. Emphasizing innovation as the essential driving force of social and economic change

3 The WEF question is “In your country, how do buyers make purchasing decisions? [1 = based solely on the lowest price; 7 = based on a sophisticated analysis of performance attributes]” “Buyers in your country are (1 = slow to adopt new products and processes, 7 = actively seeking the latest products, technologies and processes)”.

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(Schumpeter, 1934) public policy intended to boost knowledge production and supply in order to spur knowledge output and spillovers (Jones and Williams, 1998).

Supply-push policies generally use public investment through grants and subsidies to stimulate innovation in the EU and its Member States. Examples of supply-push policies include government-sponsored R&D, tax credits for firms to invest in R&D and support for education and training.

A demand-pull perspective acknowledges the importance of producing innovations but at the same time emphasizes the need for market opportunity (i.e. demand). Demand is considered as the driving force that directs innovation output to meet societal or market needs (Schmookler, 1966). Consequently, demand-side policies aim to boost demand and encourage suppliers to meet the expressed needs of consumers. Examples of demand-side policies include tax credits and rebates for consumers of new technologies, technology-oriented government procurement, technology mandates, and innovation-specific regulations and standards (Cunningham, 2009). As neither supply nor demand factors are sufficient to spur innovation (Mowery and Rosenberg, 1979), both technology-push and demand-pull forces need to interact in order to attain the successful introduction and diffusion of innovations.

Firms invest in product and service innovation based on current or expected demand for innovative goods and services. A highly skilled and educated population is an essential prerequisite to the ability of firms to develop and implement productivity enhancing innovations. Furthermore, a skilled and educated population can also drive demand as consumers ask for more sophisticated products. These pools of sophisticated consumers can form national lead markets, defined as first to adopt a dominant innovation design that is subsequently adopted by other countries. According to Georghiou (2007) “demand needs to be coordinated or aggregated to create large orders to make innovation worthwhile”.

Especially with regard to innovative entrepreneurs, it is crucial that they meet a sophisticated market which demands their innovative products and services. Only when consumers are receptive to purchasing innovative products and services do the innovations by entrepreneurs become commercially viable.

1.2 Social attitudes to demand and entrepreneurship Social attitudes to innovation influence entrepreneurship and demand for innovative goods and services. These attitudes – and their economic effects – are possibly the most difficult aspects of innovation to measure. The lack of adequate data hinders understanding and consequently the development of innovation policies to promote entrepreneurship and demand for innovative products.

Social attitudes can be defined as “the attitudes of individuals or groups with respect to social objects or phenomena such as persons, races, institutions, or traits”. Social attitudes to entrepreneurship are the attitudes of individuals or groups towards their preference and willingness

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to engage in entrepreneurial activities. Social attitudes towards (the demand for) innovation are the consumer perceptions of and willingness to try new products and services.4

Entrepreneurial activity usually involves the founding and early-stage growth of new firms, although it can also involve the reinvigoration of established firms. New firms can be created by individuals or spun off from larger firms or from the public research sector. Entrepreneurship involves individual attitudes to risk, opportunities that reduce risk, receptiveness to new ideas, access to sources of new ideas with commercial potential, and access to capital. Entrepreneurship does not need to involve technological innovation, but can be based on franchising or establishing small businesses such as restaurants, hotels, retail stores, B&B accommodation, construction firms, web or consultant services, etc. However, innovation policy is primarily interested in the creation of innovative firms that develop new technology, use technology in new ways, for example new business models to exploit the capabilities of the internet, or which are based on new organisational structures.

Research on entrepreneurship is constrained by a lack of relevant and reliable data, in particular in Europe. First, it is difficult to separate non-innovative new firms from innovative new firms, or separate the interest of individuals in establishing ‘mom and pop’ firms from an interest in founding innovative firms. One argument is that all new firms are innovative in some way, but indicators built on this assumption will be of low value for innovation policy. Second, it is difficult to obtain data on entrepreneurship because many potentially innovative new firms are either difficult to detect or their activities don’t show up in official statistics.

Both problems are illustrated in an interview study of 4,928 start-up owners drawn from a random sample of approximately 250,000 firms founded in 2004 in the United States (Ballou et al., 2008). One year after establishment, 63% of the firms had one or no employees. Only 2% had a patent, although this increased to 4% of firms active in high-technology sectors. Only 10% of the firms obtained external equity and less than 1% received venture capital funding, with 90% of firms funded by the owner or family members. Most of the firms were of micro-size and offered consulting or other services. Very few were likely to have been based on innovative business models or to have offered innovative products or services.

Research on demand is similarly constrained by a lack of data on consumer demand for innovative goods and services, even though economic theory posits that demand side factors that provide an incentive for investment in innovation are possibly more important than supply side factors such as scientific research and technological opportunities (Utterback and Abernathy, 1975). Social demand for innovative products develops from the purchase decisions of individual consumers. Other major sources of demand are businesses and governments, which may be influenced by

4 This report does not discuss attitudes to social entrepreneurship or social innovation as there is no statistical evidence of attitudes to social entrepreneurship. Social entrepreneurship “aims to provide innovative solutions to unsolved social problems through some form of business” and social innovation is “about social change in response to social needs and challenges” (OECD, 2010). The EC funded SELUSI project (http://www.selusi.eu) is one of the first projects studying social entrepreneurs (the project studies “the market behaviours and organizational design decisions of over 800 social enterprises in Europe over time”) but the project has not looked at attitudes to social entrepreneurship.

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consumers as well5. In all cases, demand has both quality (buyer sophistication) and quantity aspects (expenditures).

There are only a limited number of indicators for entrepreneurship and almost all of them do not focus on innovation. A recent report by the OECD (2009) provides results for ten entrepreneurship performance indicators for 21 OECD countries, but the results are for all types of new firms, with no separation between innovative new firms and other types of new firms. Most of the research on entrepreneurship focuses on finance, institutional factors, trade and patents.

State of the art research on demand for innovative products (other than demand based on market size) has focused on the receptiveness of individuals for innovative products (Arundel and Hollanders, 2005) and on lead markets. A growing body of literature argues that sophisticated domestic demand or ‘lead users’ for innovative products are an essential driver of innovation (Beise and Rennings, 2001; von Hippel, 1986; Morrison et al., 2002; Porter, 1990). Although there are many examples where this appears to be true6, firms may be able to overcome a lack of sophisticated domestic markets by developing links with export markets with demanding consumers. Another area of new research is on government procurement with the 2009 Innobarometer survey including several relevant questions on this topic7.

1.3 Structure of the report The structure of this report is as-follows. In Chapter 2 we examine the role of social attitudes towards innovation. Social attitudes towards innovation influence consumers’ perceptions and receptiveness towards adopting innovation and thus shaping demand for innovation. In particular, we investigate which socio-cultural factors are likely to influence social attitudes towards innovation. Understanding the role of social attitudes in shaping demand for innovation is crucial in order to formulate demand-side innovation policies. Europe needs to extend its demand-side innovation policies to complement its supply-side policy, which generally uses public investment through grants and subsidies to stimulate innovation in the EU and its member states. Demand-side innovation policies are needed to promote innovation and the diffusion of innovations by stimulating demand for and creating better conditions for the adoption of innovation in a society (Cunningham, 2009). For instance, in the IT sector, a lack of user acceptance has been found to be a key factor explaining the disparity between the investments in IT and its derived benefits (Gillooly, 1998; King, 1994). It is crucial to understand the effects of culture and social attitudes on innovation adoption in order to design effective policy measures to spur innovativeness of countries. The differences in socio-cultural environments of countries and regions may explain why similar economic policies have different effects on entrepreneurship and innovation across

5 We ignore here the role of export demand. 6 Examples include mobile telephones in Scandinavia, in early use because of large areas without land lines; pump technology in the Netherlands based on the need to pump water from land below sea level, windmills in Denmark due to feed in tariffs that created a market, and the pharmaceutical sector in the United States, due to higher drug prices (Georghiou, 2007). 7 www.proinno-europe.eu/sites/default/files/Innobarometer_2009.pdf

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cultures. Related to consumer attitudes is “consumer resistance” to new innovative products. Chapter 3 will briefly discuss different types of consumer resistance (rejection, postponement and opposition) and will explain the drivers of consumer resistance.

The importance of entrepreneurship will be discussed in Chapter 4 by looking at different types of entrepreneurs and differences in entrepreneurial activities across countries. Chapter 4 will also look at the role of social attitudes to entrepreneurship and will show that differences in countries’ attitudes to entrepreneurship can explain differences in entrepreneurial activities. Chapter 5 will conclude and discuss recommendations for the improved measuring of attitudes to innovation and entrepreneurship. The available indicators measuring social attitudes to innovation and entrepreneurship are combined in a scoreboard in Annex 3 to highlight differences between countries.

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2 Attitudes and consumer demand for innovation

2.1 Introduction There are four types of demand for innovation: consumer demand for business innovation, customer demand for government innovation, government demand for business innovation and business demand for business innovation (Ashby and Mahdon, 2009). For each of these dimensions, we checked and assessed the availability of indicators to measure demand for innovation. Regarding consumer demand for business innovations, consumers’ degree of personal innovativeness provides a good measure for demand for innovation, as a high level of receptiveness indicates a higher willingness of consumers to buy or try innovative products and services. However, no similar measure is available to capture customer demand for government innovation. Regarding government demand for business innovation, Ashby and Mahdon (2009) indicate government procurement of advanced technology products as a weak proxy measure of government receptiveness to new products and services due to the fact that it is limited to the “business perceptions of government ability to buy new technologies, rather than on government’s own willingness to buy or try new technology”. Hence, there are no publicly available measures for understanding government receptiveness towards innovation. Similarly, we lack the right indicators to capture business demand for business innovation. Given the limited availability of indicators to measure all four dimensions of demand, we focus on consumer demand for business innovation; i.e. demand for innovative products and services.

The most important challenge on the demand side of innovation is the issue of adoption and diffusion of innovation by consumers (OECD, 2011). Companies invest in research and development activities based on the current or expected demand for innovative goods and services. The successful introduction of an innovation requires it to be not only commercially viable but socially acceptable. We define social attitudes towards innovation as consumers’ receptiveness to try and adopt innovative products and services. Consumers’ receptiveness for innovative products and services can range from a ‘pro-innovation’ attitude (enthusiastically accepting or promoting an innovation) to an ‘anti-innovation’ attitude (resisting or even rejecting an innovation). Demand for innovation is defined as consumers’ actual purchasing decision of an innovative product or service. Hence, consumers’ attitude towards adopting innovative products and services has a direct impact on demand for innovation.

The success of a new product or service depends on consumer acceptance. Therefore, consumers’ attitudes towards innovation are a key demand factor. Over the recent decade, we witnessed numerous public debates on the social acceptability of different innovations. Nowadays, forms of sustainable energy (wind, solar), effects of biotechnology on foods and the environment and bioethical questions regarding stem cells and reproductive interventions are among the most debated issues in current media. Particularly, we can observe different public responses towards

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different categories of innovation. For instance, military-related innovations are generally less popular than health-related innovations. This difference makes it difficult to assert one ‘general’ social attitude towards innovation. In fact, certain innovations may meet with different public reactions, which will change over time. For instance, the 1980s experienced a particular surge in studies on public acceptance of new information technology. The initial concerns about public attitude towards new IT have been overtaken by debates on biotechnology and latterly nanotechnology. These new technologies raise novel ethical questions on the implications for health and food safety.

Current public debates about new technologies as well as differences in demand for innovation across countries (Arundel and van Cruysen, 2008) beg the question about the importance of social attitudes in shaping demand for innovation. In fact, we observe great differences in consumers’ attitudes towards innovation across Europe. Innobarometer 2005 surveyed Europeans in all 27 Member States about their attitudes to innovative products and services (innovative products were defined as new or improved ones) and grouped respondents into four distinctive categories: 11% were enthusiasts toward innovations, 39% were attracted by innovation, 33% were reluctant to purchase innovations and 16% were anti-innovation. By country, the percentage of ‘pro-innovation’ consumers varies from a low of 35% in Poland to a high of 64% in Malta. These results suggest that there are large differences across Europe in consumers’ demand for innovative products and services.

Given that the successful commercialisation of an innovation depends on the adoption decision of consumers, we find it crucial to examine which factors influence consumers’ attitudes towards innovation and hence influence consumer adoption of innovations.

In order to answer this question, we will conduct a state-of-the-art review of consumer research and innovation diffusion literature to examine the influences of the socio-cultural environment on consumer attitudes and intention to adopt innovative products and service. On basis of the Innobarometer 2005 dataset, we will test our propositions. Based on our findings we will derive policy recommendations on how countries can increase the demand for innovation by taking into account the important role of consumer attitudes towards innovation.

2.2 Factors influencing consumers’ attitudes and adoption of innovation Consumer receptiveness towards innovative products and services is found to be one of the closest measures to capture demand for innovation in a country (Ashby and Mahdon, 2009). Successful suppliers of innovations need customers who are willing to try and buy new products and services. Therefore, in order to explore the relationship between demand and innovation, Levie (2009) suggests to examine customers’ willingness or receptiveness to engage with and perceive benefit from innovative products and services. Consumers’ receptiveness or attitudes towards innovation are “more complex than simple acceptance or resistance” (Gee and Miles, 2008:12). In fact, Gee and Miles (2008) identify four distinct types of consumer attitudes towards innovation:

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• “Rejection: unwillingness to accept an innovation, either in terms of one’s own use of it or as a result of others’ use impinging upon one’s own practices.

• Resistance: unwillingness to allow the existence of the innovation, which may be manifested in campaigning against it.

• Acceptance: willingness to accept an innovation, at one extreme enthusiasm, and at the other at least to tolerate on the part of others.

• Proponents: the point of view that will seek to promote the particular innovation or some more general trajectory of innovation”.

What factors influence consumers’ attitude towards innovation? What factors can explain the large differences across Europe in consumers’ attitude towards innovative products and services? In order to answer these question, we need to refer to various strands of research, ranging from innovation diffusion theory (Rogers, 1983), technology acceptance literature (Ajzen and Fishbein, 1980, Ajzen, 1985, 1991), to cultural studies and consumer and marketing research.

By and large, research on individual adoption behaviour of innovation has centred on identifying objective ‘innovation characteristics’ i.e. perceptions of technology attributes that influence the decision to adopt a new technology. However, drawing on behavioural science and individual psychology, the role of social influence and personal innovativeness have been found as important elements in potential adopters’ decisions (Lu et al., 2005). Drawing on innovation diffusion theory, Rogers (2003) emphasises the relationships between demographics, personal innovativeness and innovation adoption behaviour. Recently, national culture has been suggested to be another important factor that influences consumer attitudes towards innovation and thus adoption behaviour.

In the following, we examine how the influence of the social environment, the influence of personal innovativeness, the influence of demographics and the influence of the cultural environment influences consumers’ attitudes towards innovation and consequently the decision to adopt an innovation.

2.2.1 Social influence on innovation adoption Consumers perceptions of a new technology are influenced not only by the objective characteristics of the technology but also by the opinions and behaviour of relevant others (Salancik and Pfeffer, 1978). Social influence is defined as the “extent to which members of a reference group influence one another’s behaviour and experience social pressure to perform particular behaviours” (Kulviwat et al., 2009:707). Therefore, social influence is an important construct in technology acceptance literature. Social influence takes the form of subjective norms and image which affects consumers’ attitude towards a technology and thus influences the consumers’ adoption decision. In the consumer setting, subjective norms often take the form of interpersonal influences coming from a variety of sources such as friends, relatives and neighbours or from inspirational figures such as movie stars. Studies conducted by Rosen and Olshavsky (1987) and Childers and Rao (1992) confirmed that familial and peer-based reference groups have a significant influence on consumer decisions. Therefore, subjective norms have an impact on the

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adoption behaviour of consumers because individuals “adapt their attitudes, behaviours and beliefs to their social context”.

Furthermore, image is another important element of social influence and plays an important role in influencing consumer adoption behaviour. Image is the degree to “which an adoption of the innovation is perceived to enhance one’s status in one’s social system” (Yang et al., 2009:26). For instance, in studies of mobile communication, some consumers adopted mobile technology merely to show off or enhance their social identities (Yang et al., 2009). Consequently, adoption decisions are influenced by socialization forces (e.g. subjective norms and image) due to the desire to align one’s behaviour with referent group norms and to enhance one’s social image (Hausman and Stock, 2003; Taylor and Todd, 1995).

While the role of social influence in technology acceptance has been commonly investigated in the context of the workplace, recent studies found that social influence plays an even more important role in consumer adoption of technology. This is due the fact that, as opposed to the workplace, adopting the technology in the consumer setting is almost always a voluntary decision. Given that social influence plays a significant role in determining consumers’ adoption decisions of innovations, we will take closer look at how exactly social influence can shape consumer’s attitudes towards innovation.

Originating from behavioural science, the Theory of Reasoned Action (TRA) and Theory of Planned Behaviour (TPB) (Ajzen and Fishbein, 1980, Ajzen, 1985, 1991) suggest that a person’s actions are influenced by the person’s behavioural and normative beliefs. Behavioural belief refers to an “individual’s positive or negative evaluation of performing a certain behaviour, while a normative belief is a person’s perception of the social pressures to perform or not perform the behaviour in question” (Lu et al., 2005:245). These two sets of belief can help shape a person’s attitude towards its intention to carry out an action.

In the context of technology acceptance research, the Theory of Reasoned Action and Theory of Planned Behaviour were used to develop the Technology Acceptance Model (TAM) by Davis (1989) to investigate IT acceptance in the 1980s. In the initial Technology Acceptance Model, researchers focussed on the role of perceived usefulness and perceived ease of use on the probability that a technology would be adopted.

According to the Technology Acceptance Model (Davis, 1989) a potential adopter assesses a new technology on the basis of two criteria:

• Perceived usefulness, defined as "the degree to which a person believes that using a particular system would enhance his or her job performance" (Davis, 1989, p.320).

• Perceived ease-of-use, defined as "the degree to which a person believes that using a particular system would be free from effort" (Davis, 1989, p.320).

The original TAM (Davis, 1989) examined the influence of perceived usefulness and perceived ease-of-use on the probability that the technology will be adopted, however without taking into account social influence. Therefore, the original TAM has been improved to include social influence as a key determinant of technology adoption (e.g. see TAM2 by Venkatesh and Davis,

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2000), and the ‘unified theory of acceptance and use of technology model’ developed by Venkatesh et al., 2003).

Social influences, in the form of subjective norms and image can affect an individual’s evaluation of a technology’s perceived usefulness. Furthermore, social influences can also shape an individual’s estimation of his or her confidence in using a new technology. If a new technology is “socially believed hard to learn and hard to use, unavoidably it will more or less affect a member’s intention toward adopting it” (Lu et al., 2005:250). We have illustrated the relationship between social influence, perceived usefulness, and perceived ease of use and individual’s attitude in Figure 2-1. Social influence shapes an individual’s evaluation of the usefulness and ease of use of a new technology. This evaluation is translated into an attitude towards using this innovation (e.g. a favourable or unfavourable attitude). The attitude toward using the innovation is suggested to have direct and positive effect on the intention to adopt the technology” (Kulviwat et al., 2009:708). The intention to use the technology will eventually lead to the actual adoption decision.

Figure 2-1: The role of social influence on attitudes towards innovation use

Source: Adapted and modified from Davis (1989), Venkatesh and Davis (2000), Venkatesh et al. (2003)

2.2.2 The influence of personal innovativeness on innovation adoption Recently, a new model of technology acceptance has been developed to capture the influence of ‘personal innovativeness’ on adoption behaviour. In particular, Agarwal and Prasad (1998) developed a scale called ‘personal innovativeness in the domain of IT’ (PIIT), which is defined as "the willingness of an individual to try out any new information technology" (Agarwal and Prasad (1998:206). Agarwal and Prasad (1998) “added this individual difference variable as a new construct to Davis’ original TAM model and hypothesized that individuals with higher levels of PIIT are expected to develop more positive perceptions about the innovation” (Lu et al., 2005:251). That is, individuals who are more risk taking and innovative are more likely to evaluate a new technology more favourably in terms of perceived usefulness and perceived ease of use.

Given that innovations present "an idea, practice, or object that is perceived as new by an individual or other unit of adoption" (Rogers, 2003:12), innovations inherently involve a risk element (Kirton, 1976; Bhatnagar et al., 2000). By nature, some individuals are more willing to take a risk and try out a new product or service, while others are more sceptical towards a new idea.

Social influence (subjective norms,

image)

Perceived usefulness

Perceived ease of use

Attitude towards

innovation

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innovation

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For instance, regarding a new wireless mobile technology, most people do not have prior experience or knowledge about this new technology. “Sheer boldness and curiosity in their characters may not only strongly amplify their perception of potential benefit, but also heighten their confidence in their capabilities to handle the technology under adoption. Meanwhile, because individuals with higher PIIT tend to be more risk taking, it is also reasonable to expect them to develop more positive intentions toward the use of” a new technology (Lu et al., 2005:252).

Figure 2-2: The role of personal innovativeness on attitude towards innovation use

Source: Adapted from Lu et al. (2005)

The important practical implication of this novel approach of PITT is that it provides a scale to measure the personal innovativeness of individuals on a continuum from high to low.

A related concept has been developed by Rogers (2003) that measures personal innovativeness (also called individual innovativeness) as the “degree to which an individual or other unit of adoption is relatively early in adopting new ideas than other members of a system” (Rogers, 2003:280). That is, Rogers (2003) categorizes adopters based on the timing at which an individual adopted an innovation, that is, he operationalises personal innovativeness as the time of adoption. Hence, Rogers’ approach is based on a post facto description of adoption behaviour; emphasising the demographic differences between the adopter groups.

In the next section, we briefly review Rogers (2003) different adopter groups in terms of their personal innovativeness and associated demographic differences.

2.2.3 Demographics and personal innovativeness Adopters in the same category are characterized to have common traits and values with regard to the adoption of an innovation (Rogers, 2003, Moore, 1999; Brancheau and Wetherbe, 1990). Rogers (2003) suggests the following categorization of adopters, stressing that these only present ‘ideal types’ derived on the basis of abstractions from empirical investigations:

• Innovators: Innovators are characterized to be venturesome with a keen interest in new ideas. Generally in possession of substantial financial resources, with an aptitude to apply complex technologies and the ability to cope with high degree uncertainty about an innovation, innovators play a significant role in the diffusion of an innovation.

Personal innovativeness

Perceived usefulness

Perceived ease of use

Attitude towards innovation use

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• Early Adopters: As opposed to innovators who are often not respected by other members of a local social system, early adopters are an integrated part in the local system and are highly respected for their opinions. A prime motivator for early adopters is to earn respect and esteem within their local system by making well-judged innovation-decision. Hereby, early adopters “help trigger the critical mass when they adopt an innovation” (Rogers, 2003:283).

• Early majority: This group makes up one third of all members of a system (Rogers, 2003) and thus presents an important link in the diffusion process. They are predominantly driven by a strong sense of practicality and value the references by their peers when it comes to the adoption of an innovation.

• Late majority: The late majority does not adopt an innovation until most others have already done so. In this way, adoption of an innovation is often an economic necessity and the result of increasing peer pressure. Nonetheless, they only adopt an innovation when they feel comfortable with their own ability to handle the new technology.

• Laggards: This group is the last ones to adopt an innovation in a social system. As their resources are often limited, laggards remain cautious about innovations and only buy them when it becomes a necessity.

In sum, due to their innovative personality, innovators and early adopters are more willing to take a risk and try out a new technology before others and hence are considered as the proponents of disruptive technologies (Moore, 1999) and radical change (Kirton, 1976). Noteworthy, innovators can be distinguished from early adopters by their greater propensity to take risks and their more advanced technical know-how.

Based on an exhaustive review of the innovation diffusion literature, Rogers (2003) establishes important differences between earlier and later adopters of innovation with regard to (a) socio-economic status, (b) personality variables and (c) communication behaviour. The underlying assumption is that socio-economic characteristics such as status, education and wealth are positively associated with innovativeness. As new ideas and technologies are costly to adopt and require large outlays of capital, wealthy people who have the financial means are more likely to be among the first to adopt these innovations.

While there seems to be no age difference between earlier and later adopters, Rogers (2003:288) found that earlier adopters have more years of formal education, are more literate, have a higher social status and greater degree of upward social mobility than later adopters.

Regarding personality values, Rogers (2003) finds that earlier adopters have “greater empathy, less dogmatism, a greater ability to deal with abstractions, greater rationality, greater intelligence, a more favourable attitude toward change, a greater ability to cope with uncertainty and risk, a more favourable attitude toward science, less fatalism and greater self-efficacy, and higher aspirations for formal educations and higher-status occupations” than later adopters (Rogers, 2003:289).

Furthermore, Rogers (2003) finds that earlier adopters exhibit different communication patterns than later adopters, as they have “more social participation, are highly interconnected in the interpersonal network of their system, are more cosmopolite, have more contact with change

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agents, greater exposure to mass media and interpersonal communication channels, engage in active information seeking, have greater knowledge of innovations, and a higher degree of opinion leadership” than later adopters (Rogers, 2003:291).

Rogers (2003) concludes that early adopters are the first ones to adopt a new technology, due to their demographic characteristics which makes them more open, risk taking and receptive towards innovation.

The Innobarometer (2005) offers interesting insight on the relationship between consumers’ receptiveness towards innovation and demographic differences. The report distinguishes four types of consumer attitudes based on the receptiveness and openness of consumers across Europe. ‘Enthusiasts’, representing 11% of the EU25 population, are “calling out for innovation” and are usually male, young, with a high level of education; “managers and students are over-presented in this group” (Innobarometer, 2005:3). The second group is classified as ‘attracted’ towards innovation and represents 39% of the population. While the third group is reluctant to adopt an innovation, the fourth group is opposed to innovative products and services. “Compared to other groups, they tend to have a lower level of education and live alone. Their principal occupation is taking care of the home or else they are retired” (Innobarometer, 2005:3).

Table 2-1: Consumer attitudes towards innovation across Europe Group Proportion of

EU25 sample Common characteristic traits (as compared to other groups)

“Enthusiasts” 11% Male, young, high level of education, managers, students “Attracted” 39% Male, young, students, white collar, living in large household “Reluctant” 33% Female, aged 40, manual workers or not economically active “Anti-innovation” 16% Female, aged 55 or over, lower level of education, living alone, retired

Source: Innobarometer (2005)

Comparing the results from the Innobarometer (2005) with Rogers (2003) observation on adopter groups, it becomes clear that demographics seem to play a key role in determining personal innovativeness and attitudes of consumers. However, since Rogers (2003) and the Innobarometer (2005) use different indicators to capture personal innovativeness and consumer attitudes, we find it crucial to test for ourselves the relationship between demographic factors and consumers’ attitudes towards innovation in this report.

In the next section, we examine the role of national culture in influencing personal innovativeness and consumer attitudes.

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2.2.4 The influence of national culture on innovation adoption Studies have shown a complex relationship between cultural values, social institutions, industry characteristics and behavioural outcomes (Hayton et al., 2002) such as the decision to adopt a new product or service. Cultural values can influence consumers’ attitudes and behaviour through their shopping patterns (Gregory et al., 2002). As cultural values are reflected and reinforced by social institutions and behaviours, culture determines the degree to which a society supports innovative behaviour, such as generating new ideas or buying new products and services. Therefore, societies that value and reward innovative behaviour are more likely to promote the development and adoption of innovation (Herbig and Miller, 1992), thus spurring demand for innovative products and services.

Consumer or personal innovativeness is found to be influenced by national cultural variables (Steenkamp et al., 1999). In fact, consumers in some countries are found to have higher levels of innovativeness than consumers in other countries. Steenkamp et al. (1999) argue that these cross-country differences in personal innovativeness are inter alia due to systematic differences in the national environment. In particular, a country’s culture is considered as a key factor influencing individuals’ perceptions, dispositions and behaviour and thereby shaping consumer behaviour (Triandis, 1989). As Steenkamp et al. (1999) state a “nation’s culture affects the needs consumer satisfy through the acquisition and use of goods”.

To understand the role of national culture in influencing consumer innovativeness and willingness to adopt innovative product and services, we refer to the work by Hofstede (1980, 1991). Hofstede gathered data from 117,000 surveys from over 88,000 employees from 72 countries (reduced to 40 countries that had more than 50 responses each) in 20 languages at IBM between 1967 and 1969 and again between 1971 and 1973. This database was later expanded with 10 additional countries and three regions (i.e. Arab countries and East and West Africa). Hofstede then aggregated national means of different sets of individual questions to generate four cultural measures (later expanded to five) for each country. For measuring national culture we will use his measures on power distance, individualism, masculinity and uncertainty avoidance. Hofstede measures of time orientation is not used in this framework as it has not been previously linked to innovation, and there is no strong theoretical argument for such a connection.

The national cultural dimensions identified by Hofstede have been widely accepted and used in market and consumer behaviour research (e.g. Dawar and Parker, 1994; Roth, 1995). Hofstede (1980) has introduced four dimensions of national culture, which have been used to study the relationship between culture and innovativeness.

The first dimension, power distance, measures the social inequality degree accepted by a society; i.e. the degree to which unequal distribution of power and wealth is tolerated. This can be captured in terms of the level of hierarchy in workplaces and distance between social strata. An explanatory framework for understanding the relation between power distance and innovation is explored by Shane’s institutional theory (1993). According to this theory the societies in which businesses operate  influence their manner of operation. Shane (1993:70) contends: “As organizational

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characteristics reflect societal values, managers might find that the organizational behaviours that promote innovation are easiest to develop in  uncertainty accepting, individualistic, non-power distant societies, and these behaviours, in turn, might help to increase national rates of innovation”. Innovations carry with them a threat to the social hierarchy by redistributing power; lower status members can become more highly valued for their potential to do more, or do it better. Thus, high power distance nations may find it hard to innovate according to Shane (1992, 1993). Furthermore Hofstede et al. discussed a similar relationship in his book “Cultures and organizations: Software of the mind” (2010). According to Hofstede high power distance nations may find it hard to encourage their citizens to innovate as inequalities among people are not only  expected but desired and communication is limited between those of different  strata. In high power distance nations subordinates in a workplace expect to be told what to do, thus, opportunities to think for one self and to use imagination are limited. By contrast, subordinates in low power distance nations expect to be consulted and having imagination is prized (Hofstede et al., 2010). With limited opportunities for advancement, people in high power distance nations  in the lower strata may feel little motivation to be innovative as it is unlikely they will be able to reap the rewards directly or even get their ideas noticed by those higher up in the social hierarchy.

It must be noted however that Hofstede and look at the relationship from the production side of innovation whereas we explore the demand side of innovation. In societies with low power distance, inequality is hardly desirable. Therefore, “people do not tend to show the symbols of power, including those regarding consumption and purchasing behaviour. In high power distance cultures the state’s visible symbols, including purchasing of goods and services, give authority to those who own them” (Dobre et al., 2009:31). Therefore, we expect that consumers in high power cultures are more tempted to purchase innovative products and services in order to enhance their social status.

Figure 2-3: Cultural values – degree of power distance

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AT BEBGHR CZ DKEE FI FR DEGR HU IE IT LV LT LU M T NLNO PL PTRO RS SK SI ES SECH TR UK EU27 AUCA JP KR US BRCN IN RU

Source: Authors’ calculations based on Hofstede’s dataset. EU27 is the unweighted average of the Member States scores.

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As Figure 2-3 illustrates, Slovakia, Romania, Croatia, Slovenia and Bulgaria are the top five European countries with the largest degree of power distance. In contrast, Ireland, Denmark and Austria are the most egalitarian countries in Europe. The average degree of power distance in the EU27 is below that in Brazil, China, India, Russia and South Korea but above that in the US.

The second cultural dimension, individualism-collectivism focuses on the interests of the individual versus those of the group. It reflects the degree to which a society’s members identify themselves as individuals (as “I”) or as members of a group (as “we”) (Hofstede, 1980; Roth, 1995; Steenkamp et al., 1999).

Roth (1995) describes collectivistic cultures as societies in which the people tend to rely on their group mates in order to ensure their material security, social status, and career opportunities. In return for this service expected from and provided by the group, each group member has to commit unwavering loyalty towards the group. A characteristic feature of collectivistic societies is therefore an overall social orientation towards conformity, as deviations from group behaviour or norms could jeopardize one’s position and opportunities in the society. In contrast, individualistic cultures can be conceptualized as societies in which the people rather rely on themselves than on others in order to secure living standards and opportunities. While family still plays a role as a collectivistic frame of identification for individualists, the most striking feature of individualists is that they place their personal goals, motivations and desires ahead of those of the in-group.

Figure 2-4: Cultural values – degree of individualism

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Source: Authors’ calculations based on Hofstede’s dataset. EU27 is the unweighted average of the Member States scores.

We assume that individualistic societies are more open towards innovative products than collectivistic societies because new products and services provide a powerful means to make oneself distinct from others, thus, to support and serve individualistic motivations. As Figure 2-4 indicates, the top five European countries with the highest degree of individualism are UK, the Netherlands, Hungary, Italy and Belgium. Individualism is highest in the United States and Australia. The average degree of individualism in the EU27 is below that in the US but above that in Brazil, China, India, Russia, Japan and South Korea.

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The third cultural dimension, masculinity, is a measure of the degree to which a society is characterized by ‘masculine’ features, as contrasted to ‘feminine’ features. Following Hofstede’s terminology, masculine features are associated with assertiveness, authority, performance and success, while feminine features are associated with nurturance, personal relationships, quality of life, service and welfare. ‘Masculine’ societies emphasize wealth, status, success, ambition, material things and achievement, whereas ‘feminine’ societies emphasize people, helping others, preserving the environment, and equality (Hofstede, 1980; Steenkamp et al., 1999). According to Hofstede (1980), Japan is the country with the highest level of masculinity, expressed especially in hierarchical work organization and bureaucratic work places, whereas Sweden and Norway appear most feminine, expressed, inter alia, by people’s empathy for their fellow workers and more emphasis on spending time on relationships and personal ties (see also Schneider and Barsoux, 1997:80; Smith, 1998:61). As Rogers (1983) points out that purchasing new items is a meaningful way for a person to assert his or her interests and to demonstrate wealth and success, we expect that people in masculine societies are more likely to value status and achievement and therefore are more attracted towards purchasing innovation as a means to enhance social image. The average degree of masculinity in the EU27 is below that in China, India, Japan and the US but above that in Russia and South Korea (Figure 2-5).

Figure 2-5: Cultural values – degree of masculinity

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Source: Authors’ calculations based on Hofstede’s dataset. EU27 is the unweighted average of the Member States scores.

The fourth dimension, uncertainty avoidance is a measure of the degree to which a society tends to feel threatened by – thus try to avoid - uncertain, risky, ambiguous or undefined situations (Hofstede, 1980, 2001). According to Hofstede (1980), Sweden is the country with the lowest uncertainty avoidance (Figure 6), which is expressed in a high tolerance for ambiguity (Newman and Nollen, 1996; Redpath, 1997; Schneider and Barsoux, 1997; Smith, 1998). The average degree of uncertainty avoidance in the EU27 is below that in Brazil, Russia and South Korea but above that in China, India and the US (Figure 2-6).

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Figure 2-6: Cultural values – degree of uncertainty avoidance

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7

Source: Authors’ calculations based on Hofstede’s dataset. EU27 is the unweighted average of the Member States scores.

Since people in countries with a high level of uncertainty avoidance are usually determined by the feeling of “what is different is dangerous” (Hofstede, 1991), it must be assumed that consumers in such countries are resistant to change from established patterns and will be focused on risk avoidance and reduction (Steenkamp et al., 1999). Conversely, in countries with low uncertainty avoidance curiosity is likely to dominate over fear (Hofstede, 1991; Lynn and Gelb, 1996)). As a consequence, people in countries with low risk avoidance should be more open towards new items, while people in countries with high risk avoidance are quite reluctant towards new items (Steenkamp et al., 1999).

From our review, we conclude that consumers in countries with high levels of individualism are more likely to be attracted to innovations as a way set oneself apart from the mass. Consumers in countries with high levels of masculinity and power distance are more likely to be attracted to innovations as a way to enhance social status and image. In contrast, consumers in countries with high uncertainty avoidance are more risk averse and thus more reluctant towards purchasing innovative products and services.

2.2.5 The conceptual model Figure 2-7 illustrates our conceptual model on the various factors that shape consumer attitudes towards innovation. Broadly speaking, the attitude towards innovation can be either favourable or unfavourable, or to follow Gee and Miles (2008) classification, consumer attitudes can range from rejection to resistance to acceptance. Social influence, in the form of subjective norms and image, influences consumers’ perceptions of the usefulness and ease-of-use of an innovative product or service. This perception is then translated in an attitude towards the innovation.

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Figure 2-7: Conceptual model on consumer attitudes

Moreover, we expect that personal innovativeness influences one’s perceptions of the usefulness and ease-of-use of an innovation, thus influencing one’s attitude towards the innovative product or service. Based on our literature review, we further found that cultural and demographic factors play an important role in shaping consumers’ levels of personal innovativeness.

Our conceptual model has been constructed on the basis of our literature review of state-of-the-art research. To capture the various factors that might influence consumer attitudes towards innovation, we needed to combine various theoretical strands, ranging from behavioural science to market research to innovation diffusion literature. Noteworthy, empirical studies in these fields use different units of analysis to assess consumer attitudes towards innovation. For instance, empirical assessment of social influence and perceived usefulness and ease-of-use are specific to a particular technology under investigation. That is, all empirical research on technology acceptance uses a certain technology (e.g. the acceptance of mobile communication, internet etc) to measure consumer’s attitude. In contrast, studies on personal innovativeness (e.g. Rogers, 2003) assert that the level of an individual’s innovativeness influences the person’s receptiveness towards innovation in general.

Given the purpose of this study, we are interested to investigate which factors influence consumers’ attitude towards innovation in general. That is, we are not interested in learning about consumers attitudes towards one particular technology.8 Therefore, we will investigate the (1) influence of personal innovativeness on consumer’s (general) attitudes towards innovation and (2) the influence of cultural and demographic variables on the level of personal innovativeness.

In the following section we will describe the methodology used for testing our conceptual model.

8 There are numerous studies in consumer research and technology acceptance literature that investigate the social acceptance and adoption of a particular technology (e.g. for studies on social acceptance of energy innovation, please refer to Wuestenhagen et al. (2007).

Personal innovativeness

Perceived usefulness

Perceived ease of use

Attitude towards

innovation

Social influence (norms, image)

Cultural factors

Demographic factors

33

2.3 Methodology

2.3.1 Motivation In the previous sections, we conducted an exhaustive review of state-of-the-art literature on innovation diffusion and consumer behaviour. It became apparent that consumer attitudes towards innovation are a key factor in influencing demand for innovative products and services. As the Innobarometer 2005 illustrates, attitudes towards innovation vary by country across Europe. Hence, differences in demand for innovation across countries can be explained by differences in attitudes towards innovation.

The aim of the following empirical analyses is to examine which factors explain the difference in consumer attitudes across countries. As we have stated earlier, consumer attitudes towards innovation are not simply captured by an accept/reject response. Rather, Gee and Miles (2008) identified four distinct types of attitudes towards innovation including ‘rejection’, ‘resistance’, ‘acceptance’ and ‘proponents’ of innovation. Similarly, the Innobarometer 2005 identified four categories of attitudes towards innovation including ‘anti-innovation’, ‘reluctant’, ‘attracted’ and ‘enthusiasts’.

A methodological problem with the existing typologies of consumer attitudes toward innovation lies in the ambiguity associated how these typologies have been created. For instance, while the Innobarometer 2005 briefly mentions the use of factor analysis and cluster analysis to create this typology, the report does not provide a detailed account on how these groups of attitudes have been generated (i.e. the choice of variables).

To address this shortcoming and to examine which factors explain the differences in consumer attitudes across countries, we refer to our conceptual model (Figure 2-7). Personal innovativeness is used to capture consumer attitudes towards innovation. We will examine the effect of personal innovativeness on the demand for innovative products and services. Furthermore, we propose that individuals’ degree of personal innovativeness is influenced by the socio-cultural environment.

2.3.2 Use of data sources and indicators To test our propositions on the relationship between socio-cultural environment, personal innovativeness and demand for innovation, we will use two datasets in combination: the Innobarometer 2005 and Hofstede’s dataset on national cultural dimensions.

Firstly, we will examine the relationship between personal innovativeness and demand for innovation. The degree of personal innovativeness of individuals largely determines their general attitudes towards innovation and hence their adoption behaviour. Hence, we expect that individuals with a high level of personal innovativeness are more receptive towards innovation and are thus more willing to purchase innovative products and services. To measure personal innovativeness, we refer to question QE1 of the Innobarometer9. This type of question is in line with extant 9 “In general, to what extent are you attracted towards innovative products and services, in other words new or improved products or services?“ Answer categories are: Very attracted; Fairly attracted; Not very attracted; Not al all attracted; Do not know.

34

literature on consumer research and innovation diffusion literature, where personal innovativeness, i.e. attitude towards an innovation is measured along a four-point unipolar scale. The Innobarometer is, to our knowledge, the only EU-wide survey providing data on peoples’ attitudes to innovative products and services.

To measure demand for innovation, we face a substantial problem that is eminent in extant innovation literature. In fact, there are no available indicators and data sources to measure actual purchase of innovative products and services. Therefore, we need to proxy actual spending behaviour by a question relating to individuals’ intention and willingness to replace a product or service already in use with an innovative one given the cost of the innovative product or service. In particular, to measure individuals’ intention to try out a new product or service, we refer to question QE4 of the Innobarometer10. Here, intention is estimated by the preference to replace a trusted product or service with an innovative one. To proxy the actual demand for innovative product and service we use question QE5 of the Innobarometer11. The difference between QE4 (Intention to try out a new product) and QE5 (Willingness to buy) is the fact that QE5 takes into consideration the cost factor of the innovation. Secondly, we will test the influence of demographics on the degree of personal innovativeness of individuals in a society. In particular, we will examine the influence of age, gender, marital status, household composition, type of community, and years of education on the degree of personal innovativeness.

Finally, in order to measure the influence of the cultural environment on the degree of personal innovativeness of individual in a society, we rely on extant methodologies from cultural studies and innovation diffusion literature that commonly use one or a few cultural dimensions (e.g. Hofstede’s dimensions) to test the general relationship between cultural dimensions and innovation at the national level. Countries vary in the share of individuals with high degrees of personal innovativeness. We will test whether this difference in share of individuals with high degree of personal innovativeness across countries can be explained by national cultural factors. For the national cultural dimensions, we use Hofstede’s (1980) work on cultural values - power distance, individualism, masculinity and uncertainty avoidance. Hofstede’s measure of time orientation is not used in this framework as it has not been previously linked to innovation, and there is no strong theoretical argument for such a connection.

10 “In general, when an innovative product or service is put on the market and can replace a product or service that you already trust and regularly buy, do…?” Answer categories are: You prefer to continue purchasing a product or service that you already trust and do not try the innovative one; You quickly try the innovative product or service at least once; Do not know. 11 “You would be willing to replace a product or a service that you already use by an innovative one…” Answer categories are: Even if this is significantly more expensive; Only if this is a little more expensive; Only if this would cost the same; I would never be willing to purchase an innovative product or service; Do not know.

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Figure 2-8: Cultural values and attitude to innovation

ATTRACTED TO INNOVATIONS

SKROSI

TR

CZ

M TITNL

LU

UKSE

DK IE

AT FI

DEHU

LV

LT ESEE

GRPTBG

HR

BEPLFR

30

35

40

45

50

55

60

65

70

75

80

0 20 40 60 80 100

POWER DISTANCE

ATTRACTED TO INNOVATIONS

SKROSI

TR

CZ

M T ITNL

LU

UKSE

DKIE

AT FI

DEHU

LV

LTES EE

GRPTBG

HR

BEPLFR

30

35

40

45

50

55

60

65

70

75

80

0 20 40 60 80 100

INDIVIDUALISM

ATTRACTED TO INNOVATIONS

SKROSI

TR

CZ

M T ITNL

LU

UKSE

DK IE

ATFI

DEHU

LV

LT ESEE

GRPTBGHR

BE PLFR

30

35

40

45

50

55

60

65

70

75

80

0 20 40 60 80 100

M ASCULINITY

ATTRACTED TO INNOVATIONS

SK ROSI

TR

CZ

M TITNL

LU

UKSE

DK IE

ATFI

DEHU

LV

LT ESEE

GRPTBG

HR

BEPLFR

30

35

40

45

50

55

60

65

70

75

80

0 20 40 60 80 100

UNCERTAINTY AVOIDANCE

Figure 2-8 shows simple scatter plots visualizing performance on each of these cultural dimensions on the horizontal axis and being attracted to innovations on the vertical axis. The hypotheses formalized in section 2.2.4 state that consumers in high power cultures, in more individualistic societies, in more masculine societies and in countries with low risk avoidance would be more attracted to innovative products. The scatter plots only suggest some evidence for the first and fourth hypothesis. In the following section we explore this in more detail by controlling for differences in demographics like age, educational attainment and occupation.

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2.3.3 Description of sample and variables For the Innobarometer 2005 for most countries about 1000 people were interviewed between 9 May and 14 June 2005. For Germany the sample size was 1500 and for Cyprus, Luxembourg and Malta the sample size was 500. Table 2-3 provides an overview of the distribution of the socioeconomic characteristics and attitudes to innovation across the European countries. There appears to be considerable room for explaining differences in attitudes to innovative products and services across countries by both differences in cultural values and demographic characteristics.

Being attracted to innovations is defined using question QE1 and combines those respondents who are either very attracted or fairly attracted to innovative products or services. Those who are not very attracted or not at all attracted are defined as not being attracted to innovations. The share of people attracted to innovative products and services varies from 37% in Germany to 75% in Luxembourg and the share of people willing to pay significantly more for an innovative product or service varies from 2% in Portugal to 16% in Cyprus.

The Innobarometer does not directly provide information on educational attainment but instead asks for respondents’ age when they stopped full-time education (question D8). Primary education is defined to include all respondents who stopped full-time education at the age of 14 or below, who have not completed full-time education or who are still studying and are younger than 18. Secondary education is defined to include all respondents who stopped full-time education at the age of 15 to 21 or who are still studying and are between 18 and 22 years old. Tertiary education is defined to include all respondents who stopped full-time education at the age of 22 or above or who are still studying and are older than 22. The share of people with tertiary education varies from 11% in Turkey to 57% in Denmark, the share of secondary education varies from 40% in Turkey to 82% in Czech Republic and the share of primary education varies from 8% in Czech Republic to 66% in Portugal. For Denmark and Sweden attractiveness to innovation is partly driven by high shares of people with a tertiary education (cf. Table 2-2 showing the average percentage distribution between being and not being attracted to innovations for the different levels of educational attainment).

The age groups are as defined in the Innobarometer report. People in Italy and Turkey are relatively young and people in Finland and Sweden are relatively old. The high share of people in Italy and Turkey attracted to innovations could thus be explained by the high share of young people aged 15 to 39. People with a partner are defined as being married, remarried or unmarried but living with partner (question D2). People living without a partner are defined as being unmarried, either never lived with a partner or now living on their own, divorced, separated or widowed. In Estonia, Latvia, Lithuania and the UK more than 45% of the respondents are living without a partner.

For the occupational classification we use the three broad groups as defined in the Innobarometer. Non-active persons include persons responsible for ordinary shopping and looking after the home, or without any current occupation or not working, students, persons being unemployed or temporarily not working and persons being retired or unable to work through illness. Self employed persons include farmers, fishermen, professionals (lawyers, medical practitioners, accountants,

37

architects, etc.), owners of a shop, craftsmen or other self-employed persons and business proprietors or owners (full or partner) of a company. Employed persons include employed professionals (employed doctors, lawyers, accountants, architects), general management, directors or top management (managing directors, directors general, other directors), middle management, other management (department heads, junior managers, teachers, technicians), persons in an employed position, working mainly at a desk, persons in an employed position, not at a desk but travelling (salesmen, drivers, etc.), persons in an employed position, not at a desk, but in a service job (hospital, restaurant, police, firemen, etc.), supervisors, skilled manual workers or other (unskilled) manual workers or servants. For occupations the share of non-active people varies from 39% in Netherlands to 66% in Lithuania and the share of self employed people varies from 3% in Lithuania to 18% in Greece. For the Netherlands and Sweden we observe high shares of employed people who are more likely to be attracted to innovations than non-active people whereas for Lithuania and Turkey the share of non-active people is high which could reduce the share of people being attracted to innovations.

Females tend to be less attracted to innovations. Countries like Estonia, Latvia and Lithuania with high shares of females in their sample might therefore be less attracted to innovative products and services.

For living environment we distinguish between living in the countryside, living in a small or medium-sized town or living in a large town. The share of people living in a rural area varies from 15% in Italy to 59% in Malta and the share of people living in a town varies from 41% in Malta to 85% in Italy. In Italy attractiveness to innovation is partly driven by a high share of people living in cities.

Table 2-2: Cross tabulations Not attracted

to innovations Attracted to innovations

Education Primary 48.5% 51.5% Secondary 41.4% 58.6% Tertiary 31.4% 68.6% Age 15 - 24 years 22.8% 77.2% 25 - 39 years 30.4% 69.6% 40 - 54 years 40.1% 59.9% 55 years and older 56.2% 43.8% Partner Living without

partner 42.4% 57.6%

Living with partner 40.3% 59.7%

Not attracted to innovations

Attracted to innovations

Occupation Non-active 47.0% 53.0% Self employed 34.1% 65.9% Employed 34.7% 65.3% Gender Female 44.6% 55.4% Male 36.5% 63.5% Living environment

Rural 43.8% 56.3% Small town 40.1% 59.9% Large town 38.2% 61.8%

38

Table 2-3: Descriptive statistics AT BE BG HR CY CZ DK EE FI FR DE GR HU IE IT LV LT LU MT NL PL PT RO SK SI ES SE TR UK Attracted to innovations .454 .614 .537 .563 .529 .638 .635 .567 .440 .592 .374 .513 .407 .642 .695 .501 .561 .748 .709 .729 .608 .521 .671 .680 .679 .496 .669 .757 .691 Intention to try innovations Continue trusted product .394 .388 .311 .555 .501 .417 .557 .453 .445 .462 .552 .453 .428 .456 .489 .552 .555 .337 .276 .459 .690 .643 .393 .514 .490 .583 .366 .314 .558 Willingness to buy innovations Even if sign. more expensive .033 .064 .058 .077 .080 .046 .085 .071 .034 .044 .045 .070 .038 .048 .127 .046 .042 .105 .107 .070 .043 .025 .116 .096 .070 .076 .072 .135 .067 Only if little more expensive .283 .348 .238 .328 .260 .390 .359 .338 .355 .325 .266 .267 .312 .355 .361 .297 .222 .415 .426 .429 .265 .152 .399 .369 .450 .325 .513 .249 .392 Only if cost same .598 .467 .590 .480 .453 .519 .442 .498 .491 .498 .550 .495 .579 .501 .432 .503 .608 .352 .367 .433 .555 .634 .427 .496 .421 .452 .346 .529 .421 Never purchase innovations .086 .121 .114 .114 .207 .046 .114 .093 .120 .132 .139 .168 .071 .096 .080 .154 .128 .128 .100 .069 .137 .189 .058 .039 .060 .147 .070 .087 .120 Cultural values Power distance 11 65 70 73 60 57 18 40 33 68 35 60 46 28 50 44 42 40 56 38 68 63 90 104 71 57 31 66 35 Individualism 55 75 30 33 35 58 74 60 63 71 67 35 80 70 76 70 60 60 59 80 60 27 30 52 27 51 71 37 89 Masculinity 79 54 40 40 57 57 16 30 26 43 66 57 88 68 70 9 19 50 47 14 64 31 42 110 19 42 5 45 66 Uncertainty avoidance 70 94 85 80 112 74 23 60 59 86 65 112 82 35 75 63 65 70 96 53 93 104 90 51 88 86 29 85 35 Education Primary .114 .177 .183 .205 .370 .084 .092 .121 .131 .215 .191 .391 .317 .201 .288 .138 .227 .209 .296 .115 .142 .657 .233 .093 .145 .475 .133 .623 .173 Secondary .764 .617 .584 .629 .483 .815 .340 .669 .480 .553 .595 .411 .591 .661 .502 .713 .598 .580 .616 .567 .683 .254 .554 .759 .629 .391 .457 .300 .711 Tertiary .122 .206 .233 .166 .147 .100 .568 .210 .390 .231 .214 .197 .093 .138 .210 .149 .175 .211 .088 .317 .175 .089 .213 .149 .226 .134 .409 .077 .116 Age 15-24 years .103 .134 .149 .144 .131 .122 .101 .153 .098 .135 .132 .160 .107 .168 .127 .159 .129 .141 .136 .094 .154 .106 .130 .122 .158 .158 .104 .248 .111 25-39 years .296 .205 .247 .253 .210 .257 .250 .188 .221 .261 .210 .272 .229 .258 .370 .271 .206 .232 .220 .267 .250 .230 .274 .247 .257 .265 .197 .353 .253 40-54 years .284 .303 .239 .252 .253 .260 .285 .221 .237 .240 .269 .212 .238 .294 .265 .237 .212 .266 .272 .330 .268 .191 .247 .309 .245 .226 .275 .238 .218 55 years and older .317 .358 .365 .351 .406 .362 .363 .439 .444 .364 .389 .356 .426 .279 .238 .333 .453 .361 .372 .308 .328 .473 .349 .322 .340 .352 .424 .161 .417 Partner Living without partner .369 .283 .311 .366 .258 .362 .370 .458 .320 .393 .401 .412 .403 .374 .402 .475 .462 .315 .347 .333 .358 .361 .328 .305 .418 .386 .332 .278 .466 Occupation Non-active .425 .526 .565 .598 .509 .436 .446 .554 .462 .494 .541 .580 .578 .485 .450 .500 .662 .567 .638 .395 .629 .547 .516 .454 .547 .547 .406 .657 .549 Self employed .082 .071 .060 .043 .065 .107 .057 .053 .070 .044 .055 .177 .047 .097 .160 .051 .032 .060 .048 .081 .106 .058 .090 .077 .059 .065 .082 .160 .057 Employed .493 .403 .375 .358 .426 .457 .497 .393 .468 .461 .404 .243 .375 .417 .389 .448 .306 .373 .314 .525 .265 .395 .394 .469 .393 .388 .512 .183 .394 Gender Female .529 .515 .535 .599 .539 .558 .495 .680 .589 .537 .493 .554 .586 .544 .604 .614 .621 .536 .596 .524 .572 .596 .542 .603 .560 .567 .483 .469 .555 Living environment Rural area .378 .515 .322 .457 .350 .291 .280 .373 .300 .413 .335 .324 .343 .389 .145 .362 .271 .555 .589 .433 .389 .437 .456 .487 .473 .382 .431 .382 .305 Small town .337 .343 .236 .298 .650 .459 .355 .279 .512 .449 .425 .188 .343 .222 .658 .325 .400 .392 .278 .327 .366 .317 .275 .378 .328 .340 .385 .265 .339 Large town .284 .142 .442 .246 .000 .250 .365 .349 .188 .138 .240 .488 .314 .389 .196 .313 .329 .054 .133 .240 .245 .246 .268 .134 .199 .278 .184 .353 .356

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2.3.4 Analytical techniques We will analyse the data using two different types of analyses. First we analyse bilateral relations between the dependent and independent variables using cross tabulations. These results provide a first insight into the possible relation between individuals’ responses on innovation attractiveness and adoption behaviour. However, these results do not take into account the effect of other variables. Therefore, we also use binary logistic regressions in order to capture the influence of several variables simultaneously.

2.4 Analysis and results By means of cross tabulations and chi-square testing, we find significant relationships between individuals’ degree of personal innovativeness (QE1) and the intention to try (QE4) and the willingness to adopt an innovative product or service (QE5). The significance level for both chi-square testing is at p<.01, hence indicating the strong relationship between personal innovativeness and the decision to try or adopt an innovative product or service.

Respondents who indicated to be ‘very attracted’ and ‘fairly attracted’ to innovative products and services are more likely to try an innovative product at least once. Specifically, ‘very attracted’ consumers are willing to replace a product or service that they already use by an innovative one even if this is significantly more expensive. Consumers who are ‘fairly attracted’ to innovative product and services are only willing to adopt an innovative product or service if this is only little more expensive than the ones already in use.

Respondents who indicated to be ‘not very attracted’ to innovative products and services prefer to continue purchasing a product or service that they already trust and will not try the innovative one. They would only consider adopting an innovative product or service if it costs the same as the ones already in use. Respondents who are ‘not at all attracted’ will neither try nor purchase an innovative product or service. Table 2-4: Cross tabulations Intention Adoption

Continue product already trusted

Try innovative

product

Even if significantly

more expensive

Only if little more

expensive

Only if cost the same

Never buy innovative

product

Very attracted *** ***

Fairly attracted *** ***

Not very attracted *** ***

Pers

onal

inno

vativ

enes

s

Not at all attracted *** ***

(*** p< .01)

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Table 2-5: Regression results, binary logistics

Model 1

Country dummies capturing

differences in social attitudes

Model 2

Cultural values capturing

differences in social attitudes

Model 3

Cultural values, controlling

for differences in income

Coefficient S.E. Wald Odds

ratioCoefficient S.E. Wald

Odds

ratioCoefficient S.E. Wald

Odds

ratio

Intercept -.515*** .080 41.113 .598 -.622*** .122 26.213 .537 -1.178*** .134 77.259 .308

Cultural values

Power distance .013*** .001 237.067 1.013 .017*** .001 330.342 1.017

Individualism .004*** .001 13.430 1.004 .003*** .001 6.817 1.003

Masculinity -.004*** .001 39.586 .996 -.005*** .001 59.901 .995

Uncertainty avoidance -.007*** .001 72.012 .993 -.006*** .001 61.376 .994

Education (primary) 221.239 167.859 159.210

Secondary .308*** .039 62.839 1.360 .230*** .036 41.524 1.259 .240*** .036 45.141 1.272

Tertiary .706*** .048 215.237 2.026 .573*** .045 162.798 1.774 .563*** .045 156.477 1.756

Age (55 and older) 1338.846 1419.525 1432.676

15-24 1.639*** .049 1116.236 5.152 1.620*** .048 1139.143 5.055 1.629*** .048 1147.346 5.098

25-39 .853*** .039 472.000 2.346 .905*** .038 564.161 2.472 .914*** .038 573.021 2.494

40-54 .450*** .038 142.141 1.568 .489*** .037 176.436 1.630 .490*** .037 176.669 1.632

Partner (living with

partner)

Living without partner -.175*** .030 34.678 .839 -.193*** .029 44.040 -.193 -.187*** .029 40.946 .830

Occupation (non-active) 37.399 37.235 35.370

Self employed .249*** .055 20.504 1.283 .294*** .054 29.848 1.342 .293*** .054 29.534 1.340

Employed .182*** .034 29.390 1.200 .145*** .033 19.728 1.156 .136*** .033 17.202 1.146

Gender (male)

Female -.310*** .027 127.210 .733 -.309*** .027 131.746 .734 -.304*** .027 127.058 .738

Living environment

(rural)

44.661

35.579

48.088

Small/medium-sized

town

.172*** .032 29.697 1.188 .147*** .031 23.125 1.159 .157*** .031 26.090 1.170

Large town .206*** .035 34.593 1.229 .180*** .034 28.252 1.197 .221*** .034 42.118 1.248

Country dummies Yes 1118.793 No No

GDP per capita .019*** .002 100.093 1.020

Test statistics

Chi-square test 3488.6*** 2621.3*** 2725.4***

Nagelkerke pseudo R2 .165 .126 .130

Correctly predicted 66.8% 65.4% 65.6%

Sample size 26773 26773 26773

(*** p< 0.01; ** p < 0.05; * p < 0.10) Reference category: Not being attracted to innovations, dependant variable: attracted to innovations. Model 1: Country dummies, no cultural values; Model 2: No country dummies, cultural values; Model 3: No country dummies, per capita GDP, cultural values

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Table 2-5 shows the regression results for 3 models. The first model only includes the different demographic variables and country dummies to explain whether or not an individual is attracted to innovative products and services. The model provides a good explanation of the probability that someone is attracted to innovations. The Chi-square statistic shows that the model with the included dependent variables provides a better fit than a model excluding these variables and almost 67% of the observed values for the independent variable are correctly predicted. Education, age, occupation, living environment, gender and living with a partner are all relevant in predicting whether someone is attracted to innovative products or services.

The second model uses Hofstede’s cultural dimensions to replace the country dummies used in the first regression. The Chi-square statistic shows that this model also provides a good explanation of the probability that someone is attracted to innovations and more than 65% of the observed values for the independent variable are correctly predicted.

Differences in income are expected to explain part of the observed differences in people’s attractiveness to innovative products and services. The Innobarometer 2005 database does not include income data at the level of and the individual and the third model uses per capita income at the country level to control for differences in purchasing power. The regression results are similar to those reported for the second model and in the following discussion we focus on the results of the second model.

Power distance is found to be positively related to a favourable attitude towards innovation. This finding is in line with the common literature on power distance and innovativeness (e.g. Dobre et al., 2009). Furthermore, in line with theory, individualism is found to be positively related to a favourable attitude towards innovation. Uncertainty avoidance is found to be negatively related to innovation attractiveness. This finding is also in line with the literature on culture and innovativeness. The surprising finding is that masculinity is found to be negatively related to innovation attractiveness, meaning that people living in masculine societies are more likely to have an unfavourable attitude towards innovation. This is surprising as the basic proposition assumes that societies with a high degree of masculinity emphasise the importance of symbols and status and are therefore expected to attach a higher value to materialism and be relatively more attracted to innovation as a means to enhance self image.

Education is positively related to innovation attractiveness; that is, the higher the education the more likely that people have a favourable attitude towards innovation. Compared to people with only primary education, those with secondary education are 1.259 times and those with tertiary education are 1.774 times more likely to be attracted to innovations.

Age is negatively related to innovation attractiveness, that is, the higher the age of an individual, the more likely that this person will have an unfavourable attitude towards innovation. Compared to people of 55 years and older, young people between 15 and 24 years of age are more than 5 times more likely to be attracted to innovations. In particular young people feel much more attracted to innovative products and services.

Compared to non-active persons, both self employed and employed persons are more attracted to innovations. People who are living without a partner are less likely to have a favourable attitude

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towards innovation as compared to people who are living with a partner. One possible explanation for this finding might be that single households have less money to spend on innovations. Compared to men, females are found to be less attracted to innovation. This finding is in line with Rogers’ (2003) observations on different groups of adopters. Compared to people in rural areas those living in towns are more attracted to innovations. A possible explanation is that people in urbanized areas are more likely to be acquainted with innovative products and services, e.g. because advertising in urban areas is more intense than in rural areas.

2.5 Attitudes to demand: conclusions and limitations Differences in cultural values explain differences in the probability that an individual is attracted to innovative products and services. In particular in countries characterized with a high degree of power distance and low degrees of masculinity and uncertainty avoidance it is more likely that someone feels attracted to innovations. But the regression results also show that educational attainment, age, gender and living environment are powerful predictors of attractiveness to innovations.

We need to emphasise that one should treat these typologies of ‘general’ attitudes towards innovation with caution. Prior studies have emphasised that consumer attitudes towards innovation vary with the types of innovation. For instance, while consumers are receptive towards innovation in information technology, they might react with suspicion in face of innovations in the field of nanotechnology. Therefore, future studies on innovation attitudes need to design surveys which differentiate between categories of innovation.

Another limitation of the results based on the Innobarometer 2005 is that a very powerful variable as income is not available. Persons with a higher disposable income are more likely to be attracted to innovations as they can afford these more expensive products. Model 3 in Table 2-5 shows that the average person in a more affluent country feels more attracted to innovative products and services. Unfortunately a question on income is not included in the Innobarometer 2005 survey. It is recommended to include such a question in any future survey aiming to better understand peoples’ attractiveness to innovations12. It is also strongly recommended to repeat the Innobarometer survey as results based on 2005 data become outdated as peoples’ attitudes, income and educational attainment change over time, and perhaps even more so during the current financial and economic crisis. The Innobarometer 2005 set of questions on peoples’ attitudes to innovations13 could easily be included in one of the standard Eurobarometer surveys on an annual basis. It is also recommended to include major non-European countries, e.g. the United States, Japan, China and India, to enable comparisons with countries outside of Europe.

12 A question on income could be formulated as follows: What is your total household income? a) Less than €10,000, b) Between €15,000 and €20,000, c) Between €20,000 and €25,000, d) Between €25,000 and €30,000, e) Between €30,000 and €40,000, f) Between €40,000 and €50,000, g) Between €50,000 and €75,000, h) Between €75,000 and €100,000, i) More than €100,000. The income brackets only serve as an example and should be defined based on the actual income distribution in European countries. 13 See Annex 1 for the Innobarometer 2005 questions on being attracted to innovations.

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3 Consumer resistance 3.1 Introduction Most commercial companies experience high rates of innovation failures (Moore, 2002) as consumer demand for innovative products and services remains low. In the previous chapter, we investigated the drivers of innovation adoption. In particular, we focused on the influence of the socio-cultural environment on adoption decision and found that personal innovativeness is a main determinant of innovation adoption. A topic that has received little attention in consumer behaviour and innovation diffusion literature is consumer resistance to innovation (Lapointe and Rivard, 2005). In fact, the notion of ‘resistance’ is often set equal to the more passive notion of ‘non-adoption’ (Penaloza and Price, 1993; Nabih et al., 1997). However, a number of scholars have objected that consumer resistance is not simply the obverse of adoption, but requires detailed theoretical conceptualization and empirical explication (Gatignon and Robertson, 1989, Herbig and Day, 1992; Ram and Sheth, 1989).

Given that many innovations still meet resistance (Garcia and Atkin, 2002, Kleijnen et al., 2009) it becomes crucial to investigate the notion of consumer resistance as an important element in the demand for innovation. Therefore, the purpose of this chapter is to contribute to our current understanding on the notion and drivers of consumer resistance.

3.2 Drivers of consumer resistance Innovation implies a change to consumers, and resistance to change is a common human response. As Ram and Sheth (1989) emphasized, innovation resistance exists across product classes. In fact, consumer resistance can be observed with a diversity of innovations. For instance, consumers expressed moral objections and actively campaigned against genetically modified food (Bredahl, 2001). Also, resistance can occur with regard to simpler innovations, such as when wine drinkers wanted to keep the traditional cork instead of the new screw cap on wine bottles (Garcia and Atkin, 2002).

Ram and Sheth (1989) identified two broad causes of resistance: (1) innovations that require a change in consumers established behavioural patterns, habits, norms and traditions, and (2) innovations that conflict with the consumers’ belief structure.

In particular, Ram and Sheth (1989) identified numerous barriers that may inhibit the consumer’s desire to adopt an innovation. These barriers have been grouped into two categories, namely functional barriers and psychological barriers. Functional barriers are likely to arise if the consumer perceives significant changes or disruptions brought about by the innovation. Psychological barriers are likely to arise through conflict with the consumer’s belief structure.

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Box 1: Barriers to change

Functional barriers:

1. Usage barriers: the innovation is not compatible with existing workflows, practices or habits. Innovations that require changes in customers’ routine require relatively long development process before gaining customer acceptance.

2. Value barriers: consumer needs incentive to change, such as strong performance–to-price value compared with product substitutes.

3. Risk barrier: all innovations, to some extent, represent uncertainty and pose potential side effects that cannot be anticipated. Customers, aware of the risks, try to postpone adopting an innovation until they can learn more about it.

a. Physical risk: harm to person or property that may be inherent in the innovation (e.g. new drugs or genetically modified food are perceived to carry some physical risk or lead to health damage;

b. Economic risk: “the fear of economic loss” (Ram, 1989: 24); the higher the cost of an innovation, the higher the perceived economic risk;

c. Functional risk: “the fear of performance uncertainty” (Ram, 1989: 24); the consumer fears that the innovation has not been fully tested and may not function properly;

d. Social risk: the adoption of an innovation may lead social ostracism or peer ridicule.

Psychological barriers:

1. Tradition barrier: the innovation requires the consumer to deviate from established traditions and daily operations; the greater the required deviation, the greater the resistance. Consumers will resist an innovation that is contrary to one’s family values and social norms.

2. Image barrier: image can relate to brand, product category or country of origin; image barrier originates from stereotyped thinking and hampers the adoption of an innovation.

Source: adapted from Ram and Sheth (1989:9)

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3.3 Types of consumer resistance

3.3.1 The resistance hierarchy Ram and Sheth (1989:6) emphasized that “innovation resistance varies in degrees. Resistance exists on a continuum, increasing from passive resistance or inertia to active resistance.” In fact, Ram and Sheth (1989) differentiated between three types of consumer resistance: (i) postponement, (ii) rejection, and (iii) opposition:

(1) Postponement: Although consumers may perceive an innovation acceptable in general, they still may decide to adopt it at a later point in time, for instance, until circumstances are more suitable (Kleijnen et al., 2009). Therefore, the decision is not final. D’Errico (2005) observed that consumers decide to delay the adoption of an innovation, when they do not regard the innovation as a standard yet and hence are still suspicious of what they perceive as “unproven technology”.

(2) Rejection: Kleijnen et al. (2009:345) emphasize that “rejection is not driven by a simple lack of awareness or ignorance about the innovation on the consumers’ part. Rather this form of resistance implies an active evaluation on the part of the consumer, which results in a strong disinclination to adopt the innovation”.

(3) Opposition: “Consumers may be convinced that the innovation is unsuitable and decide to launch an attack against its adoption” (Ram and Sheth, 1989:6). This can be understood as “innovation sabotage”, where consumers actively engage in strategies, like negative word-to-mouth or public protests to prevent the launch of the innovation (Davidson and Walley, 1985).

Based on these three categories of consumer resistance and on the various functional and psychological barriers, Kleijnen et al. (2009) developed a model of consumer resistance. By means of a qualitative focus group study, their study evaluates the relative importance of each of these barriers for the three types of consumer resistance. The results are summarized in Figure 3-1. Their investigation generated a number of important insights.

First, their study confirmed that the three categories of resistance are indeed distinct in nature and represent a hierarchical pattern. In fact, while postponement relates to more practical concerns, rejection is caused by more societal concerns for maintaining tradition and social norms. Second, their study investigated each resistance type in detail, refining the definitions and establishing which factors lead consumer to postpone, resist or oppose innovations.

Regarding postponement, the study refined the definition to “an active decision to not adopt an innovation at that moment in time” (Kleijnen et al., 2009:352). The study found that economic risk was by far the most influential type of risk and had the greatest impact on postponement as compared to the other types of resistance. The perceived economic risk referred not only to the ability to afford the innovation in the present time or in the future but also concerned the issue whether the innovation would prove to be a meaningful investment in the long run.

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Moreover, “a conflict with existing usage patterns was the other primary driver of postponement (…) essentially, consumers seemed to be unwilling to break with their existing routines to use an innovation” (Kleijnen et al., 2009:352).

Figure 3-1: The resistance hierarchy

Source: Kleijnen et al. (2009)

Based on the focus groups, rejection was defined as the “active decision to not at all take up an innovation which had been introduced to market” (Kleijnen et al., 2009:352). The study identified a number of barriers that resulted in outright rejection of an innovation rather than in postponement. Similar to the case of postponement, conflict with existing usage pattern and economic risk play an important role in consumers’ decision to reject an innovation. However, additional factors were raised by the respondents in the focus group to explain the rejection of an innovation. Prominent factors to cause rejection of an innovation included functional risks and societal risks as well as perceived image such as stereotyped thinking.

Opposition was refined to mean the “actual active behaviour directed in some way towards opposing the introduction of an innovation” and could range from “complaint letters, negative word of mouth, online activities, through to taking protest action against the introduction of a product

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(such as genetically-modified crops)” (Kleijnen et al., 2009:353). Interesting findings were made with regard to the differences in factors causing opposition as compared to the other forms of resistance. Noteworthy, none of the factors causing postponement of an innovation (economic risk and conflict with existing usage patterns) apply to the case of opposition. This implies that “even innovations which are considered to be low in economic risk, and to fit well with existing routines, may still be actively opposed by consumers” (Kleijnen et al., 2009:353).

Similar to rejection, functional and social risk as well as perceived image caused opposition. However, physical risk and conflict with existing traditions were strongly voiced to be the predominant drivers of innovation opposition.

3.3.2 Innovation resistance by mature versus younger consumers An interesting case of the ‘resistance hierarchy’ presented in Figure 3-1, is the issue of innovation resistance among mature and young consumers. While it is often argued that growing age is aligned with increasing resistance towards new products, research has shown that age has in fact a strong but different impact on consumption behaviour. For instance, Leventhal (1997) found that older consumers try new products but that the reasons which motivate older consumers to do so differ considerably from younger consumers. According to his observations, the consumption patterns of older consumers are less affected by topical trends and fashions, which he considers to be typical of younger consumers. Older consumers, so Leventhal (1997), are more driven by a specific personal need.

Developers and vendors of new products have therefore to understand the processes and phases of ageing and their impact on a consumer’s readiness to try new products (Lumpkin et al., 1985). In this regard, two basic ways of ageing are distinguished, biophysical ageing and psychosocial ageing (Kennett et al., 1995; Moschis, 1992).

Biophysical ageing basically affects the speed in which a person can perceive, process and handle information (Kennett et al., 1995), often accompanied by a general decline of physical performance and overall health status. Moschis (1992) enumerates a number of such curtailments that affect the visionary capacity of consumers, such as general changes in visual capacity, loss of acuity, dark adaptation, contrast sensitivity, sensitivity to glare, contradiction in the visual field, decline in colour sensitivity, more light absorption by the retina and a decline in the ability to focus on successive images. In this regard, reader-friendly labels with increased size of characters are a recommendation that is often given to vendors. Services provided through the Internet could improve their attractiveness for older consumers by complying with the World Wide Web Consortium’s (W3C) “Web Content Accessibility Guidelines (WCAG) 2.0”.

As the term suggests, psychosocial ageing can be distinguished between psychological ageing and social ageing. The former relates to the increasing perception of oneself as an old person, the latter relates to the change of social roles that is aligned with ageing, like changing from a life structured by salaried work into retirement (Moschis, 2003).

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The way how people react to ageing and the emotional changes aligned with this process are different, depending on capacities and attitudes of people. Moschis (2003) distinguishes two different perceptions of marketing incentives, personal perceptions and public perceptions. Personal perceptions refer, for instance, to the age a person feels, which might be much younger or older than the biological age. Public perceptions refer to the way how the public sees older consumers. As mentioned above, elderly are often perceived by others as reluctant towards changes and new products, often accompanied by the assumption that the purchasing power of the older generation is relatively limited. However, as Moschis (2003) illustrates, many mature consumers have more purchasing power than younger people, and they are apparently more inclined than younger consumers to purchase luxury goods and products with a well-recognized brand name. In fact, marketing experts in Japan, North America and Europe have recently discovered the high value of the so-called ‘silver market’ or ‘grey market’ (Synovate, 2009; Kohlbacher and Weihrauch 2009).

An empirical study by Laukkanen et al. (2007) offers interesting insight into the innovation resistance by mature consumers as compared to younger consumers. The authors apply the innovation resistance framework developed by Ram and Sheth (1989). Laukkanen et al. (2007) examine innovation resistance among mature consumers in the mobile banking context and compare the reasons for resistance among mature versus younger consumers. Following Ram and Sheth (1989), Laukkanen et al. (2007) measured resistance by means of the five barriers indicated in Box 1 (i.e., usage, value, risk, tradition and image barriers).

Laukkanen et al. (2007) identified value barrier as the strongest hindrance towards the adoption of mobile banking services for both groups, young and older consumers (though it is the most intense barrier for mature consumers). Barriers that affected specifically the older consumers are risk barrier and image barrier, which is strongest pronounced in the form of distrust in input and output mechanisms of information, concerns about the battery life of a mobile phone, fear that PIN codes would be lost and used by unauthorized persons and a general doubt about the usefulness of new technology in general. The strong impact of risk perception on the older consumers is in line with other research, e.g. Brock (1998). Another strong age-related difference found by Laukkanen et al. (2007) is the higher readiness of young consumers for self service innovations.

As Laukkanen et al. (2007) found out, adopting innovations often requires changes in consumers’ existing habits and to develop new ones. Innovation resistance appears therefore as a normal consumer response. The strength of the innovation resistance relies on the size and scope of the change of habits that the innovation implies.

A key result of the study by Laukkanen et al. (2007) is that psychological barriers have a stronger effect on mature consumers than other barriers. The authors draw an important conclusion from this finding, which may raise some concerns regarding technological approaches to overcome older consumers’ reluctance to some innovations. For instance, Dunphy and Herbig (1995) seem to assume that technology is always superior and that consumers must just be educated to enable them to use end benefit from innovations. However, if it is true that psychological factors have a stronger impact on innovation reluctance than technological barriers or other product features this strategy does not appear to be successful. Rather than such technology-driven approaches,

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strategies as suggested by Ram (1989) appear more promising. According to Ram, it is the type of innovation resistance that should determine the strategies to overcome it. An alternative strategy could be, for instance, a communication strategy emphasizing face-to-face contact. Only if innovation resistance is caused by perceived functional or economic risks, an innovation modification strategy (Dunphy and Herbig, 1995) could proof to be more effective.

3.3.3 Innovation resistance among European citizens In 2010, a Eurobarometer survey on Life Sciences and Biotechnology has been conducted among 32 European countries and has yielded interesting insights into the current attitudes towards these technologies. In particular, the report provides illustrative trends with regard to European’s attitudes towards different kinds of technologies. Based on time series data, the report assesses the changes in technological optimism and pessimism over the time period of 1991-2010.

Figure 3-2: Index of optimism about six technologies

Source: Eurobarometer Report (2010)

The countries included have been weighted according to their relative population sizes and reflect the expanding membership of the EU: thus 1991 and 1993 scores are for the original 12 Member States, 1996–2002 for EU15, 2005 for EU25 and 2010 for EU27.

As Figure 3-2 indicates, energy technologies such as wind, solar and nuclear power experience an upward trend14. Probably due to the increased media coverage of climate change, carbon 14 The changes observed over time do not necessarily coincide with the changes in EU membership. Monitoring the same group of 12 Member States between 1991 and 2010 would result in similar patterns.

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emissions and global warming, public optimism towards the contributions of renewable energy sources and nuclear power has increased. At the same time, novel issues have gained public attention. A second trend is visible with regard to the diminishing optimism in biotechnology, ICT and nanotechnology. Especially, with regard to biotechnology and nanotechnology the percentage of respondents indicating ‘making things worse’ has increased from 12 to 20 percent in the case of biotechnology and from to 5 to 10 percent in the case of nanotechnology, expressing a rising pessimism among European citizens with regard to these two technologies.

3.4 Consumer resistance: conclusions and implications Overall, it can be concluded that throughout the various types of resistance, risk plays an important role. Therefore, risk reduction strategies are crucial in diminishing consumer resistance towards innovation. One such risk reduction strategy can be to ensure the availability of information to increase knowledge about potential risks and solutions. However, prior studies have cautioned against elaborate informational campaigns as these might lead to information overload, which in turn can strengthen resistance to innovation (Herbig and Kramer, 1994). In contrast, the study by Kleijnen et al. (2009) indicates that information overload has no influence on resistance. To explain the difference in findings, Kleijnen et al. (2009) point to the fact that the young people in their sample would use more new media channels to actively acquire information rather than rely passively on the information provided by companies, as may have been the case in previous studies (e.g. in the 1980s and 1990s).

In particular, the study suggests that companies should provide tailor-made information to pre-empt consumers’ concern. For instance, companies can use new media as to illustrate of how a new product or service works in virtual environment, thus demonstrating that the innovation can fit in people’s existing living situations and habits.

Moreover, the results of the study by Kleijnen et al. (2009) highlight that decreasing resistance does not call for similar approaches as to increase adoption of innovation. While strategies to increase innovation adoption usually emphasize the benefits of the innovation, a strategy to reduce risk perception cannot rely on emphasizing additional product benefits. The concerns and worries of consumers need to be taken seriously and thus be addressed appropriately. The fact that different drivers have different effect on the resistance types, suggests that companies and policy makers need to develop specific strategies to deal with each type of consumer resistance.

For instance, regarding postponement, conflict with existing usage patterns and the fear of economic loss are the main drivers of delaying the innovation adoption decision. Hence, Kleijnen et al. (2009) recommend using marketing communication strategies which demonstrate how the innovation can fit within the consumer’s current lifestyle. Moreover, Harris and Blair (2006) suggest that innovations should be bundled with products that are already in use by the consumers to demonstrate that the innovation does not cause any conflict with the established lifestyle.

Regarding rejection, economic, functional and societal risks cause the consumer to reject the innovation. Extensive labelling information and increasing the traceability and transparency of

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ingredients or components of the information may support the consumer in his efforts to seek information and make an informed decision. To reduce the perceived functional risk of an innovation, Kleijnen et al. (2009) suggest the use of warranties and quality assurances. To encounter societal risks “the educating of the environment (rather than the actual consumer) is most important. Diminishing social risk can be accomplished by increasing consumer confidence (…) or by (…) changing the perceptions of the environment. Eliciting endorsement and testimonials of celebrities is a commonly suggested strategy” (Kleijnen et al., 2009:354).

Physical risks, the fear of harm and danger brought by the innovation, is the main driver of consumers opposition to an innovation. Testing of innovations by independent institutes might be the most effective strategy to reduce the perception of risks and overcome opposition (Yeung and Morris, 2001).

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4 Attitudes to entrepreneurship 4.1 The importance of entrepreneurship Entrepreneurship is possibly one of the most important drivers of innovation and one of the most difficult to measure. Entrepreneurial activity involves the founding and early-stage growth of new firms, although it can also involve the reinvigoration of established firms. New firms can be created by individuals or spun off from larger firms or from the public research sector. Entrepreneurship involves individual attitudes to risk, opportunities that reduce risk, receptiveness to new ideas, access to sources of new ideas with commercial potential, and access to capital.

Entrepreneurship does not need to involve technological innovation, but can be based on franchising or establishing small businesses such as restaurants, hotels, retail stores, B&B accommodation, construction firms, web or consultant services, etc. However, innovation policy is primarily interested in the creation of innovative firms that develop new technology, use technology in new ways, for example new business models to exploit the capabilities of the internet, or which are based on new organisational structures.

Most indicators of entrepreneurship either measure individual attitudes e.g. to starting a financially risky business or attitudes to self-employment. There are no indicators for entrepreneurship within existing firms, such as the rate of formation of new spin-off firms or the rate of introduction of new products. In addition, indicators of individual attitudes to entrepreneurship do not differentiate between establishing a ‘mom and pop’ shop15 and establishing a firm with an innovative business strategy (Arundel and Hollanders, 2006).

Research on entrepreneurship in Europe is constrained by a lack of relevant and reliable data for all EU Member States16. First, it is difficult to separate non-innovative new firms from innovative new firms, or separate the interest of individuals in establishing ‘mom and pop’ firms from an interest in founding innovative firms. One argument is that all new firms are innovative in some way, but analyses built on this assumption will be of low value for innovation policy. Second, it is difficult to obtain data on entrepreneurship because many potentially innovative new firms are either difficult to detect or their activities don’t show up in official statistics.

There are only a limited number of indicators for entrepreneurship and almost all of them do not focus on innovation. A report on measuring entrepreneurship by the OECD (2009) provides results for ten entrepreneurship performance indicators for 21 OECD countries, but the results are for all types of new firms, with no separation between innovative new firms and other types of new firms. Most of the research on entrepreneurship focuses on finance, institutional factors, trade and patents.

15 A ‘mom and pop’ store is a business that is privately owned and operated, with a small number of employees and relatively low volume of sales. 16 The Panel Studies of Entrepreneurial Dynamics (PSED) and the Kauffman Firm Survey (KFS) provide detailed and reliable data for the US. In the PSED mom and pop businesses are distinguished from others by expressed growth intentions, by the three technology questions from Allen and Stearns, and by the predictions of employment growth five years hence.

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Entrepreneurship has received a lot of attention over the past thirty years ever since Birch’s (1979, 1987) influential contribution on the employment generating role of Small Medium Enterprises (SMEs). Blanchflower (2000) however argues that the economic evidence is not clear and convincing regarding the subject matter. Birch has been criticised convincingly by Davis et al. (1993, 1996) who argue that “conventional wisdom about the job creating powers of small businesses rests on statistical fallacies and misleading interpretations of the data”. The authors point out that they couldn’t find a strong and systematic relationship between the net job growth rate and firm size and second that although SMEs had a higher gross rate of job creation, they did not have a higher net job creation as they also had a higher gross job destruction rate.

Ayyagari et al. (2011) using data on developing economies find that not only do small firms (less than 100 employees) and mature firms (more than 10 years) employ the largest number of people but they also generate the most new jobs, across country income groups. However the authors draw attention to the fact that small firms’ higher employment growth is not accompanied by higher sales or productivity growth. Their findings suggest that large firms and young firms have higher productivity growth.

Two recent NESTA17 reports discuss business growth and contraction in Europe and the United States and the impact of the financial crisis (Bravo-Biosca 2010; NESTA 2011). Bravo-Biosca (2010) makes the case there is less dynamism in European markets as there is less growth and less contraction of businesses compared to the United States. The lack of dynamism is a consequence of less experimentation and a slower reallocation of resources from less to more productive businesses in Europe, both being important drivers of productivity growth (Bravo-Biosca, 2010). There can be both productive and unproductive churn, but the evidence suggests that not only is the rate of churn low throughout Europe, but when it happens it also does not enhance productivity. Action therefore must go beyond a narrow focus on high-growth firms, and investigate more broadly the barriers to contraction and expansion of firms. “Policymakers should encourage an environment that rewards experimentation, penalises inertia and reduces the costs of failure: that is, an economy in which innovative firms experiment with new ideas, exploit new growth opportunities and, if successful, supplant less productive firms, which shrink and exit. This is creative destruction at work” (Bravo-Biosca, 2010). The authors highlight that policies targeting the improvement of venture capital climate will not solve the structural problem as deeper reforms are needed, targeting not only entry barriers removal18, but also the removal of barriers to growth and contraction, such as improving product and labour market regulation, tackling access to finance, and reducing the European market fragmentation that stops businesses, especially in service industries, operating across borders. Furthermore, the financial crisis has negatively affected the availability of capital needed for growth (NESTA, 2011). The 2011 NESTA report highlights that high growth businesses may be assessed as having a lower credit rating by the kind of systems banks use to make commercial lending decisions and the sharp decline in risk capital

17 NESTA is the UK National Endowment for Science, Technology and the Arts - an independent body with a mission to make the UK more innovative (http://www.nesta.org.uk/). 18 Barriers to entrepreneurship have been declining over all OECD countries. Europe made significant progress in converging with the United States.

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funding is a serious concern. Moreover, the 2011 NESTA report argues that high growth businesses can be found across all sectors, and include established firms and start-ups, small businesses and large ones. The report sees growth as a period in a firm’s development which can happen or not, followed by maintenance of a certain size. The report illustrates with examples of case studies of firms that managed to grow after 30 years of existence when demand increased.

Hurst and Pugsley (2011) show that nearly half of the nascent entrepreneurs report providing an existing good or service to an existing market. Hurst and Pugsley (2011) further show that 50% of the nascent entrepreneurs reported non-pecuniary reasons for starting their businesses such as a need for schedule flexibility and independence and 40% indicated that they started a business because they wanted to create a new product or because they had a good business idea and 34% reported they started their business to generate income. The authors also show, using panel data, that small businesses which started for other than innovative reasons were much less likely to subsequently grow, were much less likely to report wanting to grow, were much less likely to subsequently innovate, and were much less likely to report wanting to innovate. The distinction between self-employment and new organizations aspiring to grow seems to be crucial. We could potentially see self employment as entrepreneurship by necessity and distinct from entrepreneurship by opportunity. In the United States, around 4-6% takes action to initiate a business, and 40% of American adults experience bouts of self employment during their life time (Acs and Audretsch, 2003).

Governments attach high hopes to a positive effect of entrepreneurship on economic growth and therefore would like to promote setting up new businesses as well as start-up aspirations (Freytag and Thurik, 2010). Entrepreneurship is seen amongst policy makers as a vital source not only of employment but also of innovation and economic growth (Thornton, 1999). In academic literature however there is no consensus regarding the relationships between entrepreneurship and employment, innovation and economic growth. Freytag and Thurik (2010) emphasize that recent evidence documents a U-shaped relationship between the level of self employment and per capita income (Acs et al., 1994; Wennekers, 2005). This result is supported by recent evidence from the Global Entrepreneurship Monitor (GEM) documenting a similar relationship when using the rate of nascent entrepreneurship or the prevalence of young enterprises (Van Stel, 2005; Wennekers et al., 2005). However, this relationship represents a stylized fact, and any correlation analysis does not imply causality. Furthermore it is based on a cross-sectional data measured at one point in time, panel data would be needed to assess better causality.

Freytag and Thurik (2010) note that earlier research points to a long and secular decline of self employment rates over time (Blau, 1987). Parker (2004: 9-11) points out that the definition of self-employment plays an important role in this observed trend. While self employment including agricultural workers has steadily declined since the 1960s in the US, when one excludes agriculture, one observes a revival in self-employment during the 1970s-1980s, whereas by 2000 the level of self-employment in the US has fallen back to below its 1970s level. We use the COMPENDIA database to get a glimpse of entrepreneurship defined as business ownership rates

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over four decades in Europe19 (Figure 4-1). Business rates are defined as employers and own account workers in the private sector excluding agriculture, fishing and forestry.

In post-communist countries there have been two scenarios: one in which the state owned all the existing companies and the other one in which free markets operated parallel to a planned economy. During the 1970s and 1980s the Eastern bloc started to suffer from severe goods shortages as a result of the planned economy. Among the Eastern bloc nations, Hungary was a pioneer in adopting the free market practicing “goulash communism” which blended elements of a market system with their planned economy. Poland on the other hand, introduced the free market as a shock therapy in 1990s which solved the country’s food shortages; the economy appeared to have stabilized at the price of very high unemployment levels and prices. Czech Republic also underwent IMF shock therapy in 1991, however, a consistent privatization and a good economic management led to a removal of price controls over 1990-1995, low unemployment and a shift in exports from the communist economic bloc to Western markets. Slovakia was established in 1993, and the privatization process went slower and uneven during 1994-1998, while economic growth peaked at 6.5% in 1995 but declined to 1.3% in 1999. Slovakia and Czech Republic offer an ideal scenario where one can identify the effect of policies on entrepreneurship due to their similarity. The dip observed in Slovakia’s business ownership rates between 1996-2000 compared to the Czech Republic, as well as the resurgence between 2004-2009, can be seen as a result of government policy. Due to their former planned economy, in post-communist countries one could expect on the one hand higher passivity and less entrepreneurial spirit, on the other hand if business opportunities are reduced one would expect higher migration as a response to a rise in unemployment.

An interesting case is that of countries like Luxembourg, Japan and France that have declining rates of business ownership over the last four decades. Business ownership rates are higher in developing countries such as Mexico (not shown in graph). However a lot of Latin American countries have high self employment rates due to own account workers and a high rate of informal economy. Szirmai et al. (2011) note that while innovation in developed countries coincides with high R&D intensities, in developing economies, innovation is more imitative and implies technology transfer from developed economies.

In the following section we will discuss some key factors influencing entrepreneurship.

19 The dataset COMPENDIA contains harmonized data on the number of business owners and the business ownership rate (number of business owners as share of labour force) for 30 OECD countries over the period 1970-2007. The acronym COMPENDIA stands for "COMParative ENtrepreneurship Data for International Analysis". Business ownership rates have been made comparable across countries and over time. For that purpose figures from official OECD statistics have been corrected for deviating business ownership definitions and for trend breaks.

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Figure 4-1: Business ownership rates 1972-2009

Large Member States

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1972 197619801984 198819921996 200020042008

France Belgium Germany Sw itzerlandNetherlands

Nordic countries

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1972 197619801984 198819921996 200020042008

Finland Norw ayDenmark Sw eden Iceland

Small countries

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1972 197619801984 198819921996 200020042008

Austria Belgium Ireland LuxembourgSw itzerland

Southern European countries

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1972 197619801984 198819921996 200020042008

Greece ItalyPortugal SpainTurkey

Post-communist countries

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1972 197619801984 198819921996 200020042008

Czech RepublicHungaryPolandSlovakia

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1972 197619801984 198819921996 200020042008

Australia JapanUS CanadaKorea

Source: Entrepreneurs International (COMPENDIA) database, non-agricultural self employment as a percentage of the population 2010.

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4.2 Factors influencing entrepreneurship and innovation There are different strands of research in entrepreneurship across disciplines, and little has been done to integrate the various domains in a coherent framework. Acs and Audretsch (2003) provide an overview of the extent to which the field is interdisciplinary in terms of theories, methods and research outcomes. They emphasize that in psychology research there is a shift away from research on “traits” and personality towards behaviour and cognitive issues and the recognized need to focus on discovery and exploitation of opportunity (Shane and Venkataraman, 2000). In economics there has been a shift towards entrepreneurial choice models (Evans and Jovanovic, 1989) and individuals as agents of change (Audretsch, 1995). Sociology on the other hand emphasizes the role of the environment and environmental factors that affect firm formation (Thornton, 1999). Particular attention has been paid to the role of networks in gaining access to finances, knowledge transfer and establishing firms.

Baumol (1990) emphasized the role of the incentive structure in encouraging productive, unproductive or destructive entrepreneurship throughout the history of social organizations. The incentive structure that Baumol talks about in his famous 1990 article consists of the rules of the game. It is now generally accepted that institutions are the rules of the game in a society and they constrain and shape human interaction (North, 1990:3). Institutions affect the economic performance of economies and have a key impact on the behaviour of potential entrepreneurs. Institutions can be “either formal - such as political and economic rules and contracts or informal such as codes of conduct, or informal – such as codes of conduct, attitudes, values, norms of behaviour, and conventions” (Veciana et al., 2005).

This report aims to shed some light on the role played by informal institutions via norms, attitudes and values. Culture typically consists of norms and values or expectations of behaviour shared by a group, in our case a society20.

Norms offer social standards of what is acceptable and appropriate behaviour in individual’s interactions with each-other. Values are positive or negative judgements (“good” or “bad”) regarding if an actual behaviour is conform to an existing social norm that is perceived as objectively valid (Kelsen and Knight, 1966). Values are distinguished from beliefs which are “judgements about reality which affirm- without a reference to a norm regarded as objectively valid- that something is and how it is” (Kelsen and Knight, 1966). Beliefs are perceptions that certain premises are true. Davidsson and Wiklund (1997) argue that values are more abstract and global psychological evaluations that are relatively distant from specific behaviours, whereas beliefs are more concrete perceptions of attributes or other phenomena.

20 There are different conceptions of culture. Davidsson and Wiklund (1997) give two definitions: a) one way is to associate it with various behaviours that are prevalent in an area and passed from one generation to the next and b) culture has to do with mentality, e.g. values and beliefs that prevail in a society. Davidsson and Wiklund (1997) argue that values are more abstract and global psychological evaluations that are relatively distant from specific behaviours, whereas beliefs are more concrete perceptions of attributes or other phenomena.

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Cultural and social norms persist due to pressure for conformity, as individuals are discouraged from disobeying norms by the threat of social disapproval or punishment and feelings of guilt and shame that result from the internalization of social expectations. Culture and social norms can influence an individual’s attitudes and beliefs. Attitude is a learned predisposition to respond in a generally favourable or unfavourable manner with respect to the object of the attitude (Rosenberg and Hovland, 1960; Shaver, 1987). The object of an attitude can be physical objects, ideas, events, people, places, issues. Attitudes are positive or negative feelings towards an object or idea. Robinson et al. (1991) indicate that attitudes do change more easily and more often than personality traits. Robison (1991) conceptualized entrepreneurial attitudes as having three components: beliefs and thoughts, feelings, and behavioural intentions. Examples of attitudes are satisfaction, job involvement. Attitudes are also determined by perceptions. Perception is a cognitive process: lets a person makes sense of stimuli in the environment and it helps a person to adapt to a changing environment. If someone perceives positive attributes the individual is more likely to develop a positive attitude, if someone perceives negative attributes they are more likely to develop negative attitudes. Attitude formation is influenced by family upbringing, peer groups, work groups, and general social experiences. Although there is some connection between attitudes and behaviour, this connection is not strong. People with strong attitudes would likely behave in accordance with their attitudes, which means that the intensity of an attitude is important. People do not always accordingly to their attitudes, and attitudes can change as a result of social norms, persuasive communication or cognitive dissonance.

Models such as the theory of reasoned action (Fishbein and Ajzen, 1975) and the theory of planned behaviour (Ajzen, 1985) use attitudes (as well as social norms and perceived behavioural control) as behaviour prerequisites via intentions to perform particular behaviours. Attitudes could be seen as pre-requisites of preferences. The concept of preferences comes from economics and it implies a choice amongst alternative bundles of goods. The consumer behaviour model is based on the following premises (Perloff, 2009): a) individual tastes and preferences determine the amount of pleasure people derive from the goods and services they consume (utility), b) consumers face constraints or limits on their choices (budget constraint), c) consumers maximize their well-being or pleasure from consumption subject to the constraints they make. Economists generally summarize consumer’s preferences by assigning a numerical value to each possible bundle to reflect the consumer’s relative ranking of these bundles. Utility is a set of numerical values that reflects the relative rankings of various bundles of goods. Most economists assume that preferences are fixed in time and do not change. Based on their preferences and opportunities, agents make occupational choices. Based on their preferences and opportunities individuals make occupational choices.

Scholars argue that entrepreneurial variations are best understood by considering the social environment in which the firm is created as entrepreneurship is essentially a social phenomenon which has a social and cultural dimension (Berger, 1991; Shapero and Sokol, 1982; Steyaert, 2007; Thornton et al., 2011). Shapero and Sokol (1982) emphasize that “the social and cultural factors that enter in the formation of entrepreneurial events are most felt through the formation of individual values systems. More specifically in a social system that places a high value on the formation of new ventures more individuals will choose that path… More diffusely a social system

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that places a high value on innovation, risk-taking and independence is more likely to produce entrepreneurial events than a system with contrasting values.” Max Weber’s work on the role of Protestant ethics in fostering capitalism and industrialization started a tradition in sociology which focuses on the role of values in economic growth. In short Weber argued that certain aspects of the Protestant moral code led to striving for profit with no other goal than reinvestment, and hence capital accumulation, on the part of the employers. McClelland (1961) builds on Weber’s work and emphasizes that the diffusion among the population of a psychological complex of motives and the need for achievement determined variations in the pace of economic development across countries and within a country over time.

There are different conceptions of culture. Davidsson and Wiklund (1997) give two definitions: a) one way is to associate it with various behaviours that are prevalent in an area and passed from one generation to the next and b) culture has to do with mentality, e.g. values and beliefs that prevail in a society. Davidsson and Wiklund (1997) argue that values are more abstract and global psychological evaluations that are relatively distant from specific behaviours, whereas beliefs are more concrete perceptions of attributes or other phenomena.

The literature on social and cultural factors has expanded with Hofstede’s (1980) work on cultural values dimensions such as power distance, individualism, masculinity, uncertainty avoidance and long term orientation. Hofstede presents a concise taxonomy of significant cultural dimensions for explaining the behavioural preferences of people in business organizations. In general researchers have hypothesised that entrepreneurship is facilitated by cultures that are high in individualism, low in uncertainty avoidance, low in power distance, and high in masculinity. Ceteris paribus, the greater the cultural distance from this ideal type, the lower the average individual and aggregate levels of entrepreneurship (Hayton et al., 2002). His theory has been the predominating research approach (cf. Hayton et al. (2002) for an overview of several studies). Shane (1992) investigated the relationship between Hofstede’s measures of national culture and inventiveness and found that individualistic and non-hierarchical societies were more inventive than others. He also found that individualism is positively associated and power-distance is negatively associated with national innovation rates, even after adjusting for the national wealth. Lynn (1991) also provides empirical support for a relationship between certain aspects of national culture (competitiveness and valuation of money) and economic growth.

Davidsson and Wiklund (1997) find that cultural and structural determinants are correlated and they suggest that to the extent that cultural variation is the real cause for variations in new firm formation rates, studies that use only structural (i.e. economic and socio-demographic) explanatory variables may exaggerate the influence of the latter. Therefore, the authors draw attention that the theoretical interpretations as well as the policy prescriptions that are derived from such studies may be at least partly wrong. The authors attempted to control for structural factors (small firm density, absolute population, population density, population growth, unemployment level and trend, and support expenditure) and found little cultural variation in Sweden regions.

However recent incorporation of entrepreneurship into the mainstream economic literature meant more focus on the legal institutions and an emergence of an institutional approach (Licht and Siegel, 2006). Factors such as bankruptcy laws, employment protection regulation, the tax system,

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welfare system (unemployment benefits generosity and duration), finance opportunities can influence entrepreneurship (Freytag and Thurik, 2010; Armour and Cumming, 2008; Fogel et al., 2008 in Casson et al., 2008; Djankov et al., 2008; Robson, 2007). The quality of institutions plays an important role in the decision to become an entrepreneur. Trust and corruption are a societal reflection of the quality of institutions. Entrepreneurs need to be able to trust their sources of information, earn the trust of their financiers and build trusting relationship with transacting partners (Fogel et al., 2008). Entrepreneurship requires long term transactions under conditions where information-based skills are often untenable because information asymmetry, moral hazard, adverse selection and agency problems undermine transactional trust (Fogel et al., 2008). Fogel et al. (2008) emphasize the role of limited and well-defined rules and regulations, well-protected property rights, good government, and an efficient and effective judicial system in promoting transactional trust and entrepreneurship. Djankov et al. (2004) document the variation in entry costs across countries and highlight that high entry costs are more likely in corrupt countries. Corruption increases the price of starting a business a business and makes failure more likely. Corruption negatively affects the chances of survival of a business.

Microeconomic models of entrepreneurial behaviour investigate the role of objective variables as well as subjective preferences and perceptions as variables influencing the decision to found a new business (Koellinger et al., 2005). Among objective variables are liquidity constraints, conditions in the labour market, age, gender education. The probability of starting a business has been shown to increase with age up to a threshold point and to decrease thereafter, men are more likely to start a business and education has been shown to correlate negatively with the probability of self-employment except in some developed economies where post graduate training has been shown to have positive effects (Koellinger et al., 2005).

Economists emphasize the role of perceptions in starting your own business such as: alertness which is the ability to perceive unexploited opportunities, self-confidence, self-efficacy (internal locus of control), the need for achievement and overconfidence (Licht 2010; Koellinger et al., 2005; Kirzner, 1973, 1979). Koellinger et al. (2005) emphasize that under uncertainty perceptions may be considered as a mediator between preferences and behaviour and affecting both probabilities and outcomes.

Risk attitudes and ambiguity aversion also affect the entrepreneurial decision, however the causality of the relationship is still unclear as subjective risk perceptions may be systematically distorted by prior gain and losses made by the individual and a person might accept a higher risk if they know other entrepreneurs who reduce their ambiguity regarding the outcomes of an entrepreneurial occupation (Koellinger et al., 2005). Caliendo et al. (2009) shows that risk attitudes have an impact on the decision to become self-employed for employees but that they play no role in the decision to become self-employed for individuals being unemployed or inactive. The unemployed may be pushed into self-employment regardless of their risk aversion, while employees do not leave their relatively safe jobs if they are too risk averse. Ambiguity can also be reduced if the person grew up in a family of entrepreneurs. Exposure to information via social networks or family has been shown to influence both risk taking and other attitudes such as self-efficacy, self-confidence as well as cognitive skills of managing a business.

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Innovative entrepreneurs could be more likely to have a higher tolerance for risk than non-innovator entrepreneurs who typically repeat the actions of their peers and are less likely to explore their environment. Rolfe (2010) emphasizes that employers are seeking now workers with risk taking and risk management skills, communications skills and independent thinking in order to be able to promote innovations in firms. She highlights that “Risk taking is essential to innovation: anyone developing a new product, service or idea risks the possibility that it will not work, that someone else will get there first or it will be met with disinterest.” Therefore, innovation requires: capacity for innovation and creativity, exploring risks and rewards to make good decisions, taking risks in ways that are responsible, developing a positive attitude towards exploration and experimentation (Rolfe, 2010).

Although Koellinger et al. (2005) see entrepreneurship as a one period game with little learning chances and uncertainty of outcomes, the management literature emphasized the role of experience in business start-up and the fact that entrepreneurs are likely to learn from having a job or past entrepreneurship experiences. For multiple learning chances, tolerance to failure is extremely important and resilience. Tolerance to failure is essential in learning to take risks (Rolfe, 2010). Recent data from the OECD (2010) shows that countries differ in opportunity recognition and fear of failure suggesting that incentive structures, institutions and information play a role in the formation of social perceptions of risk. Landier (2005) explains the impact of the “stigma of failure” on entrepreneurs that suffer a bankruptcy and shows how this mechanism can be self reinforcing, perpetuating the status quo. He uses a model of asymmetry of information to illustrate the link between the type of culture and social mechanisms. Entrepreneurs in more conservative cultures pursue suboptimal but safe projects and if they fail the social mechanism interprets this information as revealing their quality and competence and so arises the stigma of failure. This perpetuates safe but suboptimal solutions in those cultures. In more experimental cultures, entrepreneurs will pursue riskier projects with higher payoffs but also higher failure rates and there would be a higher tolerance to failure. Therefore, a failure event conveys less information about the quality of that entrepreneur, given the risk that was incurred.

Subjective preferences and perceptions about one’s environment and the individuals’ relative position in that environment, status, also play a role. Country specific factors that influence employment choices, factors that underline the incentive structures and information upon which individuals make their choices also have an influence on the probability to become an entrepreneur. Casson (1993) highlights that “a community that accords the highest status to those at the top of hierarchical organizations encourages ‘pyramid climbing’, while awarding high status to professional expertise may encourage premature educational specialization. Both of these are inimical to entrepreneurship. The first directs ambition away from innovation (rocking the boat), while the second leads to the neglect of relevant information generated outside the limited boundaries of the profession. According high status to the ‘self-made’ man or woman is more likely to encourage entrepreneurship.” Dominance by hierarchical organizations that requires respect for status and ladder climbing discourage entrepreneurship whereas rewarding meritocracy and self-made successful entrepreneurs encourage entrepreneurship (Casson, 2003).

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After having discussed the importance of entrepreneurship and key factors influencing entrepreneurship the following section will discuss the wide variety of entrepreneurship definitions used in scientific literature and more practical definitions to be used in existing datasets.

4.3 Defining entrepreneurship

4.3.1 Entrepreneurship definitions in scientific literature There are a wide variety of definitions available and there is no agreement in scientific literature on what constitutes entrepreneurship. “There is a proliferation of theories, definitions, and taxonomies of entrepreneurship which often conflict and overlap, resulting in confusion and disagreement among researchers and practitioners about precisely what entrepreneurship is “(Parker, 2004:5).

Most of the attempts to define entrepreneurship focus either on a) functions or tasks (what does an entrepreneur do), b) psychological traits or attitudes peculiar to entrepreneurs (how does an entrepreneur think or act), c) firm and/or firm characteristics such as firm size, age (SMEs, high growth, start-ups) or d) defining entrepreneurship as a multidimensional phenomenon and by giving a too broad definition eluding the question. To illustrate, we adapt a list of definitions from Davidsson (2005):

• Lazear (2005) argues that entrepreneurs must be distinguished from self employment simply because “choosing to be an entrepreneur requires an understanding of a variety of business areas. An entrepreneur must possess the ability to combine talents and manage those of others”. Whereas self-employment is more predominant in particular industries and occupations, entrepreneurship occurs across industries.

• Entrepreneurs are those who are willing “to buy at a certain price and sell at an uncertain price” (Richard Cantillon cited in Swedberg, 2000).

• The objective probability of ‘risk’ can be calculated while ‘uncertainty’ can never be known. Knight (1921) views the entrepreneurial profit as a gain resulting from handling uncertainty and not from calculating predictable risk (Casson, 2010; Swedberg, 2000).

• A purposeful activity to initiate, maintain and aggrandize a profit oriented business (Cole 1949).

• Taking advantage of opportunity by novel combinations of resources in ways which have impact on the market (Wiklund 1998).

• The process by which individuals - either on their own or inside the organization - pursue opportunities without regard to the resources they currently control (Stevenson and Jarillo, 1990).

• The process of creating something different with value by devoting the necessary time and effort; assuming the accompanying financial, psychological and social risks; and receiving the resulting rewards of monetary and personal satisfaction (Hisrisch and Peters, 1989).

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• Entrepreneurship is about the “discovery and exploitation of opportunities” (Shane and Venkataraman, 2000).

• Entrepreneurs are “persons who are ingenious and creative in finding ways that add to their own wealth, power and prestige” (Baumol, 1990). Not all opportunity exploitation is in society’s best interest, there is productive entrepreneurship and destructive entrepreneurship that can retard economic development.

• Entrepreneurship is associated with innovative and change-oriented behaviour, task-related motivation, expertise and gain for self (Drucker, 1985; Bull and Willard, 1993).

• Entrepreneurs are those persons (business owners) who seek to generate value through the creation or expansion of economic activity, by identifying and exploiting new products, processes or markets (OECD, 2009).

• New entry (Lumpkin and Dess, 1996).

• The creation of new enterprise (Low and MacMillan, 1988).

• The creation of new organizations (Gartner, 1988).

• Entrepreneurship is a multifaceted activity, covering a multitude of activities from large scale new firm creation via developing new business models within existing firms to more flexible employment relationships for a single individual via self-employment (Estrin et al., 2011).

• Entrepreneurship is a multidimensional phenomenon spanning different units of observations: individual, firm, region, industry and nation (Thurik and Grilo, 2008; Davidsson 2004).

Aldrich’s (2005) classification of entrepreneurship definitions (Table 4-1) underlines the pitfalls of using different types of definitions. Aldrich’s classification follows closely the debate with regards to defining entrepreneurship between different disciplines. Sociological papers see entrepreneurship as mainly the creation of a new organization and the analysis takes place at the individual level or firm level focusing especially on the role of networks. Psychology papers are interested in the mental processes of an individual and therefore are more likely to frame entrepreneurship in terms of cognitive processes, or psychological traits such as creativity, some are exploring motivation or the intention to start a business. Economics is mostly interested in firms and the processes underlying employment creation and growth, therefore economists are more likely to frame entrepreneurs as innovators following the Schumpeterian tradition.

Taking the size of the firm as a definition poses three problems: a) the cut-off point is arbitrarily defined21, b) firm sizes vary by industry and c) not all entrepreneurs run small firms. Similarly defining entrepreneurship as high growth firms ignores the fact that firm size fluctuations (growth and contraction) are the result of a dynamic process and an outcome.

21 Taking the cut-off point of at least one employee suffers from the same problem. It ignores that firms can grow and that growth is a process.

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Table 4-1: Competing interpretations of the term entrepreneur Interpretation Problems posed Small and medium size enterprises Firm-size definitions are arbitrary and industry specific. Not all entrepreneurs

run small firms, and not every small firm is run by an entrepreneur (Parker, 2004:5)

High growth and high capitalization Selection bias: growth is an outcome; high capitalization does not guarantee high growth (e.g. Carland et al., 1984)

Innovation and innovativeness Selection bias: difficult to classify acts as innovative a priori; does not distinguish field of entrepreneurship from general field of business management (e.g. Schumpeter, 1912; Kanter, 1983; OECD, 2009)

Opportunity recognition Turns entrepreneurship into a problem within cognitive psychology (e.g. Shane and Venkataraman, 2000)

Creation of new organizations Difficult to determine when new social entities emerge: focus on boundaries, intentions, exchange and resources (e.g. Katz and Gartner, 1988)

Adapted from Aldrich, H.E., (2005), “Entrepreneurship”, in: Smelser, N., J., and R. Swedberg (Eds.), Handbook of Economic Sociology, Princeton University Press.

We agree with Aldrich (2005) that there is a selection bias in using growth of an enterprise as an indicator of entrepreneurship. However, Lazear (2005) argues that entrepreneurs must be distinguished from self-employment simply because “choosing to be an entrepreneur requires an understanding of a variety of business areas. An entrepreneur must possess the ability to combine talents and manage those of others”. In contrast, self-employed individuals who usually work alone do not require the kinds and combinations of skills that are necessary for real entrepreneurship. Whereas self-employment is more predominant in particular industries and occupations, entrepreneurship occurs across industries. It does seem intuitive that having the aspiration to grow the enterprise, an entrepreneur will invest more in a diverse set of skills, and that the firm size at time t does not capture this growth aspiration as it usually depends both on how successful an entrepreneur manages to be and on the institutional set up.

Schumpeter’s definition of the entrepreneur as an innovator and the entrepreneurship process as “creative destruction” leading to renewal of industries, regional and national economies, equates entrepreneurship with innovation. There are several concerns with this type of definition. The first concern is that there is a selection bias and it implies that all entrepreneurial acts are classified as innovative a priori. “Not every start-up is a Schumpeterian “new combination” and individuals choose to start a business not only because they want to seize newly opened technological opportunities, but also for a multitude of other reasons as well (mediocre labour market prospects, continuation of family business, industry specificities and so on)” (Sanditov and Verspagen, 2011). The second concern is an epistemological one that followers of the Schumpeterian tradition in fact equate entrepreneurship with innovation22. If entrepreneurship is more broadly defined then it is

22 To illustrate we give the definition of innovation and a recent definition of entrepreneurs. A broader approach refers to innovation as “the development of new products, new processes, new sources of supply, but also the exploitation of new markets and the development of new ways to organize business” (Szirmai et al., 2011). The OECD (2009) definition highlights that “entrepreneurs are those persons (business owners) who seek to generate value through the creation or

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clear that not all entrepreneurs are innovative. Adopting a broader definition allows one to explain the phenomena such as the diffusion of innovation and innovation within existing companies. Innovation is not entirely a parallel concept to entrepreneurship as innovation also happens within existing companies.

Opportunity recognition focuses on psychological traits or attitudes peculiar to entrepreneurs. First opportunities are not only a matter of cognitive processes they are also dependent on the economic environment. There are more opportunities in metropolitan than in rural areas. Second, not everyone who seeks opportunities starts their own business, for example migrants can be seen as one category that recognizes and seek opportunities.

We take creating a new organization or economic activity, either in the past or now, as a working definition for entrepreneurship23. Focusing on the creation of new organizations disregards entrepreneurial efforts within an already existing organization: corporate entrepreneurship, intrapreneurship, corporate venturing, strategic renewal, spin-offs for ideas generated within organizations (Hayton et al., 2002). However, we see the creation of new departments within existing organizations, and growth within existing companies as outcomes rather than defining entrepreneurship.

4.3.2 Self-employment as a measure of entrepreneurship In practice, it is easier to measure entrepreneurship as self-employment, as the data is more easily available. The self-employed are individuals who earn no wage or salary and who derive their income by exercising their profession or business on their own account and at their own risk (Parker, 2004:6). Most applied labour economists use self-employment as a measure of entrepreneurship on the grounds that the self employed fulfil the entrepreneurial function of risk bearing. Others in the spirit of Lazear (2005) argue that in addition to risk bearing, managing and combining the talents of other people distinguish entrepreneurs from self-employed. We proxy entrepreneurship as business ownership and own account workers (Parker, 2004). For an in-depth discussion of definition and measurement issues we refer to Parker (2004:5-8)24.

Parker (2004:8-11) highlights two stylized facts: 1) that self-employment rates are higher on average in developing than developed countries and 2) the inclusion or exclusion of agricultural workers in the calculation of self-employment rates makes a difference in self-employment rates in most (but not all) countries. A study by the European Foundation for the Improvement of Living and Working Conditions (Pedersini and Coletto, 2009) on self-employment trends in Europe highlights

expansion of economic activity, by identifying and exploiting new products, processes or markets”. If one looks at the OECD definition and the definition of innovation, the two terms coincide. 23 This definition includes social entrepreneurship. 24 Parker (2004:7) highlights that there are cases which would qualify for a “grey area“ in between paid self-employment and self-employment and that this might be a concern for policy makers. Some workers classified as self-employed are effectively employees being „periphereal“ workers subordinated to the demands of one client firm, employers actively seeking to organize their workforce in self-employment contracts, to cut costs and avoid social benefits entitlements. This might be the case particularly in construction industry, and it is of public policy concern to the extent that self-employed have contracts in worse tems than employees, lacking job security, entitlement to holiday, sick pay, employment protection, or trades and union rights (Parker, 2004:7).

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that own-account workers are common in traditional sectors such as agriculture, forestry and fishing, retail trade and crafts, construction and transports and also in the liberal professions25.

Figure 4-2: Self-employment types

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Source: Eurobarometer Entrepreneurship Survey 2004, 2007 and 2009, own calculations. Note: self-declared occupation as a percentage share of total employment.

We also note as Parker (2004) and Lazear (2005) did, that self-employment seems to be more common in particular occupations such as farmer, fisherman or forester and amongst professionals such as lawyers, doctors and accountants etc. However, the aspirations to grow cannot be linked to a particular industry, occupation or self-employment type. Even a lawyer can expand his business with associates; a doctor can set up a private clinic etc. Based on the Eurobarometer Entrepreneurship Survey (pooled data for 2004, 2007 and 2009) we see that among self-employed we can distinguish among different types (cf. Figure 4-2 showing a breakdown of self-employment into company managers, shop owners and craftsmen, self-employed professionals, other self-employed and farmers, fishermen and foresters). E.g. self-employment in agriculture appears to have a huge impact on the calculation of self-employment rates in Austria, Finland, Greece, Iceland, Ireland, Lithuania and Poland and shop owners represent a high rate of self-employment in Germany, Greece, Italy and Spain.

25 “Freelance work is an established feature of the media sector, including press and the film industry. With the growth of information and communication technologies (ICT), self-employment has spread to activities such as graphic design, web-based ventures and entertainment. Both widespread company restructuring and the impact of ICT have increased the use of subcontracting, including to micro-enterprises and self-employed workers” (Pedersini, R. and Coletto, D., 2009).

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Figure 4-3: Self-employment types by employees

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AT BE BG CY CZ DK EE FI FR DE GR HU IE IT LV LT LU MT NL NO PL PT RO SK SI ES SE UK

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Source: Eurostat, ‘Employment by sex, age groups and professional status (1000)’ calculated by Pedersini, R. and Coletto, D. (2009).

The distinction between self-employed with employees and without employees is important in order to better asses labour market conditions, but it should be used to carefully interpret the data rather than as an ad-hoc measurement of entrepreneurship. We note that the highest rate of self-employment is in Greece (Figure 4-3) but 79% of the self-employed in Greece do not employ other employees and their risk of poverty is 4 times higher compared to paid employees26 suggesting that self-employment either stands for underemployment or is an alternative to unemployment. Also Greece has a high number of unpaid family workers27.

Sanditov and Verspagen (2011) report that “Parker (2009) formulated several stylized facts based on existing empirical studies in developed countries: most start-ups are founded by employed persons, the share of individuals starting their own business is higher among unemployed than employed, and unemployed persons are more likely to stay unemployed or find a job than to start a business.”

The self-employment rate can be seen as a static measure, and it captures only the net effect of exits and entries of companies. A dynamic measure is that of churn which comprises enterprises births and deaths (e.g. nascent and former entrepreneurs). Figure 4-4 shows both the static measure of entrepreneurship and the dynamic one. Hungary, Portugal and Latvia have a high percentage of churn, and enterprise deaths are significantly higher than enterprise births in Latvia and Portugal. Enterprises survival and growth can be seen as outcomes of a dynamic measure of entrepreneurship.

26 Table 2, Survey on Household Income and Living Conditions (EU-SILC 2003). Data processed by Eric Gazon http://www.eurofound.europa.eu/comparative/tn0801018s/gr0801019q.htm 27 Table 3, ESYE, LFS 1st trimester 2007, http://www.eurofound.europa.eu/comparative/tn0801018s/gr0801019q.htm

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Figure 4-4: Entrepreneurship as a dynamic measure

Dynamic measure of self-employment % out of active enterprises 2004-2006

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AT BE BG CZ DK EE FI DE HU IT LV LT LU NL NO PT RO SK SI ES SE UK CH EU20

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Source: Eurostat and OECD Project on Entrepreneurship Indicators.

Whereas the OECD-Eurostat data provides a good picture of the dynamics of entrepreneurship, the Eurobarometer measures accurately only start-ups and current entrepreneurs. The concept of “former entrepreneur” combines in one measure all the people who have ever had a business and sold it or closed it. Therefore the former entrepreneur is a longer span measure compared to enterprise deaths. Looking at a longer span, we see that the highest percentage of entrepreneurs is observed in China: more than 40% of the population has or had had a self-employment spell during their life course (Figure 4-5. The US average of 35% is similar to Iceland, and also in Finland, Greece, Norway and South Korea at least 30% of people have had entrepreneurial experience at some stage in their life.

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Figure 4-5: Self-employment dynamics based on Eurobarometer 2004-2009

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Source: Flash Eurobarometer 2004, 2007, 2009, own calculations.

4.4.3 Preferences to being self-employment The 2004, 2007 and 2009 Eurobarometer Entrepreneurship Survey (EES) ask respondents in each of the EU27 Member States, Croatia, Iceland, Norway, Switzerland, Turkey, China, Japan, South Korea and the United States for their preference for being either self-employed or being an employee28. We pooled the 2004, 2007 and 2009 ESS results to obtain average scores for 2004-2009. Highest rates of preference for being self-employed are observed in Iceland, Portugal and the US (Figure 4-6). For the EU27 the average rate is 43.5% or almost 17%-points below that of the US which clearly signals that people in Europe have a much lower preference of being self-employed. The highest preference for being self-employment is recorded in China. The EES 2007 report states that “the preference for self-employment decreases with age but increases with the amount of time spent in education”. Also men, people already self-employed and those having parents who are self-employed express a higher desire to be self-employed. These results suggest that educational experience and having been exposed to self-employment are relevant policy areas as age and gender are factors which policy cannot influence.

28 The EES asks respondents “Suppose you could choose between different kind of jobs, which one would you prefer … 1) being an employee, 2) or being self-employed, 3) none of these”.

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Figure 4-6: Preference for being self-employed

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Source: Eurobarometer Entrepreneurship Survey 2004, 2007 and 2009, own calculations.

However, there is a difference between wanting to be self-employed and actually being self-employed. Eurostat Labour Force Survey data for 2004-2007 show that the highest share of self-employment is observed for Greece, followed by Turkey and Italy and the lowest share for Denmark, Estonia, Luxembourg and Norway (Figure 4-6). We also see that in all countries more than half of those being self-employed own a one-person business without employing any employees. In Czech Republic, Iceland, Norway, Poland, Romania, Slovakia, UK and Turkey the share of self-employed without employees is 75% or above as compared to 69% for the EU27.

Figure 4-7: Rate of self-employment with and without employees

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40

45

AT BEBGHRCY CZDK EE FI FRDEGRHU IS IE IT LV LT LUMKMTNL NOPL PTROSK SI ES SECHUK TR EU2750%

55%

60%

65%

70%

75%

80%

85%

90%

95%

Share of self-employment w ithout employees (% total employment)Share of self-employment w ith employees (% total employment)

Share of self-employment w ithout employees (% of total self-employment)

Source: Eurostat, Labour Force Survey 2001-2007, own calculations.

Self-employment is being explained by many factors, including economic opportunities and an institutional framework facilitating the start-up and growth of small companies. One would expect

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that in those countries where people have a more favourable attitude to self-employment actual rates of self-employment would also be higher. The scatter plots in Figure 4-8 seem to confirm this relation; in countries with a more favourable attitude to self-employment both the rate of self-employment with employees and self-employment without employees is higher. The latter is an important observation as there is a policy interest in firms to grow and only firms with employees can actually grow and employ more employees.

Figure 4-8: Preference for being self-employed

SELF-EM PLOYED WITH EM PLOYEES

CY

FRPL

BEPT

GR

EE

ES

LT

LV

HUDE

FI

ATIE

DKSE UKLU

NL

IT

M TCZ

SI SK

0123456789

10

30 35 40 45 50 55 60 65

PREFERENCE TO BE SELF-EM PLOYED

SELF-EM PLOYED WITHOUT EM PLOYEES

CY

IS

NO

SK

SI

CZ

M T

IT

NL

LU

UK

SE DK

IE

ATFI

DEHU

LV

LTES

EE

GR

PT

BE

PL

FR

0

5

10

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30 35 40 45 50 55 60 65

PREFERENCE TO BE SELF-EM PLOYED

4.4.4 Rate of entrepreneurship In section 4.3.1 we defined “creating a new organization or economic activity, either in the past or now” as our working definition for entrepreneurship. For calculating the rare of entrepreneurship we can use two sources. The first is the Global Entrepreneurship Monitor (GEM) which is the largest survey-based study of entrepreneurship in the world and covers more than 80 countries. We use the publicly available 2001-2008 waves of GEM as more recent data are not available at the time of conducting the analyses for this study29. The second source is the Eurobarometer Entrepreneurship Survey (EES) from 2004, 2007 and 2010. The EES asks people among others for their preference to be self-employed and their risk attitudes to entrepreneurship, as well as cultural values.

Using GEM data an entrepreneur is defined as a nascent entrepreneur involved in starting a company or as a company owner30. As shown in Figure 4-9 there is relatively low entrepreneurial

29 In this study we use data up until 2008as full GEM datasets are currently available in the public domain for 1999 - 2008. GEM data are made available to the public three years after the end of an annual data collection cycle (http://www.gemconsortium.org/about.aspx?page=gem_datasets). 30 Using the terminology from the GEM questionnaire, entrepreneurs are defined as either bstart = 1 (You are, alone or with others, currently trying to start a new business, including any self-employment or selling any goods or services to others) or ownmge = 1 (You are, alone or with others, currently the owner of a company you help manage, self-employed, or selling any goods or services to others).

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activity in most European countries as compared to most of the non-European countries, in particular Brazil, Canada, China, India and South-Korea where the rate of entrepreneurship is close to 25% and relatively close to those in Brazil, China and South Korea.

Figure 4-9: Rate of entrepreneurship (GEM)

0

5

10

15

20

25

30

35

40

45

ATBEHRCZDK FI FRDEGRHU IS IE IT LV NLNOPL PTRORS SI ES SECHTRUK EU AUCA JPKRUS BRCN IN RUSA

Source: Global Entrepreneurship Monitor, 2001-2008, own calculations.

We use EES data to construct entrepreneurship rates by combining the following questions:

• Have you ever started a business or are you taking steps to start one?

• If yes: How would you describe your situation?

1. You are currently taking steps to start a new business

2. You have started or taken over a business in the last three years which is still active today

3. You started or took over a business more than three years ago and it is still active

4. Once started a business, but currently you are no longer an entrepreneur since business has failed

5. Once started a business, but currently you are no longer an entrepreneur since business was sold, transferred or closed

Entrepreneurs are those respondents who answered yes to options 1, 2, or 3, thus those respondents who either already started a business (company owners) or are in the process of starting a business (nascent entrepreneurs).

The rate of entrepreneurship in Europe is high in Cyprus, Finland, Greece, Iceland, Norway and Turkey (Figure 4-10). The EU27 rate of entrepreneurship is well below that in China and the US. The rate of nascent entrepreneurship is highest in China and the US and very low in Belgium, Bulgaria and Malta. In China and Turkey the rate of nascent entrepreneurship is higher than the rate of company owners, which suggest much lower survival rates in these countries.

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Figure 4-10: Rate of entrepreneurship (EES)

0

5

10

15

20

25

30

ATBEBGHRCYCZDK EE FI FRDEGRHU IS IE IT LV LT LUMTNLNOPL PTROSK SI ES SECHTRUK EU JPKRUS CN

Nascent entrepreneur Company ow ner

Source: Eurobarometer Entrepreneurship Survey 2004, 2007 and 2009, own calculations.

The entrepreneurship rates using GEM and EES data are different (albeit correlated at about 75%). Differences are due to the fact that the questions in both questionnaires are not the same and also as we used data for 8 years for GEM but only the 2007 data for EES.

A further distinction can be made between entrepreneurs who started their business because they saw an opportunity to do so or those who started their business out of necessity. Entrepreneurs out of opportunity take the initiative to start a company as they willingly seek new challenges by competing with existing company owners. Entrepreneurs out of necessity might be forced into entrepreneurship not because they seek new challenges but because they lost their previous paid job. There is a clear difference between Europe and Asia where entrepreneurship out of opportunity prevails in Europe and entrepreneurship out of necessity prevails in China, Japan and South Korea (Figure 4-11).

Figure 4-11: Entrepreneurship out of opportunity or necessity

0102030405060708090

100

ATBEBGHRCYCZDKEE FI FRDEGRHU IS IE IT LV LTLUMTNLNOPL PTROSK SI ESSECHTRUK EU JPKRUS CN

Out of opportunity Out of both Out of necessity

Source: Eurobarometer Entrepreneurship Survey 2004, 2007 and 2009, own calculations.

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4.4.5 Innovative entrepreneurs As innovation refers in a strict sense the marketing of inventions, if one follows the Schumpeterian tradition the distinction between innovation and entrepreneurship is impossible to make. Fogel et al (2008), highlights that “Schumpeter (1912, 1934) suggests that an entrepreneur is not a pure inventor; and need not even be an inventor at all. Often, an entrepreneur adopts new inventions devised by others, or merely creates new combinations of old activities to fulfil familiar economic purposes more efficiently and effectively.” Even when adopting a broader definition, there is no distinction between the two terms. To illustrate we give the definition of innovation and a recent definition of entrepreneurs. A broader approach refers to innovation as “the development of new products, new processes, new sources of supply, but also the exploitation of new markets and the development of new ways to organize business” (Szirmai et al., 2011). The OECD definition highlights that “entrepreneurs are those persons (business owners) who seek to generate value through the creation or expansion of economic activity, by identifying and exploiting new products, processes or markets”. If one looks at the OECD definition and the definition of innovation, the two terms coincide.

Figure 4-12: Share of innovative companies

0%

10%

20%

30%

40%

50%

60%

70%

AT BE BGCY CZ HR DK EE FI DE GRHU IE IT LV LT LU MT NL NO PL PT ROSK SI ES SE UK TR EU SA

Source: Community Innovation Survey 2006, South African Innovation Survey, own calculations. Note: Share of companies with technological innovation (product, process, ongoing or abandoned).

Innovation is not entirely a parallel concept to entrepreneurship as innovation also happens within existing companies. There are huge differences between innovation rates of existing companies as measured using Community Innovation Survey data, with low rates below or close to 20% in Bulgaria, Hungary, Latvia and Romania and high rates above 50% in Austria, Belgium, Finland, Germany and South Africa (Figure 4-12). One could further distinguish between different types of entrepreneurship, particularly the distinction between innovative and non-innovative entrepreneurs. There is no agreement in the literature about this point, particularly since people equate entrepreneurship with innovation which makes it more difficult to distinguish different types of entrepreneurs.

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Ideally we would like to link innovation and entrepreneurship. The Eurobarometer does not allow for such a distinction as it includes no questions to determine if an entrepreneur innovates or not. The Global Entrepreneurship Monitor (GEM) however does include such a question. Using GEM data a further distinction can be made between innovative and non-innovative entrepreneurs. Innovative entrepreneurs are defined as those who think that their potential customers will consider all or some their product or service as new and unfamiliar31.

The rate of (self-assessed) innovative entrepreneurship is very high in Canada and India and in Europe this rate is above 15% in Greece, Iceland and Serbia (Figure 4-13). The rate of entrepreneurship and the rate of innovative entrepreneurship are significantly correlated. In countries with high rates of entrepreneurship we observe high rates of innovative entrepreneurship.

If we compare the share of innovative entrepreneurs (as a %-share of total entrepreneurship) across countries European countries can compare much better with their non-European competitors. Where the average share of innovative entrepreneurs is close to 15% in the EU27, it is below 15% in Australia, Brazil, Canada, India and Russia. But innovative entrepreneurship is less prevalent in the EU27 as compared to China, South Korea and South Africa. The share of innovative entrepreneurship in Europe is high in Czech Republic, Spain and Turkey and low in Hungary, Portugal and Serbia.

Figure 4-13: Rate of innovative entrepreneurship (GEM)

0

5

10

15

20

25

30

35

AT BEHR CZ DK FI FR DEGR HU IS IE IT LV NLNOPL PTRO RS SI ES SE CH TR UK EU27 AUCA JP KR US BRCN IN RU SA0%

10%

20%

30%

40%

50%

60%

70%

Rate of innovative entrepreneurs Share of innovative entrepreneurs

Source: Global Entrepreneurship Monitor, 2001-2008, own calculations.

31 Using the terminology from the GEM questionnaire innovative entrepreneurs include those entrepreneurs who have answered that all or some of potential customers consider their product or service new and unfamiliar: sunewcst = 1 or sunewcst = 2 or omnewcst = 1 or omnewcst = 2.

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4.4 Attitudes and entrepreneurship

4.4.1 Introduction Entrepreneurial activity usually involves the founding and early-stage growth of new firms, although it can also involve the reinvigoration of established firms. New firms can be created by individuals or spun off from larger firms or from the public research sector. Entrepreneurship involves individual attitudes to risk, opportunities that reduce risk, receptiveness to new ideas, access to sources of new ideas with commercial potential, and access to capital. Entrepreneurship does not need to involve technological innovation, but can be based on franchising or establishing small businesses such as restaurants, hotels, retail stores, B&B accommodation, construction firms, web or consultant services, etc. However, innovation policy is primarily interested in the creation of innovative firms that develop new technology, use technology in new ways, for example new business models to exploit the capabilities of the internet, or which are based on new organisational structures.

Attitudes are positive or negative evaluations and the associated beliefs towards events, activities, ideas. They imply a judgemental component and are influenced by affect, behaviour, cognition. Therefore attitudes can be seen as perceptions and preferences. They determine an individual’s behaviour. Attitudes which are common to a group are thus social attitudes. Autio and Wennberg (2010) define attitudes as “the weighted sum of perceived consequences and the likelihood of different outcomes of the behaviour, including norms and intrinsic rewards”. Attitudes are influenced by values, culture32, institutions and norms. Individual attitudes are partly the reflection of social attitudes. There is a growing literature that investigates the impact of social attitudes on entrepreneurship (Autio and Wennberg, 2010; Bosma and Schutjens, 2009; Grilo and Thurik, 2008; Grilo and Irigoyen, 2006; Licht and Siegel, 2006). Papers generally rely on the Global Entrepreneurship Monitor or Flash Eurobarometer on Entrepreneurship to test their hypotheses.

Autio and Wennberg (2010) focus on the effect of social peer group attitudes and behavioural norms on entrepreneurial behaviour. They test their hypotheses using the Global Entrepreneurship Monitor and employing various techniques such as Generalized Least Squares (GLS) and hierarchical linear modelling. Autio and Wennberg (2010) find that the norms of salient social groups can have up to three times as much impact on the probability of individual entry into entrepreneurship as compared with the individual s own attitudes. Their results also indicate that nearly half of the variance in individual-level entrepreneurial behaviours resides in between groups and cannot be accounted for by individual-level characteristics data. The existence of significant between-groups variance signals that social group membership (social class or status) matters for entrepreneurial behaviour. Their findings highlight the norms and attitudes of the social group

32 A culture is a social system that shares a set of common values, in which such values permit social expectations and collective understandings. Values are related to the norms of a culture, but they are more global and abstract than norms. Norms are rules for behavior in specific situations, while values identify what should be judged as good or evil. Values become embedded in the social structure over time via institutions (laws, policies), norms (customs) and traditions. Values can change over time and they are influenced by an economy’s structure and the allocation of resources which in their turn are the result of policies promoted by national governments.

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influence entrepreneurial behaviour stronger than the attitudes and perceived self-efficacy of the individual himself. Moreover, the effect of the social group reinforced the attitudes of the individual. Therefore, social networks affect job-related attitudes and engaging in entrepreneurship to larger extent (Autio and Wennberg, 2010).

Bosma and Schutjens (2009) focus on explaining national and regional differences in entrepreneurial activity and attitudes using the Global Entrepreneurship Monitor. They distinguish three components of entrepreneurial attitudes: fear of failure in starting a business, perceptions on start-up opportunities and self-assessment of personal capabilities to start a firm (self efficacy). Fear of failure is negatively influenced by population density and population growth and socialist legal origin, and positively influenced by unemployment rate. Perceived opportunities are positively influenced by population growth, networks with other entrepreneurs, and Scandinavian legal origin and negatively influenced by the unemployment rate. Perceived skills and knowledge are positively influenced by networks with other entrepreneurs. Urban regions showing high GDP growth, low unemployment rates and vibrant entrepreneurial regions where people come across other start-ups provide an environment where entrepreneurial attitudes are easier developed than elsewhere. Nascent entrepreneurship is positively influenced by population density, social networks with other entrepreneurs, perceived skills and knowledge and perceived opportunities. Start-up procedures and employment protection regulation do not have a significant effect on regional entrepreneurship. The same variables that have a positive impact on clusters of innovations population density and networks also have a positive impact on entrepreneurship (Bosma, 2009).

Grilo and Irigoyen (2006) focus on explaining latent and actual entrepreneurship using the perception of respondents of administrative complexities, the availability of financial support and risk tolerance while controlling for country specific effects and demographic variables. The authors use Flash Eurobarometer Survey on Entrepreneurship for the year 2000 that provides data for 15 EU countries and the US. Latent entrepreneurship is measured by the probability of a declared preference for self-employment over employment. Administrative complexities hinder both the willingness to become self-employed and its materialization, while lack of financial support has only a direct effect on being self-employed and no effect on preferences. Risk tolerance has no direct effect on self employment but it becomes significant in a reduced form estimation suggesting that its impact is though preferences. The study shows that even after the effects of other determinants on entrepreneurship have been controlled for, country effects are important for both latent and actual entrepreneurship. Being Greek or Irish does not have a significant impact on actual self employment status, on the contrary having any other nationality rather than being American decreases the probability of self-employment. The study raises the question whether these country differences are to be traced to intrinsic cultural differences or rather to differences in institutions and labour market conditions such as labour market legislation, social security regimes, tax environment or bankruptcy laws. The sectoral composition of economic activity might also play a role in explaining cross-country differences in entrepreneurship, as well as wage setting mechanisms that promote differences in job security and wage level differences between entrepreneurs and dependent workers across countries.

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We define social attitudes to entrepreneurship as the attitudes of individuals or groups towards their preference and willingness to engage in entrepreneurial activities. They incorporate different aspects such as risk attitudes, risk tolerance, opportunity perception and receptiveness to new ideas. Differences in social attitudes to entrepreneurship coincide with differences in observed rates of entrepreneurship. Countries with more favourable attitudes have more self-employment.

Attitudes, perceptions and preferences are influenced by the experience that the person has. Therefore it is difficult to disentangle the effect of institutions from the effect of culture. Individuals form attitudes and values within an environment which can be conducive or restrict opportunities for the creation of new organizations. Individuals learn from their choices with a lower preference for self-employment for failed entrepreneurs. Failing in the early stages of entrepreneurship leads to an increase in the risk aversion towards bankruptcy. Failing can lead to a change in preference and therefore attitudes or a change in cognition and better chances of success in the future.

4.4.2 (Social) attitudes to entrepreneurship Differences in social attitudes to entrepreneurship between countries are assumed to explain differences in observed rates of countries’ entrepreneurship. In this section we explore differences in attitudes to entrepreneurship between countries. These differences can be captured using GEM and EES data. GEM includes different questions on attitudes to entrepreneurship:

• You know someone personally who started a business in the past 2 years?

• In the next six months there will be good opportunities for starting a business in the area where you live?

• You have the knowledge, skill and experience required to start a new business?

• Fear of failure would prevent you from starting a business?

• In your country, most people would prefer that everyone had a similar standard of living?

• In your country, most people consider starting a new business a desirable career choice?

• In your country, those successful at starting a new business have a high level of status and respect?

• In your country, you will often see stories in the public media about successful new businesses?

The first 4 questions relate more to individual attitudes whereas the last 4 questions relate to peoples’ opinion about values in their country. The latter 4 questions could be seen as social attitudes, in particular the 2 questions on whether or not being an entrepreneur (starting a business) is a desirable career choice and received a high level of status and respect. But also the individual opinions can be interpreted as reflecting social attitudes. Experience with or exposure to entrepreneurial activities, either by having been an entrepreneur in the past, considering to start a new business or knowing someone who started a new business, is expected to contribute to a positive attitude to entrepreneurship. And a person’s own fear of failure will be dependent on how society reacts to people who fail starting a business, thus on society’s attitudes to failure.

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Table 4-2: Attitudes to entrepreneurship (GEM) You know someone

personally who started a

business in the past 2 years

In the next six months there will be good

opportunities for starting a

business in the area where you

live

You have the knowledge,

skill and experience required to start a new business

Fear of failure would prevent

you from starting a business

In my country, most people would prefer that everyone had a similar standard of

living

In my country, most people

consider starting a new

business a desirable

career choice

In my country, those

successful at starting a new business have a high level of

status and respect

In my country, you will often see stories in

the public media about

successful newbusinesses

Austria 46.6 Austria 42.8 Austria 56.7 Austria 35.4 Austria 59.7 Austria 37.8 Austria 71.3 Austria 56.8

Belgium 29.8 Belgium 24.5 Belgium 37.6 Belgium 27.8 Belgium 62.0 Belgium 59.9 Belgium 61.1 Belgium 42.4

Croatia 46.5 Croatia 33.8 Croatia 51.3 Croatia 33.0 Croatia 76.0 Croatia 70.6 Croatia 52.8 Croatia 56.6

Czech Rep. 32.3 Czech Rep. 26.5 Czech Rep. 38.9 Czech Rep. 31.2 Czech Rep. 63.4 Czech Rep. 63.6 Czech Rep. 46.1 Czech Rep. 62.1

Denmark 46.0 Denmark 61.3 Denmark 39.7 Denmark 35.9 Denmark 47.5 Denmark 51.2 Denmark 73.7 Denmark 35.8

Finland 47.4 Finland 50.3 Finland 39.7 Finland 32.8 Finland 64.2 Finland 39.3 Finland 85.8 Finland 69.7

France 34.5 France 17.8 France 28.2 France 41.5 France 51.6 France 60.1 France 63.9 France 41.3

Germany 39.1 Germany 22.6 Germany 39.3 Germany 44.0 Germany 60.9 Germany 52.3 Germany 74.5 Germany 49.5

Greece 38.3 Greece 26.4 Greece 57.1 Greece 54.6 Greece 67.9 Greece 69.6 Greece 71.2 Greece 45.0

Hungary 33.0 Hungary 15.1 Hungary 44.2 Hungary 27.2 Hungary 58.4 Hungary 50.6 Hungary 57.5 Hungary 25.1

Iceland 66.8 Iceland 55.0 Iceland 52.2 Iceland 37.5 Iceland 61.4 Iceland 64.8 Iceland 70.7 Iceland 82.3

Ireland 42.1 Ireland 40.3 Ireland 49.5 Ireland 35.7 Ireland 79.9 Ireland 63.9 Ireland 81.2 Ireland 77.6

Italy 33.5 Italy 32.0 Italy 37.7 Italy 37.0 Italy 63.8 Italy 70.5 Italy 65.4 Italy 44.4

Latvia 46.6 Latvia 36.1 Latvia 36.2 Latvia 39.9 Latvia 66.9 Latvia 63.6 Latvia 74.4 Latvia 68.9

Macedonia 50.0 Macedonia 50.1 Macedonia 63.6 Macedonia 36.4 Macedonia 92.9 Macedonia 80.4 Macedonia 71.9 Macedonia 67.1

Netherlands 28.4 Netherlands 39.6 Netherlands 38.8 Netherlands 24.4 Netherlands 58.2 Netherlands 81.7 Netherlands 67.4 Netherlands 60.3

Norway 40.5 Norway 45.1 Norway 41.3 Norway 23.1 Norway 65.0 Norway 60.3 Norway 64.6 Norway 71.3

Poland 36.8 Poland 17.5 Poland 35.9 Poland 39.9 Poland 71.7 Poland 64.7 Poland 58.6 Poland 36.6

Portugal 34.4 Portugal 27.1 Portugal 51.0 Portugal 38.1 Portugal 80.3 Portugal 65.8 Portugal 66.0 Portugal 47.0

Romania 36.5 Romania 25.8 Romania 24.4 Romania 33.9 Romania 48.2 Romania 61.0 Romania 63.6 Romania 52.0

Serbia 52.2 Serbia 50.2 Serbia 63.2 Serbia 27.8 Serbia 79.2 Serbia 74.5 Serbia 62.5 Serbia 65.8

Slovenia 47.7 Slovenia 37.6 Slovenia 47.7 Slovenia 29.3 Slovenia 76.1 Slovenia 54.0 Slovenia 71.8 Slovenia 59.4

Spain 35.2 Spain 33.5 Spain 49.0 Spain 47.4 Spain 62.4 Spain 69.5 Spain 59.5 Spain 43.7

Sweden 45.4 Sweden 41.0 Sweden 42.3 Sweden 34.1 Sweden 64.5 Sweden 54.0 Sweden 62.2 Sweden 55.5

Switzerland 40.7 Switzerland 36.3 Switzerland 51.9 Switzerland 32.3 Switzerland 58.5 Switzerland 51.5 Switzerland 71.8 Switzerland 54.2

Turkey 37.5 Turkey 39.2 Turkey 55.5 Turkey 31.0 Turkey 81.0 Turkey 74.1 Turkey 82.3 Turkey 63.2

UK 24.6 UK 33.5 UK 48.2 UK 32.8 UK 76.7 UK 52.9 UK 72.5 UK 56.9

EU27 34.8 EU27 33.7 EU27 44.6 EU27 38.1 EU27 65.8 EU27 60.2 EU27 66.7 EU27 50.3

Australia 37.4 Australia 41.1 Australia 53.9 Australia 32.2 Australia 71.4 Australia 53.0 Australia 68.1 Australia 61.2

Brazil 40.7 Brazil 42.9 Brazil 56.7 Brazil 38.5 Brazil 79.3 Brazil 75.8 Brazil 75.9 Brazil 73.5

Canada 33.4 Canada 39.7 Canada 52.8 Canada 25.4 Canada 74.3 Canada 73.4 Canada 69.0 Canada 75.9

China 58.5 China 33.4 China 38.7 China 22.5 China 65.7 China 72.5 China 70.5 China 81.7

India 45.2 India 49.3 India 55.7 India 32.4 India 67.1 India 67.9 India 80.6 India 78.7

Japan 22.5 Japan 9.2 Japan 15.1 Japan 24.3 Japan 40.6 Japan 30.6 Japan 50.9 Japan 56.4

Korea 45.2 Korea 13.6 Korea 30.3 Korea 41.5 Korea 70.2 Korea 68.7 Korea 67.0 Korea 65.3New Zealand 45.0 New

Zealand 51.9 New Zealand 63.4 New

Zealand 27.9 New Zealand 77.1 New

Zealand 60.8 New Zealand 68.4 New

Zealand 78.5

Russia 33.2 Russia 19.5 Russia 19.8 Russia 38.9 Russia 34.9 Russia 47.4 Russia 49.3 Russia 35.2

Singapore 29.2 Singapore 18.5 Singapore 30.6 Singapore 37.1 Singapore 51.2 Singapore 50.2 Singapore 56.0 Singapore 67.2South Africa 30.4 South

Africa 23.9 South Africa 34.1 South

Africa 25.1 South Africa 53.2 South

Africa 61.7 South Africa 61.0 South

Africa 61.4

US 35.9 US 32.7 US 56.0 US 20.0 US 50.3 US 58.9 US 63.3 US 64.7

Variance 48.4 Variance 133.0 Variance 71.2 Variance 51.7 Variance 88.7 Variance 111.9 Variance 80.8 Variance 167.1

Source: Global Entrepreneurship Monitor 2001-2008. Own calculations, variance calculated for European countries.

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In countries with ample media attention for successful business activities we expect to find a more positive attitude towards entrepreneurship. A similar assumption can be made for those countries where those starting a business receive a high level of respect and in those countries where it is considered a desirable career choice to start a business. In countries where people are more in favour of an egalitarian distribution of income we expect that there is a less positive attitude to entrepreneurship.

Europeans tend to be less exposed to entrepreneurial activities by knowing other people who recently started a business. In particular in Belgium, the Netherlands and the UK exposure is weak with less than 30% (cf. Table 4-2), but exposure is also weak in Japan, Singapore and South Africa. On average less than 35% of EU27 citizens know someone who recently started a business. Awareness of business opportunities differs significantly between countries. Of the EU27 countries Danish people are most aware of business opportunities whereas only a small share of people in France, Hungary and Poland are aware of good opportunities to start a business.

Almost 45% of EU27 citizens claim to have the knowledge, skills and experience to start a new business as compared to more than 55% of US citizens. Clearly there are differences in self-assessment between countries as it is unlikely that in some countries 75% or more of people think they have the right skills whereas in other countries less than 25% of people consider to have these skills. Differences in entrepreneurial activities between countries (e.g. with much higher rates of self-employment in some countries) could explain part of the observed differences.

Fear of failure is on average more prevalent in Europe than in non-European countries. In particular for people in Greece, Spain, Germany, France and Latvia fear of failure is an important barrier for starting a business. This fear of failure only affects a small share of the population in China, Japan and the US, Europe’s main current and future competitors. With an average fear of failure being almost twice as high as that in these 3 countries Europe faces a clear weakness starting new entrepreneurial activities.

Almost two-thirds of Europeans prefer to live in a country where there is an equal income distribution. In particular in Ireland and Portugal there is a strong preference for a similar standard of living, but also in countries like Brazil and Turkey. Countries where more than half of the population prefer an unequal income distribution include Japan, Russia and the US but also in Denmark and Romania the majority of the population do not prefer a similar standard of living.

Starting a new business is a desirable career choice in many non-European countries. In the EU27 almost 60% of the people consider becoming an entrepreneur a desirable career choice as compared to about 58% in the US. In particular in Austria, Finland, Japan and Russia starting a new business is not seen as a desirable career choice. This could be due to the existence of better career opportunities working as an employee in e.g. large businesses or the government, but it can also reflect a relatively low esteem for entrepreneurs. Being successful at starting a new business receives a high level of status and respect from about two-thirds of European citizens, in particular from people in Ireland and Finland. Europeans also have more respect for successful entrepreneurs as Japanese, Russians or US citizens.

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Figure 4-14: Social attitudes to and entrepreneurship (GEM) Rate of entrepreneurship

0

10

20

30

40

0 10 20 30 40 50 60 70You know someone personally w ho started a business in

the past 2 years

Rate of entrepreneurship

0

10

20

30

40

0 10 20 30 40 50 60 70In the next six months there w ill be good opportunities for

starting a business

Rate of entrepreneurship

0

10

20

30

40

0 10 20 30 40 50 60 70You have the know ledge, skill and experience required to

start a new business

Rate of entrepreneurship

0

10

20

30

40

0 10 20 30 40 50 60 70

Fear of failure w ould prevent you from starting a business

Rate of entrepreneurship

0

10

20

30

40

20 30 40 50 60 70 80 90In my country, most people w ould prefer that everyone had

a similar standard of living

Rate of entrepreneurship

0

10

20

30

40

20 30 40 50 60 70 80 90In my country, most people consider starting a new

business a desirable career choice

Rate of entrepreneurship

0

10

20

30

40

20 30 40 50 60 70 80 90In my country, those successful at starting a new business

have a high level of status and respect

Rate of entrepreneurship

0

10

20

30

40

20 30 40 50 60 70 80 90In my country, you w ill often see stories in the public media

about successful new businesses

Source: Global Entrepreneurship Monitor 2001-2008. Own calculations.

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There is less media attention to successful entrepreneurs in Europe than in non-European countries, in particular in Denmark, Hungary and Poland. This may indicate a less positive attitude to entrepreneurship in most European countries, except for Iceland and Ireland. A more positive social attitude to entrepreneurship favours entrepreneurial activity and we thus expect to find a higher rate of entrepreneurship in those countries with more favourable social attitudes.

The correlation results in Table 4-3 show that except for fear of failure we find positive and significant correlation results between the different (social) attitudes to entrepreneurship and the rate of entrepreneurship (this is visually shown in the scatter plots in Figure 4-14).

Table 4-3: Correlations between social attitudes to and entrepreneurship

Rate of entrepreneurship

You know someone personally who started a business in the past 2 years .513** (.001) In the next six months there will be good opportunities for starting a business .403** (.011) You have the knowledge, skill and experience required to start a new business .552** (.000) Fear of failure would prevent you from starting a business .053 (.750) In my country, most people would prefer that everyone had a similar standard of living .451** (.004) In my country, most people consider starting a new business a desirable career choice .382* (.016) In my country, those successful at starting a new business have a high level of status/respect .442** (.005) In my country, you will often see stories in the public media about successful new businesses .600** (.000)

**/*. Correlation is significant at the .01/.05 level (2-tailed). Source: GEM, 2001-2008.

A further distinction can be made between innovative and non-innovative entrepreneurs. The rate of entrepreneurship and the rate of innovative entrepreneurship are significantly correlated (correlation coefficient of .649). In countries with high rates of entrepreneurship we observe high rates of innovative entrepreneurship. Despite the strong correlation between the rate of entrepreneurship and the rate of innovative entrepreneurship only a few (social) attitudes correlate significantly with the rate of innovative entrepreneurship: knowing someone personally who started a business, those successful at starting a new business receive as high level of status and respect, and positive media attention to successful entrepreneurs (Table 4-4). More media coverage could thus have a positive impact on the share of entrepreneurs exploiting innovative activities.

Table 4-4: Correlations between social attitudes to and innovative entrepreneurship

Rate of innovative entrepreneurship

You know someone personally who started a business in the past 2 years .449** (.004) In the next six months there will be good opportunities for starting a business .173 (.293) You have the knowledge, skill and experience required to start a new business .248 (.144) Fear of failure would prevent you from starting a business .215 (.189) In my country, most people would prefer that everyone had a similar standard of living .066 (.690) In my country, most people consider starting a new business a desirable career choice .193 (.238) In my country, those successful at starting a new business have a high level of status/respect .380* (.017) In my country, you will often see stories in the public media about successful new businesses .513** (.001)

**/*. Correlation is significant at the .01/.05 level (2-tailed). Source: GEM, 2001-2008.

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Attitudes for innovative entrepreneurs, non-innovative entrepreneurs and non-entrepreneurs are not necessarily the same. Differences between across entrepreneurs and non-entrepreneurs are smallest in Europe (Figure 4-15). In the EU27 there is almost no difference between entrepreneurs and non-entrepreneurs about how they value people who either start a business or have been successful at starting a business.

Figure 4-15: Attitudes for different types of entrepreneurs

You know someone personallywho started a business in the

past three years

In the next six months there willbe good opportunities for

starting a business in the area

You have the knowledge and theskills and experience required to

start a business

Fear o f failure would prevent youfrom starting a business

In your country most peoplewould prefer that everyone had a

similar standard o f living

In your country most peopleconsider starting a business a

desirable career cho ice

In your country those successfulat starting a business have a high

level o f status and respect

In your country you will o ften seestories in the public media about

successful new businesses

EU27

0 25 50 75 100

United States

0 25 50 75 100

China

0 25 50 75 100

You know someone personallywho started a business in the

past three years

In the next six months there willbe good opportunities for

starting a business in the area

You have the knowledge and theskills and experience required to

start a business

Fear o f failure would prevent youfrom starting a business

In your country most peoplewould prefer that everyone had a

similar standard o f living

In your country most peopleconsider starting a business a

desirable career cho ice

In your country those successfulat starting a business have a high

level o f status and respect

In your country you will o ften seestories in the public media about

successful new businesses

Brazil

0 25 50 75 100

India

0 25 50 75 100

Russia

0 25 50 75 100

Non-entrepreneur Non-innovative entrepreneur Innovative entrepreneur

Source: Global Entrepreneurship Monitor, 2001-2008. Own calculations.

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The graphs also show that differences in individual attitudes and much higher than those in social attitudes: people in the same country can have different individual attitudes and at the same time share more common social attitudes to entrepreneurship. Within Europe social attitudes are most similar in Ireland, Latvia, Norway and Sweden and most dissimilar in Finland, Hungary and Poland (cf. Annex 2 for individual graphs for all European countries). But despite the observed differences between entrepreneurs and non-entrepreneurs for having the same social attitude, differences are much less as compared to differences for individual attitudes. Innovative entrepreneurs have, on average, more positive attitudes than the average entrepreneur. Innovative entrepreneurs are e.g. much less afraid of failure and are better informed about opportunities.

Table 4-5: Attitudes to entrepreneurship Entrepreneurship is

the basis of wealth creation, benefiting

us all

Entrepreneurs think only about their own

wallet

Entrepreneurs are job creators

Entrepreneurs exploit other people’s work

Non-entre-preneurs

Entrepre-neurs

Non-entre-preneurs

Entrepre-neurs

Non-entre-preneurs

Entrepre-neurs

Non-entre-preneurs

Entrepre-neurs

AUSTRIA 74.9% 78.6% 37.0% 19.0% 90.3% 95.2% 26.2% 9.5%BELGIUM 75.4% 85.2% 46.7% 38.9% 87.0% 90.7% 37.2% 27.8%CYPRUS 65.5% 74.0% 75.9% 54.2% 88.7% 90.6% 76.4% 44.8%CZECH REPUBLIC 47.1% 55.3% 47.1% 28.0% 84.7% 90.2% 33.1% 18.2%DENMARK 79.5% 76.9% 22.4% 17.3% 93.9% 88.5% 21.8% 11.5%ESTONIA 75.5% 78.8% 50.1% 33.8% 92.2% 95.0% 67.5% 52.5%FINLAND 80.4% 72.1% 27.3% 16.4% 93.7% 98.4% 36.9% 29.5%FRANCE 78.3% 80.7% 45.1% 25.0% 85.0% 88.6% 43.3% 26.1%GERMANY 68.3% 72.9% 39.5% 27.8% 84.4% 92.5% 31.6% 16.5%GREECE 71.0% 79.2% 73.2% 50.2% 86.4% 90.8% 71.2% 54.1%HUNGARY 49.9% 57.2% 50.5% 24.3% 81.5% 86.8% 44.2% 23.0%ICELAND 88.5% 87.0% 13.0% 9.0% 97.3% 98.0% 14.8% 7.0%IRELAND 69.8% 74.0% 36.1% 38.4% 89.0% 90.4% 29.3% 38.4%ITALY 67.5% 75.8% 51.8% 33.3% 88.3% 93.3% 43.5% 24.2%LATVIA 78.9% 86.4% 50.1% 21.2% 94.9% 97.0% 52.9% 34.8%LITHUANIA 81.9% 79.0% 55.0% 48.4% 90.7% 96.8% 75.3% 62.9%LUXEMBOURG 71.1% 81.8% 45.6% 36.4% 86.8% 86.4% 40.1% 31.8%MALTA 72.5% 80.0% 50.7% 33.3% 84.7% 86.7% 44.4% 40.0%NETHERLANDS 78.2% 80.8% 36.9% 21.7% 91.1% 95.8% 50.0% 42.5%NORWAY 79.2% 81.0% 22.9% 9.5% 92.2% 95.2% 23.3% 14.3%POLAND 72.8% 85.4% 61.3% 40.4% 86.7% 91.4% 73.8% 51.0%PORTUGAL 82.5% 87.8% 51.9% 38.2% 87.4% 93.1% 55.2% 40.5%SLOVAKIA 51.2% 68.4% 54.3% 26.3% 86.6% 91.2% 58.6% 33.3%SLOVENIA 68.5% 79.3% 59.8% 31.0% 82.2% 89.7% 68.1% 51.7%SPAIN 81.2% 89.3% 65.1% 38.4% 88.4% 98.2% 55.1% 25.9%SWEDEN 78.1% 84.1% 29.8% 21.7% 93.3% 94.2% 44.6% 36.2%UNITED KINGDOM 64.5% 78.9% 42.6% 27.3% 82.8% 92.2% 38.3% 34.4%UNITED STATES 72.3% 87.0% 26.7% 15.5% 87.0% 92.8% 27.9% 23.2%

Source: Eurobarometer Entrepreneurship Survey 2007, own calculations.

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EES also includes 4 value questions on entrepreneurship relevant for measuring attitudes, although based on the phrasing of the question these attitudes refer to individual attitudes rather than to social attitudes. Table 4-5 shows the difference between entrepreneurs and non-entrepreneurs in their response to each of these value questions. In most countries entrepreneurs have a more positive view towards entrepreneurship. Blue cases indicate significant differences in attitudes as one would expect. Red values indicate cases where non-entrepreneurs have a more positive attitude to entrepreneurship. We also see a lot of variation across countries. In Iceland and Norway less than 10% of entrepreneurs think that entrepreneurs only think about their own wallet, in Greece this is a (staggering) 50%. In particular non-entrepreneurs share this negative view that entrepreneurs only pursue their own wealth. The majority of both non-entrepreneurs and entrepreneurs see entrepreneurs share a positive view towards entrepreneurs as job creators. The view that entrepreneurship is the basis of wealth creation is shared by the majority of both non-entrepreneurs and entrepreneurs. However, there is clear difference towards the view that entrepreneurs exploit other people’s work. On average almost 50% of non-entrepreneurs share this view, in particular in Cyprus, Estonia, Greece, Lithuania, Poland and Slovenia. In the US less than 28% of non-entrepreneurs share this view. About 33% of entrepreneurs think that (other) entrepreneurs exploit other people’s work. The most positive entrepreneurs are found in Austria, Czech Republic, Denmark and Iceland.

A comparison with the US shows that US citizens hold a more positive view towards entrepreneurship and also that in the US differences between non-entrepreneurs and entrepreneurs are less. Although the responses to the EES questions must be seen as reflecting personal attitudes, they can be assumed to also reveal differences in social attitudes as differences in social attitudes between countries are shaped by differences in the distribution of personal attitudes in these countries.

4.5 The conceptual model and methodology We consider that a slightly adapted version of the model from Hoffman and Gabr (2006) captures the factors influencing entrepreneurship (Figure 4-16). Our understanding is that individual and social attitudes are influenced by the experience that an individual has. Therefore it is difficult to disentangle the effect of institutions from the effect of culture. Individuals form attitudes and values within an environment which can be conducive or restrict opportunities for the creation of new organizations. Ideally one would like to test such a model by modelling both occupational choices and the choice for innovation in setting up a business based on independent variables that are prior to these decisions. However, there is limited data collected available and therefore a model like this would require new data collection asking retrospective questions regarding variables affecting the entrepreneurial and innovation choice. Furthermore, asking a respondent whether his firm innovates is not a good proxy for innovation since respondents are not able to assess comparatively with respect to other firms unless they changed firms. Since a reference point is not provided it is difficult to assess what respondents have in mind when ranking innovation in their firm.

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Figure 4-16: Conceptual model

Source: Hoffman and Gabr (2006) adapted.

Given data limitations, we focus on the differences in attitudes between nascent and current entrepreneurs who are now engaged in setting up a business and non-entrepreneurs. People who already have a company have been excluded from the analysis. We also further distinguish between entrepreneurs due to necessity and entrepreneurs due to opportunity. We take the preference for self employment as indicative of the desirability of entrepreneurship and the

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observed labour market status of being an entrepreneur as measuring behaviour. We use EES 2007 and 2009 data to predict determinants of actual behaviour. Previous studies have focused on modelling latent entrepreneurship as expressed by the preference for self employment or the intention to become self employed/start a business in the future or by looking at actual labour market occupational choices. The main difficulty with the existing studies is that generally attitudes are measured at the current point in time after the person has made his or her occupational choice (Grilo and Irigoyen, 2006). Therefore attitudes are mainly measured at a posterior point in time and causality is impossible to asses in such a context. Individuals learn from their choices and therefore their attitudes change. There are few studies (Verheul et al., 2008; Grilo and Irigoyen, 2006) using the same dataset. The existing papers focus on explaining preferences and actual self-employment by looking at employment choices assuming that the choice is a revealed preference or by combining data from actual self employment status with the preference for self employment.

We take a different approach and we focus on people who are either engaged in starting up a company or who did so in the past. Table 4-6 briefly describes the variables from the Eurobarometer Entrepreneurship Survey that will be used in the regressions in section 4-6 and the descriptive analysis in this section.

Table 4-6: Operationalization of control Indicator Proxy ESS question Operationalization

High school education dummy Tertiary education dummy

Education How old were you when you stopped full time education?

(Low education dummy = reference category) Age below 25 dummy Age 25-35 dummy Age 35-45 dummy Age 45-55 dummy

Demographic controls

Age How old are you?

(Age above 55 dummy = reference category)

Gender Women dummy Would you say you live in: a) metropolitan zone Metropolitan area

dummy b) other town/urban centre Town area dummy

Labour market opportunity

City size

c) rural zone (Rural area = reference category)

Mother self-employed Could you tell me the occupation of your mother? Is she or was she: a) self-employed b) white collar employee in the private sector c) blue collar employee in the private sector d) civil servant e) without a professional activity

Mother self-employed dummy

Parental background

Father self-employed Could you tell me the occupation of your father? Is he or was he: a) self-employed b) white collar employee in the private sector c) blue collar employee in the private sector d) civil servant e) without a professional activity

Father self-employed dummy

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Indicator Proxy ESS question Operationalization Preferences Preference for self-

employment Suppose you could choose among different kinds of jobs, which one would you prefer: a) being an employee b) being self-employed c) none of these

Preference for self-employment dummy

Quality of financing Do you strongly agree, agree or disagree with the following opinion: It is difficult to start one’s own business due to a lack of financial support

Lack of financial support dummy

Quality of administrative procedures

Do you strongly agree, agree or disagree with the following opinion: It is difficult to start one’s own business due to the complex administrative procedures

Complex administrative procedures dummy

Quality of institutions

Quality of information available

Do you strongly agree, agree or disagree with the following opinion: It is difficult to obtain sufficient information on how to start a business

Lack of information dummy

Social norms The society’s risk tolerance to failing a business

One should not start a business if there is a risk it might fail

Risk tolerance to failing a business dummy

If I were to set up a business today which are the two risks you would be most afraid of? Is it:

a) the risk of uncertain income Dummy if agree b) the risk of job insecurity Dummy if agree c) the risk of losing property Dummy if agree d) the risk of spending too much energy/time Dummy if agree e) the possibility of suffering a personal failure

Dummy if agree

Individual risk attitudes

Individual risk aversion to various domains of entrepreneurship

f) the possibility of going bankrupt Dummy if agree Do you strongly agree, agree or disagree with the following opinion:

Entrepreneurs are wealth creators/ Entrepreneurs create new products and services that benefit us all

Dummy if agree

Entrepreneurs think only about their own wallet

Dummy if agree

Entrepreneurs are job creators Dummy if agree

Social and individual values on entrepreneurship

The value of entrepreneurship in society

Entrepreneurs exploit other people’s work Dummy if agree Do you strongly agree, agree or disagree with the following opinion:

My school education helped me to develop my sense of initiative

Dummy if agree

My school education helped me to better understand the role of entrepreneurs in society

Dummy if agree

My school education made me interested to become an entrepreneur

Dummy if agree

Individual entrepreneurial attitude via schools

The role played by education in fostering individual attitudes to entrepreneurship

My school education gave me skills and know how that enable me to run a business

Dummy if agree

General orientation to risk attitudes

In general I am willing to take risks Dummy if agree

Self-confidence Generally when facing difficult tasks, I am certain that I will accomplish them

Dummy if agree

Internal locus of control My life is determined by my own actions, not by others or chance

Dummy if agree

Personality / Attitude traits

Personal initiative/ openness to change/ adaptability

If I see something I do not like, I change it Dummy if agree

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Indicator Proxy ESS question Operationalization The possibility of being rejected by others for standing up for my own decisions would not stop me

Dummy if agree Self reliance for decision making

I am an inventive person who has ideas Dummy if agree Optimism I am optimistic about my future Dummy if agree Competitive I like situations in which I compete with

others Dummy if agree

External locus of control When confronted with difficult tasks I can count on luck and the help of others

Dummy if agree

The results in Table 4-7 show that non-entrepreneurs and entrepreneurs differ in several respects. Women are less likely to be entrepreneurs as 45% of entrepreneurs are women as compared to 63% for non-entrepreneurs. The opposite holds for men who are more likely to be an entrepreneur. With 48% of entrepreneurs have attained higher education as compared to only 41% for non-entrepreneurs it becomes evident that higher educational attainment in general will favour entrepreneurship. Favourable labour market opportunities arising from living in urbanised areas does seem to matter for entrepreneurship. A possible explanation here is that the majority of farmers, foresters and fishermen (of which about half are entrepreneurs) live in a rural zone.

Entrepreneurs are more likely to have grown up in a family where one or both of the parents were self-employed. Entrepreneurs have a more positive perception about the quality of institutions as a smaller share perceived the lack of available financial support, complex administrative procedures or difficulties in obtaining information as a barrier in starting a business. Entrepreneurs are more likely to agree with the statement that one should not start a business if there is a risk it might fail, and therefore have a lower risk tolerance. Entrepreneurship is in higher esteem among entrepreneurs with the majority seeing entrepreneurship as the basis of wealth creation and job creation. Non-entrepreneurs have a more negative view on entrepreneurship as more than half believe than entrepreneurs only think about their own wallet and exploit other people’s work.

Schools are not only important in raising educational attainment levels but they also play a role in shaping people’s mind in becoming an entrepreneur. Schools can have a negative impact as 1 out of 4 non-entrepreneurs claim that their employment status was influenced by school and a positive impact as 1 out of 5 entrepreneurs say that schools have had a positive influence on their choice of becoming an entrepreneur. Individual risk attitudes also differ, where entrepreneurs are less afraid of the risk of going bankrupt when starting a new business. There are almost no differences between entrepreneurs and non-entrepreneurs in the risk of job insecurity, losing property or suffering a personal failure when starting a new business.

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Table 4-7: Characteristics of non-entrepreneurs and entrepreneurs

Non-entrepreneurs Entrepreneurs

Mean score SE Mean

score SE

Demographics Women 0.63 0.48 0.45 0.50 Age 16-25 0.11 0.31 0.06 0.24 Age 26-35 0.12 0.33 0.14 0.35 Age 36-45 0.17 0.38 0.23 0.42 Age 46-55 0.19 0.39 0.25 0.43 Age >55 0.41 0.49 0.33 0.47 Education low 0.07 0.26 0.06 0.23 Education high-school 0.44 0.50 0.36 0.48 Education tertiary 0.41 0.49 0.48 0.50 Labour market opportunities Metropolitan area 0.21 0.41 0.23 0.42 Town 0.43 0.50 0.41 0.49 Parental background Mother self-employed 0.09 0.29 0.14 0.34 Father self-employed 0.23 0.42 0.32 0.47 Preferences Preference for self-employment 0.37 0.48 0.72 0.45 Individual perception of the quality of institutions

(It is difficult to start a business due to a) lack of available financial support 0.83 0.38 0.79 0.40

(It is difficult to start a business due to) complex administrative procedures 0.78 0.41 0.68 0.46

(It is difficult to obtain) sufficient information on how to start a business 0.54 0.50 0.48 0.50 Social norms Risk tolerance to failing a business 0.46 0.50 0.57 0.49 Entrepreneurship individual and social values

Entrepreneurship is the basis of wealth creation 0.79 0.40 0.86 0.34

Entrepreneurs think only about their own wallet 0.54 0.50 0.37 0.48

Entrepreneurs are job creators 0.90 0.30 0.94 0.23

Entrepreneurs exploit other people's work 0.54 0.50 0.41 0.49 Individual entrepreneurial orientation via education School influenced individual entrepreneurial attitude 0.53 0.50 0.59 0.49 School influenced the perception of the role of entrepreneur 0.49 0.50 0.52 0.50 School influenced the choice of entrepreneurship 0.27 0.44 0.41 0.49 Individual risk attitudes (If I were to set up a business today I would be most afraid of the …)

Uncertainty of your income 0.38 0.49 0.43 0.50

Risk of job insecurity 0.20 0.40 0.20 0.40

Risk of losing property 0.33 0.47 0.31 0.46

Suffering a personal failure 0.18 0.38 0.17 0.38

Possibility of going bankrupt 0.48 0.50 0.39 0.49 Sample size 31,348 7,751

Source: Eurobarometer Entrepreneurship Survey 2007 and 2009.

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4.6 Econometric results Psychologists use aggregate values over groups as measuring a social dimension and economists use country dummies to control for culture institutions and changes in economic conditions. We take two approaches: the first approach is to measure social attitudes via country dummies and the second is to build an index of attitudes.

The first approach uses country dummies to measure attitudes. We use two waves of the EES data, 2007 and 2009, and control for the role of institutions and also changing economic conditions. Our implicit assumption is that culture does not change over a short span of time but institutions and economic conditions do. We take country dummies as proxies of culture and attitudes and year dummies as a proxy of institutions and the state of the economy.

Demographic controls include age, education and gender. Labour market opportunities are proxied using the size of the city where the person lives: metropolitan area, town and rural village. Parental background refers to the occupation of the parents: the respondent’s mother or father was self-employed. Preferences for self-employment is based on the question “Suppose you could choose among different kinds of jobs, which one would you prefer: a) being an employee, b) being self-employed, c) none of these”. Quality of institutions or government is proxied using three questions referring to the availability of financing for starting a business, the complexity of the administrative procedures and whether it is difficult to obtain sufficient information on how to start a business. The same variables could be interpreted from a psychology point of view as capturing individual beliefs about the quality of institutional support. Social norms is proxied using an indicator about what the individual believes others should do if there is a risk of failure of a business. This indicator could indirectly measure social norms and how tolerant societies are to failure of a business since it has a normative dimension. The variables referring to whether the role of entrepreneurs is a positive or a negative one for society could be interpreted partially as standing for social values regarding entrepreneurship but at the same time they could also be interpreted as capturing the image of entrepreneurship in society. Finally there are four variables regarding the role played by education in fostering attitudes and skills for the individual.

The EES 2009 also includes eight additional variables measuring self reported personality traits. Robinson’s et al. (1991) scale of entrepreneurial attitudes builds on the personality traits measurement. The authors first identify four constructs that have been commonly used in dealing with business motivation and/or research on the entrepreneur: need for achievement, locus of control, self-esteem and innovation. Afterwards, the authors build four attitude subscales: achievement in business, innovation in business, perceived behavioural control of business outcomes, and perceived self-esteem in business. While “personality theories are intended to use across a broad spectrum of situations, measuring general tendencies” attitudes’ scales are context specific measuring situational specificity and are embedded in an interactionist model whereby human behaviour is being shaped and shaping the environment via learning (Robinson et al., 1991). To the extent that personality traits are more common in a certain country we could see the EES variables as capturing social attitudes since attitudes are learned through the interaction with one’s environment. Further we also create factors of the influence of schools on entrepreneurial

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attitudes and skills, the image of the entrepreneur in a society, and the quality of governmental support.

Table 4-8: Capturing social attitudes by country dummies

Model

1 Model

2 Model

3 Model

4 Model

5 Model

6 Model

7 Model

8 Model

9 Model

10 Austria 0.39*** 0.41*** 0.39*** 0.36*** 0.45*** 0.48*** 0.50*** 0.55*** 0.59** 0.61** Belgium 0.30*** 0.30*** 0.30*** 0.29*** 0.48*** 0.58*** 0.64*** 0.68** 0.70* 0.73* Cyprus 0.84 0.83 0.86 0.80* 0.81 0.88 0.96 1.50** 1.60*** 1.60***Czech Republic 0.59*** 0.64*** 0.65*** 0.71*** 1.08 1.21 1.31* 1.53*** 1.55*** 1.63***Denmark 0.39*** 0.35*** 0.36*** 0.34*** 0.51*** 0.62*** 0.65** 0.58*** 0.64** 0.66** Estonia 0.68*** 0.78* 0.78* 0.82 1.08 1.10 1.27 1.72*** 1.85*** 1.88***Finland 0.79* 0.81* 0.82 0.75* 1.05 1.09 1.18 1.24 1.44** 1.43* France 0.33*** 0.33*** 0.33*** 0.32*** 0.35*** 0.42*** 0.43*** 0.48*** 0.50*** 0.53***Germany 0.57*** 0.54*** 0.54*** 0.52*** 0.68*** 0.77* 0.84 0.88 0.96 1.04 Greece 0.86 0.86 0.88 0.72*** 0.76** 0.88 0.93 1.38** 1.46*** 1.46***Hungary 0.61*** 0.74** 0.75** 0.83* 1.07 1.32** 1.49*** 1.85*** 1.92*** 2.01***Iceland 1.08 1 0.98 0.91 0.96 1.19 1.20 1.06 1.10 1.10 Ireland 0.59*** 0.56*** 0.56*** 0.52*** 0.58*** 0.62*** 0.63*** 0.66** 0.68** 0.73* Italy 0.55*** 0.53*** 0.54*** 0.54*** 0.58*** 0.74** 0.80* 0.93 0.98 0.99 Latvia 0.48*** 0.56*** 0.57*** 0.60*** 0.65** 0.74* 0.83 1 1.08 1.15 Lithuania 0.55*** 0.52*** 0.54*** 0.57*** 0.55*** 0.65** 0.77 1 1.08 1.14 Luxembourg 0.32*** 0.29*** 0.29*** 0.28*** 0.36*** 0.44*** 0.48*** 0.57*** 0.59** 0.64** Malta 0.14*** 0.15*** 0.15*** 0.15*** 0.17*** 0.18*** 0.20*** 0.27*** 0.28*** 0.28***Netherlands 0.55*** 0.50*** 0.51*** 0.50*** 0.71*** 0.77* 0.81 0.87 0.96 0.97 Norway 0.66*** 0.55*** 0.56*** 0.55*** 0.75* 0.94 1 0.90 0.93 0.89 Poland 0.65*** 0.62*** 0.63*** 0.62*** 0.64*** 0.75** 0.84 1.19 1.24 1.28* Portugal 0.53*** 0.59*** 0.60*** 0.58*** 0.61*** 0.76** 0.85 1.02 1.03 1.11 Slovakia 0.41*** 0.45*** 0.45*** 0.53*** 0.78 0.83 0.92 1.10 1.17 1.22 Slovenia 0.26*** 0.28*** 0.28*** 0.29*** 0.35*** 0.39*** 0.45*** 0.54*** 0.57** 0.59** Spain 0.46*** 0.44*** 0.45*** 0.43*** 0.55*** 0.64*** 0.68*** 0.88 0.91 1 Sweden 0.62*** 0.60*** 0.60*** 0.58*** 0.90 1.08 1.18 1.28 1.35 1.31 United Kingdom 0.49*** 0.51*** 0.51*** 0.53*** 0.58*** 0.60*** 0.62*** 0.68*** 0.71** 0.75* Year 2009 1.15*** 1.17*** 1.17*** 1.20*** 1.23*** 1.24*** 1.24*** 1.28*** 1.31*** 1.32***Demographic controls NO YES YES YES YES YES YES YES YES YES Labour market opportunity NO NO YES YES YES YES YES YES YES YES Parental background NO NO NO YES YES YES YES YES YES YES Preferences NO NO NO NO YES YES YES YES YES YES Quality of institutions NO NO NO NO NO YES YES YES YES YES Social norms: risk tolerance NO NO NO NO NO NO YES YES YES YES Social and individual values on entrepreneurship

NO NO NO NO NO NO NO YES YES YES

Individual entrepreneurial attitude via schools

NO NO NO NO NO NO NO NO YES YES

Risk individual attitudes NO NO NO NO NO NO NO NO YES YES Pseudo R-Square 0.02 0.08 0.08 0.09 0.18 0.17 0.18 0.20 0.20 0.21 chi2 630.7 2214.4 2208.2 2371.3 4744.5 4061.9 4036.8 4063.4 3993.0 4072.2p 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Notes: Entrepreneurs are people who are in the process of starting a business or who already own a business. We use Eurobarometer Entrepreneurship Survey 2007 and 2009 data. The reference country is

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the United States. Results are displayed in relative risk ratios (exponential of coefficients) and should be interpreted with reference to 1 (exponential of coefficient 0).

In Table 4-8 we use logistic regression to illustrate how entrepreneurial attitudes and culture have an impact on the entrepreneurship rate. The first regression models the entrepreneurship rate as a function of only culture and economic conditions. Then we add various controls to see how the effect of culture changes when we add more individual level variables. The between country variation explains 2% of the entrepreneurship rate variation. Most of the variation is explained by individual variation. Similarly, (a non-reported) hierarchical logit multilevel model with a constant only gives us an estimate of the variance of residuals of 0.165. We further calculate the intra-class correlation which is a measure of the importance of countries as a level in the regression. The estimate tells us that 0.047% is explained by country variation and that most of the variation in our data is given by individual variation. We observe a big change in the variation in entrepreneurship rate explained by our model when we add demographic controls and preferences for self employment. This means that countries which are a proxy for culture do not explain that much in entrepreneurship variation. We implicitly assume that culture is constant and that labour market conditions vary across years. The results of the regressions show that individual variation in attitudes explains 19% of the variation in entrepreneurship.

The more individual level variables we control for, the less significant the effect of the country dummies becomes, and the smaller the effect becomes. The effect is measured using an exponential of the coefficient and it is therefore given in relative risk terms or odds ratios. The effect needs to be interpreted with reference to 1. Country dummy scores below 1 indicate a negative effect and those above 1 a positive effect. A score closer to 1 indicates a smaller effect, e.g. for Austria the effect for model 1 is farther away from 1 than that for model 10, the negative effect for model 1 is thus smaller than that for model 10.

The regression results in Table 4-9 show what happens when we replace the country and time dummies with variables at the country level. Logistic regressions are used and the standard errors are clustered at the country level. We construct a factor score at the country level for entrepreneurial attitudes from variables measuring personality traits based on polychoric correlations and principal factor analysis33. Our implicit assumption is that if there are incentives favouring certain social attitudes in one country they should be reflected in the cross-country variation in this factor score. We obtain two factors: the first one comprising of self-confidence, internal locus of control, personal initiative, self-reliance decision making, optimism and invention/creativity; the second factor comprises risk and competition attitudes.

Further we aggregate the factor scores at the country level. The first factor ‘entrepreneurial attitudes’ has a positive impact on entrepreneurship, whereas the second factor of risk and competition social attitudes is not statistically significantly different from 0. Entrepreneurial attitudes are higher in the United States, the United Kingdom, Ireland, Iceland and Austria. They are lower in Slovakia, Hungary, Netherlands and the Czech Republic. The entrepreneurial attitudes are close

33 We are of course aware that scales measuring attitudes should be applied, however due to data limitations we do not have such a measure.

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to zero for countries such as France, Italy, Norway, Malta, Slovenia, Finland, Spain, Estonia, Luxembourg, Latvia and Poland. However, compared to the individual variation in entrepreneurial attitudes, the country variation is more reduced and below 1 (Figure 4-17).

Figure 4-17: Entrepreneurial attitudes

-0.40

-0.20

0.00

0.20

0.40

0.60

0.80

AU BE CY CZ DK EE FI FR DE GR HU IS IE IT LV LT LU MT NL NO PL PT ES SE SK SI UK US

The risk attitudes have less variation than entrepreneurial attitudes and in fact they are not significant in any of the regressions at the country level suggesting that risk is more an individual trait (Figure 4-18).

Figure 4-18: Risk attitudes

-0.20-0.15-0.10-0.050.000.050.100.150.20

AU BE CY CZ DK EE FI FR DE GR HU IS IE IT LV LT LU MT NL NO PL PT ES SE SK SI UK US

When we control for Hofstede’s cultural values the first factor of entrepreneurial attitudes becomes statistically insignificant, suggesting that it does capture cultural aspects. We add other controls such as entrepreneur’s image in a country based on factor analysis of the variables referring to values with respect to entrepreneurship, e.g. if it has a negative impact on society. We also add a factor score capturing the quality of policies targeting business start-ups such as availability of finance and information and the complexity of procedures. As the figure below shows, business start-up policies have a positive impact in the United States, Great Britain, Finland, Norway, Netherlands, Germany, Austria, and Czech Republic. And they seem to have a negative impact mostly in southern European countries such as Italy, Greece, Spain and Portugal but also in France and Hungary.

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Table 4-9: Entrepreneurship Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Country factor entrepreneurial attitudes 1.75** 1.68* 1.69* 1.77* 1.89** 1.89** 1.63 Country factor risk attitudes 0.95 0.99 1.01 1.01 1.45 1.45 1.66 Country factor entrepreneurial image 0.88 0.92 1.06 0.81 0.81 0.64 Country factor institutional quality 1.07 1.09 1.10 1.10 0.87 Unemployment rate 1.01 0.99 0.99 1.00 Log GDP 0.65** 0.65** 0.63** GDP Growth 1.03 1.22 Power distance 1.00 Individualism 1.00 Masculinity 1.00 Uncertainty avoidance 1.00 Pseudo R-Square 0.00 0.00 0.00 0.00 0.01 0.01 0.01 chi2 8.01 9.01 9.14 7.42 37.55 42.76 38.31 p 0.02 0.03 0.06 0.19 0.00 0.00 0.00

Source: Eurobarometer 2007 and 2009. The method used is logistic regression. Results are displayed in relative risk ratios (exponential of coefficients) and should be interpreted with reference to 1 (exponential of coefficient 0).

Figure 4-19: Factor scores of the quality of institutions

Quality of institutions

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

AU BE CY CZ DK DK EE ES FI FR GR HU IE IS IT LT LU LV MT NL NO PL PT SE SI SK UK US

Source: Eurobarometer 2007 and 2009.

In addition we also control for economic conditions using the log of GDP, the unemployment rate and economic growth. Log of GDP is negatively related with the entrepreneurship rate. The Pseudo R square indicates that this model where we try to replace country and year dummies by specific cultural, economic and policy variables is worse at capturing the entire variation as it only explains 1% compared to 2% previously.

Further we distinguish between entrepreneurship due to opportunity, necessity and due to both reasons. The results indicate that first factor of entrepreneurship attitudes is positively related with

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entrepreneurship due to opportunity and that an increase in the log of GDP leads to a decrease in entrepreneurship by opportunity and due to both opportunity and necessity. An increase in GDP does not seem to affect entrepreneurs due to necessity. One would normally expect that the unemployment rate should play a role for entrepreneurs due to necessity. And it does, if we do not cluster the standard errors by country level. When we do not cluster the standard errors, the unemployment rate is positively related to entrepreneurship due to necessity but the impact is very low. For entrepreneurs due to necessity entrepreneurial attitudes seem to be important as well, an increase of one unit leading to an increase of twice as much in the relative risk ratio of becoming an entrepreneur due to necessity. Entrepreneurial attitudes do not seem to be important for entrepreneurs due to necessity and opportunity. A unit increase in the factor score of entrepreneurs’ bad image in society seems to lead to a decrease in entrepreneurship due to opportunity by 0.5 when controlling for GDP. Entrepreneur’s negative image in society seems to be also important for entrepreneurs due to necessity, but when controlling for the quality of business start-up policies this effect becomes statically insignificant. An increase of 1 unit in the quality of business start-up policies leads to a decrease in entrepreneurship due to both necessity and opportunity by almost 0.8. An increase in entrepreneurs’ negative image leads to a decrease in entrepreneurship due to opportunity and necessity. Further an increase of one unit in GDP leads to a decrease in the relative risk ratio of becoming an entrepreneur due to opportunity and necessity.

Table 4-10: Entrepreneurship due to opportunity Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Country factor entrepreneurial attitudes 2.50*** 1.92** 2.03** 2.08** 2.18*** 2.18*** 2.10** Country factor risk attitudes 1.14 1.39 1.61 1.52 2.1 2.1 1.79 Country factor entrepreneurial image 0.47*** 0.65 0.65 0.51* 0.50* 0.60 Country factor institutional quality 1.72 1.64 1.63 1.61 1.31 Unemployment rate 1.01 0.99 0.99 1.00 Log GDP 0.67* 0.67* 0.69 GDP Growth 0.84 0.83 Power distance 1.00 Individualism 1.00 Masculinity 1.00 Uncertainty avoidance 1.00 Pseudo R-Square 0.00 0.01 0.01 0.01 0.01 0.01 0.02 chi2 31.92 86.09 282.91 423.32 1076.37 2607.69 . p 0.00 0.00 0.00 0.00 0.00 0.00 .

Source: Eurobarometer 2007 and 2009. The method used is logistic regression. Results are displayed in relative risk ratios (exponential of coefficients) and should be interpreted with reference to 1 (exponential of coefficient 0). Multinomial logistic regression is used and the reference category is non-entrepreneurs.

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Table 4-11: Entrepreneurship due to necessity Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Country factor entrepreneurial attitudes 1.83 2.44* 2.34* 2.45* 2.54** 2.50** 1.97 Country factor risk attitudes 1.12 0.81 0.66 0.62 0.75 0.75 0.82 Country factor entrepreneurial image 2.77* 1.95 2.62 2.30 2.25 2.00 Country factor institutional quality 0.55 0.66 0.66 0.63 0.39 Unemployment rate 1.02 1.02 1.01 1.03 Log GDP 0.81 0.82 0.82 GDP Growth 0.65 0.93 Power distance 0.99* Individualism 1.00 Masculinity 1.00 Uncertainty avoidance 1.00 Pseudo R-Square 0.00 0.01 0.01 0.01 0.01 0.01 0.02 chi2 31.92 86.09 282.91 423.32 1076.37 2607.69 . p 0.00 0.00 0.00 0.00 0.00 0.00 .

Source: Eurobarometer 2007 and 2009. The method used is logistic regression. Results are displayed in relative risk ratios (exponential of coefficients) and should be interpreted with reference to 1 (exponential of coefficient 0). Multinomial logistic regression is used and the reference category is non-entrepreneurs.

Table 4-12: Entrepreneurship due to opportunity and necessity Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Country factor entrepreneurial attitudes 1.57 1.66 1.43 1.48 1.63 1.67 1.34 Country factor risk attitudes 0.96 0.92 0.47 0.46 0.81 0.84 0.7 Country factor entrepreneurial image 1.2 0.32 0.35 0.24* 0.25* 0.07*** Country factor institutional quality 0.12** 0.10** 0.11*** 0.12*** 0.11** Unemployment rate 1.01 0.98 0.99 0.99 Log GDP 0.55** 0.55** 0.51*** GDP Growth 1.86 2.02 Power distance 1.00 Individualism 0.99 Masculinity 1.01* Uncertainty avoidance 1.00 Pseudo R-Square 0.00 0.01 0.01 0.01 0.01 0.01 0.02 chi2 31.92 86.09 282.91 423.32 1076.37 2607.69 . p 0.00 0.00 0.00 0.00 0.00 0.00 .

Source: Eurobarometer 2007 and 2009. The method used is logistic regression. Results are displayed in relative risk ratios (exponential of coefficients) and should be interpreted with reference to 1 (exponential of coefficient 0). Multinomial logistic regression is used and the reference category is non-entrepreneurs.

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4.7 Discussion and recommendations Entrepreneurship is an important driver of new business activities and entrepreneurship is also considered to be an important driver of innovation. Europe, facing the challenges of a severe economic crisis, is in need of new businesses which will not only replace those going bankrupt in the current crisis but which will also lay the foundations for a more competitive Europe after the crisis. Innovation is considered to be a key strategy in strengthening Europe’s economy and increased innovation and increased entrepreneurship could coincide as both are linked. New innovative products and services cannot always be delivered using existing production facilities and in order to market these innovations existing companies can create new production lines or new companies will emerge. Innovation and new business activities can reinforce each other and Europe needs both.

It is therefore important to understand why entrepreneurship is more prevalent in some countries than in others. To some extent differences in entrepreneurship can be explained by differences in personal attitudes like risk taking, but also in differences in countries’ education attainment levels, their industrial composition and institutional differences in setting up a new business or expanding an existing company. These and other explanatory factors have been studied in detail by scholars, using among others data from the Global Entrepreneurship Monitor (GEM) and the Eurobarometer Entrepreneurship Survey (EES).

This study is highlighting the importance of differences in social or societal attitudes which reflect differences in values or preferences shared by many individuals in the same country. Studies trying to understand the role of social attitudes are less frequent as surveys as GEM and EES only include a few questions which could be interpreted as reflecting social attitudes to entrepreneurship. GEM includes four such questions, when respondents are being asked if they think that in their country 1) most people would prefer that everyone has a similar standard of living, 2) most people would consider starting a new business a desirable career choice, 3) most people would have a high esteem of others successful at starting a new business and 4) public media publish about successful new business. The strength of the GEM survey is that these questions have been asked in most survey rounds making it possible to compare results over time34 and, given the fact that most questions have not been changed over time, it is expected that these questions will also be included in future GEM surveys.

34 Questions 1E (You are, alone or with others, expecting to start a new business, including any type of self-employment, within the next three years) and 1F (You have, in the past 12 months, sold, shut down, discontinued or quit a business you owned and managed, any form of self-employed, or selling goods or services to anyone) were not asked in the 2001 survey. Questions 1K (In your country, most people would prefer that everyone had a similar standard of living), 1L (In your country, most people consider starting a new business a desirable career choice), 1M (In your country, those successful at starting a new business have a high level of status and respect) and 1N (In your country, you will often see stories in the public media about successful new businesses) were not asked in 2001 and 2002. Questions Q2E1 (Will all, some, or none of your potential customers consider this product or service new and unfamiliar?) and Q3D1 (Do all, some, or none of your potential customers consider this product or service new and unfamiliar?) were not asked in 2001.

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EES also includes questions which can be interpreted as social attitudes. Respondent are asked if they agree with the following statements which reflect positive or negative attitudes to entrepreneurship 1) entrepreneurship is the basis of wealth creation, 2) entrepreneurs think only at their own wallet, 3) entrepreneurs are job creators and 4) entrepreneurs exploit other people's work. Unfortunately questions on these attitudes have only been asked in the 2 most recent EES surveys (cf. Annex 4 for a comparison of the use of questions in different EES surveys over time). Two more questions reflect attitudes to entrepreneurship and these have been asked in almost all EES surveys since 2001: 5) one should not start a business if there is a risk it might fail (which reflects risk tolerance) and 6 people who started a business and failed should be given a second chance. It is strongly recommended to include these questions also in future versions of EES.

Manski (1993, 1995) analyzed the problem of identifying endogenous social effects from observations of the distribution of behaviour in a population. The question Manski asks is can we disentangle endogenous from contextual and correlated effects?

• Endogenous effects are those effects wherein the propensity of an individual to behave in a certain way varies with the prevalence of that behaviour in the group;

• Contextual effects are those effects wherein the propensity of an individual to behave in a certain way varies with the distribution of background characteristics in that group.

• Correlated effects are those effects wherein individuals in the same group tend to behave similarly because they face similar institutional environments or have similar individual characteristics.

Manski (1993, 1995) highlighted that the identification of social effects is possible if the attributes defining reference groups and those directly affecting outcomes are moderately related. On the other hand, if these attributes are either functionally dependent or are statistically independent the prospects of identification are poor to null. Moreover Manski highlights that observations of behaviour cannot be used to identify individuals' reference groups, as this would result in perfect collinearity making the parameter associated with social effects unidentified. Panel data can be used for inference of social effects by relying on the assumption that non-social forces act contemporaneously whereas social forces act on the individual with a lag under the condition that non-equilibrium outcomes are observed (Manski, 1995). Even under these circumstances, the analysis is meaningful only if one has reasons to believe that the transmission of social effects follows the assumed temporal pattern (Manski, 1995). Manski (1993) further suggests that empirical evidence may be obtained from controlled experiments or from subjective data, e.g. the statements people make about why they behave as they do.

Table 4-13: ISCED defined levels of education Level Description Principal characteristics

0 Pre-primary education Initial stage of organized instruction, designed primarily to introduce very young children to a school-type environment

1 Primary education or first stage of basic education

Normally starting between the ages of 5 and 7, designed to give a sound basic education in reading, writing and mathematics along with an elementary understanding of other subjects

2 Lower secondary or second Designed to complete basic education, usually on a more subject-oriented

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stage of basic education pattern

3 (Upper) secondary education More specialized education typically beginning at age 15 or 16 years and/or the end of compulsory education

4 Post-secondary non-tertiary education

Captures programmes that straddle the boundary between upper- and post-secondary education from an international point of view, e.g. pre-university courses or short vocational programmes

5 First stage of tertiary education

Tertiary programmes having an advanced educational content, cross-classified by field (see below)

6 Second stage of tertiary education

Tertiary programmes leading to the award of an advanced research qualification, e.g. Ph.D., cross-classified by field (see below)

Both datasets EES and GEM do not have information about the respondent’s social reference group and the reference group’s attitudes which makes it impossible to identify social effects. Another important drawback is that attitudes are measured contemporaneously with the current occupational choice, therefore causality cannot be inferred. A main research question is to determine if because the individual has certain attitudes that he selects to become an entrepreneur or if the individual changes his attitudes in response to his labour market status. Furthermore, both datasets are cross-sections making it impossible to exploit the time dimension to look into social effects as determinants of the dynamics of the entrepreneurial process such as entry, survival and exits. A subgroup of respondents should therefore be monitored over time in all survey rounds.

EES also lacks reliable data on education and does not have any indication of income, or prior occupation and employment status. EES asks respondents for their age when they stopped full-time education. Respondents can either give this age, refuse to answer, say that they have never been in full-time education or are still in full-time education. Problem with the EES question is that does not give any information on respondents’ educational attainment and it cannot be linked to the International Standard Classification of Education (ISCED) which distinguishes between several defined levels of education (Table 4-13). In Chapter 2 of this study an ad-hoc definition of primary, secondary and tertiary education has been used in the analysis of the Innobarometer 2005 data and a similar definition could have been used in the analysis of the EES data. But this definition is rather crude and better proxies for educational attainment could be calculated if respondents would be asked the highest level of education for which they graduated. Table 4-14 highlights another issue with the current EES question, i.e. how to classify the almost 900 people who stopped full-time education at an age of 30 or higher as it is unlikely that all of these are PhD graduates.

GEM has poor data on education and household income with a lot of respondents not answering these questions. The questions in GEM referring to social groups are not clear and can lead to misinterpretations. For example: the question regarding if you know other entrepreneurs, can be interpreted in two ways: 1) you know other entrepreneurs therefore you decided to become an entrepreneur yourself or 2) you decided to become an entrepreneur therefore you got in contact with other entrepreneurs to gather more information.

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Table 4-14: EES years of education by age How old where you when you stopped full-time education 0-5 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-85

15-19 26 1 5 173 2 0 0 0 0 0 0 0 0 0 0 0 0 207

20-24 10 0 9 299 218 1 0 0 0 0 0 0 0 0 0 0 0 537

25-29 9 1 18 416 432 161 0 0 0 0 0 0 0 0 0 0 0 1037

30-34 9 3 38 649 501 231 39 0 0 0 0 0 0 0 0 0 0 1470

35-39 11 4 93 767 606 227 48 34 0 0 0 0 0 0 0 0 0 1790

40-44 13 2 93 931 577 194 46 38 29 0 0 0 0 0 0 0 0 1923

45-49 12 5 151 944 510 162 38 20 14 19 0 0 1 0 0 0 0 1876

50-54 19 5 247 990 554 163 42 17 24 12 18 0 0 0 1 0 0 2092

55-59 30 11 288 939 465 132 33 19 13 14 3 17 0 0 0 0 0 1964

60-64 37 11 341 801 389 131 32 15 16 9 2 9 17 0 0 0 0 1810

65-69 28 11 309 680 247 100 29 14 10 5 3 3 0 6 0 0 0 1445

70-74 50 15 261 443 196 66 23 9 9 6 6 4 1 1 9 0 0 1099

75-79 42 11 181 277 130 53 17 10 8 2 3 1 1 0 0 6 0 742

80-84 14 12 97 156 65 32 11 7 1 0 1 0 3 1 1 0 5 406

85-89 7 0 24 49 22 4 2 1 0 0 2 1 1 0 0 0 1 114

90-96 2 1 14 12 11 1 1 0 1 0 0 0 0 0 0 0 0 43

How

old

are

you

319 95 2174 8555 4946 1659 364 186 126 67 38 36 24 8 11 6 311

Source: Eurobarometer Entrepreneurship Survey 2007

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5 Conclusions and recommendations 5.1 Summary Europe is faced with many challenges: global competition is increasing, Europe’s population is ageing and governments are facing increasing budgetary constraints. Europe’s 2020 strategy has emphasized the role of innovation for improving our competitiveness, standard of living and well-being. But innovation is not something which should be taken for granted; Europe not only needs to invest more resources to improve its innovativeness but it should also improve the framework conditions for innovation. The 2006 Aho report35 recommended “the need for Europe to provide an innovation friendly market for its businesses”. Rather than stressing innovation inputs such as R&D, the Aho Report stresses innovation demand and the myriad of socio-cultural factors that encourage innovation, such as entrepreneurship, risk taking, flexibility and adaptability, and mobility. These socio-cultural factors define differences in social attitudes to innovation which influence entrepreneurship and demand for innovative goods and services. Social attitudes can be defined as “the attitudes of individuals or groups with respect to social objects or phenomena such as persons, races, institutions, or traits”.

Social attitudes to demand

Social attitudes towards innovation are defined as consumers’ receptiveness to try and adopt innovative products and services. Consumers’ receptiveness for innovative products and services can range from a ‘pro-innovation’ attitude (enthusiastically accepting or promoting an innovation) to an ‘anti-innovation’ attitude (resisting or even rejecting an innovation). Demand for innovation is defined as consumers’ actual purchasing decision of an innovative product or service. Hence, consumers’ attitudes towards adopting innovative products and services have a direct impact on demand for innovation. Differences in social influence and personal innovativeness explain differences across Europe in consumers’ attitudes towards innovative products and services.

Consumers’ perceptions of a new technology are influenced not only by the objective characteristics of the technology but also by the opinions of others. Social influence can take the form of subjective norms, i.e. the interpersonal influences coming from a variety of sources such as friends, relatives and neighbours. Moreover, social influence can take the form of ‘image’, i.e. the degree to which an adoption of the innovation is perceived to enhance one’s status. In general, social influence has an impact on consumers’ perceptions of the usefulness and ease-of-use of an innovative product or service. This perception is then translated in a more positive or negative attitude towards a new innovation.

Personal innovativeness is defined as "the willingness of an individual to try out any new technology”. That is, individuals who are more risk taking and innovative are more likely to evaluate a new technology more favourably in terms of perceived usefulness and perceived ease

35 http://ec.europa.eu/invest-in-research/action/2006_ahogroup_en.htm

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of use. Differences in cultural background and demographics explain differences in personal innovativeness. E.g. people with a higher level of education and self-employed and white collar workers are more attracted to innovations.

However, whereas social attitudes are defined as consumers’ receptiveness to try and adopt innovative products and services in general, prior studies have emphasised that consumer attitudes towards innovation differ with different innovations. For instance, while consumers are receptive towards innovation in information technology, they might react with suspicion in face of innovations in the field of nanotechnology.

Consumer resistance

Innovation implies a change to consumers, and resistance to change is a common human response. There are three types of consumer resistance: (1) ‘postponement’: consumers decide to adopt an innovation at a later point in time, for instance, until circumstances are more suitable; (2) ‘rejection’ involving an active evaluation on the part of the consumer resulting in a strong reluctance to adopt the innovation; and (3) ‘opposition’ where consumers are convinced that the innovation is not suitable and may even actively engage in public protests to prevent the launch of the innovation.

Risk plays an important role in consumer resistance. Economic risk and being unwilling to break with existing routines are important drivers of postponement behaviour. Conflict with existing usage patterns and economic risk also play an important role in consumers’ decision to reject an innovation. Additional factors to cause rejection include functional risks and societal risks. Physical risk and conflict with existing traditions are the predominant drivers of innovation opposition.

Risk reduction strategies are crucial in diminishing consumer resistance towards innovation. While strategies to increase innovation adoption usually emphasize the benefits of the innovation, a strategy to reduce risk perception cannot rely on emphasizing additional product benefits. The concerns and worries of consumers need to be taken seriously and thus be addressed appropriately. Given that different drivers have different effects on the resistance types, companies and policy makers need to develop specific strategies to deal with each type of consumer resistance.

Social attitudes to entrepreneurship

Entrepreneurial activity usually involves the founding and early-stage growth of new firms, although it can also involve the reinvigoration of established firms. New firms can be created by individuals or spun off from larger firms or from the public research sector. Entrepreneurship involves individual attitudes to risk and receptiveness to new ideas. Attitudes are positive or negative evaluations and the associated beliefs towards events, activities, ideas. They imply a judgemental component and are influenced by effect, behaviour and cognition. Therefore attitudes can be seen as perceptions and preferences and they determine an individual’s behaviour. Attitudes which are common to a group are social attitudes. Attitudes are influenced by values, culture36, institutions

36 A culture is a social system that shares a set of common values, in which such values permit social expectations and collective understandings. Values are related to the norms of a culture, but they are more global and abstract than

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and norms. Individual attitudes are partly the reflection of social attitudes. Social attitudes to entrepreneurship are defined as the attitudes of individuals or groups towards their preference and willingness to engage in entrepreneurial activities. They incorporate different aspects such as risk attitudes, opportunity perception and receptiveness to new ideas. Differences in social attitudes to entrepreneurship coincide with differences in observed rates of entrepreneurship. E.g. in countries with a more favourable attitude to self-employment the actual rate of self-employment is higher.

Attitudes, e.g. perceptions and preferences, are influenced by the experience that the person has. Therefore it is difficult to disentangle the effect of institutions from the effect of culture. Individuals form attitudes and values within an environment which can be conducive or restrict opportunities for the creation of new organizations. Individuals learn from their choices with a lower preference for self-employment for failed entrepreneurs. Failing in the early stages of entrepreneurship leads to an increase in the risk aversion towards bankruptcy. Failing can lead to a change in preference and therefore attitudes or a change in cognition and better chances of success in the future. Entrepreneurship is positively associated with education, and negatively with gender. Individuals with high-school or tertiary education are more likely to become entrepreneurs. Women are less likely to be entrepreneurs. Entrepreneurs are more likely to have a higher preference for self-employment, and to think that people who started a business and failed should be given a second chance, and less likely to agree with the statement that they would never invest money in a business managed by someone who failed in the past. They are less likely to be afraid of the risk of bankruptcy when starting a business and more likely to think that their school education made them interested in becoming an entrepreneur. Overall, it seems that entrepreneurs have a positive orientation towards learning from obstacles and are more likely to be supportive of others.

Those who start a business out of opportunity are more likely to assert that their school education made them interested to become an entrepreneur and less likely to think that entrepreneurs exploit other people’s work. They also have a much higher preference to be self-employed. Entrepreneurs by necessity are one-third of the entrepreneurs by opportunity. Those who start a business out of necessity are more likely to have enjoyed higher education and are more likely to think that one should not start a business if there is a risk it might fail. Belgians are more likely to start a business out of opportunity whereas British are more likely to start a business out of necessity. Entrepreneurs by necessity differ from entrepreneurs by opportunity by the fact that they are better educated, having a tertiary or high-school degree. The results suggest that entrepreneurs by opportunity hold a more positive view towards entrepreneurship and are less risk-averse than non-entrepreneurs and entrepreneurs by necessity. Out of all the risks, Europeans are mostly afraid of the risk of bankruptcy. This risk could be properly addressed by promoting programmes training entrepreneurs in acquiring skills to minimize such a risk and by modifying appropriately existing regulations.

norms. Norms are rules for behavior in specific situations, while values identify what should be judged as good or evil. Values become embedded in the social structure over time via institutions (laws, policies), norms (customs) and traditions. Values can change over time and they are influenced by an economy’s structure and the allocation of resources which in their turn are the result of policies promoted by national governments.

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5.2 Recommendations for improved monitoring in surveys It is important to understand why entrepreneurship is more prevalent in some countries than in others and why in some countries there is more demand for innovative products and services.

To some extent differences in entrepreneurship can be explained by differences in personal attitudes like risk taking, but also in differences in countries’ education attainment levels, their industrial composition and institutional differences in setting up a new business or expanding an existing company. These and other explanatory factors have been studied in detail by scholars, using among others data from the Global Entrepreneurship Monitor (GEM) and the Eurobarometer Entrepreneurship Survey (EES). This study is highlighting the importance of differences in social or societal attitudes which reflect differences in values or preferences shared by many individuals in the same country. Studies trying to understand the role of social attitudes are less frequent as surveys as GEM and EES only include a few questions which could be interpreted as reflecting social attitudes to entrepreneurship.

GEM includes four such questions, when respondents are being asked if they think that in their country 1) most people would prefer that everyone has a similar standard of living, 2) most people would consider starting a new business a desirable career choice, 3) most people would have a high esteem of others successful at starting a new business and 4) public media publish about successful new business. The strength of the GEM survey is that these questions have been asked in most survey rounds making it possible to compare results over time.

EES also includes questions which can be interpreted as social attitudes. Respondent are asked if they agree with the following statements which reflect positive or negative attitudes to entrepreneurship 1) entrepreneurship is the basis of wealth creation, 2) entrepreneurs think only at their own wallet, 3) entrepreneurs are job creators and 4) entrepreneurs exploit other people's work. Unfortunately questions on these attitudes have only been asked in the 2 most recent EES surveys. Two more questions reflect attitudes to entrepreneurship and these have been asked in almost all EES surveys since 2001: 5) one should not start a business if there is a risk it might fail (which reflects risk tolerance) and 6 people who started a business and failed should be given a second chance. It is strongly recommended to include these questions also in future versions of EES.

Manski (1993, 1995) analyzed the problem of identifying endogenous social effects from observations of the distribution of behaviour in a population. The question Manski asks is can we disentangle endogenous from contextual and correlated effects37? Manski highlighted that the identification of social effects is possible if the attributes defining reference groups and those directly affecting outcomes are moderately related. Panel data can be used for inference of social effects by relying on the assumption that non-social forces act contemporaneously whereas social

37 Endogenous effects are those effects wherein the propensity of an individual to behave in a certain way varies with the prevalence of that behaviour in the group; contextual effects are those effects wherein the propensity of an individual to behave in a certain way varies with the distribution of background characteristics in that group; and correlated effects are those effects wherein individuals in the same group tend to behave similarly because they face similar institutional environments or have similar individual characteristics.

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forces act on the individual with a lag under the condition that non-equilibrium outcomes are observed (Manski, 1995). Even under these circumstances, the analysis is meaningful only if one has reasons to believe that the transmission of social effects follows the assumed temporal pattern (Manski, 1995). Manski (1993) further suggests that empirical evidence may be obtained from controlled experiments or from subjective data, e.g. the statements people make about why they behave as they do. Both datasets EES and GEM do not have information about the respondent’s social reference group and the reference group’s attitudes which makes it impossible to identify social effects. Another important drawback is that attitudes are measured contemporaneously with the current occupational choice, therefore causality cannot be inferred. A main research question is to determine if because the individual has certain attitudes that he selects to become an entrepreneur or if the individual changes his attitudes in response to his labour market status. Furthermore, both datasets are cross-sections making it impossible to exploit the time dimension to look into social effects as determinants of the dynamics of the entrepreneurial process such as entry, survival and exits. A subgroup of respondents should therefore be monitored over time in all survey rounds.

EES also lacks reliable data on education and does not have any indication of income, or prior occupation and employment status. EES asks respondents for their age when they stopped full-time education. Respondents can either give this age, refuse to answer, say that they have never been in full-time education or are still in full-time education. Problem with the EES question is that does not give any information on respondents’ educational attainment and it cannot be linked to the International Standard Classification of Education (ISCED) which distinguishes between several defined levels of education. In Chapter 2 of this study an ad-hoc definition of primary, secondary and tertiary education has been used in the analysis of the Innobarometer 2005 data and a similar definition could have been used in the analysis of the EES data. But this definition is rather crude and better proxies for educational attainment could be calculated if EES would directly ask respondents for the highest level of education for which they graduated.

A limitation of the results based on the Innobarometer 2005 is that a potentially very powerful variable as income is not available. Persons with a higher disposable income are more likely to be attracted to innovations as they can afford these more expensive products. Unfortunately a question on income is not included in the Innobarometer 2005 survey. It is recommended to include such a question in any future survey aiming to better understand peoples’ attractiveness to innovations38. It is also strongly recommended to repeat the Innobarometer survey as results based on 2005 data become outdated as peoples’ attitudes, income and educational attainment change over time, and perhaps even more so during the current financial and economic crisis. The Innobarometer 2005 set of questions on peoples’ attitudes to innovations could easily be included in one of the standard Eurobarometer surveys on an annual basis. It is also recommended to

38 A question on incomoe could be formulated as follows: What is your total household income? a) Less than €10,000, b) Between €15,000 and €20,000, c) Between €20,000 and €25,000, d) Between €25,000 and €30,000, e) Between €30,000 and €40,000, f) Between €40,000 and €50,000, g) Between €50,000 and €75,000, h) Between €75,000 and €100,000, i) More than €100,000. The income brackets only serve as an example and should be defined based on the actual income distribution in European countries.

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include some of the major non-European countries, e.g. the United States, Japan, China and India, to enable comparisons with countries outside of Europe.

Attitudes to entrepreneurship and attitudes to innovative products and services could be linked and questions probing these attitudes should be combined in one survey. The Innobarometer 2005 questions on being attracted to innovative products and services could easily be included in the EES as these surveys already share most of the questions on demographics and socio-economic status.

GEM has poor data on education and household income with a lot of respondents not answering these questions. The questions in GEM referring to social groups are not clear and can lead to misinterpretations. For example: the question regarding if you know other entrepreneurs, can be interpreted in two ways: 1) you know other entrepreneurs therefore you decided to become an entrepreneur yourself or 2) you decided to become an entrepreneur therefore you got in contact with other entrepreneurs to gather more information.

5.3 Policy discussion Over the past century, the theoretical framework to understand the innovation process and the design of innovation policies has been predominantly influenced by technology-push innovation theories. Emphasizing innovation as the essential driving force of social and economic change (Schumpeter, 1934) public policy intended to boost knowledge production and supply in order to spur knowledge output and spillovers (Jones and Williams, 1998).

Supply-push policies generally use public investment through grants and subsidies to stimulate innovation in the EU and its Member States. Examples of supply-push policies include government-sponsored R&D, tax credits for firms to invest in R&D and support for education and training.

A demand-pull perspective acknowledges the importance of producing innovations but at the same time emphasizes the need for market opportunity. Demand is considered as the driving force that directs innovation output to meet societal or market needs (Schmookler, 1966). Demand-side policies aim to boost demand and encourage suppliers to meet the expressed needs of consumers. Examples of demand-side policies include tax credits and rebates for consumers of new technologies, technology-oriented government procurement, technology mandates, and innovation-specific regulations and standards (Cunningham, 2009).

Entrepreneurship is one of the most important drivers of innovation and involves individual attitudes to risk, opportunities that reduce risk, receptiveness to new ideas, access to sources of new ideas with commercial potential, and access to capital. Entrepreneurship does not need to involve technological innovation, but can be based on franchising or establishing small businesses. However, innovation policy has been primarily interested in the creation of innovative firms that develop new technology, use technology in new ways, for example new business models to exploit the capabilities of the internet, or which are based on new organisational structures.

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Firms invest in product and service innovation based on current or expected demand for innovative goods and services. Especially with regard to innovative entrepreneurs, it is crucial that they meet a sophisticated market which demands their innovative products and services. Social demand for innovative products develops from the purchase decisions of individual consumers. Only when consumers are receptive to purchasing innovative products and services do the innovations by entrepreneurs become commercially viable.

Social attitudes to innovation influence entrepreneurship and demand for innovative goods and services. It is thus crucial to understand the effects of culture and social attitudes on innovation adoption in order to design effective policy measures to spur innovativeness of countries. Differences in socio-cultural environments of countries and regions may explain why similar economic policies have different effects on entrepreneurship and innovation across cultures.

Consumer demand for innovation

The successful commercialisation of an innovation depends on the adoption decision of consumers. Consumer receptiveness towards innovative products and services is found to be one of the closest measures to capture demand for innovation in a country. Successful suppliers of innovations need customers who are willing to try and buy new products and services.

Consumers perceptions of a new technology are influenced not only by the objective characteristics of the technology but also by the opinions and behaviour of relevant others (Salancik and Pfeffer, 1978). Social influence takes the form of subjective norms and image which affects consumers’ attitude towards a technology and thus influences the consumers’ adoption decision. Subjective norms often take the form of interpersonal influences coming from a variety of sources such as friends, relatives and neighbours or from inspirational figures such as movie stars. Studies conducted by Rosen and Olshavsky (1987) and Childers and Rao (1992) confirmed that familial and peer-based reference groups have a significant influence on consumer decisions.

According to the Technology Acceptance Model (Davis, 1989) a potential adopter assesses a new technology on the basis of two criteria: ‘perceived usefulness’ defined as "the degree to which a person believes that using a particular system would enhance his or her job performance" and ‘perceived ease-of-use’ defined as "the degree to which a person believes that using a particular system would be free from effort". Social influences, in the form of subjective norms and image can affect an individual’s evaluation of a technology’s perceived usefulness. Furthermore, social influences can also shape an individual’s estimation of his or her confidence in using a new technology. An extension of the TAM model by Agarwal and Prasad (1998) had added ‘personal innovativeness in the domain of IT’ which is defined as "the willingness of an individual to try out any new information technology". Individuals who are more risk taking and innovative are more likely to evaluate a new technology more favourably in terms of perceived usefulness and perceived ease of use.

As cultural values are reflected and reinforced by social institutions and behaviours, culture determines the degree to which a society supports innovative behaviour. Societies that value and reward innovative behaviour are more likely to promote the development and adoption of innovation (Herbig and Miller, 1992). Cross-country differences in personal innovativeness are

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inter alia due to systematic differences in the national environment (Steenkamp et al., 1999). Based on Hofstede’s (1980, 1981) seminal work on cultural values, differences in the degree of power distance, individualism, masculinity and uncertainty avoidance can be related to differences in attitudes to innovation. Our econometric analysis shows that in countries with higher degrees of power distance and individualism people are more attracted to innovations and in countries with higher degree of uncertainty avoidance and masculinity people are less attracted to innovations.

From the reported findings we can conclude that policies promoting more favourable social attitudes to demand can have a profound impact on creating a larger and more sophisticated market for new innovative products and services. Cunningham’s (2009) typology of demand-oriented measures distinguishes between direct and indirect support measures (Table 5-1).

Tax incentives for the purchase or use of innovations are hardly being used in Europe (Izsak and Edler, 2011) Demand subsidies, support measures raising awareness and voluntary labels and information campaigns seem to be the most relevant policy options.

Demand subsidies can persuade consumers to buy innovative products by lowering the cost price. Subsidies on energy-saving products (e.g. insulation used in the construction of new houses) can trigger consumers to buy such products and thereby increasing the market potential for firms supplying such products. Subsidising innovative products (or technologies) should not be done on an ad-hoc and discontinuous basis but should be repeated for a longer period time as this will increase the possibility that consumers also become more aware of the positive product characteristics (e.g. ‘good for the environment’) and will thus be more willing to buy such products in the long-run even if the subsidies diminish or disappear.

Table 5-1: Demand-oriented support measures Direct support for private demand Demand subsidies Co-financing The purchase of innovative technologies by private or industrial demanders is

directly subsidized Tax incentives Co-financing Amortisation possibilities for certain innovative technologies Indirect support for private and public demand: information and enabling (soft steering) Awareness building measures

Informing

State actors start information campaigns, advertise new solutions, conduct demonstration projects (or supports them) and try to create confidence in certain innovations (in the general public, opinion leaders, certain target groups)

Voluntary labels or information campaigns

Supporting Informing

The state supports a coordinated private marketing activity which signals performance and safety features

Training and further Education

Enabling

The private consumers or industrial actors are made aware of innovative possibilities and simultaneously placed in a position to use them

Articulation and Foresight

Organising discourse

Societal groups, potential consumers are given voice in the market place, signals as to future preferences (and fears) are articulated and signalled to the marketplace (including demand based foresight)

Source: Cunningham (2009).

Unawareness with new innovative products will deter consumers from buying these products. Awareness building measures should reduce such unawareness by emphasising the benefits of

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innovations. The introduction of labels will also contribute to reducing unawareness as consumers will perceive these as guarantees of quality and potential use.

Consumer resistance

Most commercial companies experience high rates of innovation failures (Moore, 2002) as consumer demand for innovative products and services remains low. Many innovations meet resistance (Garcia and Atkin, 2002, Kleijnen et al., 2009) and consumer resistance is an important element in the demand for innovation. Innovation resistance exists across product classes (Ram and Sheth, 1989). Ram and Sheth (1989) differentiate between three types of consumer resistance: postponement, rejection and opposition. While postponement relates to more practical concerns, rejection is caused by more societal concerns for maintaining tradition and social norms.

Adopting innovations often requires changes in consumers’ existing habits and to develop new ones. Innovation resistance appears therefore as a normal consumer response. The strength of the innovation resistance relies on the size and scope of the change of habits that the innovation implies (Laukkanen et al., 2007).

Psychological barriers have a stronger effect on mature consumers than other barriers (Laukkanen et al., 2007). If it is true that psychological factors have a stronger impact on innovation reluctance than technological barriers or other product features then technology-driven policies assuming that new technologies are always superior and that consumers must just be educated to enable them to use end benefit from innovations may be inefficient if applied to older generations of consumers. Instead, it is the type of innovation resistance that should determine the strategies to overcome it (Ram, 1989). An alternative strategy could be, for instance, a communication strategy emphasizing face-to-face contact. Only if innovation resistance is caused by perceived functional or economic risks, an innovation modification strategy (Dunphy and Herbig, 1995) could proof to be more effective.

For all types of resistance risks plays an important role. Therefore, risk reduction strategies are crucial in diminishing consumer resistance towards innovation. Information campaigns signalling performance and safety features (cf. Table 5-1) could be used by governments but such campaigns such not overload the consumer with information as this could increase resistance to innovation (Herbig and Kramer, 1994).

Decreasing resistance requires a different approach as to increase adoption of innovation (Kleijnen et al., 2009). While strategies to increase innovation adoption usually emphasize the benefits of the innovation, a strategy to reduce risk perception cannot rely on emphasizing additional product benefits. The concerns and worries of consumers need to be taken seriously and thus be addressed appropriately. Conflict with existing usage patterns and the fear of economic loss are the main drivers of delaying the innovation adoption decision. Policies should emphasize that the innovation fits within the consumer’s current lifestyle.

Functional and societal risks cause the consumer to reject the innovation. Extensive labelling information and increasing the traceability and transparency of ingredients or components of the information may support the consumer in his efforts to seek information and make an informed

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decision. The perceived functional risk of an innovation can be reduced by using warranties and quality assurances (Kleijnen et al., 2009).

Physical risks, the fear of harm and dangers brought by an innovation cause consumers to oppose to innovations. Testing of innovations by independent institutes is an effective strategy to reduce the perception of risks and overcome opposition (Yeung and Morris, 2001).

Entrepreneurship

Entrepreneurship has received a lot of attention over the past thirty years ever since Birch’s (1979, 1987) influential contribution on the employment generating role of Small Medium Enterprises (SMEs) and governments attach high hopes to a positive effect of entrepreneurship on economic growth and therefore promote setting up new businesses as well as start-up aspirations (Freytag and Thurik, 2010). But the economic evidence is not clear and convincing (Blanchflower, 2010, Davis et al., 1993, 1996), e.g. there appears to be a U-shaped relationship between income and the rate of self-employment (Acs et al., 1994, Van Stel, 2005, Wennekers, 2005). But innovative start-ups do grow faster than non-innovative start-ups (Hurst and Pugsley, 2011). Despite the sometimes contradicting empirical results, there is a strong believe that higher rates of entrepreneurship will favour a country’s economic and innovation performance.

Entrepreneurship depends not only on economic factors (e.g. access to capital) but also on the social environment in which the firm is created as entrepreneurship is essentially a social phenomenon which has a social and cultural dimension (Berger, 1991, Shapero and Sokol, 1982, Steyaert, 2007, Thornton et al., 2011). E.g. Shapero and Sokol (1982) emphasize that “the social and cultural factors that enter in the formation of entrepreneurial events are most felt through the formation of individual values systems. More specifically in a social system that places a high value on the formation of new ventures more individuals will choose that path”. Davidsson and Wiklund (1997) find that cultural and structural determinants are correlated and they suggest that to the extent that cultural variation is the real cause for variations in new firm formation rates, studies that use only structural (i.e. economic and socio-demographic) explanatory variables may exaggerate the influence of the latter.

Even before deciding to become an entrepreneur there are many events and external factors that affect the potential entrepreneur his/her success (Wintjes, 2004). Access to resources and knowledge can come from former employment experiences, an entrepreneurial family, educational programmes, university policies, etc. Also after the decision to start a company the entrepreneurship is ‘shaped’ by the social attitudes of others, e.g. banks, innovation centres, venture capitalist, governments or large companies. As the firms grows the role of the founding entrepreneur decreases.

Social attitudes to entrepreneurship by shaping personal attitudes become important in understanding and explaining differences in entrepreneurship. In countries with a more favourable attitude to entrepreneurs we observe a higher rate of entrepreneurship and also positive media attention attributes to more entrepreneurship. Networks are also important: knowing other entrepreneurs has a positive impact on becoming an entrepreneur oneself. Education also matters, as education can provide the knowledge and skills required to start a business. But also previous

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entrepreneurial experience, even involving failed attempts trying to start a business, will have a positive impact on entrepreneurship.

From the above it follows that entrepreneurs are shaped by their family environment, by the knowledge, skills and attitudes gathered during their formal education, from their working experience, from their interactions with others in social groups and from their exposure to the media. Policy interventions in any of these will have a two-stage effect. The first is a direct effect, e.g. educational policies introducing entrepreneurship classes in schools, in which the individual’s attitudes are likely to be changed in the short-run. The second is an indirect effect in which the changes in the individual’s attitudes will shape social attitudes in the longer run thereby having a positive impact on the attitudes of future individuals. Policies will have no direct effect on family environment but the latter can be changed in the future as many young entrepreneurs will be parents in the near future. For governments educational policies and the role of mass media are of particular interest.

Entrepreneurship education “should develop both general competences, e.g. self-confidence, adaptability, risk-assessment, creativity, and specific business skills and knowledge” (McCoshan et al., 2010). McCoshan et al. (2010) in their review of entrepreneurship education in Europe conclude that such education is typically an extra-curricular activity driven by individual teachers. More integrated efforts are needed at all levels of education and McCoshan et al. (2010) recommend a national strategy for entrepreneurship education. At the supranational level the European Commission should perform three functions: it should act as a catalyst collecting and disseminating good practices, it should have a platform function providing stakeholders the opportunity to discuss common issues and it should act as an enabler by mobilising the resources to support education activities at EU level and within the Member States.

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6 References Acs, Z.J., Audretsch, D. and Evans, D.S. (1994), “The determinants of variations in the self-employment

rates across countries and over time. London, UK: Centre for Economic Policy Research. Discussion paper DP871.

Acs, Z.J. and Audretsch, D. (2003), Handbook of Entrepreneurship Research, New York, Springer. Agarwal, R. and Prasad, J. (1998), A conceptual and operational definition of personal innovativeness in the

domain of information technology, Information Systems Research 9(2), 204-215. Ajzen, I. (1985), From intentions to actions: A theory of planned behaviour. In Kuhl, J. and Beckman, J.

(Eds.), Action-control: From cognition to behaviour (pp. 11-39). Heidelberg: Springer. Ajzen, I. (1991), The theory of planned behaviour, Organizational Behaviour and Human Decision Processes

50(2), 179-211. Ajzen, I. and Fishbein, M. (1980), Understanding attitudes and predicting social behaviour, Prentice-Hall,

Englewood Cliffs, NJ. Armour, J. and D. Cumming (2008), Bankruptcy Law and Entrepreneurship, American Law and Economics

Review 10 (2), 303-350. Arundel, A. and Cruysen, A. van (2008), Knowledge Economy Indicators, WP1 Policy Scenarios: Demand

for innovation. Deliverable 1.4c. Arundel, A. and Hollanders, H. (2005), EXIS: An exploratory approach to Innovation Scoreboards, Trend

Chart, DG Enterprise, March 2005. Arundel, A. and Hollanders, H. (2006), Searching the forest for the trees: “Missing” indicators of innovation,

Trend Chart, DG Enterprise, July 2006. Ashby, K. and Mahdon, M. (2009), Measuring the nature of demand for innovation in the UK: The challenges

of an indicator approach, Innovation Index Working Paper, London: NESTA. Audretsch, D.B. (1995), Innovation and Industry Evolution, MIT Press, Cambridge MA. Autio, E. and Wennberg, K. (2010), You think, therefore, I become: Social attitudes and the transition to

entrepreneurship, Paper presented at DRUID Summer Conference 2010, Imperial College London Business School, June 16-18 2010.

Ayyagari, M., Demirgüç-Kunt, A., Maksimovic, V. (2011), Small vs. Young Firms Across the World: Contribution to Employment, Job Creation and Growth, World Bank Policy Research Working Paper Series 5631.

Ballou, J., Barton, T., DesRoches, D., Potter, F., Reedy, EJ, Robb, A., Shane, S. and Zhao, Z. (2008), The Kauffman Firm Survey: Results from the baseline and first follow-up surveys. Kauffman Foundation, Kansas City, March 2008.

Baumol, W. (1990), Entrepreneurship: Productive, unproductive, and destructive, Journal of Political Economy 98(5), 893–921.

Beise, M. and Rennings, K. (2001), Lead markets of environmental innovations: A framework for innovation and environmental economics. ZEW, Mannheim.

Berger, B. (1991), The culture of entrepreneurship, San Francisco, CA: ICS Press. Bhatnagar, A., Misra, S. and Rao, H.R. (2000), On risk, convenience, and internet shopping behaviour,

Communications of the ACM 43(11), 98-106. Birch, D.L. (1979), The Job Generation Process, MIT Program on Neighbourhood and Regional Change,

Cambridge. Birch, D.L. (1987), Job Creation in America, New York: The Free Press. Blanchflower, D.G. (2000), Self-Employment in OECD Countries, Labour Economics 7, 471-505. Blau, D. (1987), A time-series analysis of self-employment in the United States, Journal of Political Economy

95(3), 445-467.

114

Bosma, N.S. (2009), The Geography of Entrepreneurial Activity and Regional Economic Development. Multilevel analyses for Dutch and European Regions. PhD Dissertation Utrecht University, Utrecht. ISBN 978-90-902-3994-I.

Bosma, N.S. and Schutjens, V.A.J.M. (2009), Mapping Entrepreneurial Activity and Entrepreneurial Attitudes in European regions, International Journal of Entrepreneurship and Small Business 7(2), 191-213.

Brancheau, J.C. and Wetherbe, J.C. (1990), The adoption of spreadsheet software: Testing innovation diffusion theory in the context of end-user computing, Information Systems Research 1(2), 115-143.

Bredahl, L. (2001), Determinants of consumer attitudes and purchase intentions with regard to genetically modified foods – Results of a cross-national survey, Journal of Consumer Policy 24, 23–61.

Bravo-Biosca, A. (2010), Growth Dynamics: Exploring business growth and contraction in Europe and the US, London: FORA and NESTA.

Bull, I. and Willard, G.E. (1993), Towards a Theory of Entrepreneurship, Journal of Business Venturing 8, 183-195.

Caliendo, M., Fossen, F. and Kritikos, A. (2009), Risk attitudes of nascent entrepreneurs-new evidence from and experimentally validated survey, Small Business and Economics 32(2), 153-167.

Carland, J.W., Hoy, F., Boulton, W. R. and Carland, J. C (1984), Differentiating Entrepreneurs from Small Business Owners: A Conceptualization, Academy of Management Review 9(3), 354-359.

Casson, M.C. (1993), Entrepreneurship, The Concise Encyclopedia of Economics, Library of Economics and Liberty. 25 February 2012. <http://www.econlib.org/library/Enc1/Entrepreneurship.html>.

Casson, M.C. (2010) Entrepreneurship: theory, institutions and history, Eli F. Heckscher Lecture, 2009, Scandinavian Economic History Review 58(2). 139-170. ISSN 0358-5522

Casson, M.C., Yeung, B., Basu, A. and Wadeson, N. (eds.) (008), The Oxford Handbook of Entrepreneurship, Oxford University Press.

Childers, T.L. and Rao, A. (1992), The influence of familial and peer-based reference groups on consumer decisions, Journal of Consumer Research 19, 198-211.

Cole, A. H. (1949), Entrepreneurship and entrepreneurial history. Change and the Entrepreneur, 88-107. In: Davidsson, P. (2004), Researching Entrepreneurship, Springer, Boston.

Cunningham, P. (2009), Demand-side Innovation Policies, PRO Inno TrendChart Policy Brief 1, European Commission: DG Enterprise.

D’Errico, R.A. (2005), Harris interactive poll finds mixed news for VoIP adoption, The Business Review, March 15.

Davidson, R.S. and Walley, P.B. (1985), Computer fear and addiction: Analysis, prevention and possible modification, Journal of Organizational Behavior Management 6, 37–51.

Davidsson, P. (2004), Researching Entrepreneurship, International Studies in Entrepreneurship, New York: Springer Science.

Davidsson, P. and Wilklund, J. (1997), Cultural Values and Regional Variations in New Firm Formation, Journal of Economic Psychology 18, 153-340.

Davis, F.D. (1989), Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly 13(3), 319-339.

Davis, S., Haltiwanger, J. and Schuh, S. (1993), Small Business and Job Creation: Dissecting the Myth and Reassessing the Facts, NBER Working Papers 4492.

Davis, S., Haltiwanger, J. and Schuh, S. (1996), Job Creation and Destruction, MIT Press. Dawar, N. and Parker, P. (1994), Marketing Universals: The Use of Brand Name, Price, Physical

Appearance, and Retailers' Reputation as Signals of Product Quality, Journal of Marketing 58(2), 81-95. Djankov, S., Qian, Y., Roland, G. and Zhuravskaya, E. (2008), What Makes an Entrepreneur?, mimeo. Dobre, C., Dragomir, A. and Preda, G. (2009), Consumer Innovativeness: A Marketing Approach,

Management & Marketing 4(2), 19-34.

115

Drucker, P. (1985), Innovation and entrepreneurship, New York: Harper & Row. Dunphy, S. and Herbig, P.A. (1995), Acceptance of innovations: The customer is the key!, The Journal of

High Technology Management Research 6, 193-209. Estrin, S., Korosteleva, J. and Mickiewicz, T. (2011), Which Institutions Encourage Entrepreneurs to Create

Larger Firms?, CEPR Discussion Papers 8247, CEPR Discussion Papers. Eurobarometer Report (2010), Europeans and Biotechnology in 2010, Directorate General for Research in

Science in Society and Food, Agriculture & Fisheries and Biotechnology. European Commission (2005), Flash Eurobarometer 160 (Entrepreneurship), GESIS Data Archive, Cologne,

ZA4184 Data file Version 1.0.0, doi:10.4232/1.4184 European Commission (2008), Flash Eurobarometer 192 (Entrepreneurship), The GALLUP Organisation,

Brussels. GESIS Data Archive, Cologne, ZA4726 Data file Version 1.0.0, doi:10.4232/1.4726 European Commission (2011), Flash Eurobarometer 283 (Entrepreneurship in the EU and Beyond), The

GALLUP Organisation, Brussels. GESIS Data Archive, Cologne, ZA5439 Data file Version 1.0.0, doi:10.4232/1.10210

Evans, D.S. and Jovanovic, B. (1989), An Estimated Model of Entrepreneurial Choice under Liquidity Constraints, Journal of Political Economy 97, 808-827.

Fishbein, M. and Ajzen, I. (1975), Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, Addison Wesley, Reading, MA.

Fogel, K., Hawk, A., Morck, R. and Yeung, B. (2008), Institutional obstacles to entrepreneurship, in: Casson, M. and Yeung, B. (Eds.), Oxford Handbook of Entrepreneurship, Oxford, Oxford University Press, 540-579.

Freytag, A. and Thurik, A.R. (2010), Introducing Entrepreneurship and Culture. In Freytag, A. and Thurik, A.R. (Eds.), Entrepreneurship and Culture, Berlin: Springer Verlag, 1-10.

Gabr, H.M. and Hoffman, A. (2006), A General Policy Framework for Entrepreneurship, FORA, Division for Research and Analysis, Ministry of Business and Economic Affairs, April. Copenhagen.

Garcia, R. and Atkin, T. (2002), Coo-petition for the diffusion of resistant innovations: A case study in the global wine industry, Institute for Global Innovation Management Working Paper, 05-002 (1–22).

Gartner, W.B. (1988), Who is the entrepreneur? is the wrong question, American Journal of Small Business 12, 11-32.

Gatignon, H. and Robertson, T.S. (1989), Technology Diffusion: An Empirical Test of Competitive Effects, Journal of Marketing 53(1), 35-49.

Gee, S. and Miles, I. (2008), Mini Study 04 – Innovation Culture, Global Review of Innovation Intelligence and Policy Studies, INNOGRIPS.

Georghiou, L. (2007), Demanding Innovation: lead markets, public procurement and innovation, NESTA Provocation 02, NESTA, London.

Gillooly, C. (1998), Disillusionment, Information Week 669, 46–51. Gregory, G.D., Munch, J.M. and Peterson, M. (2002), Attitude functions in consumer research: comparing

value-attitude relations in individuals and collectivist cultures, Journal of Business Research 55, 933-942.

Grilo, I. and Irigoyen, J-M. (2006), Entrepreneurship in the EU: To Wish and not to be, Small Business Economics 26(4), 305-318.

Grilo, I. and Thurik, R. (2008), Determinants of entrepreneurial engagement levels in Europe and the US, Industrial and Corporate Change 17(6), 1113-1145.

Harris, J. and Blair, E.A. (2006), Consumer preference for product bundles: The role of reduced search costs, Journal of the Academy of Marketing Science 34(4), 506–513.

Hausman, A. and Stock, J.R. (2003), Adoption and implementation of technological innovation within long-term relationships, Journal of Business Research 56(8), 681-686.

116

Hayton, J.C., George, G. and Zahra, S. (2002), National culture and entrepreneurship: A review of behavioural research, Entrepreneurship Theory & Practice 26, 33-52.

Herbig, P.A. and Day, R.L. (1992), Customer acceptance. The key to successful introductions of innovations, Marketing Intelligence & Planning 10(1), 4-15.

Herbig, P.A. and Miller, J.C. (1992), Cultural Aspects of Innovation, Journal of Global Marketing (6)3, 23-45. Hippel, E. von (1986), Lead users: a source of novel product concepts, Management Science 32, 791-805. Hisrich, R.D. and Peters, M.P. (1989), Entrepreneurship: Starting, Developing, and Managing a New

Enterprise, Homewood: B.P.I./Irwin. Hoffmann, A. and Gabr, H.M. (2006), A General Policy Framework for Entrepreneurship, FORA - Ministry of

Economic and Business Affairs’ Division for Research and Analysis, Denmark. Hofstede, G. (1980), Culture's consequences: International differences in work-related values, Newbury

Park, CA: Sage. Hofstede, G. (1991), Cultures and Organisations: Software of the Mind, McGraw-Hill, Berkshire, England. Hofstede, G., Hofstede G.J. and Minkov, M. (2010), Cultures and Organizations: Software of the Mind, 3rd

Edition, McGraw-Hill USA. Hurst, E. and Pugsley, B.W. (2011), What Do Small Business Do?, NBER working paper 17041. Innobarometer (2005), Population Innovation Readiness, Special Eurobarometer 236/Wave 63.4 – TNS

Opinion & Social. Izsak, I. and Edler, J. (2011), Trends and Challenges in Demand-Side Innovation Policies in Europe”, INNO

Policy Thematic Report, Brussels, European Commission. Jones, C.I. and Williams, J.C. (1998), Measuring the Social Return to R&D, The Quarterly Journal of

Economics. 113(4), 1119-1135. Jönköping International Business School (2007), The promotion of entrepreneurship in the audio-visual

media (esp. TV), Brussels, European Commission, DG Enterprise. Katz, J. and Gartner, W.B. (1988), Properties of emerging organizations, Academy of Management Review

13, 429-441. Kelsen, H. and Knight, M. (1964), Norm and Value, California Law Review 54(4), 1624-1629. Kennett, P.A., Moschis, G.P. and Bellenger, D.N. (1995), Marketing financial services to mature consumers,

Journal of Services Marketing 9(2), 62-72. King, R.T. (1994), California DMV’s computer overhaul ends up as costly ride to junk heap, Wall Street

Journal, New York, Apr. 27, Eastern edition. Kirton, M. (1976), Adaptors and innovators: A description and measure, Journal of Applied Psychology 67(5),

622-629. Kirzner, I.M. (1973), Competition and entrepreneurship, Chicago: University of Chicago Press. Kirzner, I.M. (1979), Perception, Opportunity and Profit, Chicago: University of Chicago Press. Kleijnen, M., Lee N. and Wetzels, M., (2009), An exploration of consumer resistance to innovation and its

antecedents, Journal of Economic Psychology 30, 344-357. Knight, F. (1921), Risk, Uncertainty, and Profit, Houghton Mifflin. Kohlbacher and Weihrauch (2009), Japan’s Silver Market Phenomenon - Golden Opportunity or Rusty

Reality? Available at: http://i.dijtokyo.org/articles/JCU-0905_SilverMarket.pdf Koellinger, P., Minniti, M., and Schade, C. (2005), ‘‘I think I can, I think I can’’: Overconfidence and

entrepreneurial behaviour, Discussion paper 501, DIW. Kulviwat, S., Bruner, G.C. and Al-Shuridah, O. (2009), The role of social influence on adoption of high tech

innovations: the moderating effect of public/private consumption, Journal of Business Research 62, 706-712.

Lapointe, L. and Rivard, S. (2005), A multilevel model of resistance to information technology implementation, MIS Quarterly 29(3), 461–491.

117

Laukkanen, T., Sinkkonen S., Kivijärvi M. and Laukkanen, P. (2007), Innovation resistance among mature consumers, The Journal of Consumer Marketing 24, 419-419.

Lazear, E.P. (2005), Entrepreneurship, Journal of Labor Economics 23(4), 649-680. Leventhal, R.C. (1997), Aging consumers and their effects on the marketplace, Journal of Consumer

Marketing 3(4), 325-328. Levie, J. (2009), The IIIP Innovation confidence index 2008 Report. Available at http://www.iii-

p.org/research/IIIP-Innovation-Confidence-Index-2008.pdfibid Licht, A.N. (2010), Entrepreneurial Motivations, Culture, and the Law. In Freytag, A. and Thurik, A.R. (Eds.),

Entrepreneurship and Culture, Berlin: Springer Verlag, 9-38. Licht, A.N. and Siegel, J.I. (2006), The social dimensions of entrepreneurship. In Casson, M. and Yeung, B.

(eds.), Oxford Handbook of Entrepreneurship, Oxford, Oxford University Press, 511-539. Low. M.B. and MacMillan, I.C. (1988), Entrepreneurship: Past Research and Future Challenges, Journal of

Management 14, 139-161. Lu, J., Yao, J.E. and Yu, C.S. (2005), Personal innovativeness, social influences and adoption of wireless

Internet services via mobile technology, Journal of Strategic Information Systems 14, 245-268. Lumpkin, G.T. and Dess, G.G. (1996), ‘Clarifying the Entrepreneurial Orientation Construct and Linking it to

Performance, Academy of Management Review 21, 135-172. Lynn, R. (1991), The Secret of the Miracle Economy: Different National Attitudes to Competitiveness and

Money, London: The Social Affairs Unit. Lynn, M. and Gelb, B.D. (1996), Identifying innovative national markets for technical consumer goods,

International Marketing Review 13(6), 43-57. Manski, C. (1993), Identification of Endogenous Social Effects: The Reflection Problem, Review of Economic

Studies 60, 331-42. Manski, C. (1995), Identification Problems the Social Sciences, Cambridge, Mass., Harvard University Press. McClelland, D. C. (1961), The Achieving Society, Princeton, Van Nostrand. McCoshan, A., Llpyd, P., Blakemore, M., Gluck, D., Betts, J., Lepropre, M. and McDonald, N. (2010),

Towards Greater Cooperation and Coherence in Entrepreneurship Education, report and evaluation of the Pilot Action High Level Reflection Panels on Entrepreneurship Education, Brussels, European Commission, DG Enterprise.

Moore, G.A. (1999), Crossing the chasm (2nd ed.), New York: HarperCollins. Moore, G.A. (2002), Crossing the chasm: Marketing and selling high-tech products to mainstream

consumers, New York, NY: HarperCollins Publishers. Morrison, P., Roberts, J., and Midgley, D. (2002), The nature of lead users and measurement of leading

edge status. INSEAD Working Papers, INSEAD, Paris. Moschis, G.P. (1992), Marketing to Older Consumers, Westport, Connecticut: Quorum. Moschis, G.P. (2003), Marketing to older adults: an updated overview of present knowledge and practice,

Journal of Consumer Marketing 20 (6), 516 – 525. Mowery, D. and Rosenberg, N. (1979), The influence of market demand upon innovation: a critical review of

some empirical studies, Research Policy 8, 102-153. Nabih, M.I., Bloem, J.G. and Poiesz, T.B.C. (1997), Conceptual issues in the study of innovation adoption

behaviour, Advances in Consumer Research 24, 190–196. NESTA (2011), Vital growth: The importance of high-growth businesses to the recovery, London: NESTA. Newman, K.L. and Nollen, S.D. (1996), Culture and congruence: The fit between management practices and

national culture, Journal of International Business Studies 27(4), 753-779. North, D.C. (1990), Institutions, Institutional Change, and Economic Performance, Cambridge: Cambridge

University Press.

118

OECD (2009), Measuring Entrepreneurship: A digest of indicators, OECD-Eurostat Entrepreneurship Indicators Program, OECD, Paris.

OECD (2010), SMEs, Entrepreneurship and Innovation, OECD Studies on SMEs and Entrepreneurship. OECD (2011), Demand-side Innovation Policies, OECD Publishing. Parker, S.C. (2004), The Economic of Self-Employment and Entrepreneurship, Cambridge University Press. Pedersini, R. and Coletto, D. (2009), Self-employed workers: industrial relations and working conditions,

European Foundation for the Improvement of Living and Working Conditions (Eurofound). Peñaloza, L. and Price, L.L. (1993), Consumer resistance. A conceptual overview, Advances in Consumer

Research 20, 123–128. Perloff, J.M. (2009), Microeconomics, 5th edition, Addison Wesley. Porter, M.E. (1990), The Competitive Advantage of Nations, Free Press, New York. Ram, S. (1989), Successful innovation using strategies to reduce consumer resistance, Journal of Product

Innovation Management 6(1), 20–34. Ram, S. and Sheth, J.N. (1989), Consumer resistance to innovations: The marketing problem and its

solutions, Journal of Consumer Marketing 6(2), 5–14. Redpath, L. (1997), A comparison of native culture, non-native culture and new management ideology,

Revue Canadienne des Sciences de l'Administration 14(3), 327-339. Robinson, P., Stimpson, D.V., Huefner, J. and Hunt, H. K. (1991), An attitude approach to the prediction of

entrepreneurship, Entrepreneurship Theory and Practice 15(4), 13–31. Robson, M. (2007), Explaining Cross-National Variations in Entrepreneurship: the Role of Social Protection

and Political Culture, Comparative Labor Law & Policy Journal 28(4), 863-92 Rogers, E.M. (2003). Diffusion of innovations (5th ed.), New York: Free Press. Rolfe, H. (2010), Learning to take risks, learning to success, NESTA: London. Rosen, D.L. and Olshavsky, R.W. (1987), A Protocol Analysis of Brand Choice Strategies Involving

Recommendations, Journal of Consumer Research 14, 440-444. Rosenberg, M.J. and Hovland, C.I. (1960), Cognitive, affective, and behavorial components of attitudes, in:

C.I. Hovland and M.J. Rosenberg (eds.), Attitude Organization and Change: An Analysis of Consistency among Attitude Components, Yale University Press, New Haven CT, 1-14.

Roth, M.S. (1995), The Effects of Culture and Socioeconomics on the Performance of Global Brand Image Strategies, Journal of Marketing Research 32 (May), 163-175.

Salancik, G.R. and Pfeffer, J. (1978), A social information processing approach to job attitudes and task design, Administrative Science Quarterly 23, 224-253.

Sanditov, B. and Verspagen, B. (2011), Multilevel analysis of the determinants of innovative entrepreneurship across Europe, Paper presented at the Final DIME Conference, 6-8 April 2011, Maastricht.

Schmookler, J. (1966), Invention and Economic Growth, Harvard University Press, Cambridge, MA. Schneider, S.C. and Barsoux, J.L. (1997), Managing Across Cultures, Europe, Prentice Hall. Schumpeter, J. (1912, 1934), The Theory of Economic Development, Cambridge, Mass: Harvard University

Press. Shane, S. (1992), Why do some societies invent more than others?, Journal of Business Venturing 7, 29-46. Shane, S. (1993), Cultural influences on national rates of innovation, Journal of Business Venturing 8, 59-73. Shane, S. and Venkataraman, S. (2000), The promise of entrepreneurship as a field of research, Academy

of Management Review 26(1), 217–226. Shapero, A. and Sokol, L., (1982), The Social Dimensions of Entrepreneurship, in C. Kent, D. Sexton, and K.

H. Vesper (eds.), The Encyclopedia of Entrepreneurship, Englewood Cliffs, NJ, Prentice-Hall, 72-90. Shaver, K.G. (1987), Principles of social psychology (3rd ed.). Cambridge, MA: Winthrop.

119

Smelser, N.J. and Swedberg, R. (Eds.) (2005), Handbook of Economic Sociology, Princeton University Press.

Smith, M. (1998), Culture and organisational change, Management Accounting 76(7): 1-5. Steenkamp, J.E.M., Hofstede, F. and Wedel, M. (1999), A cross-national investigation into the individual and

national cultural antecedents of consumer innovativeness, Journal of Marketing 63, 55-69. Stevenson, H.H. and Jarillo, J.C. (1990), A Paradigm of Entrepreneurship: Entrepreneurial Management,

Strategic Management Journal 11, 17-27. Steyaert, C. (2007), ‘Entrepreneuring’ as a conceptual attractor? A review of process theories in 20 years of

entrepreneurship studies, Entrepreneurship & Regional Development, Special Issue 19(6), 453-477. Swedberg, R. (2000), Entrepreneurship: the social science view, Oxford University Press. Synovate (2009), Here comes the silver market. Available at:

http://www.synovate.com/changeagent/index.php/site/full_story/here_comes_the_silver_market Szirmai, E., Naudé, W. and Goedhuys, M. (2011), Entrepreneurship, Innovation and Economic

Development, Oxford: Oxford University Press. Taylor, S. and Todd, P.A. (1995), Understanding information technology usage: A test of competing models,

Information Systems Research 6(2), 144-176. Thornton, P.H. (1999), The sociology of entrepreneurship, Annual Review of Sociology 25, 19–46. Thornton, P.H., Ribeiro-Soriano. D. and Urbano, D. (2011), Socio-Cultural Factors and Entrepreneurial

Activity an Overview, International Small Business Journal 29, 105–18. Triandis, H.C. (1989), The self and social behaviour in differing cultural contexts, Psychological Review

96(3), 506-52. Utterback, J. and Abernathy, W. (1975), A dynamic model of process and product innovation. Omega 3, 639-

656. Van Stel, A.J., Carree, M.A. and Thurik, R. (2005), The Effect of Entrepreneurship on National Economic

Growth: An Analysis using the GEM Database, Small Business Economics 24(3), 311‐321. Veciana, J.M., Aponte, M. and Urbano, D. (2005), University students' attitudes towards entrepreneurship: A

two countries comparison, International Entrepreneurship and Management Journal 1(2), 165–182. Venkatesh, V, Morris, M.H., Davis, G.B. and Davis, F.D. (2003), User acceptance of information technology:

toward a unified view, MIS Quarterly 27 (3), 425-478. Venkatesh, V. and Davis, F.D. (2000), A theoretical extension of the technology acceptance model: Four

longitudinal field studies, Management Science 46(2), 186-204. Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003), User acceptance of information technology:

Toward a unified view”, MIS Quarterly 27(3), 425-478. Verheul, I., Thurik, A.R. and Grilo, I. (2008), Explaining preferences and actual involvement in self-

employment: New insights into the role of gender, Research in Management ERS-2008-003-ORG, 3000 DR Rotterdam: ERIM.

Wennekers, S., van Stel, A., Thurik, R. and Reynolds, P. (2005), Nascent entrepreneurship and the level of economic development, Small Business Economics 24(3), 293–309.

Wiklund, J. (1998), Small firm growth and performance – Entrepreneurship and beyond, Jönköping: Jönköping International Business School.

Wuestenhagen, R., Wolsink, M. and Buerer, M.J. (2007), Social acceptance of renewable energy innovation: an introduction to the concept, Energy Policy 35(5), 2683-2691.

Yang, H.D., Moon, Y.J. and Rowley, C. (2009), Social influence on knowledge workers adoption of innovative information technology, Journal of Computer Information Systems, Fall 2009.

Yeung, R. and Morris, J. (2001), Consumer perception of food risk in chicken meat, Nutrition and Food Science 31(6), 270-279.

120

Annex 1: Innobarometer 2005 questions on being attracted to innovation The Innobarometer (2005) questions on being attracted to innovative products and services are as follows:

Question QE1 In general, to what extent are you attracted towards innovative products or services, in other words new or improved products or services?

• Very attracted • Fairly attracted • Not very attracted • Not at all attracted

Question QE2 Compared to your friends and family, would you say you tend to be …? • More inclined to purchase innovative products or services

• Less inclined to purchase innovative products or services • As inclined to purchase innovative products or services

Question QE3 What does “innovation” mean for you? The creation of new products or services or the improvement of existing products or services

• The creation of new products or services • The improvement of existing products or services

Question QE4 In general, when an innovative products or service is put on the market and can replace a product or service that you already trust and regularly buy, do …?

• You prefer to continue purchasing a product or service that you already trust and do not try the innovative one

• You quickly try the innovative products or service at least once

Question QE5 You would be willing to replace a product or service that you already use by an innovative one …

• Even if this is significantly more expensive • Only if this is a little more expensive • Only if this would cost the same • I would never be willing to purchase an innovative product or service

121

Annex 2: Differences in attitudes between (non) (innovative) entrepreneurs This annex shows differences between attitudes to entrepreneurship for innovative entrepreneurs, non-innovative entrepreneurs and non-entrepreneurs (cf. section 4.4.2 in the report).

You know someone personallywho started a business in the

past three years

In the next six months there willbe good opportunities for

starting a business in the area

You have the knowledge and theskills and experience required to

start a business

Fear o f failure would prevent youfrom starting a business

In your country most peoplewould prefer that everyone had a

similar standard o f living

In your country most peopleconsider starting a business a

desirable career cho ice

In your country those successfulat starting a business have a high

level o f status and respect

In your country you will o ften seestories in the public media about

successful new businesses

Austria

0 25 50 75 100

Belgium

0 25 50 75 100

Czech Republic

0 25 50 75 100

You know someone personallywho started a business in the

past three years

In the next six months there willbe good opportunities for

starting a business in the area

You have the knowledge and theskills and experience required to

start a business

Fear o f failure would prevent youfrom starting a business

In your country most peoplewould prefer that everyone had a

similar standard o f living

In your country most peopleconsider starting a business a

desirable career cho ice

In your country those successfulat starting a business have a high

level o f status and respect

In your country you will o ften seestories in the public media about

successful new businesses

Denmark

0 25 50 75 100

Finland

0 25 50 75 100

France

0 25 50 75 100

Non-entrepreneur Non-innovative entrepreneur Innovative entrepreneur

122

You know someone personallywho started a business in the

past three years

In the next six months there willbe good opportunities for

starting a business in the area

You have the knowledge and theskills and experience required to

start a business

Fear o f failure would prevent youfrom starting a business

In your country most peoplewould prefer that everyone had a

similar standard o f living

In your country most peopleconsider starting a business a

desirable career cho ice

In your country those successfulat starting a business have a high

level o f status and respect

In your country you will o ften seestories in the public media about

successful new businesses

Germany

0 25 50 75 100

Greece

0 25 50 75 100

Hungary

0 25 50 75 100

You know someone personallywho started a business in the

past three years

In the next six months there willbe good opportunities for

starting a business in the area

You have the knowledge and theskills and experience required to

start a business

Fear o f failure would prevent youfrom starting a business

In your country most peoplewould prefer that everyone had a

similar standard o f living

In your country most peopleconsider starting a business a

desirable career cho ice

In your country those successfulat starting a business have a high

level o f status and respect

In your country you will o ften seestories in the public media about

successful new businesses

Iceland

0 25 50 75 100

Ireland

0 25 50 75 100

Italy

0 25 50 75 100

Non-entrepreneur Non-innovative entrepreneur Innovative entrepreneur

123

You know someone personallywho started a business in the

past three years

In the next six months there willbe good opportunities for

starting a business in the area

You have the knowledge and theskills and experience required to

start a business

Fear o f failure would prevent youfrom starting a business

In your country most peoplewould prefer that everyone had a

similar standard o f living

In your country most peopleconsider starting a business a

desirable career cho ice

In your country those successfulat starting a business have a high

level o f status and respect

In your country you will o ften seestories in the public media about

successful new businesses

Latvia

0 25 50 75 100

Netherlands

0 25 50 75 100

Norway

0 25 50 75 100

You know someone personallywho started a business in the

past three years

In the next six months there willbe good opportunities for

starting a business in the area

You have the knowledge and theskills and experience required to

start a business

Fear o f failure would prevent youfrom starting a business

In your country most peoplewould prefer that everyone had a

similar standard o f living

In your country most peopleconsider starting a business a

desirable career cho ice

In your country those successfulat starting a business have a high

level o f status and respect

In your country you will o ften seestories in the public media about

successful new businesses

Spain

0 25 50 75 100

Poland

0 25 50 75 100

Portugal

0 25 50 75 100

Non-entrepreneur Non-innovative entrepreneur Innovative entrepreneur

124

You know someone personallywho started a business in the

past three years

In the next six months there willbe good opportunities for

starting a business in the area

You have the knowledge and theskills and experience required to

start a business

Fear o f failure would prevent youfrom starting a business

In your country most peoplewould prefer that everyone had a

similar standard o f living

In your country most peopleconsider starting a business a

desirable career cho ice

In your country those successfulat starting a business have a high

level o f status and respect

In your country you will o ften seestories in the public media about

successful new businesses

Romania

0 25 50 75 100

Serbia

0 25 50 75 100

Slovenia

0 25 50 75 100

You know someone personallywho started a business in the

past three years

In the next six months there willbe good opportunities for

starting a business in the area

You have the knowledge and theskills and experience required to

start a business

Fear o f failure would prevent youfrom starting a business

In your country most peoplewould prefer that everyone had a

similar standard o f living

In your country most peopleconsider starting a business a

desirable career cho ice

In your country those successfulat starting a business have a high

level o f status and respect

In your country you will o ften seestories in the public media about

successful new businesses

Sweden

0 25 50 75 100

Switzerland

0 25 50 75 100

United Kingdom

0 25 50 75 100

Non-entrepreneur Non-innovative entrepreneur Innovative entrepreneur

125

Annex 3: A scoreboard of attitudes to innovation and entrepreneurship This annex combines the statistical data on attitudes to demand for innovation and entrepreneurship into a scoreboard of attitudes to innovation (comparable to the Innovation Union Scoreboard) (cf. Tables A3-2 and A3-3). The “performance” for attitudes to demand and entrepreneurship can be summarised in a single score using composite indicators. For this the values for the indicators as shown in Tables 0-2 and 0-3 are first normalised to a common range of 0 to 1 by, for each indicator, first subtracting the lowest observed score among all countries and then dividing by the difference between the highest and lowest observed scores among all countries. Average “performance” for each country is then calculated as the unweighted average of the normalised scores over all indicators.

As the correlation results in Table A3-1 show, there is only a weak correlation between favourable attitudes and actual innovation performance as measured by the Global Innovation Index. Favourable attitudes to demand would be negatively correlated with innovation performance, but this result is not observed for the innovation performance measure used in the Innovation Union Scoreboard.

Table A3-1: Innovation performance and attitudes to innovation and entrepreneurship

Innovation Control Variables

Global Innovation Index Summary Innovation

Index (IUS 2010)

Correlation -.284* -.131 Attitudes to demand for

innovation Significance (2-tailed) .076 .481

Correlation -.093 -.167

GDP

Attitudes to

entrepreneurship Significance (2-tailed) .593 .369

Partial correlations. * significant at p<.10

For demand for innovation most favourable attitudes are observed for Cyprus, Greece, Luxembourg and Slovakia (Figure A3-1). For all of the non-European countries data is insufficient to calculate a composite indicator score.

For entrepreneurship most favourable attitudes are observed for Brazil, Canada, China, Greece, Portugal and India. The EU27 doesn’t compare well with several of its global competitors and, a bit surprisingly, European attitudes would be more favourable than those in the US. Attitudes to entrepreneurship are least favourable in Japan and Russia.

126

Figure A3-1: Composite indicator for attitudes to demand for innovation

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

AT BEBG HRCY CZ DK EE FI FR DEGR HU IS IE IT LV LT LU M TNL NO PL PT RO RS SK SI ES SE CHTR UK EU27 AU CA JP KR US BRCN IN RU SA

Figure A3-2: Composite indicator for attitudes to entrepreneurship

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

AT BEBG HRCY CZ DK EE FI FR DEGR HU IS IE IT LV LT LU M TNL NO PL PT RO RS SK SI ES SE CHTR UK EU27 AU CA JP KR US BRCN IN RU SA

The data haven been used to create country profiles to highlight positive and negative attitudes within countries and differences between countries.

127

Table A3-2: Social attitudes and demand for innovation (Scoreboard data)

POWER DISTANCE

(HOFSTEDE) (+)

INDIVIDUALISM

(HOFSTEDE) (+)

MASCULINITY (HOFSTEDE)

(+)

UNCER-TAINTY

AVOIDANCE (HOFSTEDE)

(-)

WILLINGNESS TO TAKE

RISKS (EB) +

ATTRACTED TOWARDS

INNOVATIVE PRODUCTS

(IB) (+)

INTENTION TO TRY

INNOVATIVE PRODUCTS

(IB) (+)

WILLINGNESS TO

PURCHASE INNOVATIVE PRODUCTS

(IB) (+)

INNOVATIVE PRODUCTS SIMPLIFY

EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS

ARE GADGETS (IB)

(-)

INNOVATIVE PRODUCTS

ARE A MATTER OF

FASHION (IB) (-)

PURCHASING INNOVATIVE

PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF

INNOVATION ARE OFTEN

EXAGGE-RATED (IB) (-)

EUROBAROM

ETER 2010 INNOBAROME

TER 2005 INNOBAROME

TER 2005 INNOBAROME

TER 2005 INNOBAROME

TER 2005 INNOBAROME

TER 2005 INNOBAROME

TER 2005 INNOBAROME

TER 2005 INNOBAROME

TER 2005 EU27 51 60 47 71 61 58.3 47.9 4.1 41.6 18.9 29.4 16.5 67.7 AUSTRIA 11 55 79 70 55 45.4 39.4 31.6 4.8 15.9 3.9 11.4 68.2 BELGIUM 65 75 54 94 55 61.4 38.8 41.2 36.9 21.3 33.6 15.0 6.9 BULGARIA 70 30 40 85 67 53.7 31.1 29.6 41.7 4.7 17.4 13.7 8.7 CROATIA 73 33 40 80 52 56.3 55.5 4.5 39.6 32.1 31.1 13.4 75.0 CYPRUS -- -- -- -- 71 52.9 5.1 34.0 53.7 35.6 36.6 27.1 6.6 CZECH REPUBLIC 57 58 57 74 50 63.8 41.7 43.5 49.2 12.3 25.8 12.9 72.1 DENMARK 18 74 16 23 63 63.5 55.7 44.4 42.9 16.2 28.0 19.5 69.6 ESTONIA 40 60 30 60 61 56.7 45.3 4.9 6.8 24.1 38.6 33.8 53.5 FINLAND 33 63 26 59 63 44.0 44.5 38.9 41.5 27.2 49.1 7.6 47.9 FRANCE 68 71 43 86 68 59.2 46.2 36.9 26.1 22.0 31.9 9.4 68.2 FYROM -- -- -- -- -- -- -- -- -- -- -- -- -- GERMANY 35 67 66 65 60 37.4 55.2 31.1 4.3 21.3 17.2 16.6 61.8 GREECE 60 35 57 112 67 51.3 45.3 33.7 48.3 21.7 42.3 38.7 59.0 HUNGARY 46 80 88 82 37 4.7 42.8 35.0 32.0 1.8 27.9 12.8 65.9 ICELAND -- -- -- -- 50 -- -- -- -- -- -- -- -- IRELAND 28 70 68 35 69 64.2 45.6 4.3 42.8 29.0 33.9 12.8 71.2 ITALY 50 76 70 75 75 69.5 48.9 48.8 35.7 1.4 24.8 1.7 83.3 LATVIA 44 70 9 63 52 5.1 55.2 34.3 36.4 16.9 29.8 2.2 68.2 LITHUANIA 42 60 19 65 51 56.1 55.5 26.4 24.6 9.6 27.4 14.2 84.0 LUXEMBOURG 40 60 50 70 65 74.8 33.7 52.0 46.8 28.0 43.7 22.8 56.0 MALTA 56 59 47 96 65 7.9 27.6 53.3 41.2 16.8 27.6 19.8 73.2 NETHERLANDS 38 80 14 53 60 72.9 45.9 49.8 36.9 24.7 26.9 12.3 51.7 NORWAY 31 69 8 50 69 -- -- -- -- -- -- -- -- POLAND 68 60 64 93 66 6.8 69.0 3.9 31.8 16.3 29.1 22.8 68.8 PORTUGAL 63 27 31 104 61 52.1 64.3 17.6 37.7 23.8 28.8 11.7 86.5 ROMANIA 90 30 42 90 74 67.1 39.3 51.5 47.0 8.2 29.4 1.9 83.9

128

POWER DISTANCE

(HOFSTEDE) (+)

INDIVIDUALISM

(HOFSTEDE) (+)

MASCULINITY (HOFSTEDE)

(+)

UNCER-TAINTY

AVOIDANCE (HOFSTEDE)

(-)

WILLINGNESS TO TAKE

RISKS (EB) +

ATTRACTED TOWARDS

INNOVATIVE PRODUCTS

(IB) (+)

INTENTION TO TRY

INNOVATIVE PRODUCTS

(IB) (+)

WILLINGNESS TO

PURCHASE INNOVATIVE PRODUCTS

(IB) (+)

INNOVATIVE PRODUCTS SIMPLIFY

EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS

ARE GADGETS (IB)

(-)

INNOVATIVE PRODUCTS

ARE A MATTER OF

FASHION (IB) (-)

PURCHASING INNOVATIVE

PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF

INNOVATION ARE OFTEN

EXAGGE-RATED (IB) (-)

EUROBAROM

ETER 2010 INNOBAROME

TER 2005 INNOBAROME

TER 2005 INNOBAROME

TER 2005 INNOBAROME

TER 2005 INNOBAROME

TER 2005 INNOBAROME

TER 2005 INNOBAROME

TER 2005 INNOBAROME

TER 2005 EU27 51 60 47 71 61 58.3 47.9 4.1 41.6 18.9 29.4 16.5 67.7 SERBIA 86 25 43 92 -- -- -- -- -- -- -- -- -- SLOVAKIA 104 52 110 51 53 68.0 51.4 46.5 54.1 13.1 24.2 16.1 7.5 SLOVENIA 71 27 19 88 58 67.9 49.0 51.9 61.7 24.0 17.8 27.5 54.0 SPAIN 57 51 42 86 71 49.6 58.3 4.1 37.2 19.2 27.1 12.5 79.8 SWEDEN 31 71 5 29 63 66.9 36.6 58.5 5.5 29.7 4.2 15.8 49.4 SWITZERLAND 34 68 70 58 61 -- -- -- -- -- -- -- -- TURKEY 66 37 45 85 55 75.7 31.4 38.4 38.0 22.7 34.6 22.6 77.2 UNITED KINGDOM 35 89 66 35 59 69.1 55.8 45.9 34.7 19.8 23.4 9.5 73.9 AUSTRALIA 36 90 61 51 -- -- -- -- -- -- -- -- -- BRAZIL 69 38 49 76 -- -- -- -- -- -- -- -- -- CANADA 39 80 52 48 -- -- -- -- -- -- -- -- -- CHINA 80 20 66 30 65 -- -- -- -- -- -- -- -- INDIA 77 48 56 40 -- -- -- -- -- -- -- -- -- JAPAN 54 46 95 92 34 -- -- -- -- -- -- -- -- RUSSIA 93 39 36 95 -- -- -- -- -- -- -- -- -- SOUTH AFRICA -- -- -- -- -- -- -- -- -- -- -- -- -- SOUTH KOREA 60 18 39 85 64 -- -- -- -- -- -- -- -- UNITED STATES 40 91 62 46 78 -- -- -- -- -- -- -- --

129

Table A3-3: Social attitudes and entrepreneurship (Scoreboard data)

KNOW SOMEONE

WHO STARTED A BUSINESS (GEM) (+)

GOOD OPPORTUNITI

ES FOR STARTING A BUSINESS (GEM) (+)

HAS KNOWLEDGE,

SKILL, EXPERIENCE TO START A BUSINESS (GEM) (+)

FEAR OF FAILURE

PREVENTS STARTING A BUSINESS (GEM) (-)

PREFERENCE FOR SIMILAR STANDARD OF LIVING (GEM) (+)

ENTREPRE-NEUR IS A

DESIRABLE CAREER CHOICE

(GEM) (+)

ENTREPRE-NEURS HAVE

A HIGH STATUS AND

RESPECT (GEM) (+)

POSITIVE MEDIA

ATTENTION TO

ENTRENEUR-SHIP (GEM)

(+)

PREFERENCE TO BE SELF-EMPLOYED

(EB) (+)

ENTREPRE-NEURS

CREATE NEW PRODUCTS

THAT BENEFIT US ALL (EB) (+)

ENTREPRE-NEURS THINK ABOUT THEIR OWN WALLET

(EB) (-)

ENTREPRE-NEURS ARE

JOB CREATORS

(EB) (+)

ENTREPRE-NEURS

EXPLOIT OTHERS (EB)

(-)

GEM 2001-

2007 GEM 2001-

2007 GEM 2001-

2007 GEM 2001-

2007 GEM 2001-

2007 GEM 2001-

2007 GEM 2001-

2007 GEM 2001-

2007 EUROBARO-METER 2010

EUROBARO-METER 2010

EUROBARO-METER 2010

EUROBARO-METER 2010

EUROBARO-METER 2010

EU27 34.3 34.2 44.2 37.3 65.9 59.7 67.1 5.6 44.0 81.9 56.8 89.7 56.7

AUSTRIA 46.6 42.8 56.7 35.4 59.7 37.8 71.3 56.8 39.3 88.8 48.8 94.5 36.7 BELGIUM 29.6 25.1 37.5 28.0 62.3 61.6 63.1 42.8 26.3 74.8 57.0 9.1 46.4 BULGARIA -- -- -- -- -- -- -- -- 54.2 7.1 67.8 86.6 7.3 CROATIA 45.3 32.0 49.2 32.8 74.7 53.3 7.5 57.2 42.5 61.9 74.3 75.4 74.9 CYPRUS -- -- -- -- -- -- -- -- 65.1 79.0 78.2 91.3 76.5 CZECH REPUBLIC 32.3 26.5 38.9 31.2 7.2 81.9 74.9 5.3 35.4 8.9 58.1 87.8 42.1 DENMARK 45.7 61.0 4.1 35.3 47.2 5.5 73.5 36.3 31.1 93.2 23.5 93.3 22.1 ESTONIA -- -- -- -- -- -- -- -- 38.9 89.8 65.9 93.0 76.3 FINLAND 46.5 5.0 39.0 33.5 62.8 6.8 74.2 68.8 41.9 97.0 32.0 97.6 49.0 FRANCE 34.6 17.2 28.4 41.4 51.4 6.0 63.5 4.5 5.4 74.5 5.9 87.4 48.6 FYROM -- -- -- -- -- -- -- -- -- -- -- -- -- GERMANY 39.2 22.1 38.8 44.1 59.7 52.0 73.8 49.3 4.6 82.7 49.6 88.6 4.6 GREECE 37.5 25.9 55.9 55.0 67.6 68.6 69.7 42.7 6.7 76.4 76.9 88.2 76.7 HUNGARY 33.0 14.2 42.7 25.7 58.0 51.3 57.6 25.8 37.5 76.5 56.9 87.1 48.7 ICELAND 66.9 57.6 51.4 38.2 63.2 38.0 85.4 69.5 58.0 93.2 18.0 98.4 13.0 IRELAND 42.6 41.9 49.1 35.5 62.3 65.4 7.9 82.6 47.0 9.8 41.2 92.0 38.4 ITALY 33.4 32.2 36.5 35.5 62.8 71.2 65.6 45.3 5.1 76.2 61.6 87.7 52.6 LATVIA 47.8 39.0 36.0 41.1 77.5 77.7 61.2 65.0 5.9 83.3 52.4 92.2 52.5 LITHUANIA -- -- -- -- -- -- -- -- 56.5 87.5 62.0 95.2 79.8 LUXEMBOURG -- -- -- -- -- -- -- -- 41.5 74.3 54.3 89.6 6.8 MALTA -- -- -- -- -- -- -- -- 37.1 9.1 68.6 93.3 72.3 NETHERLANDS 27.8 39.8 37.8 24.7 58.2 81.1 67.4 59.9 38.5 77.2 38.0 92.6 55.5 NORWAY 4.8 45.7 4.9 23.4 65.8 6.2 64.1 71.1 4.0 91.8 22.7 96.3 31.1 POLAND 36.8 17.5 35.9 39.9 71.7 64.7 58.6 36.6 52.4 84.8 66.0 89.4 75.3 PORTUGAL 34.4 27.1 51.0 38.1 8.2 66.3 81.3 79.7 48.5 85.5 55.6 92.3 6.9

130

KNOW SOMEONE

WHO STARTED A BUSINESS (GEM) (+)

GOOD OPPORTUNITI

ES FOR STARTING A BUSINESS (GEM) (+)

HAS KNOWLEDGE,

SKILL, EXPERIENCE TO START A BUSINESS (GEM) (+)

FEAR OF FAILURE

PREVENTS STARTING A BUSINESS (GEM) (-)

PREFERENCE FOR SIMILAR STANDARD OF LIVING (GEM) (+)

ENTREPRE-NEUR IS A

DESIRABLE CAREER CHOICE

(GEM) (+)

ENTREPRE-NEURS HAVE

A HIGH STATUS AND

RESPECT (GEM) (+)

POSITIVE MEDIA

ATTENTION TO

ENTRENEUR-SHIP (GEM)

(+)

PREFERENCE TO BE SELF-EMPLOYED

(EB) (+)

ENTREPRE-NEURS

CREATE NEW PRODUCTS

THAT BENEFIT US ALL (EB) (+)

ENTREPRE-NEURS THINK ABOUT THEIR OWN WALLET

(EB) (-)

ENTREPRE-NEURS ARE

JOB CREATORS

(EB) (+)

ENTREPRE-NEURS

EXPLOIT OTHERS (EB)

(-)

GEM 2001-

2007 GEM 2001-

2007 GEM 2001-

2007 GEM 2001-

2007 GEM 2001-

2007 GEM 2001-

2007 GEM 2001-

2007 GEM 2001-

2007 EUROBARO-METER 2010

EUROBARO-METER 2010

EUROBARO-METER 2010

EUROBARO-METER 2010

EUROBARO-METER 2010

EU27 34.3 34.2 44.2 37.3 65.9 59.7 67.1 5.6 44.0 81.9 56.8 89.7 56.7

ROMANIA 39.3 26.4 27.4 29.6 48.4 61.0 61.3 49.2 5.3 78.5 67.2 86.2 63.1 SERBIA 52.4 47.8 62.4 27.9 74.9 7.9 53.0 55.8 -- -- -- -- -- SLOVAKIA -- -- -- -- -- -- -- -- 28.7 82.6 71.5 85.9 74.6 SLOVENIA 46.2 36.1 46.4 29.1 63.4 63.6 46.1 62.1 43.2 75.2 69.8 83.1 77.3 SPAIN 33.7 35.9 48.5 46.5 61.7 7.1 59.8 43.4 41.0 89.4 65.9 86.8 57.4 SWEDEN 45.4 41.0 42.3 34.1 64.5 54.0 62.2 55.5 33.3 84.9 36.2 95.1 56.8 SWITZERLAND 4.7 36.3 51.9 32.3 58.5 51.5 71.8 54.2 45.2 8.9 47.4 92.6 37.4 TURKEY 38.0 39.7 56.6 29.8 69.2 67.7 8.0 73.5 47.6 8.5 6.3 85.8 49.4 UNITED KINGDOM 24.7 33.7 48.1 32.9 76.7 53.1 72.6 57.1 45.7 84.5 51.3 87.5 46.3 AUSTRALIA 37.4 41.1 53.9 32.2 71.4 53.0 68.1 61.2 -- -- -- -- -- BRAZIL 39.5 42.9 56.8 37.8 79.7 77.0 75.9 72.9 -- -- -- -- -- CANADA 33.4 39.7 52.8 25.4 56.7 86.7 85.9 79.8 -- -- -- -- -- CHINA 58.5 33.4 38.7 22.5 81.5 75.0 83.6 63.5 72.3 87.4 43.3 88.2 42.0 INDIA 39.6 45.7 52.5 3.6 74.3 73.4 69.0 75.9 -- -- -- -- -- JAPAN 21.8 9.1 14.5 22.1 38.8 31.6 5.3 56.1 4.1 79.1 48.8 81.5 62.4 RUSSIA 32.4 18.2 19.5 36.4 31.1 43.4 44.6 3.9 -- -- -- -- -- SOUTH AFRICA 28.6 21.8 33.4 24.1 51.6 59.1 58.6 58.4 -- -- -- -- -- SOUTH KOREA 45.9 12.6 28.2 43.9 65.7 72.5 7.5 81.7 5.8 77.2 6.9 81.9 58.8 UNITED STATES 36.0 32.0 55.8 19.5 5.0 57.9 6.2 61.4 56.0 94.3 31.8 95.9 32.0

131

AUSTRALIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Australia data are not available for the indicators using ESS and IB data.

Australia compares well to the EU27 on the GEM indicators. Only for entrepreneurs as a desirable career choice Australia is doing slightly worse. Australia appears to have a more positive attitude towards entrepreneurship and innovation as compared to the EU27.

132

AUSTRIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Austria has a more negative attitude towards innovative products as compared to the EU27. Austrians are less attracted to innovative products, are less willing to buy such products and are also less willing to take risks. Austria has a more positive attitude towards entrepreneurship. Entrepreneurs have a high status and there is positive media attention to successful entrepreneurs. Entrepreneurs are considered to be job creators are less considered to exploit others. The picture for Austria is a mixed one with a more positive attitude towards entrepreneurship and a less positive attitude towards innovative products. More conservative domestic consumers could threaten entrepreneurial activities in the country.

133

BELGIUM (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Belgium has a more negative attitude towards innovative products as compared to the EU27 but the country scores better on Hofstede’s cultural values. Belgians are less willing to take risks and although they are more attracted to innovative products they are less likely to buy such products. Belgium has a more negative attitude towards entrepreneurship resulting in a lower preference to be self-employed. The picture for Belgium shows a more negative attitude towards both innovation and entrepreneurship. Belgium’s reluctance to adopt innovative products and to start new business activities could threaten the country’s innovative performance.

134

BRAZIL (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Brazil data are not available for the indicators using ESS and IB data.

Brazil compares well to the EU27 on the GEM indicators. But Brazil scores less well on Individualism and Uncertainty avoidance. Overall Brazil appears to have a more positive attitude towards entrepreneurship and innovation as compared to the EU27.

135

BULGARIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Bulgaria data are not available for the indicators using GEM data.

Bulgaria has a more negative attitude towards innovative products as compared to the EU27. Bulgarians are less attracted to innovative products and are less willing to buy such products. Bulgaria also has a more negative attitude towards entrepreneurship. Entrepreneurs are more likely to be seen as thinking about their own wallet and exploiting others. Nevertheless the preference to be self-employed is higher than in the EU27. The picture for Bulgaria is a mixed one with several indicators suggesting more positive attitudes but most of the indicators suggesting more negative attitudes. Bulgaria appears to have a less positive attitude towards entrepreneurship and innovation as compared to the EU27.

136

CANADA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Canada data are not available for the indicators using ESS and IB data.

Canada compares well to the EU27 on most of the GEM indicators. Only for preference for a similar standard of living Canada is doing slightly worse. Canada appears to have a more positive attitude towards entrepreneurship and innovation as compared to the EU27.

137

CHINA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For China data are not available for the indicators using IB data.

China compares well to the EU27 on most of the GEM and ESS indicators. People in China are more willing to take risks and to avoid uncertainty. China appears to have a more positive attitude towards entrepreneurship and innovation as compared to the EU27.

138

CROATIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Croatia has a more negative attitude towards innovative products as compared to the EU27. The evidence for entrepreneurship is mixed with the ESS indicators showing a more negative attitude and the GEM indicators showing a more positive attitude to entrepreneurship. A possible explanation here could be that the GEM data refer to the pre-crisis period 2001-2007 whereas the ESS data refer to 2009, one of the crisis years (unfortunately there are no ESS 2004 or 2007 results available for Croatia). The picture for Croatia is a mixed one with a more negative attitude towards innovative products and a comparable attitude towards innovative products.

139

CYPRUS (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Cyprus data are not available for the indicators using Hofstede’s cultural values and GEM data.

Cyprus has a more negative attitude towards entrepreneurship as compared to the EU27. The evidence for innovative products is mixed with 4 indicators showing more positive attitudes and 5 indicators showing more negative attitudes. Cyprus appears to have a less positive attitude towards entrepreneurship and innovation as compared to the EU27.

140

CZECH REPUBLIC (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

The Czech Republic has a more positive attitude towards innovative products as compared to the EU27. More people are attracted to innovative products and are willing to buy them despite the fact that people in the Czech Republic are less willing to risks. The Czech Republic has a more positive attitude towards entrepreneurship. Becoming an entrepreneur is a desirable career choice and successful entrepreneurs receive high status and respect. The Czech Republic appears to have a more positive attitude towards both entrepreneurship and innovation as compared to the EU27.

141

DENMARK (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Denmark has a more positive attitude towards innovative products as compared to the EU27 although the country performs less well on Power distance and Masculinity. But the IB indicators show that Danes are more attracted to innovative products, are more willing to try and buy these products. The GEM data suggest more negative attitudes towards entrepreneurship whereas the ESS data clearly show more positive attitudes. In particular the more negative characteristics of entrepreneurs – thinking about their own wallet and exploiting others – is something not shared by most Danes. Denmark appears to have a more positive attitude towards both entrepreneurship and innovation as compared to the EU27.

142

ESTONIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Estonia data are not available for the indicators using GEM data.

Estonia has a more negative attitude towards innovative products as compared to the EU27. The willingness of Estonians to take risks is similar to that of the EU27, The ESS data suggest a more negative attitude towards entrepreneurship with a more pronounced opinion on the more negative characteristics of entrepreneurs. Estonia appears to have a less positive attitude towards both entrepreneurship and innovation as compared to the EU27.

143

FINLAND (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Finland has a more negative attitude towards innovative products as compared to the EU27. The IB indicators show that Finns are less attracted to innovative products and are less willing to try and buy these products. Both the GEM and ESS data suggest a more positive attitude towards entrepreneurship. The picture for Finland is a mixed one with a more positive attitude towards entrepreneurship and a less positive attitude towards innovative products. More conservative domestic consumers could threaten entrepreneurial activities in the country.

144

FRANCE (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

France has a more negative attitude towards innovative products as compared to the EU27. The IB indicators show that French people are less willing to try and buy these products. Hofstede’s data show that French people are more likely to avoid uncertainty but ESS data show that they are more willing to take risks. Both the GEM and ESS data suggest a more negative attitude towards entrepreneurship although the results for the ESS data are not that clear. France appears to have a more negative attitude towards both entrepreneurship and innovation as compared to the EU27.

145

GERMANY (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Germans are less attracted to innovative products and are less willing to buy such products. But Germany scores well on Individualism, Masculinity and Uncertainty avoidance. The GEM data show a more negative attitude towards entrepreneurship. There is more fear of failure and becoming an entrepreneur is a less desirable career choice. But successful entrepreneurs do receive high status and respect. The ESS data suggest a more positive attitude towards entrepreneurship. Germany has a more negative attitude towards innovation but a similar attitude to entrepreneurship as compared to the EU27.

146

GREECE (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Greece has a more negative attitude towards innovative products as compared to the EU27. Hofstede’s data show that Greek people are more likely to avoid uncertainty but ESS data show that they are more willing to take risks. But Greeks are less attracted to innovative products and are less willing to try and buy innovative products. Becoming an entrepreneur is a desirable career choice and entrepreneurs are in high respect. But many Greeks also think that entrepreneurs mainly serve their own interests as they exploit others and think about their own wallet. Germany has a more negative attitude towards innovation but a similar attitude to entrepreneurship as compared to the EU27

147

HUNGARY (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Hungarians have a positive view about innovative products but they are less attracted to these products and they are less willing to try and but such products. Hungary scores well on Individualism and Masculinity and scores less well on uncertainty avoidance and willingness to take risks. Most of the GEM and ESS data point to a more negative attitude towards entrepreneurship. Entrepreneurs receive less respect and less positive media attention and becoming an entrepreneur is a less desirable career choice. Hungary appears to have a less positive attitude to entrepreneurship and a comparable attitude to innovative products as the EU27.

148

ICELAND (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Iceland data are not available for the indicators using Hofstede’s cultural values and IB data.

Most of the GEM and ESS data point to a more positive attitude towards entrepreneurship. Nevertheless becoming an entrepreneur is considered to be a less desirable career choice. Iceland appears to have a more positive attitude to entrepreneurship as the EU27.

149

INDIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For India data are not available for the indicators using ESS and IB data.

India compares well to the EU27 on all GEM indicators. But India scores less well on Individualism. India appears to have a more positive attitude towards entrepreneurship and innovation as compared to the EU27.

150

IRELAND (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Ireland Hofstede’s data suggest a more positive attitude towards innovative products. The statistical evidence from the Innobarometer is less conclusive with 4 indicators suggesting more negative and 3 indicators suggesting more positive attitudes. But the combined results do show that Irish people favour innovative products more than the average European. Ireland has a more positive attitude towards entrepreneurship. There is much more positive media attention and entrepreneurs are positively benefiting the society. With more positive attitudes to both innovative product and entrepreneurship Ireland is a country where innovation finds fertile ground.

151

ITALY (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Italians are in favour of innovative products. They are clearly attracted to such product and are also willing to buy them. Italians are also more willing to take risks and Italy scores well on Individualism and Masculinity. Italians are less positive attitudes to entrepreneurship. Although becoming an entrepreneur is a desirable career choice, entrepreneurs receive less status and respect. Italians also don’t belief as much that entrepreneurs create benefits for society. Overall Italy appears to have a less positive attitude towards entrepreneurship as compared to the EU27.

152

JAPAN (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Japan data are not available for the indicators using IB data.

Japan compares less well to the EU27 on most of the GEM and ESS indicators. Fear of failure is less important for preventing people to start a business and there is also more positive media attention for successful entrepreneurs. However, people in Japan are less willing to take risks and to avoid uncertainty. Japan appears to have a less positive attitude towards entrepreneurship and innovation as compared to the EU27.

153

LATVIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Latvia has a more negative attitude towards innovative products as compared to the EU27. Although Latvians are more willing to try innovative products, they are less attracted to them and they are less willing to such products. Latvia has a more positive attitude towards entrepreneurship. Becoming an entrepreneur s a highly desirable career choice and Latvians prefer to be self-employed.

154

LITHUANIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Lithuania data are not available for the indicators using GEM data.

Lithuania has a more negative attitude towards innovative products as compared to the EU27. The advantages of innovative products are often exaggerated and they contribute less to everyday life. The preference to be self-employed is high and Lithuanians think that entrepreneurs create products benefiting us all and that they create jobs. But at the same time there is a strong negative view that entrepreneurs exploit others. Overall it is not clear if Lithuania has a more or less favourable attitude to entrepreneurship as compared to the EU27.

155

LUXEMBOURG (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Luxembourg data are not available for the indicators using GEM data.

Luxembourg has a slightly more positive attitude towards innovative products as compared to the EU27. The preference to be self-employed is below that of the EU27 and the ESS results show a more negative attitude to entrepreneurship.

156

MALTA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Malta data are not available for the indicators using GEM data.

Malta has a slightly more positive attitude towards innovative products as compared to the EU27. The Maltese are both more attracted to and willing to buy innovative products. But they try to avoid uncertainty and are less eager to try new innovation products. The preference to be self-employed is below that of the EU27 and Maltese people think that entrepreneurs create products benefiting us all and that they create jobs. But at the same time there is a strong negative view that entrepreneurs exploit others and only think about their own wallet. Overall it is not clear if Malta has a more or less favourable attitude to entrepreneurship as compared to the EU27.

157

NETHERLANDS (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

The Netherlands appears to have a more positive attitude towards innovative products. Dutch people are more attracted to these products and are more willing to buy them. They also tend not to avoid uncertainty although they as risk-averse as the average European. Evidence on attitudes to entrepreneurship is mixed, with several indicators suggesting more negative attitudes and other indicators more positive attitudes. But becoming an entrepreneur is a desirable career choice and entrepreneurs are considered to make a positive contribution to society. The Netherlands appears to have a more positive attitude towards both entrepreneurship and innovation as compared to the EU27.

158

NORWAY (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Norway data are not available for the indicators using IB data.

Norway compares well to the EU27 on most of the GEM and ESS indicators. Norwegians are more willing to take risks but their preference to be self-employed is below that of the EU27. Norway appears to have a less positive attitude towards entrepreneurship and innovation as compared to the EU27.

159

POLAND (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Poland we observe a mixed picture. Polish people are attracted to and willing to try innovative products but they are less likely to buy these products. Polish people also think that the merits of innovative products are exaggerated and that they contribute less to everyday life. There is more uncertainty avoidance and less willingness to take risks. Several of the GEM and ESS indicators suggest more negative attitudes to entrepreneurship. Nevertheless there is a higher preference to be self-employed and becoming an entrepreneur is a desirable career choice.

160

PORTUGAL (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Portugal has a more negative attitude towards innovative products as compared to the EU27. Portuguese are only more willing to try new innovative products. Portugal has a more positive attitude towards entrepreneurship. Entrepreneurs have a high status and there is positive media attention to successful entrepreneurs. Becoming an entrepreneur is a desirable career choice and there is a higher preference to be self-employed.

161

ROMANIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Romania has a more positive attitude towards innovative products as compared to the EU27 but a more negative attitude towards entrepreneurship. Entrepreneurs have a high status and there is positive media attention to successful entrepreneurs. Entrepreneurs are not in high esteem and are seen to pursue their own advantage and exploit others.

162

RUSSIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Russia data are not available for the indicators using ESS and IB data.

Russia compares less well to the EU27 on the GEM indicators. Russia also performs less well for 3 of Hofstede’s indicators on cultural values. Russia appears to have a more positive attitude towards entrepreneurship and innovation as compared to the EU27.

163

SERBIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Serbia data are not available for the indicators using IB and ESS data.

The GEM data show that Serbia has a more positive attitude towards entrepreneurship.

164

SLOVAKIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Slovakia data are not available for the indicators using GEM data.

Slovakia has a more positive attitude towards innovative products as compared to the EU27. People are more attracted to, willing to try and willing to but such products. The ESS data show that Slovakia has a more negative attitude towards entrepreneurship.

165

SLOVENIA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Slovenia has a more positive attitude towards innovative products as compared to the EU27 based on the IB data. Hofstede’s data on cultural values suggest a more negative attitude. The GEM data suggest that Slovenia has a more positive attitude towards entrepreneurship whereas the ESS data suggest a more negative attitude. But the fact that entrepreneurs are not in high esteem and are seen to pursue their own advantage and exploit others would suggest a more negative attitude to entrepreneurship as compared to the EU27.

166

SOUTH KOREA (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For South Korea data are not available for the indicators using IB data.

South Korea compares well to the EU27 on about half of the indicators. People in South Korea have a less positive view on entrepreneurs despite the fact that there is more positive media attention to successful entrepreneurship. People in South Korea would score worse on Uncertainty avoidance but at the same time would be willing to take more risks. With mixed results it is unclear if South Korea has a more positive or negative attitude towards entrepreneurship and innovation as compared to the EU27.

167

SPAIN (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Spain has a comparable attitude towards innovative products as the EU27. Spanish people are less attracted to innovative products but more willing to try innovative products. They are also more willing to take risks but at the same time want to avoid uncertainty. The evidence on attitudes to entrepreneurship is mixed. Becoming an entrepreneur is a desirable career choice but successful entrepreneur receive less status and respect. Spanish people also believe that entrepreneurs think about their own wallet although they create new products benefiting all.

168

SWEDEN (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Sweden has a neither a more negative nor a more positive attitude towards innovative products and entrepreneurship as compared to the EU27. Swedish people are more attracted to and willing to but innovative products. But becoming an entrepreneur is a less desirable career choice and the preference to be self-employed is below average.

169

SWITZERLAND (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For Switzerland data are not available for the indicators using IB data.

Switzerland has a more positive attitude towards entrepreneurship although becoming an entrepreneur is a less desirable career choice.

170

TURKEY (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

Turkey has a more negative attitude towards innovative products as compared to the EU27. Turkish people are more attracted to innovative products, but less willing to try and buy such product. There is also more uncertainty avoidance and there is less willingness to take risks. Turkey has a more positive attitude towards entrepreneurship. Entrepreneurs have a high status and there is positive media attention to successful entrepreneurs.

171

UNITED KINGDOM (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

The UK has a more positive attitude towards innovative products as compared to the EU27. The UK performs well on Hofstede’s cultural values and people are more attracted to and willing to try and buy innovative products. The UK has a more positive attitude towards entrepreneurship although becoming an entrepreneur is not a desirable career choice.

172

UNITED STATES (performance relative to EU27)

0 20 40 60 80 100 120 140 160 180

POWER DISTANCE (HOFSTEDE) (+)

INDIVIDUALISM (HOFSTEDE) (+)

M ASCULINITY (HOFSTEDE) (+)

UNCERTAINTY AVOIDANCE (HOFSTEDE) (-)

WILLINGNESS TO TAKE RISKS (EB) +

ATTRACTED TOWARDS INNOVATIVE PRODUCTS (IB) (+)

INTENTION TO TRY INNOVATIVE PRODUCTS (IB) (+)

WILLINGNESS TO PURCHASE INNOVATIVE PRODUCTS (IB) (+)

INNOVATIVE PRODUCTS SIM PLIFY EVERYDAY LIFE (IB) (+)

INNOVATIVE PRODUCTS ARE GADGETS (IB) (-)

INNOVATIVE PRODUCTS ARE A M ATTER OF FASHION (IB) (-)

PURCHASING INNOVATIVE PRODUCTS IS RISKY (IB) (-)

ADVANTAGES OF INNOVATION ARE OFTEN EXAGGERATED (IB) (-)

KNOW SOM EONE WHO STARTED A BUSINESS (GEM ) (+)

GOOD OPPORTUNITIES FOR STARTING A BUSINESS (GEM ) (+)HAS KNOWLEDGE, SKILL, EXPERIENCE TO START A BUSINESS

(GEM ) (+)FEAR OF FAILURE PREVENTS STARTING A BUSINESS (GEM ) (-)

PREFERENCE FOR SIM ILAR STANDARD OF LIVING (GEM ) (+)

ENTREPRENEUR IS A DESIRABLE CAREER CHOICE (GEM ) (+)

ENTREPRENEURS HAVE A HIGH STATUS AND RESPECT (GEM ) (+)

POSITIVE M EDIA ATTENTION TO ENTRENEURSHIP (GEM ) (+)

PREFERENCE TO BE SELF-EM PLOYED (EB) (+)

ENTREPRENEURS CREATE NEW PRODUCTS THAT BENEFIT US ALL(EB) (+)

ENTREPRENEURS THINK ABOUT THEIR OWN WALLET (EB) (-)

ENTREPRENEURS ARE JOB CREATORS (EB) (+)

ENTREPRENEURS EXPLOIT OTHERS (EB) (-)

-120 -100 -80 -60 -40 -20 0 20 40 60

For the US data are not available for the indicators using IB data.

The US compares well to the EU27 on most of the GEM and ESS indicators. ESS results show that entrepreneurs are held in more esteem but GEM results show that less US citizens think that entrepreneurs deserve a high status and respect or that becoming an entrepreneur is a desirable career choice. As the country also performs better on 3 of Hofstede’s indicators on cultural values, the US appears to have a more positive attitude towards entrepreneurship and innovation as compared to the EU27.

173

Annex 4: A comparison of the Eurobarometer entrepreneurship questionnaires Flash-

EB 83 Flash-EB 107

Flash-EB 134

Flash-EB 146

Flash-EB 160

Flash-EB 192

Flash-EB 283

EU-15 EU-15 EU-15 EU-15 EU-25 EU-25 EU-27 Variable/question 2000 2001 2002 2003 2004 2007 2009 1 COUNTRY Country Country Country Country Country Country Nation2 REGION D5

NUTS1D5 NUTS1

D5 NUTS1

D5 NUTS1

Region Region Region

3 GENDER D1 D1 D1 D1 D1 D1 D1 4 AGE D2 D2 D2 D2 D2 D2 D2 5 LOCATION (rural-urban) D6 D6 D6 D6 D6 D6 D6 6 High-school education (Ref: secondary and low education) D3 D3 D3 D3 D3 D3 D3 7 Tertiary education (Ref: secondary and low education) D3 D3 D3 D3 D3 D3 D3 8 OCCUPATION D4 D4 D4 D4 D4A D4 D4 9 As a self-employed person, do you own a business? NA NA NA NA D4B 10 Preference for self-employment Q1 Q1 Q1 Q1 Q1 Q1 Q1 11 Why would you prefer to be an employee rather than self-

employed? (open end question - spontaneous) NA NA NA NA Q2 Q2 Q2

12 Why would you prefer to be self-employed rather than an employee? (open end question - spontaneous)

NA NA NA NA Q3 Q3 Q3

13 Difficulty in starting own business Q2 NA NA NA NA NA NA 14 Expression regarding setting up or taking over a business NA Q2 Q2 Q2 Q7 NA NA 15 Reason why to start a business - Dissatisfaction with previous

situation NA NA NA NA Q8A Q12A Q11A

16 Reason why to start a business - Appropriate business idea NA NA NA NA Q8B Q12B Q11B 17 Reason why to start a business - Contact with an appropriate

business partner NA NA NA NA Q8C Q12C Q11C

18 Reason why to start a business - Receiving the necessary financial means

NA NA NA NA Q8D Q12D Q11D

19 Reason why to start a business - Changes in family circumstances NA NA NA NA Q8E Q12E NA 20 Reason why to start a business - Best alternative at that time NA NA NA NA Q8F NA NA 21 Reason why to start a business - A role model NA NA NA NA NA NA Q11E 22 Reason why to start a business - Addressing an unmet social or

ecological need NA NA NA NA NA NA Q11F

23 Started out of opportunity or out of necessity NA NA NA NA Q9 Q13 Q12 24 Best qualified to advise people on setting up a new business NA Q3 NA Q4 NA NA NA 25 If you had the means to start your own business, would you set up a

new one or take over an existing one? NA Q4 NA Q3 Q10 Q14 Q13

26 Would you prefer to own your own company and invest in it or rather to work for yourself but not necessarily own your own company?

NA NA NA NA Q4 Q4 NA

27 How desirable is it for you to become self-employed within the next 5 years?

NA NA NA NA Q5 Q5 NA

28 Would it be feasible for you to be self-employed within the next 5 years?

NA NA NA NA Q6 Q6 Q4 ?

29 Why would it not be feasible for you to be self-employed within the next 5 years?

NA NA NA NA NA Q7 Q5

30 Have you ever started a business or are you taking steps to start one?

NA NA NA NA NA Q11 Q8

31 Not started a business or not taking steps - description of persons situation

NA NA NA NA NA Q11A Q9

32 Started a business or taking steps - description of persons situation NA NA NA NA NA Q11B Q10 33 It is difficult to start own business due to lack of available financial

support Q3B Q5A Q3A Q6A Q12A Q16A Q18A

34 It is difficult to start own business due to complex administrative procedures

Q3E Q5B Q3B Q6B Q12B Q16B Q18B

174

35 It is difficult to obtain sufficient information on how to start a business Q3C NA NA NA Q12C Q16C Q18C 36 One should not start a business if there is a risk it might fail

(Risk tolerance) Q3F Q5H Q3G Q6G Q12D Q16E Q18D

37 People who have started a business and failed should be given a second chance

Q3A Q5E Q3D Q6D NA Q16F Q18E

38 The economic climate is not favourable for people who want to start their own business.

Q3D NA NA Q6H Q12E NA NA

39 I would never invest money in a business managed by someone who has failed in the past

NA Q5G Q3F Q6F NA Q16G NA

40 Entrepreneurship cannot be taught. NA Q5C NA NA NA NA NA 41 I would be ready to pay or to allocate some of my free time to follow

courses on how to start and run a business NA Q5D Q3C Q6C NA NA NA

42 I would be less inclined to order goods from someone who has already failed in business

NA Q5F Q3E Q6E NA NA NA

43 Where should basic knowledge of how to run a business be taught - at school or in secondary education

NA Q6A NA Q5A.A NA NA NA

44 Where should basic knowledge of how to run a business be taught - at university or in tertiary education

NA Q6B NA Q5A.C NA NA NA

45 Where should basic knowledge of how to run a business be taught - during specific courses for adults

NA Q6C NA Q5A.D NA NA NA

46 Where should basic knowledge of how to run a business be taught - nowhere, it cannot be taught

NA Q6D NA Q5A.E NA NA NA

47 Where should basic knowledge of how to run a business be taught - somewhere else

NA Q6E NA Q5A.F NA NA NA

48 Where should basic knowledge of how to run a business be taught - technical secondary school

NA NA NA Q5A.B NA NA NA

49 Education system encourages young people to create a firm. NA NA NA Q5B NA NA NA 50 My school education helped me to develop my sense of initiative NA NA NA NA NA Q9A Q6A 51 My school education helped me to better understand the role of

entrepreneurs in society NA NA NA NA NA Q9B Q6B

52 My school education made me interested to become an entrepreneur NA NA NA NA NA Q9C Q6C 53 My school education gave me skills and know how that enable me to

run a business NA NA NA NA NA NA Q6D

54 At school or university, have you participated in any course or activity about entrepreneurship or setting up a business?

NA NA NA NA NA Q8 NA

55 Entrepreneurship is the basis of wealth creation NA NA NA NA NA Q10A Q7A 56 Entrepreneurs think only at their own wallet NA NA NA NA NA Q10B Q7B 57 Entrepreneurs are job creators NA NA NA NA NA Q10C Q7C 58 Entrepreneurs exploit other people's work NA NA NA NA NA Q10D Q7D 59 If I were to set up a business today I would be most afraid of the risk

of bankruptcy NA Q7A.F Q4F Q7 Q11 Q15 Q14

60 If I were to set up a business today I would be most afraid of the risk of losing property

NA Q7A.C Q4C Q7 Q11 Q15 Q14

61 If I were to set up a business today I would be most afraid of the risk of losing my income

NA Q7A.A Q4A Q7 Q11 Q15 Q14

62 If I were to set up a business today I would be most afraid of the risk of job insecurity

NA Q7A.B Q4B Q7 Q11 Q15 Q14

63 If I were to set up a business today I would be most afraid of the risk of suffering a personal failure

NA Q7A.E Q4E Q7 Q11 Q15 Q14

64 If I were to set up a business today I would be most afraid of the risk of the need to devote too much energy or time to it

NA Q7A.D Q4D Q7 Q11 Q15 Q14

65 In case of bankruptcy what are the two consequences you would be most afraid of - financial consequences, loss of property

NA Q7B.A NA NA NA NA NA

66 In case of bankruptcy what are the two consequences you would be most afraid of - legal consequences

NA Q7B.B NA NA NA NA NA

67 In case of bankruptcy what are the two consequences you would be most afraid of - consequences for others (employees, shareholders)

NA Q7B.C NA NA NA NA NA

68 In case of bankruptcy what are the two consequences you would be most afraid of - consequences for your family

NA Q7B.D NA NA NA NA NA

69 In case of bankruptcy what are the two consequences you would be most afraid of - negative reactions of your close relations

NA Q7B.E NA NA NA NA NA

70 In case of bankruptcy what are the two consequences you would be NA Q7B.F NA NA NA NA NA

175

most afraid of - your own personal feelings 71 What could explain that most businesses are so-called one-person

business (no employees) max. two answers NA NA NA Q8 NA NA NA

72 How much time do you think is needed for a one person business to get trough all administrative procedures to hire the first employee

NA NA NA Q9 NA NA NA

73 Mother self-employed NA Q8B Q5B D7B D7B D7B D8 74 Father self-employed NA Q8A Q5A D7A D7A D7A D7 75 Feelings towards the following groups of people - People who start

and own rapidly growing businesses Q4A NA NA NA NA NA NA

76 Feelings towards the following groups of people - Owners of small businesses

Q4B NA NA NA NA NA NA

77 Feelings towards the following groups of people - Executives in large corporations

Q4C NA NA NA NA NA NA

78 Status of entrepreneurs compared to managers NA NA NA NA NA Q17 Q15 79 Imagine that someone in your family wants to become self employed

would you approve…. Daughter Q5A NA NA NA NA NA NA

80 Imagine that someone in your family wants to become self employed would you approve…. Son

Q5B NA NA NA NA NA NA

81 When one runs a business, what do you think most determine its success? - directors personality

NA NA NA NA Q13A NA NA

82 When one runs a business, what do you think most determine its success? - general management

NA NA NA NA Q13B NA NA

83 When one runs a business, what do you think most determine its success? - overall economy

NA NA NA NA Q13C NA NA

84 When one runs a business, what do you think most determine its success? - political context

NA NA NA NA Q13D NA NA

85 When one runs a business, what do you think most determine its success? - outside entities

NA NA NA NA Q13E NA NA

86 Feelings about household income these days NA NA NA NA NA NA D9 87 In general, I am willing to take risks NA NA NA NA NA NA D10A 88 Generally, when facing difficult tasks, I am certain that I will

accomplish them NA NA NA NA NA NA D10B

89 My life is determined by my own actions, not by others or by chance NA NA NA NA NA NA D10C 90 If I see something I do not like, I change it NA NA NA NA NA NA D10D 91 The possibility of being rejected by others for standing up for my

decisions would not stop me NA NA NA NA NA NA D10E

92 I am an inventive person who has ideas NA NA NA NA NA NA D10F 93 I am optimistic about my future NA NA NA NA NA NA D10G 94 I like situations in which I compete with others NA NA NA NA NA NA D10H 95 When confronted with difficult tasks I can count on luck and the help

of others NA NA NA NA NA NA D10I

96 Imagine you inherited X Euro. What would you do with the money? NA NA NA NA NA NA Q16 97 Imagine a friend of yours started a business. Which advice would you

rather give him or her? NA NA NA NA NA NA Q17

Similar coding across all years Similar coding for 2007 and 2009 If blank coding/value differs Similar coding for 2002 and 2003

176

Annex 5: Country abbreviations AT Austria AU Australia BE Belgium BG Bulgaria BR Brazil CA Canada CH Switzerland CN China CY Cyprus CZ Czech Republic DE Germany DK Denmark EE Estonia ES Spain FI Finland FR France GR Greece HR Croatia HU Hungary IE Ireland IN India IS Iceland

IT Italy JP Japan KR South Korea LT Lithuania LU Luxembourg LV Latvia MT Malta NL Netherlands NO Norway PL Poland PT Portugal RO Romania RS Serbia RU Russia SA South Africa SE Sweden SI Slovenia SK Slovakia TR Turkey UK United Kingdom US United States