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Simulation of Market Demand for Traceable Pork with Different Levels of Safety Information: A Case Study in Chinese Consumers

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  • Linhai Wu
  • Xiaolin Liu
  • Dian Zhu
  • Hongsha Wang
  • Shuxian Wang
  • Lingling Xu

Abstract

type="main"> The Chinese government has always promoted the pork traceability system; however, expensive traceable pork of limited variety containing single-level safety information cannot meet the differentiated consumer demand of the Chinese market. A survey was conducted of 2,080 consumers in five cities distributed in east, south, southwest, northeast, and central China, in which traceable pork hindquarter profiles were constructed by combining traceable safety information attributes with government certification, appearance, and price. Individual consumers’ part-worth utilities were estimated using a choice experiment and hierarchical Bayesian inference. On this basis, combined with ordinary pork hindquarter profiles in the real market, different traceable pork hindquarter profiles were set to develop seven market schemes. Furthermore, market shares of each scheme were simulated using the random first choice method. Most consumers chose appearance rather than safety in the choice experiment, which also indicated that traceable safety information certified by the government had a higher part-worth utility. Simulation results suggested that a larger market share could be better achieved by supplying multilevel traceable pork hindquarters in the market at the same time, rather than by supplying single-level traceable pork hindquarters. Moreover, income was found to be the key factor in determining consumers’ demand. Le gouvernement chinois a toujours fait la promotion du système de traçabilité des porcs. Toutefois, les produits traçables, qui sont couteux, peu variés et accompagnés d'un seul niveau d'information sur la salubrité, ne peuvent satisfaire la demande particulière des consommateurs chinois. Un sondage dans lequel figuraient des renseignements sur les quartiers arrière de porcs, dont de l'information sur la salubrité, la certification du gouvernement, l'apparence et le prix, a été réalisé auprès de 2080 consommateurs dans cinq villes situées dans l'est, le sud, le sud-ouest, le nord-est et le centre de la Chine. Nous avons estimé les utilités partielles des consommateurs à l'aide des méthodes des choix discrets et de l'inférence bayésienne hiérarchique. À partir de ces données, combinées à des renseignements sur des quartiers arrière de porcs ordinaires sur le marché réel, nous avons élaboré sept scénarios de marché. Nous avons aussi simulé les parts de marché de chaque scénario à l'aide de la méthode du premier choix aléatoire. Dans la méthode des choix discrets, la plupart des consommateurs ont choisi l'apparence plutôt que la salubrité, ce qui indique que l'information sur la salubrité certifiée par le gouvernement avait une utilité partielle élevée. Les résultats de la simulation autorisent à penser qu'il serait possible de conquérir une plus grande part de marché si les quartiers arrière de porcs étaient accompagnés d'information de plusieurs niveaux en même temps plutôt que d'information d'un seul niveau. D'après nos résultats, le revenu représente le facteur clé dans la détermination de la demande des consommateurs.

Suggested Citation

  • Linhai Wu & Xiaolin Liu & Dian Zhu & Hongsha Wang & Shuxian Wang & Lingling Xu, 2015. "Simulation of Market Demand for Traceable Pork with Different Levels of Safety Information: A Case Study in Chinese Consumers," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 63(4), pages 513-537, December.
  • Handle: RePEc:bla:canjag:v:63:y:2015:i:4:p:513-537
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    1. James, Jennifer S. & Rickard, Bradley J. & Rossman, William J., 2009. "Product Differentiation and Market Segmentation in Applesauce: Using a Choice Experiment to Assess the Value of Organic, Local, and Nutrition Attributes," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 38(3), pages 1-14, December.
    2. Sebastien Pouliot & Daniel A. Sumner, 2013. "Traceability, recalls, industry reputation and product safety," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(1), pages 121-142, February.
    3. James, Jennifer S. & Rickard, Bradley J. & Rossman, William J., 2009. "Product Differentiation and Market Segmentation in Applesauce: Using a Choice Experiment to Assess the Value of Organic, Local, and Nutrition Attributes," Agricultural and Resource Economics Review, Cambridge University Press, vol. 38(3), pages 357-370, December.
    4. Dickinson, David L. & Bailey, DeeVon, 2002. "Meat Traceability: Are U.S. Consumers Willing To Pay For It?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 27(2), pages 1-17, December.
    5. Peter E. Rossi & Robert E. McCulloch & Greg M. Allenby, 1996. "The Value of Purchase History Data in Target Marketing," Marketing Science, INFORMS, vol. 15(4), pages 321-340.
    6. Teisl, Mario F. & Roe, Brian E., 2010. "Consumer willingness-to-pay to reduce the probability of retail foodborne pathogen contamination," Food Policy, Elsevier, vol. 35(6), pages 521-530, December.
    7. Ji Yong Lee & Doo Bong Han & Rodolfo M. Nayga Jr & Song Soo Lim, 2011. "Valuing traceability of imported beef in Korea: an experimental auction approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(3), pages 360-373, July.
    8. Golan, Elise H. & Krissoff, Barry & Kuchler, Fred & Calvin, Linda & Nelson, Kenneth E. & Price, Gregory K., 2004. "Traceability In The U.S. Food Supply: Economic Theory And Industry Studies," Agricultural Economic Reports 33939, United States Department of Agriculture, Economic Research Service.
    9. Buhr, Brian L., 2003. "Traceability And Information Technology In The Meat Supply Chain: Implications For Firm Organization And Market Structure," Journal of Food Distribution Research, Food Distribution Research Society, vol. 34(3), pages 1-14, November.
    10. Pouliot, Sebastien & Sumner, Daniel A., 2013. "Traceability, Product Recalls, Industry Reputation and Food Safety," Staff General Research Papers Archive 32133, Iowa State University, Department of Economics.
    11. Ortega, David L. & Wang, H. Holly & Wu, Laping & Olynk, Nicole J., 2011. "Modeling heterogeneity in consumer preferences for select food safety attributes in China," Food Policy, Elsevier, vol. 36(2), pages 318-324, April.
    12. Kim Darby & Marvin T. Batte & Stan Ernst & Brian Roe, 2008. "Decomposing Local: A Conjoint Analysis of Locally Produced Foods," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(2), pages 476-486.
    13. Tonsor, Glynn T. & Olynk, Nicole & Wolf, Christopher, 2009. "Consumer Preferences for Animal Welfare Attributes: The Case of Gestation Crates," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(3), pages 713-730, December.
    14. Tomas Nilsson & Ken Foster & Jayson L. Lusk, 2006. "Marketing Opportunities for Certified Pork Chops," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 54(4), pages 567-583, December.
    15. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    16. Riccardo Scarpa & George Philippidis & Fiorenza Spalatro, 2005. "Product-country images and preference heterogeneity for Mediterranean food products: A discrete choice framework," Agribusiness, John Wiley & Sons, Ltd., vol. 21(3), pages 329-349.
    17. Mickael Bech & Dorte Gyrd‐Hansen, 2005. "Effects coding in discrete choice experiments," Health Economics, John Wiley & Sons, Ltd., vol. 14(10), pages 1079-1083, October.
    18. G. Salkeld & M. Ryan & L. Short, 2000. "The veil of experience: do consumers prefer what they know best?," Health Economics, John Wiley & Sons, Ltd., vol. 9(3), pages 267-270, April.
    19. McCulloch, Robert E. & Polson, Nicholas G. & Rossi, Peter E., 2000. "A Bayesian analysis of the multinomial probit model with fully identified parameters," Journal of Econometrics, Elsevier, vol. 99(1), pages 173-193, November.
    20. Ulrich Enneking, 2004. "Willingness-to-pay for safety improvements in the German meat sector: the case of the Q&S label," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 31(2), pages 205-223, June.
    21. Ubilava, David & Foster, Kenneth, 2009. "Quality certification vs. product traceability: Consumer preferences for informational attributes of pork in Georgia," Food Policy, Elsevier, vol. 34(3), pages 305-310, June.
    22. Olynk, Nicole J. & Tonsor, Glynn T. & Wolf, Christopher A., 2010. "Consumer Willingness to Pay for Livestock Credence Attribute Claim Verification," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 35(2), pages 1-20, August.
    23. Loureiro, Maria L. & Umberger, Wendy J., 2007. "A choice experiment model for beef: What US consumer responses tell us about relative preferences for food safety, country-of-origin labeling and traceability," Food Policy, Elsevier, vol. 32(4), pages 496-514, August.
    24. Jill E. Hobbs, 2004. "Information asymmetry and the role of traceability systems," Agribusiness, John Wiley & Sons, Ltd., vol. 20(4), pages 397-415.
    25. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132-132.
    26. Hobbs, Jill E., 2003. "Consumer Demand For Traceability," Working Papers 14614, International Agricultural Trade Research Consortium.
    27. Danny Campbell & Edel Doherty, 2013. "Combining discrete and continuous mixing distributions to identify niche markets for food," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(2), pages 287-312, March.
    28. Allenby, Greg M. & Rossi, Peter E., 1998. "Marketing models of consumer heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 57-78, November.
    29. Fredrik Carlsson & Peter Frykblom & Carl Johan Lagerkvist, 2007. "Consumer Benefits of Labels and Bans on GM Foods—Choice Experiments with Swedish Consumers," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(1), pages 152-161.
    30. Alfnes, Frode & Guttormsen, Atle G. & Steine, Gro & Kolstad, Kari, 2006. "Ajae Appendix: Consumers’ Willingness To Pay For The Color Of Salmon: A Choice Experiment With Real Economic Incentives," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 88(4), pages 1-8, November.
    31. James, Jennifer S. & Rickard, Bradley J. & Rossman, William J., 2009. "Product Differentiation and Market Segmentation in Applesauce: Using a Choice Experiment to Assess the Value of Organic, Local and Nutrition Attributes," Working Papers 48916, Cornell University, Department of Applied Economics and Management.
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    Cited by:

    1. Bo Hou & Jing Hou & Linhai Wu, 2019. "Consumer Preferences for Traceable Food with Different Functions of Safety Information Attributes: Evidence from a Menu-Based Choice Experiment in China," IJERPH, MDPI, vol. 17(1), pages 1-18, December.
    2. Jason A. Winfree, 2023. "Collective reputation and food," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 45(2), pages 666-683, June.
    3. Wongprawmas, Rungsaran & Canavari, Maurizio, 2017. "Consumers’ willingness-to-pay for food safety labels in an emerging market: The case of fresh produce in Thailand," Food Policy, Elsevier, vol. 69(C), pages 25-34.
    4. Ellen Goddard & Wuyang Hu, 2015. "Introduction to the Special Issue on Food Marketing, Information, and Labeling," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 63(4), pages 431-433, December.
    5. Wu, Linhai & Liu, Pingping & Chen, Xiujuan & Hu, Wuyang & Fan, Xuesen & Chen, Yuhuan, 2020. "Decoy effect in food appearance, traceability, and price: Case of consumer preference for pork hindquarters," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 87(C).

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