1

Faculty of Business and Law

University entrepreneurship education experiences:

enhancing the entrepreneurial ecosystems in a UK

city-region

Fumi Kitagawa1, Don J. Webber

2,

Anthony Plumridge2 and Susan Robertson

3

1University of Edinburgh

2University of the West of England, Bristol

3University of Bristol

Economics Working Paper Series

1505

2

University entrepreneurship education experiences:

enhancing the entrepreneurial ecosystems in a UK

city-region

Fumi Kitagawa1, Don J. Webber

2,

Anthony Plumridge2 and Susan Robertson

3

1University of Edinburgh;

2University of the West of England, Bristol;

3University of Bristol

The recognition of a strong association between education and economic prosperity

has enthused higher education institutions (HEIs) to amplify their initiatives to

stimulate entrepreneurship within their local economies and beyond. However, the

actual processes and impacts made through entrepreneurship education, and the

extent to which and the conditions with which different types of programmes are

effective, are not understood well. This article fills part of this gap by adopting the

concept of university-based entrepreneurship ecosystems and contributes to the

understanding of different impacts of entrepreneurship education and their

implications for city-region development. Student-level data are gathered across two

HEIs within one city-region in England, which include demographic backgrounds,

university experiences and motivations and propensities to start-up businesses. Our

analysis reveals that students who believe their university education has helped them

develop competencies to address challenges of becoming an entrepreneur were 78

percent more likely to have experienced an increase in their stated preference to start-

up a business. This suggests that HEIs should be more actively engaged in

stimulating student entrepreneurial behaviour and developing university-based

entrepreneurial ecosystems that may lead to greater city-region economic

development.

Acknowledgement: The authors thank the ESRC for funding data collection and conference

delegates for helpful comments at the SW England and Wales branches joint Regional Studies

Association conference.

Keywords: Business start-up; Entrepreneurial propensity; Student motivations

JEL classifications: L26; I26; R58

Address for correspondence: Don J. Webber, Bristol Business School, University of the West

of England, Bristol, BS16 1QY, UK. Email: Don.Webber@uwe.ac.uk

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Introduction

Entrepreneurship is established as a major stimulant of economic growth and social

transformation, and the roles that higher education institutions (HEIs) play in developing

regional and national entrepreneurship ecosystems have been attracting both policy and scholarly

attention in many countries (Fetters et al., 2010). The recent increase in the number of HEIs

using their initiatives to stimulate enterprise and entrepreneurship within their local economies

and beyond is driven, at least in part, by the growing recognition of an association between

students’ entrepreneurship experiences at HEIs and the performance of the wider economy

(European Commission, 2015; GEM, 2012; Linan et al., 2011). As a consequence, educators of

enterprise and entrepreneurship are likely to experience challenges to meet increasing and wider

demands from policy communities, as well as pleas for entrepreneurial guidance from students at

different life and career stages, who are from broadening disciplinary backgrounds, and who

have varied, diverse and unevenly developed career aims and objectives.

In this light, this article locates universities’ entrepreneurship education in broader

institutional and local contexts of “university-based entrepreneurship ecosystems” (Greene et al.,

2011). Entrepreneurship education is implemented through different types of inputs at varying

scales including individuals, organisations, society and the economy (European Commission,

2015) but the actual processes and impacts of such mechanisms, and the extent to which and the

conditions with which different types of programmes are effective, are not understood well. The

operational definitions of enterprise and entrepreneurship across universities varies and there are

different aspects covered under these concepts that can include employability skills, social

enterprise, self-employment, venture creation, employment in small businesses, small business

management and the management of high-growth ventures (Pittaway and Cope, 2007, p.480).

Moreover, the changing intellectual, economic, social and cultural movements for

entrepreneurship education and learning will have been influenced by the recent recession, the

growing interest in social, ethical and responsible entrepreneurship and the growing emphasis on

the individual’s active entrepreneurial learning rather than merely on supply side HEI initiatives.

Starting a business is just one of many alternatives for students who pass through the

education system and transit into their working lives. In this article, we conceptualise

entrepreneurship education broadly. Following Fayolle and Gailly (2009), entrepreneurship

education is defined as “the activities aiming to foster entrepreneurial mind-sets, attitudes and

skills” and covers a range of aspects such as “idea generation, start-up, growth and innovation.”

According to Stanboulis and Balaras (2014), entrepreneurship education is not only important for

the development of entrepreneurship and self-employment but also for the enrichment of

students’ attitudes and characteristics necessary to manage the uncertain environment of self-

employment.

The Developing Entrepreneurial Graduates: Putting entrepreneurship at the centre of

higher education (CIHE/NCGE/NESTA, 2008) report called for a joined up approach across

industry, government and higher education sectors to respond to societal and economic

challenges to develop entrepreneurial environments within HEIs and beyond. These challenges

require graduates to have innovative and entrepreneurial mind-sets, skills and behaviour in order

to enable them to be effective entrepreneurs. Government policy assumes that entrepreneurship

education curriculum taught in UK HEIs can positively influence graduates’ attitudes towards an

alternative career path and simultaneously equip them with skills to enable them to become an

entrepreneur with the necessary knowledge and skills to start up, manage and develop an

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economically viable business (Matley and Carey, 2007). However, data show that the percentage

of undergraduate students leaving universities in the UK to become self-employed is low.

Greater comprehension of university-based entrepreneurship ecosystems, with specific foci on

entrepreneurship training, would provide strategic understanding of the changing roles of

universities. We will set this agenda in a particular geographical context: entrepreneurship

education may lead to economic and social development in a city-region.

This article makes inroads into these issues by presenting empirical findings from

research that was specifically designed to investigate students’ attitudes towards

entrepreneurship in relation to their entrepreneurship education experiences at their universities.

This study has three aims: to investigate the motivations of students who embark on an education

strongly related to entrepreneurship; to examine changes in students’ attitudes towards setting

up a business while attending an HEI and; to elucidate if differences in HEIs environments affect

motivations, perceived barriers and actual student entrepreneurial behaviours. To carry out these

investigations we draw on an original data set collated from a survey of students attending two

universities with different organisational characteristics located in one of the UK city-region.

The remainder of this article proceeds as follows. In the next section we present a review

of the existing entrepreneurship ecosystems literature with emphasise on knowledge gaps. The

subsequent section provides details of the method, data and institutional contexts including UK

policy developments. The empirical analysis that follows highlights the relative importance of

individual and contextual factors in shaping students’ entrepreneurial propensities. The final

sections discuss the findings and conclude with future research and policy implications.

Conceptual frameworks

University-based entrepreneurial ecosystems, incentives and entrepreneurship education

Studies over recent decades demonstrate that the development of university-based

entrepreneurship ecosystems (Greene et al., 2010) is conditioned by a number of factors

including the knowledge infrastructure, industry environments, knowledge and technology

transfer systems, policies at national and local levels and strategies adopted by individual

universities and their leadership. According to Moore (1993, p.76), the ecosystem concept is

understood as “an economic community supported by a foundation of interacting organizations

and individuals.” Business ecosystems are often described in states: birth, expansion, leadership

and self-renewal where a “business ecosystem, like its biological counterpart, gradually moves

from a random collection of elements to a more structured community” (Moore, 1993, p.76).

Meanwhile, Aulet’s (2008) conception of the ecosystem includes different actors and facets

including individuals, organizations and resources, and specifically includes government,

demand, invention, funding, infrastructure, entrepreneurs and culture. This framework enables

the schematic understanding of different types and sources of inputs of entrepreneurship

education and makes, through ecosystems, multi-dimensional outcomes.

Other conceptions of entrepreneurial ecosystems and incentives exist. Entrepreneurial

event theory considers firm creation to be the result of interaction among contextual factors,

which act on an individual’s perceptions of the desirability and feasibility of becoming an

entrepreneur (Linan et al., 2010). The subjectivist theory of entrepreneurship focuses on

individuals, their knowledge, resources and skills, and the processes of discovery and creativity

through interactions. As knowledge is invariably mentioned as a necessary requirement for

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entrepreneurial activity, it is opportune for universities to service their local and regional

economies by providing entrepreneurship education and stimulating entrepreneurial activities.

Outcomes of entrepreneurial education are varied and can include changes in individual actions,

greater propensities to find a job (‘employability’), greater propensities to start a business, new

entrepreneurs, new ‘intrapreneurs,’ societal change and social mobility and inclusion, and

economic growth (European Commission, 2015).

From this perspective the provision of enterprise and entrepreneurial knowledge could

enhance the propensity of a student to embark on the path towards starting up a business, and this

could affect the development of a local economy. For instance, Rupasingha and Goetz (2013)

indicate that higher self-employment rates are associated with income and employment growth in

the US. Recent literature on skills and workforce development argues for ‘pro-innovation’

organisational practices (OECD, 2010). In this light, educating and training graduates with

entrepreneurial behaviour and skills seem to be critical not only for business start-ups but also

for workforce development and the inducement of workplace innovation.

Factors and processes that affect entrepreneurship attitudes, behaviour and career

There is a lack of consensus on the factors that contribute to an individual’s decision to start a

business (Krueger and Brazeal, 1994). Entrepreneurial careers are recognised as more complex

than organisational careers and require the simultaneous appreciation of multiple factors

(Greenhouse et al., 2000; Rae, 2007). Career choices are influenced by a number of issues

including family background, social and economic background, educational experience, formal

and informal exposures to entrepreneurial activities and enterprise training/education provisions

at HEIs and throughout a student’s life course. Understanding of “entrepreneurial intension”

(Autio et al., 2001) therefore requires an understanding of students’ demographic characteristics

and social backgrounds, which can be idiosyncratic and heterogeneous, as well as an

understanding of career patterns in order to design more effective entrepreneurial education

initiatives (Jack and Anderson, 1999; Cooper et al., 2004).

There is still a considerable gap in the understanding of the influence of entrepreneurship

education in the making of an entrepreneur (Nabi et al., 2010). An individual’s belief with

respect to their abilities in a range of activities central to entrepreneurship may influence the

likelihood of pursuing entrepreneurial behaviour. However, changing beliefs and attitudes are

not always sufficient to bring about behaviour change. Individual’s intentions matter here as

intentions are conceived as reflecting a “person’s willingness to pursue a certain behaviour,

taking into account constraints and limits which might be imposed by the external environment

or the background/abilities of the individual” (Cooper and Lucas, 2006, p.670). High levels of

confidence are seen as an essential component shaping the propensity to start-up a business, with

self-confidence in one’s own skills being linked to “innovation, opportunity recognition and

intention to start a new venture” (Cooper and Lucas, 2006, p.669).

Individual differences in business start-up propensities are known to stem from various

characteristics including a number of demographic factors such as age, education, work status

and household income (Blanchflower, 2004) and past economic inactivity or unemployment

(Rosti and Chelli, 2005). There is contested evidence about the factors that affect the propensity

to start-up a business. Previous studies show that women are significantly less likely to own a

business than men (Blanchflower, 2004; Minniti and Nardone, 2007) even though business

failure rates are not related to the gender of the proprietor (Perry, 2002; Kepler and Shane, 2007).

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The neoclassical economics literature assumes that students make a rational choice to embark on

self-employment and that this choice is affected by a range of de/incentivising issues. There is

evidence to suggest that starting a business may be related to the fixed costs of work and hence

are related to convenience, such as for a parent with childcare responsibilities (Edwards and

Field-Hendrey, 2002). There is also evidence to suggest that decisions concerning employment,

marriage, household production and child-rearing are interdependent (Cowling and Taylor, 2001)

and that men are more likely to opt for self-employment to improve their long-term career

options while women are more likely to start their own business from a position of economic

inactivity or unemployment (Rosti and Chelli, 2005).

The empirical analysis that follows highlights the relative importance of individual and

contextual factors in shaping entrepreneurial propensities. Within the university-based

entrepreneurial ecosystems framework, entrepreneurship education is seen as an incentivising

factor for individuals to become an entrepreneur as it provides knowledge of the entrepreneurial

institutional framework (Lian et al., 2011) and of entrepreneurial competencies (Sanchez, 2013)

that give extra credence to an individual’s tenacity to become an entrepreneur (Lian et al., 2011).

Research method and institutional contexts of the study

Context of the study: The UK policy background

In the UK, the government agenda has focused on encouraging more graduates to pursue an

entrepreneurial career path (i.e. to start-up their own business) with an aspiration for the UK to

be “the best place in the world to start and grow a business” (DBIS, 2008). During the last

decade, a number of initiatives have been created to stimulate enterprise and entrepreneurship at

HEIs in the UK (CIHE/NCGE/NESTA, 2008). McKeown et al. (2006) found that the provision

of entrepreneurship education is varied, with both entrepreneurship and innovation courses on

offer. Entrepreneurship education is most often offered at postgraduate level and on a part time

basis, including courses on technology transfer. Matlay and Carey (2007) provided a longitudinal

study of UK HEIs and recognise that there are a number of actual and perceived barriers for

educators that need to be overcome or mitigated against in order to facilitate a better

understanding of stakeholder needs. They also emphasised that the measurement of the outcomes

of entrepreneurship education in the UK is still proving elusive. The challenges for educators of

entrepreneurship remain in the scaling-up of provision and in generating sustainable demand.

It is also known that institutional differences between old universities (pre-1992) and new

universities (post-1992) in the UK will condition the delivery of entrepreneurship education

(McKeown et al., 2006) and hence potentially shape entrepreneurial aspirations differently. Post-

1992 universities have always been more tightly integrated into their locality and have always

encompassed a broader range of activities, including interacting with local schools, firms, local

authorities and communities, and providing consultancy and Continuing Professional

Development (CPD) training opportunities to local industry. Other universities, often the more

traditional and prestigious institutions, tend to emphasise their national and international

orientations of research, teaching and other scholarly activities, rather than local and regional

connections. Nevertheless, recent years have witnessed that even those less locally-oriented

institutions are increasingly looking to their regions and localities for support and claim credit for

adding to the area’s economic and social strength (Charles et al., 2014).

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Recent policy changes in the UK have affected the institutional conditions for start-ups

and the potential roles of HEIs. In England, the recent change in home undergraduate students’

tuition fees seems to have further raised students’ interest in the employability agenda, which

includes start-ups opportunities as part of their career options. Under the 2010-2015 coalition

government, changes in the governance of local economic development increased the importance

of city-regions (Kitagawa and Robertson, 2011) and this ‘scalar shift’ happened against the

backdrop of the financial and economic crisis (Hutton and Lee, 2012) which has been used as a

justification for the policies of central government. These changes have had knock-on effects on

universities including a shortage of private sector investment, changes in student behaviour and

changes in demands and expectations from local stakeholders (Charles et al., 2014).

Research methods

Against such policy backgrounds, this study investigates the changing entrepreneurial attitudes

of students by comparing student cohorts from two universities in one city-region in England. In

order to carry out this comparative study, an online questionnaire survey was developed in order

to collect data that would contribute to improving the understanding of university students’

experiences, perceptions and attitudes towards entrepreneurship, their entrepreneurial activities

and education experiences, and their perceptions of skills and knowledge gained through their

university’s programmes. For convenience the survey was distributed between March 2011 and

May 2011 at both undergraduate and postgraduate levels across two universities located in a

single core city of the UK: The University of Bristol (UoB) and the University of the West of

England, Bristol (UWE). UWE is classified as a new (post-1992) university while UoB is an old

university. The two universities have different strengths and strategies regarding enterprise

education and academic entrepreneurship which reflects the two institutions’ historical

developments and differences in teaching and research activities.

In order to highlight some of the characteristics of the two universities, Tables 1 to 3

present data from the HEBCI survey (2009/10) of the two HEIs. While this institutional level

data only presents a snap-shot of entrepreneurial activities of the two institutions, the different

natures of university-based entrepreneurial ecosystems may emerge through such data. In terms

of the estimated current turnover of all active firms, UWE graduate1 start-up firms exceeds all

other English HEIs and the nature of entrepreneurial ecosystems at the two HEIs seems to be

very different. While UoB has strength in “Spin-offs with some HEI ownership,” UWE has a

higher number of graduate and staff start-ups. For universities, there tends to be a tension

between resourcing university-owned spin-outs and student-owned start-ups, which are

1 Other initiatives employed by UWE include Enterprise Fairs, where approximately 200 final year undergraduate

students from a range of degree programmes conduct a 30-second elevator pitch in front of a team of 18 tutors

and conduct poster presentations in front of anyone and everyone from within and beyond the university. This

forms the final element of an Enterprise Project, which is a final year dissertation module organised around the

creation and development of a business plan. These business plans correspond to a wide range of business

ventures covering everything from cutting edge software applications to artisan food businesses and also include

a considerable number of business plans focussed around sustainability (reflecting Bristol’s status as European

Green Capital). There are a range of prizes associated with the module all generously sponsored by Peter Fane of

Nurture Landscapes (http://www.nurturelandscapes.co.uk/) who is an alumnus of UWE, and prizes are for the

Best Enterprise Project, Best ‘sustainable’ Enterprise Project, and ‘The Project with the Most Potential’. Staff,

students and members of the public can participate in the day and to make nominations for what they believe to

be ‘The Project with the Most Potential.’

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subsidised by public funding. In the case of the latter, the motivation is more about education

process and individual development than about traditional tech transfer.

{Insert Table 1 about here}

{Insert Table 2 about here}

{Insert Table 3 about here}

The following sections present the findings from the student survey conducted at the two

universities in 2011about the students’ attitudes and orientations about starting up businesses.

Data description

The response rate of the questionnaire turned out to be 4 percent and the profile of our

respondents at the two HEIs is set out in Tables 4 to 10. After accounting for omitted

observations of variables that are necessary for this study, the final sample sizes were 1,210

UWE students and 1,144 UoB students. Table 4 shows the greater representation of postgraduate

students at the UoB, which reflects the composition of the student body across these two

universities. It is difficult to compare the Faculty composition of the two universities in our

sample as the Faculty structures differ.

Both full-time and part-time students are included in the sample, and the differences in

part-time/full-time student ratio at under- and post-graduate levels are broadly in line with the

two universities’ cohorts. Table 5 reveals the gender bias in the sample and Table 6 shows the

age distribution of respondents, which reflects the higher proportion of mature students in the

student population at UWE, all of which reflect differences between the cohorts.

{Insert Table 4 about here}

{Insert Table 5 about here}

{Insert Table 6 about here}

A complex web of factors characterise the relationships between the educational

achievement of children and the educational level of their parents. As there have been many

studies showing a significant positive relationship, it is not surprising that the higher grades

required to obtain a place at the UoB are reflected in our sample with a greater proportion of

parents attaining tertiary education, as shown in Table 7. Table 8 shows a higher proportion of

UK students amongst UWE respondents than those attending UoB, which reflects the

composition of the student body at the UoB that traditionally attracts a greater proportion of

international students. Table 9 shows that a greater proportion of UWE respondents studying

applied disciplines than at UoB, and this too reflects the very different origins and evolution of

the two HEIs.

{Insert Table 7 about here}

{Insert Table 8 about here}

{Insert Table 9 about here}

9

Entrepreneurial attitudes

A key question in our survey focused on students stated intentions of starting up a business.

Given the importance of the business cycle and confidence for the realisation of entrepreneurial

orientations, we generate a new variable called “Start-up soon” which is equal to 1 (one) if the

student responded to the questions “Are you interesting in starting-up a business sometime in the

future” with either “Yes, within five years”, “Yes, within ten years” or “Yes, in the future, not

decided when”; this variable is equal to 0 (zero) if the responded instead stated “No.”2 This is our

proxy for entrepreneurial orientation and is the dependent variable in the regression estimations

below. Table 10 presents the full breakdown of this variable split by university. Although about

the same proportion of students in both universities stated that they would not start up their own

business (33% for UoB, 29% for UWE), there is an important disparity between universities with

students at UWE being almost 50 percent more likely to want to start up their own business

within the next five years (13 percent at UoB, 20 percent at UWE).

{Insert Table 10 about here}

Also included at the bottom of Table 10 is the distribution of attitude changes to

entrepreneurial orientation since the student enrolled in the university degree. Although the

majority of students’ entrepreneurial orientation had not changed, there was a positive movement

towards greater entrepreneurial orientation with 16.6% of respondents indicating that they were

more positive towards entrepreneurial activities after their studies than before they started their

degree.

Entrepreneurial intensions

It is possible to achieve a greater understanding of student-level entrepreneurial orientations by

using this data set to investigate the likelihood of respondents to express an intention of starting

up a business.3 This is achieved by undertaking a series of regressions as set out below in Table

11 where we adopt a specific-to-general model building approach. The dependent variable in

each regression is binary corresponding to whether the student suggested that they will “Start-up

soon” their own business.

{Insert Table 11 about here}

Column 1 indicates that males are 2.1 times more likely to want to start up a business

soon than are females and UWE students are 1.7 times more likely to want to start up a business

soon than are UoB students. This might be associated with the greater emphasis placed on

vocational and applied programs in newer HEIs. Both of these results are statistically significant

across all five columns. There is also only weak tentative evidence that full-time students are

more entrepreneurial than part-time students and postgraduate are more entrepreneurial than

2 We exclude from our analysis those respondents who indicated that they were “Unsure” or had already started

their own business. 3 Although this research does not circumnavigate the terminal issue of intentions not necessarily matching

realisation, it is nevertheless a step towards better understanding of entrepreneurial aspirations.

10

undergraduate students, suggesting that university entrepreneurial guidance should be available

to all students across all levels and modes of study.

Columns 2 and 3 introduce family factors into the regression. If the father has primary

education as their highest level of education then the student is most likely to want to start up a

business: if the father has secondary education then the student is about (1 / 0.550 =) 82 percent

more likely not to want to start up a business and if the father has a tertiary education then there

is no statistically significant additional effect but if anything the effect would seem to be to

reduce entrepreneurial aspirations even further. Note that neither mothers’ educational

attainment nor fathers’ occupational status appear to have any effect on a students’

entrepreneurial aspirations. Relative to the mother being unemployed, if a student’s mother is in

a lower supervisory and technical occupation then the student is likely to have greater

entrepreneurial aspirations. These findings are in line with the suggestion that students of

relatively poorly educated parents and/or a mother in a relatively poor employment position are

more likely to have the perception that they need to rely on their own employment initiatives

(including entrepreneurial expertise) rather than on the value of educational credentials as a

ticket to a good job.

Prior experiences

The survey asked about prior vocationally-relevant experience, and this information is included

in column 4. Prior vocationally-relevant experience was categorised as full-time work

experience, part-time work experience, informally arranged internships (e.g. organized on

student’s own initiative), formal internships (e.g. placement year provided as part of degree

programme) and experience in running their own business. Of these, students who had arranged

an internship informally were 1.9 times more likely to intend to start their own business. Column

5 also provides evidence that those students who had already had experience of running their

own business were 2.2 times more likely to intend to start their own business. Both of these

results are sensitive to the inclusion of perceived benefits of going to university, as included in

column 5. Students who suggested that going to university to gain skills in order to start up their

own businesses were 3.2 times more likely to want to start up a business than those who did not

go to university for this reason. The lack of statistical significance of a range of entrepreneurial-

related activities that may be associated with the decision to go to university could reflect a broad

interpretation of entrepreneurship and a lack of a perceived relevance of education for starting up

a business. Finally, students who have a family member who owns a business are 1.7 times more

likely to want to start up their own business.

The analysis above suggests that entrepreneurial orientation is developed prior to

attending an HEI and is associated with only certain family backgrounds. Prior activity

associated with starting a business is most strongly associated with an intention to start a

business after leaving university. There is also the indication that those students who show

initiative in arranging work experience and internships are more likely to start a business; this

effect is likely to be associated with prior entrepreneurial orientation, peer groups, university

guidance and/or something else. Having established this indicative baseline, it is opportune to

progress and identify factors that change students’ entrepreneurial orientations.

11

Changing attitudes to setting up a business

This section examines the change in students’ entrepreneurial orientation since starting their

degree, as tabulated in Table 10. The questionnaire administered to UWE students included

supplementary questions designed to explore this issue, thus the remaining analysis refers to

respondents from UWE only. As the change in students’ entrepreneurial orientation has an

ordered Likert response, an option for the analysis of this data is to implement ordered logistic

regression; these are presented in Table 12.

{Insert Table 12 about here}

Column 1 assesses whether gender, degree stage, student type and the 2011 business

cycle economic situation were associated with changes in entrepreneurial orientation while at

university. Although attitudes did not change more for males than females or more for full-time

students relative to part-time students, attitudes did change more for undergraduates relative to

postgraduates with undergraduates being 1.5 times more likely to state an improvement in their

entrepreneurial attitude while attending the HEI. Perhaps PG programmes are generally viewed

as less relevant to entrepreneurship or perhaps the students’ entrepreneurial tendencies were

already affected in their undergraduate studies. Further investment by a student in a PG

programme may be viewed as more valuable for mainstream employment than starting a

business.

The economic situation of 2011 affected students’ attitudes towards entrepreneurial

activities with students who stated that the economy encouraged (discouraging) them to start up a

business being 1.8 ([1/0.669=] 1.49) times more likely to state that their attitude improved

(deteriorated). This may reflect perceptions of the probability of achieving projected returns, or

return-related threshold issues as emphasised by McCann and Folta (2012), but may be less

relevant for students if they do not have a baseline estimate of projected returns.

Students’ perceptions of the skills needed for entrepreneurial success were included in

column 2, as greater knowledge, reflection and/or recognition of the need for these skills may

have been accrued while attending university. Out of a wide variety of potentially important

skills and competencies included in the regression (see notes on the bottom of Table 12) the only

statistically significant one that the students suggested was important in changing their

entrepreneurial orientation was communication skills. Students who think that communication

skills are needed to become an entrepreneur are about 1.4 times more likely to have experienced

an improvement in their attitude towards setting up a business, perhaps because they believe they

are good at this skill.

Challenges associated with becoming an entrepreneur

The questionnaire also asked students to provide information about their perceptions of the

challenges associated with becoming an entrepreneur. The list of potential challenges included:

obtaining finance, evolving a business idea, competition in the market, building a team,

acquiring the necessary management skills and identifying markets. Respondents were asked

whether UWE had helped them develop the skills necessary to overcome these challenges. Only

one issue was reported by students as being a potential challenge: if the student suggested that

their biggest challenge to becoming an entrepreneur is identifying markets then they were 1.2

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times more likely to have experienced an improvement in their attitude to setting up their own

business, perhaps because they have improved their knowledge of markets at UWE. Similarly,

students who believe that their UWE education has helped them develop competencies to

address challenges of being an entrepreneur were about 1.8 times more likely to have

experienced an improvement in their attitude towards setting up their own business.

Extracurricular and extra-university activities

Questions were also asked about enterprise and entrepreneurship extracurricular activities and

whether these were perceived to be useful for their future career development. The response rates

to these extra questions varied and would have severely restricted the regression sample and

hence these issues are addressed separately.

Table 13 highlights students’ perceptions of the usefulness of a range of extracurricular

activities. Roughly 75 percent of students indicated that they did not find these activities useful.

There is only one activity which more than 30 percent of students suggested was useful:

short/intensive programmes on entrepreneurship and enterprise skills. One-to-one drop in

sessions on enterprise advice was also perceived to be relatively useful. This suggests that

universities promotion of entrepreneurial and enterprise extracurricular skills should focus on the

provision of either intensive courses or a drop in session.

{Insert Table 13 about here}

In contrast, Table 14 highlights the students’ perceptions of the usefulness of a range of

extra-university activities. The vast majority of these extra-university activities were perceived to

be much more useful than extracurricular activities. The two most useful activities were

volunteering in enterprise activities and enterprise activities in the private sector; the perception

of the usefulness of the latter was found to be equally helpful irrespective of whether the activity

was locally or internationally focused, whereas the former seems to have been more useful if it

had a domestic focus. The perceived usefulness of learning from friends or through buying or

selling on the Internet were both low, with less than a third of respondents suggesting that these

were useful. Nevertheless, less than half the students suggest that extra-university activities were

useful, suggesting the need for greater effort to identify a better match between private enterprise

activities and students’ entrepreneurial needs.

{Insert Table 14 about here}

The analysis of the survey data shows that the entrepreneurial propensity of the students

are influenced by a variety of demographic attributes, educational levels, parental education,

parental occupational backgrounds, family influences, previous work experiences (including

having already started up a business), and being affiliated with different HEI. Additional

analyses related the impact of university experiences to the entrepreneurial propensities of the

student. Student background characteristics, self-selection into courses providing start up

business skills and already having experience in running a business do explain part of the

differences between the universities. However, findings in this article also reveal that students

who think that the task of identifying markets is a big challenge to becoming an entrepreneur are

more likely to have experienced an improvement in their attitudes to setting up their own

13

business, perhaps due to the provision of such useful knowledge at their HEIs. In particular,

students who believe that their university education has helped them develop competencies to

address challenges of becoming an entrepreneur are about 78 percent more likely to have

experienced an improvement in their attitude to setting up their own business.

Concluding remarks: towards a broader conception and communication of the university-

based entrepreneurial ecosystems

The findings from this study provide unique insights to the literature in terms of students’

learning experiences and how different entrepreneurship factors such as demographic attributes

and prior experiences interplay in their changes in attitudes, competences development and

career making processes. The data set provides a unique comparative study of two universities

and their students’ perceptions set in one city-region. Analysis of the data reveals clear

asymmetries. One asymmetry is found in terms of gender while another asymmetry is found in

the nature of university-based entrepreneurial ecosystems across the two HEIs. These condition

both the likelihood of a student being aspirational and any behavioural changes experienced at

university towards starting their own business.

The findings are useful from two main different perspectives. First, although the study is

of specific value to the universities at both institutional level and School/Departmental levels in

terms of gaining profiles of student populations that capture their entrepreneurship experiences

and their perceptions of university programmes, it is also a strong indication that student bodies

are heterogeneous in their propensities to start up businesses and the possibilities of being

encouraged to start up businesses. Such knowledge helps university academics and educators in

designing future entrepreneurship provisions to meet growing diverse students’ demands and

experiences within and across universities.

Secondly, the study would be of value to Bristol city-region where the two universities

provide a large number of graduates with a variety of high-level skills as part of the university-

based entrepreneurial ecosystems. As the HEBCI data indicates, graduate start-ups impact the

local economy in terms of external investment, number of firms and turnover. Although

universities in Bristol attract young and mature students with a variety of experiences both from

the UK and beyond, a significant number of graduates remain in the city-region after their

studies, including those who start-up their own businesses. Greater understanding the

entrepreneurship and enterprise education profiles of university graduates and their destinations

can shape strategies of city-region development. Different universities have different

organisational structures and different student needs and demands. Further study is needed in

order to understand the institutional characteristics of entrepreneurship education and activities at

the two HEIs as well as the relationships and embeddedness of this education to the city-region

entrepreneurial ecosystems.4

While the literature highlights concepts such as the entrepreneurial university (Clark,

1998; Etzkowitz, 2003) and university entrepreneurship (Rothaermel et al., 2007) as important

university-based entrepreneurial orientations, earlier studies on universities’ entrepreneurship

activities tended to focus on a rather narrow set of activities related to the commercialisation of

research, such as patenting and spin-off firm formation. Recent studies argue that undue policy

and research interest has been placed on the commercialisation of research results and the

protection of intellectual properties emanating from universities while neglecting other types of

4 One example is the universities’ links to incubators and entrepreneurial networks in the city-regions

14

entrepreneurial and engagement activities that can be less visible but equally or even more

important (Leydesdorff and Meyer, 2010; Walsh et al., 2008; D'Este and Patel, 2007). It has been

pointed out that leading research universities seem to benefit from the commercialisation of

publicly funded research (Hughes et al., 2013) and also that economic returns from patent

application and university spin-off companies is small and skewed (Harrison and Leitch, 2010).

For most universities, effective knowledge transfer is made through graduates and local

processes and practices that are contingent upon the nature of industrial development in the

regional economy (Dill, 2014). The conceptualisation of university-based entrepreneurial

ecosystems needs to balance the diverse characteristics associated with different types of HEIs

and the synergies between research, teaching and other types of entrepreneurial activities.

Furthermore, through our investigation, several issues have emerged that need further

consideration in order to ensure greater integration of students’ experiences in to the

conceptualisation of the university-based entrepreneurial ecosystems.

First, the number of students engaged in entrepreneurship education is not large in

relation to the whole student population. The impact of entrepreneurship education needs to be

put in perspective as it seems to be directly and positively influencing a small portion of the

students. Secondly, entrepreneurship education consist of a diverse range of activities, such as

combining curricular and non-curricular activities, awareness raising, supporting those with

experiences and encouraging those who had no prior experiences. In particular, there is a lack of

data and insufficient understanding of students’ experiences including the relative importance of

extra-curricular activities and informal enterprise experiences. Thirdly, there is a lack of

consistent data on entrepreneurship education and related activities available at the city-region

level encompassing universities’ organisational boundaries.

Given the growing role of city-regions in local economic governance in England, and the

increasing attention focused towards entrepreneurial-based local development, the student-level

data and the results presented in this study contribute to an improved future strategic

development policy. Furthermore, greater access to and use of cross-HEI data on graduates’

destinations and the roles played by local intermediaries (including local incubators) could

improve understanding of the impact of co-organised training courses at the city-region level on

strategic development.

The findings of the study highlight the need to develop a broader and more integrated

conceptualisation of university-based entrepreneurial ecosystems. University-based

entrepreneurial ecosystems need to be seen as a wide spectrum consisting of education and extra

curriculum activities as well as the more usual conceptualisation based on the commercialisation

of research and spin-off firm formation. Entrepreneurial activities encompass not only

technology-based start-ups but also other areas such as social enterprise and start-ups in creative

industry. Different types of knowledge creation, skills and competences are needed in order to

shape entrepreneurial developments and stimulate entrepreneurial propensities, and should be

identified as an integral part of university-based entrepreneurial ecosystems. For example, an

important issue appears to be the need for universities to use outreach policies and activities to

engage students with private sector enterprises, including alumni networks.

Through learning-by-doing activities students can improve their entrepreneurial and

enterprise skills. We further argue that HEIs should be aware of the important roles that

university-based entrepreneurial ecosystems can have in addressing the development problems

experienced by their city-regions. HEIs should be more aware of the important roles that they

have in influencing student entrepreneurial behaviour, and should communicate their

15

contributions more effectively. The impacts that entrepreneurship education has on business

start-ups and entrepreneurial activities in general need to be integrated in a broad

conceptualisation of the university-based entrepreneurial ecosystems. Future research should

investigate and improve understanding of students’ perceived barriers and challenges to

becoming an entrepreneur. The trajectories and impact of graduate start-ups of local

development are also areas that need further examination as part of the long term evolution of

university-based entrepreneurial ecosystems. Greater understanding of the processes of

entrepreneurial training and of the wider impacts on skills and the economy will can be used to

enhance the functioning and sustainability of entrepreneurship ecosystems at the city-region

level.

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17

Table 1: Active and surviving firms

Number of active firms

Spin-offs with some HEI

ownership

Formal spin-offs,

not HEI owned Staff start-ups Graduate start-ups

2009/10 2008/09 2009/10 2008/09 2009/10 2008/09 2009/10 2008/09

University of Bristol 20 21 7 6 2 1 2 3

University of the West

of England, Bristol 1 1 1 1 14 11 41 30

Number still active which have survived at least 3 years

Spin-offs with some HEI

ownership

Formal spin-offs,

not HEI owned Staff start-ups Graduate start-ups

2009/10 2008/09 2009/10 2008/09 2009/10 2008/09 2009/10 2008/09

University of Bristol 17 16 7 6 1 1 2 3

University of the West

of England, Bristol 1 1 1 1 9 5 15 13

Table 2: Employment and turnover of active firms

Estimated current employment of all active firms (FTE)

Spin-offs with some HEI

ownership

Formal spin-offs,

not HEI owned Staff start-ups Graduate start-ups

2009/10 2008/09 2009/10 2008/09 2009/10 2008/09 2009/10 2008/09

University of Bristol 120 92 49 72 28 28 10 12

University of the West

of England, Bristol 0 0 2 2 30 28 174 162

Number still active which have survived at least 3 years

Spin-offs with some HEI

ownership

Formal spin-offs,

not HEI owned Staff start-ups Graduate start-ups

2009/10 2008/09 2009/10 2008/09 2009/10 2008/09 2009/10 2008/09

University of Bristol 6400 3539 532 450 300 300 830 508

University of the West

of England, Bristol 0 0 100 100 2692 2395 44217 12555

18

Table 3: Estimated external investment received (£ thousands)

Spin-offs with some HEI

ownership

Formal spin-offs,

not HEI owned Staff start-ups Graduate start-ups

2009/10 2008/09 2009/10 2008/09 2009/10 2008/09 2009/10 2008/09

The University of

Bristol 7800 8790 8000 3000 0 0 0 0

University of the West

of England, Bristol 0 0 0 0 0 0 25 5045

Table 4: Enrolment status of sample population

UWE UoB

Number % of respondents Number % of respondents

UG Full-time 930 77 730 64

UG Part-time 46 4 11 1

PG Full-time 130 11 312 27

PG Part-time 88 7 70 6

UG Exchange student (< a year) 3 0 13 1

PG Exchange student 3 0 3 0

Other 10 1 5 0

Totals 1210 100 1144 100

Response rate 4.84 6.36

19

Table 5: Gender of sample population

Gender UoB (N=1144)

%

UWE (N=1210)

%

Total (N=2354)

%

Male (N=903) 39.4 37.4 38.4

Female (N=1451) 60.6 62.6 61.6

Table 6: Age range of sample population

Age

UoB

(N=1144)

%

UWE

(N=1210)

%

Total

(N=2354)

%

17-21 52.3 45.9 48.9

22-26 31.6 30.1 30.7

27-31 8.0 8.6 8.3

31-35 2.5 5.0 3.7

36-40 1.5 3.3 2.4

41-plus 4.1 7.2 5.6

Total 100 100 100

Table 7: Highest level of education of father and mother by institution

Highest level

UoB

%

UWE

%

Father

primary 4.5 7.4

secondary 29.3 47.1

tertiary 66.3 45.5

Mother

primary 4.4 6.9

secondary 33.2 51.6

tertiary 62.4 41.6

Total 100 100

Table 8: Region of origin of student sample population

UoB

%

UWE

%

Total

%

UK home 76.7 85.2 81.2

EU 8.6 7.2 7.8

International (non EU) 13.2 6.4 9.7

Other 1.6 1.2 1.3

20

Table 9: Frequency of respondents by Faculty and University

Respondents by Faculty/Division

(N=2354)

% Respondents

by Faculty/Division

UoB (48.6%)

Arts 9

Engineering 8

Medical and Vet 5

Medicine and Dentistry 3

Science 13

Social Science and Law 11

UWE (51.4%)

Business and Law 10

Creative Arts, Humanities and Education 14

Environment and Technology 11

Health and Life Sciences 14

Hartbury College 2

Other 1

21

Table 10: Entrepreneurial orientation

UoB

(N=1144)

UWE

(N=1210)

Number % of institution Number % of institution

Already started my own business

28

2

50

4

Yes, within five years

} =1 for

“Start-up

soon”

78 7 161 13

Yes, within ten years 74 6 81 7

Yes, in the future, not decided when 230 20 303 25

No }

=0 for

“Start-up

soon”

373 33 345 29

Unsure 361 32 270 22

Totals 1144 100 1210 100

Total intending at any time 410 36 595 49

My attitude towards setting up my own business has changed since I enrolled in my university degree

I was initially very positive but now I am negative 14 1.4 %

I was slightly positive but now I am negative 51 5.1 %

My attitude has not changed 770 76.9 %

I was slightly negative but now I am positive 138 13.8 %

I was very negative but now I am positive 28 2.8 %

22

Table 11: Ordinary logistic regression: desire to start-up a businessa

(1) (2)b (3)

c (4)

d (5)

e

N 1638 1638 1638 1638 1638

Male 2.135***

(0.227)

2.141***

(0.228)

2.144***

(0.231)

2.161***

(0.236)

2.291***

(0.324)

Female Control variable

UWE 1.656***

(0.174)

1.728***

(0.188)

1.753***

(0.199)

1.863***

(0.215)

1.349**

(0.204)

Bristol University Control variable

Under graduate 0.799

(0.101)

0.795

(0.101)

0.776**

(0.100)

0.793

(0.105)

0.603***

(0.102)

Post graduate Control variable

Full time 1.397

(0.248)

1.387

(0.247)

1.354

(0.247)

1.388

(0.256)

1.000

(0.236)

Part time Control variable

Dad: Tertiary education – 0.610

(0.165)

0.614

(0.169)

0.610

(0.170)

0.628

(0.224)

Dad: Secondary education – 0.550**

(0.145)

0.546**

(0.145)

0.550**

(0.148)

0.690

(0.240)

Dad: Primary education Control variable

Mum: Lower supervisory and technical

occupations – –

0.313***

(0.138)

0.296***

(0.132)

0.237***

(0.133)

Mum: Unemployed Control variable

Gained enterprise experience while

spending time as an intern – – –

1.857***

(0.336)

1.394

(0.315)

Gained enterprise experience: started up

own business before university – – –

1.654

(0.509)

2.156**

(0.839)

Start business skills – – – – 3.213***

(0.256)

Family member owns a business – – – – 1.683***

(0.248)

Constant 0.647

(0.114)

0.747

(0.210)

0.690

(0.282)

0.533

(0.226)

0.042***

(0.032)

Log pseudo-likelihood -1084.432 -1080.603 -1070.921 -1061.487 -712.426

Wald chi2 75.91*** 83.57*** 102.93*** 121.80*** 725.57***

Notes: a Dependent variable in all these regressions is “Start-up soon”. Odds-ratios are presented with robust standard errors

in parentheses. ***, ** and * signify statistical significance at the 1%, 5% and 10% levels respectively. b

Mother’s education was also included from this regression onwards, but remained consistently statistically

insignificant. c All dad job occupation variables were included from this point onwards with Dad: Unemployed as the control

variable. All variables were consistently statistically insignificant throughout. Also included from this regression

onwards were all the job descriptions of the mother; in this case all jobs descriptions were statistically insignificant

throughout except for Mum: Low sup job, with Mum: Unemployed as the control variable. d Also included from this regression onwards were Gained enterprise experience in full time work, Gained enterprise

experience in part time work while in education and Gained enterprise experience in a formerly organized program,

all of which remained statistically insignificant throughout. e Also included in this regression were issues related to the benefits of going to university, including Qualifications

are important, Personal Development is important, Advancement of career opportunities, Academic Knowledge,

Technical knowledge and Management skills, all of which were not found to be statistically significant.

23

Table 12: Ordered logistic regression: changing attitudes to setting up a business

(1) (2)a (3)

b

N 1001 1001 969

Male 1.189

(0.186)

1.192

(0.193)

1.086

(0.182)

Female Control variable

Undergraduate 1.453*

(0.313)

1.476*

(0.321)

1.622**

(0.367)

Post graduate Control variable

Full time 1.226

(0.320)

1.254

(0.330)

1.124

(0.307)

Part time Control variable

Perceives the current economic situation encourages

them to start up a business

1.868***

(0.450)

1.860**

(0.453)

1.747**

(0.441)

Perceives the current economic situation neither encourages

nor discourages them to start up a business Control variable

Perceives the current economic situation discourages

them to start up a business

0.669**

(0.111)

0.683**

(0.114)

0.726*

(0.125)

Think communication skills needed to become

an entrepreneur –

1.327*

(0.216)

1.433**

(0.246)

Biggest challenge to becoming an entrepreneur is

identifying markets – –

1.195**

((0.107)

Believes UWE education has helped them develop the

competences to address challenges of being an entrepreneur – –

1.777***

(0.170)

Cut 1 -3.925

(0.371)

-4.167

(0.642)

-2.868

(0.744)

Cut 2 -2.330

(0.286)

-2.571

(0.597)

-1.245

(0.702)

Cut 3 2.070

(0.281)

1.865

(0.593)

3.422

(0.716)

Cut 4 4.025

(0.331)

3.862

(0.617)

5.514

(0.742)

LR chi2 27.88*** 36.50*** 80.08***

Log likelihood -773.27 -768.96 -712.42 Notes: Odds-ratios are presented with robust standard errors in parentheses. ***, ** and * signify statistical

significance at the 1%, 5% and 10% levels respectively. a Also included in this regression onwards are Motivation, Team work, Negotiation skills, Management skills, Finance

skills, Market knowledge, Technical competency and Innovative capacity. None of these were found to be

statistically significant at the 5% level. b Also included in this regression are the importance of entrepreneurial challenges associated with finance, having a

business idea, being competitive in the market, working as a team and acquiring management skills and knowledge.

None of these were found to be statistically significant at the 10% statistical significance level.

24

Table 13: Percentages finding extracurricular activities useful

Short/intensive

programme on

entrepreneurship and

enterprise skills

1:1 drop in

session on

enterprise

advice

Ideas and

social

networking

challenge

Bizidea

competition

Business

incubator

Local

enterprise

network

Not useful (1) 32 32 30 36 37 43

(2) 12 18 20 15 17 12

Neither / nor (3) 20 21 24 24 21 19

(4) 19 18 16 15 14 12

Very useful (5) 17 11 10 12 11 14

(4) + (5) 36 29 26 27 25 26

Table 14: Percentages finding extra-university activities useful

Local

enterprise

activity in

private

sector

Volunteer

enterprise

activities

International

enterprise

activity in

private sector

International

volunteer

enterprise

activities

Learning

through

media

Learning

through

friends

Buying &

selling on

Internet

(e.g. Ebay)

Not useful (1) 12 11 13 16 15 12 22

(2) 13 14 19 17 27 25 23

Neither / nor (3) 33 30 25 30 30 33 28

(4) 22 24 17 16 17 18 15

Very useful (5) 20 20 26 23 11 12 11

% (4) + (5) 42 44 43 39 28 30 26

25

Recent UWE Economics Papers

See http://www1.uwe.ac.uk/bl/research/bristoleconomics/research for a full list

2015

1505 University entrepreneurship education experiences: enhancing the entrepreneurial ecosystems in a

UK city-region

Fumi Kitagawa, Don J. Webber, Anthony Plumridge and Susan Robertson

1504 Can indeterminacy and self-fulfilling expectations help explain international business cycles? Stephen McKnight and Laura Povoledo

1503 User-focused threat identification for anonymised microdata

Hans-Peter Hafner, Felix Ritchie and Rainer Lenz

1502 Reflections on the one-minute paper

Damian Whittard

1501 Principles- versus rules-based output statistical disclosure control in remote access environments

Felix Ritchie and Mark Elliot

2014

1413 Addressing the human factor in data access: incentive compatibility, legitimacy and cost-effectiveness

in public data resources

Felix Ritchie and Richard Welpton

1412 Resistance to change in government: risk, inertia and incentives

Felix Ritchie

1411 Emigration, remittances and corruption experience of those staying behind

Artjoms Ivlevs and Roswitha M. King

1410 Operationalising ‘safe statistics’: the case of linear regression

Felix Ritchie

1409 Is temporary employment a cause or consequence of poor mental health?

Chris Dawson, Michail Veliziotis, Gail Pacheco and Don J Webber

1408 Regional productivity in a multi-speed Europe

Don J. Webber, Min Hua Jen and Eoin O’Leary

1407 Assimilation of the migrant work ethic

Chris Dawson, Michail Veliziotis, Benjamin Hopkins

1406 Empirical evidence on the use of the FLQ formula for regionalizing national input-output tables: the case of the

Province of Córdoba, Argentina

Anthony T. Flegg, Leonardo J. Mastronardi and Carlos A. Romero

1405 Can the one minute paper breathe life back into the economics lecture?

Damian Whittard

1404 The role of social norms in incentivising energy reduction in organisations

Peter Bradley, Matthew Leach and Shane Fudge

26

1403 How do knowledge brokers work? The case of WERS

Hilary Drew, Felix Ritchie and Anna King

1402 Happy moves? Assessing the impact of subjective well-being on the emigration decision

Artjoms Ivlevs

1401 Communist party membership and bribe paying in transitional economies

Timothy Hinks and Artjoms Ivlevs

2013

1315 Global economic crisis and corruption experience: Evidence from transition economies

Artjoms Ivlevs and Timothy Hinks

1314 A two-state Markov-switching distinctive conditional variance application for tanker freight returns

Wessam Abouarghoub, Iris Biefang-Frisancho Mariscal and Peter Howells

1313 Measuring the level of risk exposure in tanker shipping freight markets

Wessam Abouarghoub and Iris Biefang-Frisancho Mariscal

1312 Modelling the sectoral allocation of labour in open economy models

Laura Povoledo

1311 The US Fed and the Bank of England: ownership, structure and ‘independence’

Peter Howells

1310 Cross-hauling and regional input-output tables: the case of the province of Hubei, China

Anthony T. Flegg, Yongming Huang and Timo Tohmo

1309 Temporary employment, job satisfaction and subjective well-being

Chris Dawson and Michail Veliziotis

1308 Risk taking and monetary policy before the crisis: the case of Germany

Iris Biefang-Frisancho Mariscal

1307 What determines students’ choices of elective modules?

Mary R Hedges, Gail A Pacheco and Don J Webber

1306 How should economics curricula be evaluated?

Andrew Mearman

1305 Temporary employment and wellbeing: Selection or causal?

Chris Dawson, Don J Webber and Ben Hopkins

1304 Trade unions and unpaid overtime in Britain

Michail Veliziotis

1303 Why do students study economics?

Andrew Mearman, Aspasia Papa and Don J. Webber

1302 Estimating regional input coefficients and multipliers: The use of the FLQ is not a gamble

Anthony T. Flegg and Timo Tohmo