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Willingness to purchase Genetically Modified food: an analysis applying artificial Neural Networks

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  • Salazar-Ordóñez, M.
  • Rodríguez-Entrena, M.
  • Becerra-Alonso, D.

Abstract

Findings about consumer decision-making process regarding GM food purchase remain mixed and are inconclusive. This paper offers a model which classifies willingness to purchase GM food, using data from 399 surveys in Southern Spain. Willingness to purchase has been measured using three dichotomous questions and classification, based on attitudinal, cognitive and socio-demographic factors, has been made by an artificial neural network model. The results show 74% accuracy to forecast the willingness to purchase. The highest relative contributions lie in the variables related to beliefs, especially those link to perceived risks; while the variables with the least relative contribution are age and knowledge on GMO.

Suggested Citation

  • Salazar-Ordóñez, M. & Rodríguez-Entrena, M. & Becerra-Alonso, D., 2014. "Willingness to purchase Genetically Modified food: an analysis applying artificial Neural Networks," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182937, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaae14:182937
    DOI: 10.22004/ag.econ.182937
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    References listed on IDEAS

    as
    1. W. Bruce Traill, 2004. "Effect of information about benefits of biotechnology on consumer acceptance of genetically modified food: evidence from experimental auctions in the United States, England, and France," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 31(2), pages 179-204, June.
    2. Jutta Roosen & Jayson L. Lusk & John A. Fox, 2003. "Consumer demand for and attitudes toward alternative beef labeling strategies in France, Germany, and the UK," Agribusiness, John Wiley & Sons, Ltd., vol. 19(1), pages 77-90.
    3. Klaus G. Grunert, 2005. "Food quality and safety: consumer perception and demand," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 32(3), pages 369-391, September.
    4. Wuyang Hu & Michele M. Veeman & Wiktor L. Adamowicz, 2005. "Labelling Genetically Modified Food: Heterogeneous Consumer Preferences and the Value of Information," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 53(1), pages 83-102, March.
    5. repec:ags:inpuer:188880 is not listed on IDEAS
    6. House, Lisa & Lusk, Jayson L. & Jaeger, Sara & Traill, W. Bruce & Moore, Melissa & Valli, Carlotta & Morrow, Bert & Yee, Wallace M.S., 2004. "Objective And Subjective Knowledge: Impacts On Consumer Demand For Genetically Modified Foods In The United States And The European Union," 2004 Annual meeting, August 1-4, Denver, CO 20125, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
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