Schwartz Marketing

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Journal of Marketing ManagementVol. 28, Nos. 11–12, October 2012, 1438–1463

The usefulness of Schwartz’s ‘Values Theory’in understanding consumer behaviour towards

differentiated products

Athanasios Krystallis, Aarhus University, DenmarkMarco Vassallo, National Research Institute for Food and Nutrition

(INRAN), Italy George Chryssohoidis, University of East Anglia, UK

Abstract The Values Theory adopts a generic framework whereby a set of

values is employed across consumer decision-making contexts in a mannerthat makes no distinction among various product categories. The present studyadvances this theory by exhibiting the adaptation capability of the genericvalues instrument (the Portrait Value Questionnaire, PVQ), demonstrating thattailor-made PVQ versions can reflect consumers’ motives towards differentiatedproducts (i.e. organic foods). A questionnaire was completed by approximately1000 households in each of eight EU countries (N = 8171). The organicfood-relevant PVQ was developed through a preliminary qualitative phase (i.e.a means-end chain analysis), and its factorial design was validated through CFA,showing high statistical performance. PVQ-based European clusters with strongself-transcendence values comprised large numbers of organic purchasers.Moreover, results point to the fact that when a circumplex taxonomy, suchas the PVQ, is applied in a real context (i.e. organic food purchases), thesituation-relevant value domains merge into new hierarchical dimensions inabsolute respect of the original taxonomy. This conclusion points to PVQ’srobustness in adaptability to different situations of human value perspective.

Keywords values; PVQ; value segmentation; differentiated products; behaviour

Introduction

Human values are enduring beliefs that one specific state of existence or modeof conduct for an individual’s life is preferable over an alternative end-state ormode of conduct (Kahle, 1983; Rokeach, 1968, 1973). Early on, the values conceptwas drawn on to shed light on the attitudes and behaviour of individuals andthe functioning of organisations, institutions, and societies (Rokeach, 1973; terHofstede, 1980). Rokeach (1968, 1973, 1979) is credited for operationally defining

ISSN 0267-257X print/ISSN 1472-1376 online© 2012 Westburn Publishers Ltd.http://dx.doi.org/10.1080/0267257X.2012.715091http://www tandfonline com


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Krystallis et al. Consumer values and behaviour towards differentiated products 143

and investigating values as ‘. . . an organised set of preferential standards that areused in making selections of objects and actions, resolving conflicts, invoking socialsanctions, and coping with needs or claims for social and psychological defences of choice made or proposed . . . ’ (Rokeach, 1979, p. 20). Values represent the mostabstract cognitions or extreme global attitudes and serve as standards or models for

evaluating attitudes, beliefs, and behaviour. Values are stable constructs that do notchange easily, even when investing considerable effort. As a result, values can serveas predictors of behaviour over extended periods of time, and they are of particularimportance for marketing decisions.

Schwartz (1992, 1994, 1996), Schwartz and Sagiv (1995), and P.B. Smith andSchwartz (1997) propose a systematic theory of the content and organisationof individuals’ value systems called the Values Theory. This theory identifiesa comprehensive set of 10 different types of cross-cultural values (valuedomains), namely benevolence, universalism, self-direction, stimulation, hedonism,achievement, power, security, conformity, and tradition. Analyses of more than

200 samples from more than 60 nations support the distinctiveness of the 10 valuesand the structure of their relations (Schwartz, 2004a, 2004b; Schwartz et al.,2001; Schwartz & Sagiv, 1995). A concrete 40-item typology called the PortraitValue Questionnaire (PVQ) has recently been designed to operationalise thoseconstructs.

In line with much research in the area, the Values Theory adopts ageneric framework whereby the set of values is unquestionably employed inan undifferentiated manner across various consumer decision-making contexts,involving different types of products. This stance is very helpful when aimingto capture the behavioural components that can systematically be examined toidentify common ground across populations with parsimony and reasoning, as inthe endeavours by ter Hofstede (1980), House, Hanges, Javidan, Dorfman, andGupta (2004), Schwartz (1992, 1994, 1996), and Trompenaars (1994). Yet, theissue of fundamental importance here is whether values-based paradigms can beemployed in specific context-related consumer behaviour, an issue already addressedin organisational research (e.g. Earley, 2006). The present work shows the usefulnessof contextualising theoretical justifications initially developed for the systematicassessment of general consumer behaviour phenomena. The work advances theoryby exhibiting the adaptation capability of existing taxonomies, such as the PVQ,and demonstrates that tailor-making of the core-values generic instrument canpurposefully reflect consumers’ motives in specific decision-making contexts. This

theory proves to be especially powerful in its explanatory ability, statistically robust,and flexible to fit into specifically contextualised decision making – in this casedecision-making that involves differentiated products.

First discussed in the marketing literature in the 1950s (W. Smith, 1956),the issue of product differentiation was delineated more than 20 years ago byDickson and Ginter (1987). In their seminal work, Dickson and Ginter defineddifferentiated products as product offerings that consumers perceive to differ fromtheir competition on any physical or non-physical characteristic, including price.The perceptual differences between differentiated and ‘undifferentiated’ productsare created by usage experience, word of mouth, and communication, whereas

actual differences are a matter of product characteristics (Dickson & Ginter, 1987).Based on the above-described operationalisations, organic foods are exemplarydifferentiated products, since they differ from their competition (conventional food


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1440 Journal of Marketing Management, Volume 28

products) in both actual (i.e. environmental friendliness, price) and perceived (i.e.healthiness, tastiness) characteristics of their marketing mix.

Organic foods as differentiated products may appeal to different types of valuemotives, as also postulated by past research (e.g. Brunsø, Scholderer, & Grunert,2004; Dreezens, Martijn, Tenbult, Kok, & de Vries, 2005; Kihlberg & Risvik,

2007; Krystallis, Vassallo, Chryssohoidis, & Perrea, 2008; Worsley & Lea, 2008)and thus constitute a fertile ground for testing the tailoring the PVQ instrument.This work tests a PVQ-based inventory of values pertaining explicitly to organicfoods, using nationally representative samples of more than 1000 consumers fromeight EU countries (8171 respondents in total). The work builds on the assumptionthat consumers who place more emphasis on values relevant to organic food(e.g. universalism and benevolence) also demonstrate a relevant set of beliefs andpurchasing behaviour towards organic products. Therefore, the primary hypothesisis that a subset of PVQ values relevant to organic food choice explains consumerbehaviour in the specific context. Accepting this hypothesis has substantial marketing

implications, namely that subsets of values – specific to contexts at hand – canprovide a sound basis for consumer behaviour understanding, market segmentation,and strategy development, both at national and cross-national levels.

The paper is organised as follows. The next two sections offer inclusivedescriptions of the Values Theory, the PVQ typology, and the theoreticalsubstantiation, objectives, and contribution of the study. The methodology sectionintroduces the process of developing a 16-item PVQ-based inventory of valuesrelevant to organic food, the sample, and the questionnaire. In the analysis section,invariance tests and confirmatory factor analyses (CFA) to validate the PVQ-basedinventory are described, followed by hierarchical and k-means cluster analyses testingthe ability of the 16-item PVQ-based inventory to explain the behaviour towardsdifferentiated food products of pan-European value segments. The paper continueswith the discussion section in relation to the objectives of the survey, while theconclusion section summarises the key findings.

Schwartz’s Values Theory in context-specific decision making

Five main features of values that are considered the common background for socialscience research on values (Schwartz & Bilsky, 1987) can be outlined as follows:values are (1) concepts or beliefs; (2) about desirable end-states or behaviours;

(3) transcending specific situations; (4) guiding the evaluation of persons, behaviour,and events; and (5) ordered by relative importance. The Values Theory (Schwartz,1992, 1994, 1996) enables researchers to treat people’s value systems as coherentstructures. The critical idea builds on 10 universal values that form a circular structureof motivationally opposed but compatible elements (Figure 1).

Two orthogonal dimensions summarise the integrated structure (Schwartz et al.,2001; Schwartz, Sagiv, & Boehnke, 2000): the vertical dimension of ‘self-enhancement–self-transcendence’ contrasts the values of power and achievement(which emphasise the pursuit of self-interests) with the values of universalismand benevolence (which involve concern for the welfare and interests of others).

Moreover, the horizontal dimension of ‘openness to change–conservation’ contraststhe values of self-direction and stimulation (which emphasise independent thoughtand readiness for new experience) with the values of security, conformity, and


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Figure 1 Schwartz’s taxonomy of motivational value domains.

Self-trancendence

Universalism Benevolence

Tradition

Concer-vation

Self-enhancement

Conformity

Security

Power

Achievement

Hedonism

Stimulation

Self-direction

Opennessto change

tradition (which involve self-restriction, order, and resistance to change). Hedonismconceptually shares elements of both ‘openness-to-change’ and ‘self-enhancement’.The circumplex character (i.e. an equally spaced, circular, dimensional factorstructure) lies in the assumption that if a specific behaviour correlates positively withone value, the expected pattern of associations with all other values follows from thiscircular value structure, meaning that this behaviour will also be positively correlatedwith the neighbouring values (or negatively correlated with values that lie at theopposite poles of the circumplex).

Recently, the PVQ was suggested as an instrument to test the Values Theoryempirically. The PVQ is a 40-item typology that includes short portraits of 40 different– hypothetical – people (Schwartz, 2004a, 2004b; Schwartz, Lehman, & Roccas,1999; Schwartz et al., 2001). Each portrait points implicitly to the importance of a value; for example: ‘He/she really wants to enjoy life. Having a good time isimportant to him/her’ describes a person to whom hedonic values are important.The prompt ‘Think about how much each person is or is not like you’ accompanies

each portrait. Responses are: ‘very much like me’, ‘like me’, ‘somewhat like me’,‘a little like me’, ‘not like me’, and ‘not like me at all’. Respondents thus comparethe portrait with themselves rather than themselves with the portrait. In this way,respondents pay attention only to personality aspects relating to the portrait, so thesimilarity test is likely to focus only on these aspects. The number of portraitsfor each value reflects the breadth of a value’s conceptual definition: six foruniversalism; five for security; four for tradition, conformity, benevolence, self-direction, and achievement; and three for stimulation, hedonism, and power. Theorder of the portraits in the PVQ should be such that portraits of the same conceptualmeaning are separated by at least three portraits with a different meaning.

Numerous international samples show that consensus regarding the hierarchicalorder of the values is surprisingly high (Schwartz, 2004a, 2004b; Schwartz & Bardi,2001; Schwartz et al., 2000): benevolence, self-direction, and universalism are the


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most important ones; power, tradition, and stimulation are the least important ones.Since its development, numerous scientific applications have validated the ValuesTheory (e.g. Bilsky & Koch, 2000; Bubeck & Bilsky, 2004; Fontaine, Richardson, &Foog, 2002; Saroglou, Delpierre, & Dernelle, 2004), and especially in decision-making contexts involving a wide range of human behaviours, such as various

social contexts (e.g. Alkire, 2005; Goodwin, Kozlova, Nizharadze, & Polyakova ,2004; Kurman & Ronen-Ellon, 2004; Reallo, Koido, Ceulemans, & Allikl, 2002),family context (e.g. Knafo, 2003a, 2003b; Knafo & Schwartz, 2001, 2003), politicalcontext (e.g. Caprara, Schwartz, Capanna, Vecchione, & Barbaranelli, 2006), sexualcontext (e.g. Goodwin, Kozlova, et al., 2004; Goodwin, Realo, Kwiatkowska,Kozlova, Nguyen, & Nizharadze, 2002), religious context (e.g. Paryente & Orr,2004; Saroglou et al., 2004), work context (e.g. Arciniega & Gonzalez, 2002, 2005;Knafo & Sagiv, 2004; Koivula & Verkasalo, 2006; Poling, Woehr, Arciniega, &Gorman, 2004), service contexts (e.g. Chan, Bond, Spencer-Oatey, & Rojo , 2004;Fegg, Wasner, Neudert, & Botasio, 2005; Lee, Soutar, Daly, Kelley, & Louviere,

2007), and various types of risk management-related contexts (e.g. Cohrs, Kielman,Maes, & Moschner, 2005; Cohrs, Moschner, Maes, & Kielman, 2005; Floriano,Mora, & MacLean, 2007; Goodwin et al., 2004; Konty, Duell, & Joireman, 2004).

The Values Theory is also validated in numerous consumer behaviour applicationsin food-related contexts, since strong empirical support has been found for thelink between values and food choice (e.g. Allen & Baines, 2002; Allen, Wilson,Ng, & Dunne, 2000; Feather, Norman, & Worsley, 1998). There is also evidencethat particular value orientations are associated with the habitual consumption of particular differentiated food products, such as vegetarian foods (e.g. Lea, 2001,in Worsley & Lea, 2008), environmentally friendly foods (e.g. Bamberg, 2002, inSchwartz, 2004b), genetically modified foods (e.g. Dreezens et al., 2005), and organicfoods (e.g. Kihlberg & Risvik, 2007; Krystallis et al., 2008). Recently, the PVQhas been used in value-based segmentation studies (e.g. Kihlberg & Risvik, 2007;Krystallis et al., 2008; Lee et al., 2007). In this respect, it is worth highlighting thatvalues are a useful basis for segmenting consumers because they can be closely relatedto motives and behaviour, and because they are limited in number and central to theconsumer’s self-concept (Kamakura & Mazzon, 1991; Kamakura & Novak, 1992;Wedel, ter Hofstede, & Steenkamp, 1998).

Theoretical substantiation, objectives, and contribution

As postulated by the Values Theory, the above-described PVQ’s circumplex structureessentially means that consumer segments with different value structures are likelyto demonstrate different purchasing behaviour towards products with differentiatedphysical and non-physical attributes. For instance, Brunsø et al. (2004) postulatethat when environmentally friendly production is a consumer’s central motive infood selection, universalism values are important enough to explain organic foodpurchases. However, Magnusson, Arvola, Koivisto Hursti, Åberg, and Sjoden (2003)state that egoistic motives are better predictors of food purchase than altruistic ones.Moreover, Worsley and Lea (2008) claim that people who hold strong egalitarian

values may be more concerned about poverty and animal welfare, since these areimplicitly linked to concepts of equality (e.g. among humans, and between humansand animals).


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It is thus meaningful to hypothesise that preference for differentiated products isoften the outcome of more than one pertinent motive. By doing so, we introducethe idea of ‘more’ versus ‘less’ pertinent motives and the importance of tailoringextant instruments for their assessment. For instance, Schwartz (2004b) argues thatif respondents perceive environmentally friendly purchasing as self-protective (e.g.

avoiding pesticides in food), this could mitigate the otherwise negative influence of conservation values such as security. Consequently, organic food consumers mightbe guided by self-transcendence values, although the importance assigned to othervalues may still play a role. Following this line of thought, similar hypotheses canbe developed for other expressions of consumer behaviour towards differentiatedproducts: when someone prioritises the hedonic component of consumption, ors/he demonstrates exploratory buying behaviour, or s/he emphasises the adoptionof socially acceptable norms in consumption behaviour, hedonism, stimulation,and/or conformity values respectively are likely reasons for preferring products thatpossess unique physical and non-physical attributes that appeal to relevant value

components.Building on the above discussion, this paper aims at promoting the tailoring of the instruments assessing consumer behaviour towards differentiated products andexhibiting the explanatory power of subsets of personal values for that purpose.The paper examines whether using a shorter PVQ inventory relevant to consumerbehaviour towards specific differentiated products (i.e. organic foods) is conceptuallymeaningful and empirically robust. Consequently, the paper (a) tests the statisticalrobustness of a shorter PVQ version tailored to values relevant to organic foods;(b) confirms the organisation of these PVQ values into latent constructs andexamines whether Schwartz’s organisation of values into domains and dimensionsreplicates itself; and (c) uses the shorter PVQ version developed above in a value-based segmentation task to explain consumer behaviour towards organic foods byidentifying per value-based consumer segment the (combination of) value motivesthat are more important for organic food purchasing.

From a practitioner’s point of view, this paper further aims at offering theEuropean industry substantial marketing insights into the usefulness of tailoringconsumers’ personal values instruments to understand consumer behaviour towardsdifferentiated goods; highlighting the explanatory ability of simple and flexiblemarketing data collection tools, such as the PVQ; and providing evidence forthe strategic marketing value derived from value-based segmentation endeavours.Kihlberg and Risvik (2007) postulate that, for marketers, it is of great importance

to understand the value structure underlying consumption patterns. When segmentschange or mature, it is necessary for strategic market communication to be in linewith these changes. Thus the values communicated should be recognised as importantto the targeted segment, and a good marketing strategy requires an understanding of the value basis of each strategically important segment.

Methodology

Development of the 16-item PVQ inventory for organic products

In order to identify organic food-relevant values from the overall PVQ typology,professional research agencies conducted qualitative means-end chain (MEC)


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analyses with 100 consumers in each of the countries Germany, Great Britain,Denmark, and Spain. The Food-Related Lifestyle (FRL) segmentation approachcontributed to the identification of different consumer segments in each country.1

The aim of the MEC studies was to explore consumer knowledge structuresregarding organic foods across different consumer segments in each country, focusing

on organic food-related consumer values. MEC contributed to the elicitation of 11 organic food-related value codes (Table 1). Based on the outcome of theMEC study, the questionnaire developed for subsequent data collection included16 PVQ items corresponding to seven value domains that covered the ValuesTheory self-transcendence and openness to change dimensions, and partially the self-enhancement and conservation dimensions (Bredahl, Thøgersen, Dean, Pemartin, &Stiebel, 2004).

The sample and the questionnaire

The survey used samples of approximately 1000 consumers from each of eight EUcountries with proven variance in terms of consumer attitudes towards organic foodand diverse organic market conditions (8171 respondents in total). Professionalresearch agencies collected the data in each country. Persons aged 18 and above,sharing or in charge of grocery shopping, completed the questionnaire. Mean ageof participants was 45.9 years (SD = 15.67). Overall, the country samples werenationally representative in each of the eight countries in terms of education, income,and geographic distribution (Table 2).

The questionnaire comprised 39 variables divided into five sections.Section 1 concerned actual perceived knowledge about organic foods. Threeitems from the Flynn and Goldsmith (1999) scale measured consumers’ actualperceived knowledge on a seven-point Likert-type agreement scale, with endpoints1 = ‘strongly disagree’ to 7 = ‘strongly agree’. The three items were: ‘I do not feelvery knowledgeable about organic food’, ‘Compared to most other people, I knowless about organic foods’, and ‘When it comes to organic food, I really don’t knowa lot’. Section 2 was about organic food-related consumer beliefs (nine items). Fiftytelephone interviews with people of different ages and professions in each of theeight countries (mean age = 41.06, SD = 10.37) contributed to the elicitation of nine organic-relevant belief items. The prompt about beliefs during these telephoneinterviews was ‘Please indicate how likely it is that organic foods are . . . ’. The ninebelief items included five positive beliefs (organic foods are free from chemicals, are

more tasty, are better for the environment, are healthier, and are more natural) andfour negative beliefs (organic foods are more expensive, do not keep fresh for aslong, are less attractive, and are not really organic). Replies to the correspondingnine belief questions were given on a seven-point Likert-type likelihood scale withendpoints 1 = ‘extremely unlikely’ to 7 = ‘extremely likely’. Section 3 includedorganic food-relevant PVQ values (16 items). Section 4 examined organic food

1The FRL concept builds on MEC theory to explain how consumers mentally relate food acquisition andconsumption to the attainment of basic life values. Five interrelated domains constitute the link between

attributes and values: ways of shopping, cooking methods, quality aspects, consumption situations, andpurchasing motives (Brunsø & Grunert, 1995; Brunsø, Grunert, & Bredahl, 1996; Grunert, Brunsø, &Bisp, 1997; Grunert, Brunsø, Bredahl, & Bech, 2001).


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Table 1 Values elicited though means-end chain, value codes, and correspondencewith Schwartz’s PVQ taxonomy.

Value codesValues items elicited

through MEC Corresponding PVQ domains and

items

1. Healthiness anda long life Healthiness, preserve agood health, livelonger, quality of life

Security 31a: He tries hard to avoid getting sick.Staying healthy is very important tohim.

2. Pleasure andenjoyment

Happiness, pleasure,satisfaction,contentment

Hedonism10: He seeks every chance he can to

have fun. It is important to him to dothings that give him pleasure.

37: He really wants to enjoy life. Havinga good time is very important to him.

3. Family welfare Responsibility for the

health and future ofchildren/family/partner

Benevolence

12: It’s very important to him to helppeople around him. He

4. Benevolence Benevolent to others,make others feel good,altruistic, dosomething good forthe children/partner;

Responsibility for futuregenerations, evolution,social justice, avoidinequality

wants to care for their well-being.27: It is important to him to respond to

the needs of others. He tries tosupport those he knows.

5. Responsibilityfor nature

Responsibility for natureand environment,treating animalsdecently, unity withnature, protecting theenvironment

Universalism19: He strongly believes that people

should care for nature. Looking afterthe environment is important to him.

40: It is important to him to adapt tonature and to fit into it. He believesthat people should not changenature.

6. Excitement Excitement, an excitinglife, an eventful life, avaried life

Stimulation6: He thinks it is important to do lots of

different things in life. He always

looks for new things to try.15: He likes to take risks. He is always

looking for adventures.

7. Independenceand achievement

Independence, freedom,self-reliance,individuality, in control

Self-confidence,self-respect,self-efficacy

Achievement, wisdom,learning things,

ambition

Self-direction11: It is important to him to make his

own decisions about what he does.He likes to be free to plan and tochoose his activities forhimself.

34: It is important to him to beindependent. He likes to rely on

himself.(Continued )


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Table 1 (Continued).

Value codesValues items elicited

through MEC Corresponding PVQ domains and

items

Achievement13: Being successful is important to

him. He likes to impress otherpeople.

24: He thinks it is important to beambitious. He wants to show howcapable he is.

8. Hedonism Hedonism, food assensory experience

Hedonism26: Enjoying life’s pleasures is

important to him. He likes to ‘spoil’himself.

9. Security Security, feeling of

safety, certainty

Security

5: It is important to him to live insecure surroundings. He avoidsanything that might endanger hissafety.

10. Socialtogetherness

Social togetherness, notlonely, a good sociallife, familytogetherness

Benevolence18: It is important to him to be loyal to

his friends. He wants to devotehimself to people close to him.

11. Socialisation ofchildren

Socialisation of children,transfer good valuesto children

a

Numbers indicate the order of appearance in the original 40-item Schwartz’s PVQ.

purchasing behaviour (two items). Section 5 concerned the sociodemographic profileof the respondents (nine items). The fact that the belief and the value itemshave been measured with reversed scales does not cause problems due to thefact that only the PVQ value items will be used for analytical purposes (seebelow).

Analysis and results

Descriptive results

Almost two-thirds of the pan-European sample constituted organic food buyersof a certain type: 30.9% was regular purchasers, buying organic products on amonthly (18.6%) or weekly (12.3%) basis, with an additional 34.5% being occasionalpurchasers, buying organic foods a few times a year (28.4%) or ‘always whenpossible’ (6.1%).

The three perceived knowledge variables showed high reliability (Cronbach’sα ranging from .73 for Spain to .85 for Germany). The average self-perceivedknowledge score of the sample was 3.8 on the 1–7 scale. The large standard deviation(SD = 1.86) indicated that the sample included a great variety of consumers in termsof their self-perceived knowledge of organic foods.


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T a b l e

2

S o c i o d e m o g r a p h i c p r o fi l e o f t h e s a m p l e , % ,

N =

8 1 7 1 .

C o u n t r y p a r t i c i p a t i o n

I t a

l y ( I T )

D e n m a r k

( D K )

U n i t e d K i n g d o m

( U K )

F

i n l a n d

( F I N )

G r e e c e

( G R )

S p a i n ( E S P )

G e r m a n y

( G E )

S w e d e n

( S W E )

1 2

. 3

1 3 . 5

1 1 . 8

1

2 . 8

1 1 . 6

1 1 . 7

1 2 . 2

1 4 . 3

G e n d e r

M a l e

F e m a l e

N / A

3 2

. 0

6 7 . 3

. 7

A g e < 3 0

3 1 – 4 0

4 1 – 5 0

5

1 – 6 0

> 6 1

N / A

1 9

. 4

2 1 . 6

2 1 . 2

1

8 . 1

1 9 . 1

. 6

H o u s e h o l d s i z e

1

2

3

4

> 4

N / A

1 6

. 8

3 3 . 8

1 8 . 5

2

0 . 1

8 . 3

2 . 5

N u m b

e r o f c h i l d r e n u n d e r t h e a g e o f 5

0

1

2

3

> 3

N / A

6 6

. 0

9 . 9

2 . 8

. 2

. 0

2 1 . 1

N u m b

e r o f c h i l d r e n a g e d 6 – 1 2 y e a r s

0

1

2

3

> 3

N / A

6 2

. 6

1 1 . 7

4 . 8

. 4

. 1

2 0 . 5

N u m b

e r o f c h i l d r e n a g e d 1 3 – 1 8 y e a r s

0

1

2

3

> 3

N / A

6 2

. 7

1 2 . 3

4 . 1

. 5

. 0

2 0 . 3

( C o n t i n u e d )


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T a b l e

2

( C o n t i n u e d ) .

P l a c e

o f r e s i d e n c e ( × 1 0 0 0 i n h a b i t a n t s )

< 1 0

1 0 – 4 9

5 0 – 9 9

1

0 0 – 2 4 9

2 5 0 – 4 9 9

> 5 0 0

2 0

. 9

2 3 . 3

1 3 . 1

1

2 . 8

7 . 2

2 1 . 7

E d u c a

t i o n a l l e v e l

N o

f o r m a l o r l e s s

t h a

n p r i m a r y e d u c .

P r i m a r y

e d u c a t i o n

c o m p l e

t e d

S e c o n d a r y

e d u c a t i o n ( h i g h

s c h o o l o r

t e c h n i c a l

e d u c a t i o n )

T

e r t i a r y

e d u c a t i o n

( u n i v e r s i t y )

P o s t g r a d u a t e

d e g r e e

N / A

7 . 4

1 6 . 0

4 9 . 2

2

3 . 4

3 . 4

. 6

M o n t h l y h o u s e h o l d i n c o m e ( c a t e g o r i e s

l o w - h i g h ) a

1 :

v e r y l o w

2 : l o w

3 : l o w – a v e r a g e

4

: a v e r a g e

5 : h i g h –

a v e r a g e

6 : h i g h

7 : v e r y h i g h

N o a n s w e r :

1 2

. 1

2 3 . 1

2 5 . 5

2

0 . 9

1 0 . 8

1 . 2

. 8

5 . 6

a I n c o m

e c a t e g o r i e s a r e a d a p t e d i n e a c h c o u n t r y t o r e p r e s e n t e x i s t i n g i n c o m

e i n c r e m e n t s .


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The nine organics-related belief variables showed satisfactory reliability for mostof the countries (Cronbach α ranging from .54 for Finland to .75 for Spain).The highest mean likelihood appeared for the high price of organic foods (6.1),followed by their environmental friendliness (5.5), healthiness (5.4), naturalness(5.2), chemical-freeness (5.0), and tastiness (4.9). Then, the likelihood of negative

beliefs followed, such as: organics do not keep fresh so long (4.6), are notreally organic (4), and are less appealing (3.9). Overall, the beliefs about thepositive characteristics of organic foods were stronger than those about negativecharacteristics (mean scores 5.2 and 4.6 respectively, p


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Table 3 Descriptive statistics and reliabilities of the 16-item value inventory, N = 8171.

Var.no Value item Mean/SDaItem/totalcorrelation

Schwartz Values (16 items)

A. Benevolence5 It’s very important to him to help the people around

him. He wants to care for their well-being.2.1/.99 .60

8 It is important to him to be loyal to his friends. Hewants to devote himself to people close to him.

2/.98 .59

12 It is important to him to respond to the needs ofothers. He tries to support those he knows.

2.2/.96 .63

Mean and SD benevolence 2.1/.97

Cronbach’s α .77

B. Universalism

9 He strongly believes that people should care fornature. Looking after the environment isimportant to him.

2.1/1.07 .62

16 It is important to him to adapt to nature and to fitinto it. He believes that people should not changenature.

2.3/1.13 .60

Mean and SD universalism 2.1/1.08

Cronbach α .71

C. Self-direction

4 It is important to him to make his own decisionsabout what he does. He likes to be free to plan

and to choose his activities for himself.

2.1/1.08 .56

14 It is important to him to be independent. He likes torely on himself.

2.2/1.13 .56

Mean and SD self-direction 2.2/1.10

Cronbach α .72

D. Stimulation

2 He thinks it is important to do lots of different thingsin life. He always looks for new things to try.

2.8/1.28 .51

7 He likes to take risks. He is always looking foradventures.

3 9/1.43 .51

Mean and SD stimulation 3.3/1.35

Cronbach α .67

E. Hedonism

3 He seeks every chance he can to have fun. It isimportant to him to do things that give himpleasure.

2.7/1.26 .61

13 Enjoying life’s pleasures is important to him. Helikes to ‘spoil’ himself.

2.9/1.35 .64

15 He really wants to enjoy life. Having a good time isvery important to him.

2.6/1.28 .69

Mean and SD hedonism 2.7 /1.29

Cronbach α .80(Continued )


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Table 3 (Continued).

Var.no Value item Mean/SDaItem/totalcorrelation

F. Achievement

6 Being successful is important to him. He likes toimpress other people.

3.3/1.44 .59

10 He thinks it is important to be ambitious. He wantsto show how capable he is.

3.3/1.40 .59

Mean and SD achievement 3.3/1.41

Cronbach α .74

G. Security

1 It is important to him to live in secure surroundings.He avoids anything that might endanger hissafety.

2.3/1.20 .37

13 He tries hard to avoid getting sick. Staying healthy is

very important to him.

2.1/1.11 .37

Mean and SD security 2.2/1.15

Cronbach α .54

All-item Cronbach α .86a1 = ‘very much like me’; 2 = ‘like me’; 3 = ‘somewhat like me’; 4 = ‘a little like me’; 5 = ‘not like me’;

6 = ‘not like me at all’.

p < .001; Satorra–Bentler scaled χ 2 [83] = 2706.84, p < .001, CFI = .97, TLI-NNFI = .96, RMSEA = .062). The standardised factor loadings also assessedconvergent validity, ranging from .69 to .82 (Kline, 2005). The estimated correlationswere under .85, also satisfying discriminant validity (Kline, 2005). The mostsubstantial correlations appeared in the benevolence, universalism, and securityvalues and in the stimulation, hedonism, and achievement values, whereas self-direction presented a moderate correlation with security (Table 4).

The presence of both substantial correlations (Fabrigar, Wegener, MacCallum, &Strahan, 1999) and discriminant validity between the factors suggested that higher-order factors might exist (Bagozzi, Lee, & van Loo, 2001). Subsequently, a second-order model of the 16 PVQ items was specified as follows: universalism (var. 10,17), benevolence (var. 6, 9 and 13), and security (var. 2 and 14) as indicatorsof a ‘collectivistic’ second-order value factor 1; and hedonism (var. 4, 12, 16),

Table 4 Correlations among first-order factors, N = 8171.

First-order factors

Benev. Univer. Secur. Stim. Hedon. Self-dir. Achiev.

Benev. 1

Univer. .61 1

Secur. .66 .72 1

Stim. .28 .29 .21 1

Hedon. .40 .29 .46 .75 1

Self-dir. .46 .45 .54 .53 .60 1

Achiev. .22 .20 .31 .77 .59 .44 1


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Table 5 Correlations among first- and second-order factors, N = 8171.

First-order factorsSecond-order

factors

Benev. Univer. Secur. Stim. Hedon. Self-d. Achiev. Fact. 1 Fact. 2

Benev. 1Univer. .61 1

Secur. .68 .70 1

Stim. .36 .37 .41 1

Hedon. .34 .35 .39 .76 1

Self-dir. .27 .28 .32 .62 .58 1

Achiev. .29 .30 .34 .66 .62 .50 1

Fact. 1 .77 .79 .88 .47 .44 .36 .38 1

Fact. 2 .40 .41 .46 .90 .85 .69 .73 .52 1

achievement (var. 7, 11), stimulation (var. 8, 3), and self-direction (var. 5 and 15) asindicators of an ‘individualistic’ second-order value factor 2. The second-order CFAagain showed good statistical properties even after rejection of the independencemodel (normal theory χ 2 [83] = 4881.51, p < .001; Satorra–Bentler scaled χ 2

[83] = 3830.91; p


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Figure 2 Confirmatory factor analysis model of the 16-item value inventory(standardised solution).

Ben_1

Ben_2

Ben_3

Uni_2

Uni_3

Sec_1

Sti_1

Sti_2

Hed_1

Hed_2

Hed_3

Self_1

Self_2

Ach_1

Ach_2

0.77

0.77

0.76

0.74

0.79

0.74

0.75

0.70

0.73

Stimu

Hedo

Self 0.73

0.69

0.85

0.90

Fact2

Fact1

0.88

0.79

0.77

1.00

1.00

0.52

Achive

Chi–Square=4884.51, df=96, p–value=0.00000, RMSEA=0.069

Sec

Uni

Bene

0.67

0.55

0.81

0.78

0.760.700.73

0.41

0.40

0.43

0.46

0.38

0.45

0.44

0.51

0.47

0.55

0.70

0.34

0.39

0.43

0.51

0.47

Sec_2

second-order factor correlation vectors were located in the direction predicted inthe outcome of the second-order CFA model (Figures 3 and 4). Chi-square andDuncan and Scheffe post-hoc ANOVA tests established the statistically significantdifferences ( p < .05) across the five clusters. In order to develop the profiles of

each cluster, a cross-tabulation between the cluster membership variable and thestatistically significant variables was made (Table 6).The sample’s mean similarity with the individualistic value factor lay at the

‘somewhat like me’ increment (3.0 in the 1–7 scale), while mean similarity with thecollectivistic value factor was stronger, at the ‘like me’ increment (2.4). The samepattern of closer similarity with the collectivistic factor emerged across clusters 1, 2,3, and 4 that together represent 90% of the sample. Clusters 1 (20.6% of the sample)and 3 (32.0% of the sample) showed the strongest similarity with collectivistic values,followed by cluster 2 (28.8% of the sample). Clusters 1 and 2 also showed thestrongest similarity with individualistic values. The remaining two smaller clusters

4 (8.4% of the sample) and 5 (10.1% of the sample) showed weaker similarity thanthe other clusters as regards both collectivistic – mainly – and individualistic values(together with cluster 3).


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Figure 3 Discriminant analysis: all-group scatter plot.

Canonical Discriminant Functions

5,0

2,5

0,0

F u n c t i o n

2

–2,5

–5,0

–10 –5 0

Function 1

5 10 15

Cluster Numberof case

12345Group Centroid

Figure 4 Graphical representation of the correlations between the discriminantfunctions with the second-order factorial dimensions as vectors.

Self-trascendence

UniversalismSelf-direction

Fact2

Opennessto change

Stimulation

Hedonism

Achievement

Self-enhancement

Security

Fact1

Benevolence

Concervation

At the individual cluster level, chi-square tests revealed the following profiles.Cluster 1 included the largest percentage of regular organic buyers on both amonthly and weekly basis, and the lowest percentage of non-buyers. Its memberswere consumers mainly from Scandinavia and Italy. Cluster 2 included the largestpercentage of occasional organic buyers, the second largest percentage of regularorganic buyers, and the lowest percentage of non-buyers, together with cluster 1.

Its members come from ‘mature’ organic markets such as Scandinavia and Germany.Cluster 3 included the lowest percentage of regular buyers of both types but thelargest percentage of people who buy ‘always when possible’ and of non-buyers


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Table 6 Cluster profiles, statistically significant differences, %, N = 8171.

Variable description Sig.

Cluster1:

20.6%

Cluster2:

28.8%

Cluster3:

32.0%

Cluster4:

8.4%

Cluster5:

10.1%

Clustering factorsa

Factor 1: Collectivistic ∗ 1.43 2.23 1.96 3.40 3.23

Factor 2: Individualistic ∗ 1.87 2.43 3.56 4.24 3.02

Mean factor score/cluster ∗ 1.65 2.33 2.76 3.82 3.13

Organic food shopping behaviour ∗∗

Never bought nor considered buying 15.8 16.3 17.9 19.1 20.2

Not yet bought but have considered it 15.0 13.8 17.2 15.0 15.1

Have bought but will not anymore 1.9 2.6 1.9 2.2 2.2

Total non-buyers 32.7 32.7 37.0 36.3 37.5

Buy few times a year 27.5 30.3 28.0 28.5 25.9

Buy always when possible 5.7 5.8 7.0 4.6 5.7

Total occasional buyers 33.2 36.1 35.0 33.1 31.6

Buy once or a couple of times a month 20.4 19.1 16.8 17.4 19.7

Buy weekly 13.7 12.1 11.1 13.2 11.1

Total regular buyers 34.0 31.2 27.9 30.6 30.8

Intensity of beliefs held about organicsb

Organics are free from chemicals ∗ 4.99 4.90 5.03 5.03 4.84

Organics taste better ∗ 4.88 4.87 5.07 4.98 4.91

Organics are healthier ∗ 5.40 5.36 5.55 5.38 5.40

Organics are not really organic ∗ 3.93 3.99 4.08 3.94 4.10

Socio-demographic variablesGender: Female ∗∗ 65.7 67.0 70.2 69.2 66.3

Education: Secondary school ∗∗ 50.3 48.4 48.4 45.6 49.4

Education: Tertiary and post-graduate 28.2 27.9 25.8 28.2 26.9

Children 6–12 years old in thehousehold:

∗∗

0 81.5 78.5 76.9 78.0 82.1

1 12.2 14.9 16.3 13.8 13.7

2 5.5 6.3 6.1 7.9 3.7

>2 .8 .4 .7 .3 .4

Country: ∗∗

IT 14.1 11.1 12.4 9.7 10.1

DK 16.7 12.9 12.5 12.0 11.1

UK 12.9 9.5 12.0 15.4 12.5

FN 12.4 11.8 13.4 14.7 13.4

GR 7.2 10.5 15.1 15.5 14.0

SP 7.7 10.3 15.1 14.0 12.3

GE 12.4 14.7 9.9 9.4 11.9

SE 16.5 19.2 9.5 9.3 14.6a1 = ‘very much like me’; 2 = ‘like me’; 3 = ‘somewhat like me’; 4 = ‘a little like me’; 5 = ‘not like me’;

6 = ‘not like me at all’.b1 = ‘extremely unlikely’; 2 = ‘unlikely’; 3 = ‘rather unlikely’; 4 = ‘neither unlikely nor likely’; 5 =

‘rather likely’; 6 = ‘likely’; 7 = ‘extremely likely’.∗D ncan and Scheffe post hoc paired ANOVA tests p 05 ∗∗Chi sq are tests p 05


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who have considered buying organics. Its members come mainly from South Europe(i.e. Spain and Greece), as well as Finland. Cluster 4 included the second highestpercentage of participants who had neither bought nor considered buying organicfood, but also the second highest percentages of occasional ‘few times a year’ andof regular ‘weekly’ buyers. Finally, cluster 5 included the highest percentage of non-

buyers, the lowest percentage of occasional buyers, but the second highest percentageof ‘monthly’ buyers.

Discussion and conclusion

Using nationally representative samples of more than 1000 consumers from eightEU countries, the present survey tested a PVQ-based inventory of values developedto fit consumer behaviour towards differentiated products (i.e. organic food).The purpose of the survey was to advance theory by contextualising existing

instruments. Its theoretical contribution lies in its explicit effort to exhibit theusefulness of tailoring, as well as the adaptation capability of existing taxonomies,such as the PVQ, for understanding consumer behaviour in differentiated productcontexts.

The 16-item PVQ-based inventory that included organic food-relevant consumervalues exhibited good statistical performance. Cronbach’s alpha levels per valuedomain did not show significant differences from the relevant reliabilities of the original PVQ dimensions (Schwartz et al., 2001), being either slightlylower (security, stimulation, and hedonism) or slightly higher (benevolence, self-direction, universalism, and achievement). However, the classification of consumers’value similarity was somewhat different: benevolence was less important, whileuniversalism and security were more important. The second-order factorial designof the 16 PVQ values (collectivistic and individualistic factors) also showed goodstatistical properties in terms of acceptable goodness-of-fit indices and validity.

Benevolence and universalism were found to form a joint factor reflecting the self-transcendence dimension of the Values Theory, which is also shown in certain casesin the literature. For instance, Schwartz (2004a, 2004b) reports that benevolenceand universalism formed a joint area in one-third of 14 samples of adults, universitystudents, and adolescents from Chile, Germany, Indonesia, Italy, Peru, Poland,and Ukraine. Moreover, the high correlation of security with both benevolenceand universalism (.68 and .70 respectively – see Table 5), together with the high

standardised factor loading (.88) of security in the collectivistic second-order factor,made benevolence, universalism, and conservation merge. This indicates that asregards differentiated products, where tradition and conformity values do not play arole, people’s quest for security is embodied in their wider collectivistic value system.

On the other hand, the individualistic second-order factor incorporated theopenness-to-change dimension as well as the largest part of the self-enhancementdimension. The high correlation between stimulation and hedonism (.76 – seeTable 5), as well as the high standardised factor loadings of stimulation and hedonismwith the individualistic factor (.90 and .85 respectively), are clearly the reasons forthis finding. In other words, for differentiated products where power values do not

play a role, people’s need for stimulation and hedonism almost merge, resulting inopenness-to-change and self-direction forming a joint motivational area relevant tothe individual.


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Customisation of PVQ inventories

A key question then is whether it is conceptually meaningful to develop differentPVQ-based inventories of values by means of confirmatory factor analysis when acertain type of differentiated products is involved. The development of the 16-itemPVQ inventory’s factorial construct of values that pertain to the specific differentiatedproducts under study is our major contribution in this respect and gives a positiveanswer to the above question. CFA was suggested as an analytical technique in manyPVQ applications (see Perrinjaquet, Furrer, Usunier, Cestre, & Vallette-Florence,2007, for a recent example). Moreover, Schwartz in his work adopts CFA toevaluate the structure of values and to confirm the 10-domain value structure of theValues Theory (Schwartz & Boehnke, 2004). The reason why confirmatory factoranalyses are necessary when dealing with PVQ is clearly explained by Schwartz, whoessentially tested the circumplex structure theory using CFA.

A relevant issue lies in the potential existence of high-order factors in the PVQtaxonomy: ‘ . . . Schwartz treats the high-order types merely as a way to describe

the value structure more simply’ (Schwartz & Boehnke, 2004, p. 237). Additionally:‘ . . . Higher-order types can be formed, and alternative combinations of adjacentvalues into higher-order types are as legitimate as the previously designated higher-order types’ (Schwartz & Boehnke, 2004, p. 251). This latter statement impliesthat a researcher can meaningfully hypothesise that high-order dimensions exist inthe PVQ taxonomy. The researcher can also examine the existence of other high-order dimensions that do not strictly belong to the initially postulated taxonomy.Consequently, different kinds of dimensions can be hypothesised and tested intailoring the taxonomy to specific contexts. For instance, using simple principalcomponent analysis and the full 56-item SVS, Kihlberg and Risvik (2007) concluded

that there are two higher-order value constructs named ‘individual’ and ‘collective’,incorporating almost the same elements of the Values Theory as in the presentstudy. Moreover, Kihlberg and Risvik (2007) found that the values that explainorganic product consumption are related to the predominance of individual andcollective values over other types of values – such as those excluded from the presentsurvey. Their findings validate the use of short value typologies to examine consumerbehaviour towards differentiated products, as in our case.

In the present work, the pattern of the correlations at the first-order level hadsatisfactory discriminant validity, and the subsequent substantial correlations gavegrounds for hypothesising the existence of higher-order factors. This latter point isin line with Schwartz and Boehnke (2004): ‘. . . The continuum idea implies thatthe array of value items can be partitioned into as many or as few categories as isoptimal for a researcher’s purposes’ (p. 251). In sum, the support for a motivationalcontinuum of values gives researchers the freedom and flexibility to choose higher-order combinations of adjacent values particularly suited to the topics they study.

Explanatory power of customised PVQ inventories

An additional question that remains to be answered is whether the different PVQ-based value inventories developed to fit specific differentiated product contexts have

any real ability to explain consumer behaviour. Taking organic foods as a case, thetrend of stronger endorsement of the collectivistic values (benevolence, universalism,and security) emerges for clusters 1 to 4, which together represent 90% of the sample.


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which together represent more than 80% of the sample. The successive decrease inmean similarity with both factors when moving from cluster 1 to cluster 5 leads tothe following conclusions.

(a) Agreement with individualistic and collectivistic values usually decreases

progressively and jointly for both value factors, a trend that leads to theidentification of distinctive consumer segments. Consequently, in the widerEuropean population, consumers can belong to various segments holdingcollectivistic and individualistic values very strongly (i.e. ‘very much like me’,cluster 1), strongly (‘like me’, clusters 2 and 3), moderately (‘somewhat like me’,cluster 5), and weakly (‘a little like me’, cluster 4), with corresponding organicfood purchasing behaviours.

(b) Clusters with higher percentages of regular organic buyers (clusters 1 and 2) oroccasional organic buyers (clusters 2 and 3) hold collectivistic values morestrongly. On the other hand, clusters with higher percentages of non-buyers

(clusters 4 and 5) hold both collectivistic and individualistic values less strongly.(c) However, the importance assigned to individualistic values also plays a role in

organic food purchasing: as shown in the regular organic buyer clusters 1 and2, the individualistic values complement the collectivistic values as motivatorsof organic purchasing. In this respect, organic food purchasing is the combinedoutcome of mainly universalism, benevolence, stimulation, and hedonism.

From a practitioner’s point of view, the present findings offer substantial marketinginsights in relation to the usefulness of personal values for monitoring consumermarkets for differentiated products, highlighting the predictive ability of simple andflexible marketing data collection tools, such as the PVQ, and providing evidence forthe marketing value derived from value-based consumer segmentation. For instance,the Values Theory can successfully explain consumer behaviour in an organic foodpurchasing context for 81.5% of the European sample (i.e. clusters 1, 2, and 3 holdcollectivistic values more strongly than the average sample member).

However, it is worth noting that not one value cluster contains regular organicpurchasers as the majority of its members, while the difference between the highest(clusters 1 and 2) and the lowest (cluster 5) percentage of organic buyers is only4.8%. Additionally, perceived knowledge and belief likelihood levels do not differessentially across clusters (Duncan and Scheffe post-hoc ANOVA tests, p < .05 –

see Table 6). Moreover, the weak similarity with both the collectivistic and theindividualistic values can hardly explain the substantial percentages of regular organicbuyers in cluster 5 and – especially – in cluster 4 (18.5% of the sample). Finally,strong similarity with collectivistic values appears in cluster 3, despite the fact that thiscluster includes the lowest percentage of regular buyers and an average percentage of yearly buyers.

Despite the fact that values are able to guide behaviour, their inability to explainbehaviour directly was also described in past research. For instance, Brunsø et al.(2004) supported the view that some kind of attitudinal construct should be invokedas a mediator between values and behaviour proposing the FRL. In the context of

consumer behaviour towards differentiated products, however, it might be possible toidentify other causes of the irregularities between organic food purchasing frequencyand segments’ value profile, as described above. For instance, it is possible that the


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more ‘random’, thus also being more difficult to predict within the Values Theoryframe. Regarding cluster 3, the organic market conditions of limited availabilitythat prevail in Greece and Spain (41.2% of the Spanish and 40.3% of the Greeksbelong to that cluster) may to a certain extent explain the contradiction describedabove. Moreover, cluster 3 represents a group of European consumers with a great

potential to become organic buyers, as indicated by the highest percentage of peoplein all the clusters that have considered buying organic produce. It is thus possiblethat restricting market conditions in relation to the differentiated products underconsideration can lead to consumer behaviour for which the Values Theory haslimited explanatory power.

In summary, this paper carries the following message: when some of its valuedomains are empirically missing (i.e. when they are not practically important forpurchasing behaviour towards specific product categories or types), the adaptationcapacity of the Values Theory is high. Conceptualisation of the PVQ in order to reflecta real context situation makes the value domains that are relevant to the context

merge into new hierarchical dimensions in absolute respect of the underlying originaltheory. This conclusion points towards robustness of the taxonomy in being able toadapt itself to different human behaviour contexts (i.e. purchasing behaviour).

The results of the present research pertain to organic foods; in this respect,they might not safeguard the drawing of global conclusions. Further researchshould exploit the ability of tailor-made PVQ-based inventories to explain consumerbehaviour towards other differentiated products. Recent evidence (e.g. Brunsø et al.,2004; Dreezens et al., 2005; Kihlberg & Risvik, 2007; Krystallis et al., 2008;Magnusson et al., 2003; Worsley & Lea, 2008) suggests that this is possible, althoughthis body of research all pertains to the food sector. Finally, further research shouldconsider applicability of this approach in cases of limited consumer knowledge aboutthe product, low consumer involvement and loyalty, or restricted market conditions(e.g. fragmented distribution channels and low availability) that might mitigate thebehaviour-related explanatory power of the PVQ.

Acknowledgements

The research reported here was funded by the European Commission and based on resultsfrom the FP5 Integrated Project QLRT-2002–02446: ‘Consumer Decision-making on OrganicProducts, CONDOR’.

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About the authors

Athanasios Krystallis is Professor of marketing at the Department of Business Administration,School of Business and Social Sciences, Aarhus University, and co-responsible for consumerresearch at the MAPP Centre. He holds an MSc degree in food marketing and a PhD inconsumer behaviour (both from the University of Newcastle upon Tyne, UK). His scientificinterests focus on food consumer behaviour with emphasis on perceived extrinsic sustainabilityattributes and marketing strategy.

Correspondingauthor: Athanasios Krystallis, Aarhus School of Business and Social Sciences

(ASBSS), Aarhus University, Haslegaardsvej 10, DK-8210, Aarhus V, Denmark.T +45 8948 6374E [email protected]

Marco Vassallo is a newly appointed associate statistical researcher at the National ResearchInstitute on Food and Nutrition in Rome, Italy. He holds an MSc Degree in Statistics andEconomics (from the University ‘La Sapienza’ of Rome, Italy) and is currently a second-yearPhD candidate in Agri-Food Economics and Statistics at the University ‘Alma Mater Studiorum’of Bologna. His main research area is focused on food consumer behaviour with emphasis onthe application of socio-cognition models, and other factorial frameworks issued from thehealth and cognitive psychology, to cross-national consumer’s choices.

E [email protected]

George Chryssochoidis is senior lecturer in marketing at Norwich Business School, Universityof East Anglia, UK. His current research is on consumer-led new product innovation andthe use of information on new products. He is a member of the work group that definesthe strategic research agenda for the European Technology Platform F4F, has been an ITC(World Trade Organisation/UNCTAD) Expert in Marketing, has published more than 40 peerreviewed articles, and has been principal investigator in more than 20 research funded projectsfrom national, EU, and UKERC sources.

E [email protected]

mailto:[email protected]:[email protected]:[email protected]:[email protected]


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