Consumers' willingness to adopt genetically modified foods

Compatibility; Genetically modified foods; Health belief model; Net benefit; Willingness to adopt; Food Science; Business, Management and Accounting (miscellaneous)

Abstract :

[en] Purpose: This study investigates consumers' willingness to adopt genetically modified foods (GM) and the role of innovation and behavioral determinants. Design/methodology/approach: A new integrated model that expands the Health Belief Model (HBM) into the Innovation Diffusion Theory (IDT) was developed and examined. A total of 241 consumers were selected from the capital of Iran, Tehran, through a multistage random sampling. The data were analyzed using SEM-PLS modeling. Findings: The extended HBM model was able to predict about 84% of the variance changes in consumers' willingness to adopt GM foods. The effects of net benefit and perceived compatibility on the willingness were also significant. In addition, the mediating effect of compatibility on the relationship between net benefit/self-efficacy and willingness to adopt GM foods was also significant. Originality/value: This study contributes to the literature by developing the HBM into the IDT to assess consumers' willingness to adopt GM foods.

Disciplines :

Agriculture & agronomy

Author, co-author :

Fozouni Ardekani, Zahra ; Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran

Akbari, Morteza ; Faculty of Entrepreneurship, University of Tehran, Tehran, Iran

Pino, Giovanni; University of Chieti-Pescara, Pescara, Italy

Zúñiga, Miguel Ángel ; Morgan State University, Baltimore, United States

Azadi, Hossein ; Université de Liège - ULiège > TERRA Research Centre > Modélisation et développement ; Department of Geography, Ghent University, Ghent, Belgium ; Research Group Climate Change and Security, Institute of Geography, University of Hamburg, Hamburg, Germany ; Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic

Language :

English

Title :

Consumers' willingness to adopt genetically modified foods

Publication date :

05 February 2021

Journal title :

British Food Journal

ISSN :

0007-070X

eISSN :

1758-4108

Publisher :

Emerald Group Holdings Ltd.

Volume :

123

Issue :

Pages :

1042 - 1059

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://www.emerald.com/insight/content/doi/10.1108/BFJ-04-2019-0260/full/xml

Available on ORBi :

since 27 February 2025

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Bibliography

Ajzen, I. (2002), “Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior”, Journal of Applied Social Psychology, Vol. 32, pp. 665-683.
Akbari, M., Fozouni Ardekani, Z., Pino, G. and Maleksaeidi, H. (2019), “An extended model of theory of planned behavior to investigate highly-educated Iranian consumers' intentions towards consuming genetically modified foods”, Journal of Cleaner Production, Vol. 227, pp. 784-793.
Arvola, A.M., Vassallo, M., Dean, P., Lampila, A., Lahteenmaki, S.A. and Shepherd, R. (2008), “Predicting intentions to purchase organic food: the role of affective and moral attitudes in the theory of planned behaviour”, Appetite, Vol. 50, pp. 443-454.
Azadi, H. and Ho, P. (2010), “Genetically modified and organic crops in developing countries: a review of options for food security”, Biotechnology Advances, Vol. 28, pp. 160-168.
Bandura, A. (1982), “Self-efficacy mechanism in human agency”, American Psychologist, Vol. 37, pp. 122-147.
Becker, M.H. and Rosenstock, I.M. (1987), “Comparing social learning theory and the health belief model”, Advances in Health Education and Promotion, Vol. 2, pp. 245-249.
Bett, C., Ouma, J.O. and Groote, H.D. (2010), “Perspectives of gatekeepers in the Kenyan food industry towards genetically modified food”, Food Policy, Vol. 35, pp. 332-340.
Bimbo, F., Bonanno, A., Nocella, G., Viscecchia, R., Nardone, G., Devitiis, B. and Carlucci, D. (2017), “Consumers' acceptance and preferences for nutrition-modified and functional dairy products: a systematic review”, Appetite, Vol. 113, pp. 141-154.
Buglar, M.E., White, K.M. and Robinson, N.G. (2010), “The role of self-efficacy in dental patients' brushing and flossing: testing an extended health belief model”, Patient Education and Counseling, Vol. 78, pp. 269-272.
Bylund, C.L., Galvin, K.M., Dunet, D.O. and Reyes, M. (2011), “Using the extended health belief model to understand siblings' perceptions of risk for hereditary hemochromatosis”, Patient Education and Counseling, Vol. 82, pp. 36-41.
Chang, S.-C. and Tung, F.-C. (2008), “An empirical investigation of students' behavioural intentions to use the online learning course websites”, British Journal of Educational Technology, Vol. 39, pp. 71-83.
Chen, M.F. and Li, H.L. (2007), “The consumer's attitude toward genetically modified foods in Taiwan”, Food Quality and Preference, Vol. 18, pp. 662-674.
Chen, L., Gillenson, M. and Sherrell, D. (2002), “Enticing online consumers: an extended technology acceptance perspective”, Information & Management, Vol. 39 No. 8, pp. 705-719.
Cheung, R. and Vogel, D. (2013), “Predicting user acceptance of collaborative technologies: an extension of the technology acceptance model for e-learning”, Computers and Education, Vol. 63, pp. 160-175.
Chin, W.W. (1998), “The partial least squares approach for structural equation modeling”, in Marcoulides, G.A. (Ed.), Methodology for Business and Management. Modern Methods for Business Research, Lawrence Erlbaum Associates Publishers, Mahwah, NJ.
Chin, W.W. (2010), “How to write up and report PLS analyses”, in Esposito Vinzi, V., Chin, W.W., Henseler, J. and Wang, H. (Eds), Handbook of Partial Least Squares: Concepts, Methods and Applications, Springer Berlin Heidelberg, Berlin, Heidelberg.
Colson, G. and Huffman, W.E. (2011), “Consumers' willingness to pay for genetically modified foods with product-enhancing nutritional attributes”, American Journal of Agricultural Economics, Vol. 93, pp. 358-363.
Costa-Font, M. and Gil, J.M. (2009), “Structural equation modelling of consumer acceptance of genetically modified (GM) food in the Mediterranean Europe: a cross country study”, Food Quality and Preference, Vol. 20, pp. 399-409.
Cox, D.F. and Rich, S.U. (1964), “Perceived risk and consumer decision-making: the case of telephone shopping”, Journal of Marketing Research, Vol. 1, pp. 32-39.
De Steur, H., Gellynck, X., Storozhenko, S., Liqun, G., Lambert, W., Van Der Straeten, D. and Viaene, J. (2010), “Willingness-to-accept and purchase genetically modified rice with high folate content in Shanxi Province, China”, Appetite, Vol. 54, pp. 118-125.
Domingo, J.L. and Gine Bordonaba, J. (2011), “A literature review on the safety assessment of genetically modified plants”, Environment International, Vol. 37, pp. 734-742.
Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, Vol. 18, pp. 39-50.
Frewer, L.J., Van Der Lans, I.A., Fischer, A.R.H., Reinders, M.J., Menozzi, D., Zhang, X., Van Den Berg, I. and ZIMMERMANN, K.L. (2013), “Public perceptions of agri-food applications of genetic modification – a systematic review and meta-analysis”, Trends in Food Science and Technology, Vol. 30, pp. 142-152.
Gao, H. and Knight, J.G. (2009), “Chinese gatekeeper perceptions of genetically modified food”, British Food Journal, Vol. 111, pp. 56-69.
Ghanian, M., Ghoochani, O.M., Kitterlin, M., Jahangiry, S., Zarafshani, K., Van Passel, S. and Azadi, H. (2016), “Attitudes of agricultural experts toward genetically modified crops: a case study in Southwest Iran”, Science and Engineering Ethics, Vol. 22, pp. 509-524.
Ghasemi, S., Karami, E. and Azadi, H. (2013), “Knowledge, attitudes and behavioral intentions of agricultural professionals toward genetically modified (GM) foods: a case study in Southwest Iran”, Science and Engineering Ethics, Vol. 19 No. 3, pp. 1201-1227.
Ghasemi, S., Ahmadvand, M., Karami, E. and Karami, A. (2019), “Social risk perceptions of genetically modified foods of engineers in training: application of a comprehensive risk model”, Science and Engineering Ethics, Vol. 26, pp. 641-665, doi: 10.1007/s11948-019-00110-6.
Ghoochani, O.M., Ghanian, M., Baradaran, M., Alimirzaei, E. and Azadi, H. (2018), “Behavioral intentions toward genetically modified crops in Southwest Iran: a multi-stakeholder analysis”, Environment, Development and Sustainability, Vol. 20, pp. 233-253.
Giovanis, A.N., Binioris, S. and Polychronopoulos, G. (2012), “An extension of TAM model with IDT and security/privacy risk in the adoption of internet banking services in Greece”, EuroMed Journal of Business, Vol. 7 No. 1, pp. 24-53.
Hair, J.F., Ringle, C.M. and Sarstedt, M. (2011), “PLS-SEM: indeed a silver bullet”, Journal of Marketing Theory and Practice, Vol. 19 No. 2, pp. 139-152.
Hair, J.F., Hult, G.T.M., Ringle, C.M. and Sarstedt, M. (2017), A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), Sage, Thousand Oaks, CA.
Henseler, J., Ringle, C.M. and Sinkovics, R.R. (2009), “The use of partial least squares path modeling in international marketing”, in Sinkovics, R.R. and Ghauri, P.N. (Eds), New Challenges to International Marketing (Advances in International Marketing), Emerald Group Publishing, Bingley.
Henseler, J., Dijkstra, T.K., Sarstedt, M., Ringle, C.M., Diamantopoulos, A., Straub, D.W., Ketchen, D.J., Hair, J.F., Hult, G.T.M. and Calantone, R.J. (2014), “Common beliefs and reality about PLS: comments on Rönkkö and Evermann (2013)”, Organizational Research Methods, Vol. 17, pp. 182-209.
Hudson, J., Caplanova, A. and Novak, M. (2015), “Public attitudes to GM foods. The balancing of risks and gains”, Appetite, Vol. 92, pp. 303-313.
Irwin, M.R., Victor, J.S. and Marshall, H.B. (1988), “Social learning theory and the health belief model”, Health Education Quarterly, Vol. 15, pp. 175-183.
Jiang, C., Zhao, W., Sun, X., Zhang, K., Zheng, R. and Qu, W. (2016), “The effects of the self and social identity on the intention to microblog: an extension of the theory of planned behavior”, Computers in Human Behavior, Vol. 64, pp. 754-759.
Jin, C.H. (2014), “Adoption of e-book among college students: the perspective of an integrated TAM”, Computers in Human Behavior, Vol. 41, pp. 471-477.
Kajale, D.B. and Becker, T.C. (2013), “Determinants of consumer support for mandatory labeling of genetically modified food in India: a student survey”, British Food Journal, Vol. 115, pp. 1597-1611.
Kazemi Najaf Abadi, A. and Skandarian, H. (2015), “Legislative obligations of member states under Cartagena protocol and the extent to which the Islamic Republic of Iran has adhered to such commitments”, Public Law Research, Vol. 16 No. 44, pp. 129-148.
Kikulwe, E.M., Wesseler, J. and Falck-Zepeda, J. (2011), “Attitudes, perceptions, and trust. Insights from a consumer survey regarding genetically modified banana in Uganda”, Appetite, Vol. 57, pp. 401-413.
Kim, D.J., Ferrin, D.L. and Rao, H.R. (2008), “A trust-based consumer decision-making model in electronic commerce: the role of trust, perceived risk, and their antecedents”, Decision Support Systems, Vol. 44, pp. 544-564.
Kim, Y.G., Jang, S.Y. and Kim, A.K. (2014), “Application of the theory of planned behavior to genetically modified foods: moderating effects of food technology neophobia”, Food Research International, Vol. 62, pp. 947-954.
Magnusson, M.K. and Koivisto Hursti, U.K. (2002), “Consumer attitudes towards genetically modified foods”, Appetite, Vol. 39, pp. 9-24.
Martinez-Poveda, A., Molla-Bauza, M.B., Del Campo Gomis, F.J. and Martinez, L.M.-C. (2009), “Consumer-perceived risk model for the introduction of genetically modified food in Spain”, Food Policy, Vol. 34, pp. 519-528.
Mccomas, K.A., Besley, J.C. and Steinhardt, J. (2014), “Factors influencing U.S. consumer support for genetic modification to prevent crop disease”, Appetite, Vol. 78, pp. 8-14.
Miles, S., Ueland, Ø. and Frewer, L.J. (2005), “Public attitudes towards genetically‐modified food”, British Food Journal, Vol. 107, pp. 246-262.
Montuori, P., Triassi, M. and Sarnacchiaro, P. (2012), “The consumption of genetically modified foods in Italian high school students”, Food Quality and Preference, Vol. 26, pp. 246-251.
Mucci, A., Hough, G. and Ziliani, C. (2004), “Factors that influence purchase intent and perceptions of genetically modified foods among Argentine consumers”, Food Quality and Preference, Vol. 15 No. 6, pp. 559-567.
Ng, B.-Y., Kankanhalli, A. and Xu, Y. (2009), “Studying users' computer security behavior: a health belief perspective”, Decision Support Systems, Vol. 46, pp. 815-825.
Nicolia, A., Manzo, A., Veronesi, F. and Rosellini, D. (2014), “An overview of the last 10 years of genetically engineered crop safety research”, Critical Reviews in Biotechnology, Vol. 34, pp. 77-88.
Pino, G., Amatulli, C., De Angelis, M. and Peluso, A.M. (2016), “The influence of corporate social responsibility on consumers' attitudes and intentions toward genetically modified foods: evidence from Italy”, Journal of Cleaner Production, Vol. 112, pp. 2861-2869.
Pouresmaeili, A., Vaezi Kakhki, M.R. and Bameri, E. (2017), “A comparative study of the consumers rights of GM crops in Iran and European union”, Bioethics Journal, Vol. 7, pp. 99-114.
Prati, G., Pietrantoni, L. and Zani, B. (2012), “The prediction of intention to consume genetically modified food: test of an integrated psychosocial model”, Food Quality and Preference, Vol. 25, pp. 163-170.
Preacher, K.J. (2006), “Quantifying parsimony in structural equation modeling”, Multivariate Behavioral Research, Vol. 41 No. 3, pp. 227-259.
Raykov, T. and Marcoulides, G.A. (1999), “On desirability of parsimony in structural equation model selection”, Structural Equation Modeling: A Multidisciplinary Journal, Vol. 6 No. 3, pp. 292-300.
Renko, N., Brcic´‐Stipcevic´, V. and Renko, S. (2003), “Attitudes of the Croatian population toward genetically modified food”, British Food Journal, Vol. 105, pp. 148-161.
Ribeiro, T.G., Barone, B. and Behrens, J.H. (2016), “Genetically modified foods and their social representation”, Food Research International, Vol. 84, pp. 120-127.
Roden, J. (2004), “Revisiting the health belief model: nurses applying it to young families and their health promotion needs”, Nursing and Health Sciences, Vol. 6, pp. 1-10.
Rodríguez-Entrena, M., Salazar-Ordóñez, M. and Sayadi, S. (2013), “Applying partial least squares to model genetically modified food purchase intentions in southern Spain consumers”, Food Policy, Vol. 40, pp. 44-53.
Rogers, E.M. (2003), Diffusion of Innovations, Free Press, New York, NY.
Rosenstock, I.M. (1974), “The health belief model and preventive health behavior”, Health Education Monographs, Vol. 2, pp. 354-386.
Saher, M., Lindeman, M. and Hursti, U.K.K. (2006), “Attitudes towards genetically modified and organic foods”, Appetite, Vol. 46 No. 3, pp. 324-331.
Siegrist, M., Hartmann, C. and Sutterlin, B. (2016), “Biased perception about gene technology: how perceived naturalness and affect distort benefit perception”, Appetite, Vol. 96, pp. 509-516.
Stevens, J.P. (1992), Applied Multivariate Statistics for the Social Sciences, Erlbaum, Hillsdale, NJ.
Valente, M. and Chaves, C. (2018), “Perceptions and valuation of GM food: a study on the impact and importance of information provision”, Journal of Cleaner Production, Vol. 172, pp. 4110-4118.
Vijayasarathy, L.R. (2004), “Predicting consumer intentions to use on-line shopping: the case of an augmented technology acceptance model”, Information and Management, Vol. 41, pp. 747-762.
Wu, J.H. and Wang, S.C. (2005), “What drives mobile commerce?: an empirical evaluation of the revised technology acceptance model”, Information and Management, Vol. 42, pp. 719-729.
Yazdanpanah, M., Forouzani, M. and Hojjati, M. (2015a), “Willingness of Iranian young adults to eat organic foods: application of the health belief model”, Food Quality and Preference, Vol. 41, pp. 75-83.
Yazdanpanah, M., Komendantova, N. and Ardestani, R.S. (2015b), “Governance of energy transition in Iran: investigating public acceptance and willingness to use renewable energy sources through socio-psychological model”, Renewable and Sustainable Energy Reviews, Vol. 45, pp. 565-573.
Zhao, Q., Chen, C.D., Wang, J.L. and Chen, P.C. (2017), “Determinants of backers' funding intention in crowdfunding: social exchange theory and regulatory focus”, Telematics and Informatics, Vol. 34 No. 1, pp. 370-384.
Zhu, W., Yao, N., Ma, B. and Wang, F. (2018), “Consumers' risk perception, information seeking, and intention to purchase genetically modified food: an empirical study in China”, British Food Journal, Vol. 120, pp. 2182-2194.