consumer acceptance of genetically modified food in spain

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Consumer Acceptance of Genetically Modified Food (GM) in Spain: A Structural EquationApproachAuthor(s): Montserrat Costa-Font and Jos Maria GilSource: Risk Management, Vol. 10, No. 3, Risk, Attitudes and Behaviour (Jul., 2008), pp. 194-204Published by: Palgrave Macmillan Journals

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Article

CONSUMER ACCEPTANCE OFGENETICALLY MODIFIED FOOD(GM) IN SPAIN: A STRUCTURALEQUATION APPROACH

Montserrat Costa-Font and Jos? Maria GilThe Centre for Research inAgro-Food Economics and Development(CREDA-UPC4RTA), Barcelona, Spain

Correspondence: Montserrat Costa-Font, Edifici ESAB, Parc Mediterrani de laTecnolog?a,Avinguda del Canal Olimpic s/n, 08860-Castelldefels, Barcelona.E-mail: [email protected]

AbstractRecent studies suggest that purchase intentions of genetically modified (GM) andother related food products are determined by individual attitudes towards the product. Simultaneously, these attitudes are formed by the perception of risks and benefitsassociated with the product. They are also determined by whether consumers trust theinformation sources. To investigate these issues, in this paper we use structural equation models and representative data from the Eurobarometer 2002 to examine theseissues further. We hypothesize and test that both science interest and governmentconfidence are key predictors for GMF risk and benefit perception. Our results supportthe so-called theory of reasoned action . That is we find unambiguous evidence sup

porting a structural association between behaviour, attitudes and purchase intentionstowards GM food. Evidence suggests that peoples trust in science and governmentinformation source is potentially the key issue that determines further acceptance.Therefore, by shifting trust in science and information conveyed by public authorities,it is possible to make GMF products acceptable to consumers.

Keywordsconsumer intentions; GM food perception; trust; causal modelsRisk Management (2008) 10, 194-204.doi:10.1057/rm.2008.3

Risk Management 2008, 10, (194-204) ? 2008 Palgrave Macmillan Ltd 1460-3799/08 $30.00www.palgrave-journals.com/rm

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IntroductionAcceptance of new science developments such as biotechnology applications is a matter of significant interest worldwide, and has a huge

impact on the extent of technology diffusion in key areas such asfood production. Indeed, the inception of genetic modification (GM) techniques in food production is envisaged as an opportunity to improve foodproduction technologies and/or product differentiation in the food chainand ultimately fulfill a consumer's preference for diversity. Interestingly,farmers and manufacturers perceive potential benefits from efficiency improvements despite some associated cost due to the reimbursement of intellectualproperty rights. Parallel

to this is thepublic controversy

that has arisenas a result of the uncertainties and perceived risks - both to health andthe environment that the technology is communicated to portray. Consumersperceive GM food as potentially threatening the sustainability of traditionalfood markets we have known for years. As a result, consumers mightdread the expansion of GM food in supermarkets, and ultimately are saidto even refuse to consume at the extreme any product made out of thistechnology.In the light of this evidence, a careful understanding of a consumer's reactions towards GM food is a key issue to subsequently lead to the introductionof GM food into the market. This is especially the case in Spain where traditional values contrast that of the progressive introduction of modern technology. Besides, Spain is the country within the European Union with the largestland devoted to GM food harvesting. In the past few years Spain has increasedthe land devoted to GM food production by approximately 75,000 hectare(MAPA, 2007). Hence, Spanish evidence is especially relevant from a stand

point of attitude formation due to the complex mix of several different factors.Therefore, this paper takes advantage of this feature and examines a Spanishconsumer's attitudes regarding GM products.

Objective of the studyWe aim at explaining the behavioural process and mechanisms that gives riseto consumer acceptance of GM food along with new food-related productswith intensive technology innovation. We argue that public attitudes towardsGM food are formed as a result of a reasoning mechanism that departs fromtrust in science and in public authorities and ultimately affects a consumer'sfinal purchase decision. In light of the existing methods, we have selected astructural equation model approach - namely causal models - as those thatconvey the higher relevance so as to provide insights on the consumers'decision-making process in this setting.

Consumer Acceptance of Genetically Modified Food (GM) in Spain




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Conceptual model and hypothesis of analysisThe conceptual model presented

in this study (see Figure 1) attemptsat

describing the reasoning process that we believe is behind GM foodacceptance. The formulation of the model follows from the evidence ofprevious literature. Briefly, we isolate and define the influential elements inGMfood consumers' decision-making process to provide a baseline idea to betterunderstand the process of attitude formation.

Our underlying conceptual framework is directly related to the Theory ofPlanned Behaviour, which briefly states that a person's intention to perform(or not), a behaviour is the most important immediate determinant of anaction (Ajzen, 2005; p 117). The advantage of this theory links individuals'

attitudes-

acceptance or rejection of a product-

with the associated valuationof the product by means of behavioural intentions.Our model sets out a number of causal relations defined by the followinghypothesis:

Hj : Consumer science interest increases GMfood positive perceptions.Previous evidence from the Fishbein's Multiattribute Model (Fishbein, 1963)revealed that subjective knowledge influences individual perception of riskand benefits of GMF (House et al., 2004; Lusk et al., 2004). Indeed, people'sinterest in science is an important element in shaping subjective knowledge .

Therefore, it can be hypothesized that consumer interest in science enhances apositive influence on individual GM food positive perception.

H^ Trust of governments defines consumer perceptions of GM food.Trust is broadly acknowledged as acting as a filter of information by manyempirical studies (which one?), and ultimately is conceptualized as determining the access to people's information sources, and as a result people's perception (Siegrist et al., 2000). In particular, government confidence

- truston government - is envisaged as determining consumer perceptions - bothpositive and negative - of GM food (Traill et al., 2004). Therefore, we expectthese two latent variables to be causally related.

Figure 1 Consumer theoretical process of acceptance

Montserrat Costa-Font and Jos? Maria Gil




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H3: Consumer perceptions determine consumer attitudes.

A consumer's perceptions of risk and benefit of a GM product are the result ofan individual's evaluations of product attributes (Fishbein, 1963). Yet, an individual's weighting of these perceptions gives rise to a definition of an individual's attitudes to GM products. This empirical association has been tested instudies by Frewer et al. (1998) and Hossain et al. (2002).

H4: The decision topurchase results from the expression of attitudes towards GMfood.

An attitude towards a product, such as its acceptance or rejection, is the chiefaspect that individuals evaluate in their purchasing decision. Moreover, thisattitude, which was formed, previously can be modified due to certaininformation received at the time of purchase as well as the one conveyed bythe product label.

Research methodologyThe sampleData from the Eurobarometer survey 58.0 have been used, which collect representative data from different European countries. We have empirically examined the information for the Spanish subsample. From the 1,000 respondents,half of the sample was eliminated by list-wise deletion due to incompletesurveys. Therefore, finally 502 responses were useful for the analysis.The Spanish sample ismade up of 49% male respondents and 51% womenrespondents. Moreover, the age distribution is as follows: 23% of respondentsare 15-30 years of age, 33% 26-44, 27% 45-64 and finally 17% of individuals are older than 65 years. 37.5 % of respondents live in a rural area, 37.5%in a small or middle-sized town and finally 25% live in a large city.

MeasuresA 3-point Likert scale was used to measure the model constructs. The scale ofresponses goes from disagree to agree with a central point, don't know .This response stratification is based on a previous distribution of Europeansociety (see Gaskell et ai, 2003; Gaskell, 2006). Following Gaskell ?tal. (2003)and Gaskell (2006), we divided them into three groups: GM food disagrees ,undecided or indifferent and GM food agrees .

Analytical proceduresThis study employs structural equation modelling to contrast the relationsdefined in the proposed model. A two-step modelling was performed, which





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implies a first step defining a confirmatory factor analysis (CFA) and anext step defining a structural regression model (SR). To do so we employedLISREL 8.5. This study uses ordinal data, arguably a rudimentary measurement of continuous variables, where the scale is considered as thresholdsof the continuous variables (J?reskog and S?rbom, 1996). Correlationsamong ordinal variables are called polychoric and polyserial correlations,which are theoretical correlations of the continuous (J?reskog and S?rbom,1996). In order to perform the analysis, we have used the general weightedleast-squares (WLS) method instead of maximum likelihood (ML) becauseboth the data present a nonnormal distribution and because ML does notallow us to employ the weight matrix required for the analysis, which isthe inverse of the estimated asymptotic covariance matrix W of the polychoricand polyserial correlations (Kline, 2005). Given that in our case the observedvariables take an ordinal format, and therefore have no units of measurement,we assume as standardized observed and latent variables (J?reskog andS?rbom, 1993).

Finally, we assessed the goodness of the model. To validate the measurementmodel, we followed Hair et al. (1999) indications. First, we restricted factor

loadings, which relate each indicator with the constructs, to be higher than0.5. Moreover, the computation of the composite reliability and the extractedvalidity for each construct was also measured, with thresholds of 0.7 and 0.5,respectively.

Regarding the structural model, its analysis begins with an assessmentof the significance of the estimated parameters in the structural equations(Hair et al., 1999). Then, the reliability coefficient of each equation and

the correlation matrix among constructs was examined (Barrio and Luque,2000). Finally, parameters such as Chi square (/2), (/2/d.f.), Root MeanSquare Error of Approximation (RMSE), Goodness of Fit Index (GFI), the

Adjusted Goodness of Fit Index (AGFI), the Comparative-Fit-Index (CFI),the Normed-Fit-Index (NFI) and the NonNormed-Fit-Index (NNFI) will alsobe considered as indicators of the model goodness-of-fit for the CFA and theSR model.

Descriptive analysisPrior to the statistical application, we have performed a descriptive analysis ofthe data. Interestingly, 65% of the Spanish sample reveals some interest inscience. Moreover, 64% understands science and technology stories and morethan 50% felt themselves well informed about the issue. Interestingly, morethan 75% of the sample state some confusion when hearing conflicting viewson science and technology. Indeed, the contrast among the two last assertionsreveals that people, although understanding science, do not necessarily upholda clear opinion about science developments. This last point reinforces the





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statements of the literature review, where some authors conclude that Spanishconsumers are not sufficiently informed about biotechnology, a kind oftechnology application (Noomene and Gil, 2004; Vilella-Vila et al., 2005).The same comes up for the question on food selection. Almost 90% of thesample were concerned about food quality and in knowing how to select foodon the basis of quality standards. Interestingly, 80% were confused when hearing new stories about what should be eaten.The following questions of the survey were more directly concerned withGM perceptions. In particular, when asking about the product utility, risk,moral acceptance and whether to encourage GM technology, respondents aredivided on three main groups as also stated in the literature review (Hossain et

al., 2003; Gaskell et al., 2004). Again, about 50% tend to agree while don'tknow option and disagreement represents around 20-30%. Therefore abouthalf of the Spanish sample considers that GM food technology is useful, ethically acceptable and must be encouraged, but is also aware of its associatedrisks.

General attitudes regarding GM food were analysed on the basis of a set ofquestions that either support or reject a derived utility or a general statementconcerning GM food. Interestingly, 40% of respondents state that GM food isuseful for them, for their economy and for the third world. However, 20%had no opinion. Indeed, ignorance is markedly important when askingabout the adequacy of GM food regulations, where 40% of respondentsdo not know what to say. As for strong assertions regarding GM food(e.g., whether it poses no threat to future generations or whether it is harmfulor safe for people's health), there is almost an equal percentage of agreement,undecision and disagreement. Therefore, we can conclude that there is still nota clear-cut formed attitude on the matter extensible to the majority of the

Spanish population.Interestingly, questions revealing higher agreement were those that referredto personal ability and interest in the selection of GM food for consumption

purposes. In fact, 50% revealed abilityand that the

judgement and selection ofGM food is important for them. Paradoxically, most respondents consider thatit is difficult for them to perform judgements on GM food. Also for these questions the undecision is about 20%.Finally the last group of questions examined refers to the purchase or

consumption intentions. As for this set of questions there is a clear patternpointing towards rejection of GM food purchase intentions, applicablefor as much as 50% of the respondents. Moreover, non-decision is onlyrevealed for less of 14% of the sample. Thus, some respondents are undecidedaccording to their perceptions and attitudes. Finally, consumers' positionappears to be tailored towards GM food scepticism. However, had GMfood grown in a more environmentally friendly way, 46% of the respondentswould buy it.





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^j? RiskManagement200ResultsMeasurement modelIn a first step of the study, confirmatory factor analysis has been performed forthe total set of constructs - Science Interest, Government Confidence, GMfood perceptions, GM food attitudes - subsequent to independent factor analysis for each construct. All the errors were assumed to be uncorrelated. The

main parameters test for the robustness of the constructs appears to showacceptable results as Table 1 shows (factor loadings, ?-values, R2, compositereliability, which must be >0.7, and extracted validity, which must be >0.5)(Hair et al., 1999). Moreover, all constructs were measured at least bytwo indicators as proposed by Kline (2005) among others. Given that inour case the observed variables were ordinal and therefore have no units of

measurement, we have assumed results as standardized (J?reskog and S?rbom,1993).

Other parameters referred to the overall measurement model performed asexpected (X(55)2= 69.3 and (#2/d.f.) = 1.26, which is smaller than 3 (Carminesand Mclver, 1981)). The Root Mean Square Error of Approximation (REMSEA) is 0.023, which is under the 0.5-0.8 threshold offered by Hair et al.(1999) and Kline (2005) among others. The Goodness-of-fit index (GFI) was

0.99, the Adjusted Goodness of Fit Index (AGFI) 0.99, the Comparative-FitIndex (CFI) 1, the Normed-Fit Index (NFI) 0.98 and the Non-Normed Index(NNI) 0.99; all were greater than 0.90 as offered by Marcoulides and Schu

macker (1996) and Chen and Li (2007). Furthermore, Table 1 shows that allfactor loadings for all the variables are clearly high, with ?-values significant atthe 0.001 level. Moreover, the composite reliability is also sufficient for all theindicators included and the only parameter that reveals smaller reliability refers to the validity of GM food attitude (0.46), although given that it is closeto the 0.5 threshold, and due to the relevance of this construct, we have preserved it in the model.

Structural modelTesting the proposed model by means of the structural equation model, a goodfit has been obtained. Indeed, X602= $7A and (x2/d.f.= 1.46). Moreover, REMSEA is 0.030, GFI 0.99, AGFI 0.99, CFI 1,NFI 0.98 and NNI 0.99.

Figure 2 shows the path diagram obtained after testing the proposed causalrelations of a consumer's decision-making process regarding GM food. Fromthis result we can conclude that two exogenous latent variables - Science interest and Government confidence - are the start point of this decision-makingprocess. Moreover, three endogenous latent variables

- GMF perceptions,GMF attitudes and Consumer intentions - are the stages that consumers needin order to define their actions.





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Risk Management #201Table 1 Indicators and reliability of the standardized confirmatory factor analysis

Constructs Factor t-valuesloading

R2 Compositereliability

Extractedvalidity

Science interest (SI)Interest in science and 0.93 35.43.86technologyI feel well informed about 0.92 37.23.84science and technologyI understand science stories in 0.87 28.99.76the news

Government confidence (GC)Spanish government making 0.70 8.54 0.49regulations on biotechnology isdoing a good job for societyThe European Commission 0.85 9.88 0.72

making laws on biotechnologyfor all EU countries is doing agood job for society

GMF (positive) perceptions (GMFP)To use modern biotechnology 0.86 21.76 0.73in the production of foods isuseful for societyTo use modern biotechnology

0.84 19.55 0.71in the production of foods is

morally acceptableGMF (positive) attitude (GMFA)GMF will be useful in the fight 0.62 15.20 0.38

against third world hungerEating GMF will be harmful -0.58 13.37 0.34to my health and my family'shealthIt is safe for me to eat GM 0.82 25.46 0.67food

0.93 0.82

0.75 0.61

0.84 0.72

0.72 0.46

Consumer (positive) Intentions (CI)If food Iwas eating in a 0.92 45.48 0.85restaurant contained genetically

modified ingredients,Iwould not mind.Iwould buy GMF if it 0.94 51.20 0.88contained less fat thanordinary foodIwould buy GM food if it 0.92 45.29 0.85tasted better than ordinaryfood.

0.95 0.86





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Figure 2 Final model *P


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namely structural equation modelling. Our structural equation model assumesthat perceptions of GMF express both positive and negative dimensions, aswell as moral concerns. Accordingly, it allows identifying and quantifying theunderlying constraints of revealed decision making.This study has taken advantage of a large representative subsample of theEurobarometer 2002 database for the Spanish population. The evidence indicates that acceptance of GM food is in a very early stage and individuals stilldo not reveal a clear-cut position on the matter. However, in conceptualizingthe decision-making price we find that ultimately peoples' trust in science andgovernment information source is potentially the key issue that determinesfurther acceptance. Therefore, by shifting trust in science and information conveyed by public authorities, it is possible to make GMF products acceptable toconsumers.

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Carmines, E. and Mclver, J. (1981). AnalyzingModels with Unobserved Variables:

Analysis of Covariance Structures. In Bohrnstedt, G.W and Borgatta, E.E (eds) SocialMeasurement - Current Issues. Beverly Hills: Sage Publications Inc.Chen, M.-F. and Li, H.-L. (2007). The Consumer's Attitude Toward Genetically ModifiedFoods in Taiwan. Food Quality and Preference. Vol. 18, pp 662-674.Fishbein, M. (1963). An Investigation of the Relationships Between Beliefs Aboutan Object and the Attitude Toward that Object. Human Relations. Vol. 16,pp 233-240.Frewer, L.J., Howard, C. and Aaron, I. (1998). Consumers Acceptance Of Transgenic

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