Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-23T05:05:46.742Z Has data issue: false hasContentIssue false
  • English
  • Français

Consumer Likelihood to Purchase Chickens with Novel Production Attributes

Published online by Cambridge University Press:  28 April 2015

John C. Bernard ,
John D. Pesek Jr.  and
Xiqian Pan
John C. Bernard
Affiliation:
Department of Food and Resource Economics at the University of Delaware
John D. Pesek Jr.
Affiliation:
Department of Food and Resource Economics at the University of Delaware
Xiqian Pan
Affiliation:
Department of Food and Resource Economics at the University of Delaware
Get access Rights & Permissions [Opens in a new window]

Abstract

Typical supermarket chickens are produced with novel or controversial attributes. This continues despite contrasting growth in consumer interest in organic and natural foods. This study surveyed Delaware consumers' likelihood to purchase chicken given different attributes: free range, given antibiotics, irradiated, fed genetically modified (GM) feed, GM chicken, and price. Examining conjoint analysis data with a heteroskedastic two-limit tobit model, GM chicken and other novel attributes were found to lower purchase likelihood significantly. Understanding these results should help the industry meet consumer preferences while aiding its continued expansion to benefit workers and growers across the South.

Keywords

antibioticschickenconjoint analysisgenetically modifiedheteroskedasticirradiatedtobitQ13D12C24
Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 39 , Issue 3 , December 2007 , pp. 581 - 596
Copyright
Copyright © Southern Agricultural Economics Association 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bernard, J.C., Pan, X., and Sirolli, R.. “Consumer Attitudes towards Genetic Modification and Other Controversial Production Attributes for Chicken.” Journal of Food Distribution Research 36(2005):1–11.Google Scholar
Bernard, J.C., Zhang, C., and Gifford, K.. “An Experimental Investigation of Consumer Willingness to Pay for Non-GM Foods When an Organic Option Is Present.” Agricultural and Resource Economics Review 35(2006):374-85.CrossRefGoogle Scholar
Box, G.E.P., Hunter, J.S., and Hunter, W.G.. Statistics for Experimenters, 2nd ed. New York: John Wiley and Sons, 2005.Google Scholar
Boyle, K.J., Holmes, T.P., Teisl, M.F., and Roe, B.. “A Comparison of Conjoint Analysis Response Formats.” American Journal of Agricultural Economics 83(2001):441-54.CrossRefGoogle Scholar
Bradlow, E.T. “Current Issues and a ‘Wish List’ for Conjoint Analysis.” Applied Stochastic Models in Business and Industry 21(2005):319-23.CrossRefGoogle Scholar
Bureau of Labor Statistics (BLS). Internet site: http://www.bls.gov/data/ (Accessed June 2002).Google Scholar
Buzby, J., and Farah, H.. “Chicken Consumption Continues Longrun Rise.” Amber Waves. (2006).Google Scholar
Carlsson, F., Frykblom, P., and Lagerkvist, C.J.. “Consumer Preferences for Food Product Quality Attributes from Swedish Agriculture.” Ambio 34(2005):366-70.CrossRefGoogle ScholarPubMed
Dillman, D.A.Mail and Internet Surveys, 2nd ed. New York: John Wiley and Sons, 2000.Google Scholar
Dimitri, C., and Greene, C.. Recent Growth Patterns in the U. S. Organic Foods Market. Washington, DC: USDA/Economic Research Service, 2002.Google Scholar
Elrod, T., Louviere, J.J., and Davey, K.S.. “An Empirical Comparison of Ratings-Based and Choice-Based Conjoint Models.” Journal of Marketing Research 29(1992):368-77.CrossRefGoogle Scholar
Frenzen, P.D., Majchrowicz, A., Buzby, J.C., and Imhoff, B.. Consumer Acceptance of Irradiated Meat and Poultry Products. Washington, DC: U.S. Department of Agriculture, Economic Research Service, Agriculture Information Bulletin No. 757, 2000.Google Scholar
Gil, J.M., and Sanchez, M.. “Consumer Preferences for Wine Attributes: A Conjoint Approach.” British Food Journal 99(1997):3–11.CrossRefGoogle Scholar
Green, P.E., and Rao, V.R.. “Conjoint Measurement for Quantifying Judgmental Data.” Journal of Marketing Research 8(1971):355-63.Google Scholar
Greene, W.H. Personal Communication. March 2007.Google Scholar
Haefele, M.A., and Loomis, J.B.. “Improving Statistical Efficiency and Testing Robustness of Conjoint Marginal Valuations.” American Journal of Agricultural Economics 83(2001):1321-7.CrossRefGoogle Scholar
Halbrendt, C., Pesek, J., Parson, A., and Lindner, R.. “Using Conjoint Analysis to Assess Consumers’ Acceptance of PST-Supplemented Pork.” Valuing Food Safety and Nutrition. Caswell, J.A., ed. Colorado: Westview Press, 1995.Google Scholar
Harper, G.C., and Makatouni, A.. “Consumer Perception of Organic Food Production and Farm Animal Welfare.” British Food Journal 104(2002):287-99.CrossRefGoogle Scholar
Harrison, R.W., Gillespie, J., and Fields, D.. “Analysis of Cardinal and Ordinal Assumptions in Conjoint Analysis.” Agricultural and Resource Economics Review 34(2005):238-52.CrossRefGoogle Scholar
Harrison, R.W., and Mclennon, E.. “Analysis of Consumer Preferences for Biotech Labeling Formats.” Journal of Agricultural and Applied Economics 36(2004):159-71.CrossRefGoogle Scholar
Harrison, R.W., Özayan, A., and Meyers, S.P.. “A Conjoint Analysis of New Food Products Processed from Underutilized Small Crawfish.” Journal of Agricultural and Applied Economics 30(1998):257-55.CrossRefGoogle Scholar
Harrison, R.W., and Sambidi, P.R.. “A Conjoint Analysis of the U.S. Broiler Complex Location Decision.” Journal of Agricultural and Applied Economics 36(2004):639-55.CrossRefGoogle Scholar
Harrison, R.W., Stringer, T., and Priyawiwatkul, W.. “An Analysis of Consumer Preferences for Value-Added Seafood Producers Derived from Crawfish.” Agricultural and Resource Economics Review 31(2002):157-70.CrossRefGoogle Scholar
Hayes, D.J., Fox, J.A., and Shogren, J.F.. “Experts and Activists: How Information Affects the Demand for Food Irradiation.” Food Policy 27(2002):185-93.CrossRefGoogle Scholar
Heiman, A., Just, D.R., and Zilberman, D.. “The Role of Socioeconomic Factors and Lifestyle Variables in Attitude and the Demand for Genetically Modified Foods.” Journal of Agribusiness 18(2000):249-60.Google Scholar
Hwang, Y.-J., Roe, B., and Teisl, M.. “An Empirical Analysis of United States Consumers’ Concerns about Eight Food Production and Processing Technologies.” AgBioForum 8(2005):40-9.Google Scholar
Johnson, R.M. “Trade-off Analysis of Consumer Values.” Journal of Marketing Research 11(1974):121-7.CrossRefGoogle Scholar
Knight, A.J. “Does Application Matter? An Examination of Public Perception of Agricultural Biotechnology Applications.” AgBioForum 9(2006):121-8.Google Scholar
Larue, B., West, G.E., Gendron, C., and Lambert, R.. “Consumer Response to Functional Foods Produced by Conventional, Organic, or Genetic Modification.” Agribusiness: An International Journal 20(2004):155-66.CrossRefGoogle Scholar
Lee, K.H., and Hatcher, C.B.. “Willingness to Pay for Information: An Analyst’s Guide.” Journal of Consumer Affairs 35(2001):120–140.CrossRefGoogle Scholar
Long, J.S.Regression Models for Categorical and Limited Dependent Variables. Newbury Park, CA: Sage Publications, 1997.Google Scholar
Louviere, J.J.Analyzing Decision Making: Metric Conjoint Analysis. Newbury Park, CA: Sage Publications, 1988.CrossRefGoogle Scholar
Lusk, J.L., Jamal, M., Kurlander, L., Roucan, M., and Taulman, L.. “A Meta-Analysis of Genetically Modified Food Valuation Studies.” Journal of Agricultural and Resource Economics 30(2005):28–44.Google Scholar
Lusk, J.L., Norwood, F.B., and Pruitt, J.R.. “Consumer Demand for a Ban on Antibiotic Drug Use in Pork Production.” American Journal of Agricultural Economics 88(2006):1015-33.CrossRefGoogle Scholar
Lusk, J.L., Roosen, J., and Fox, J.A.. “Demand for Beef from Cattle Administered Growth Hormones or Fed Genetically Modified Corn: A Comparison of Consumers in France, Germany, the United Kingdom, and the United States.” American Journal of Agricultural Economics 85(2003):16–29.CrossRefGoogle Scholar
Mackenzie, J. “A Comparison of Contingent Preference Models.” American Journal of Agricultural Economics 75(1993):593–603.CrossRefGoogle Scholar
Martinez, M.G., Aragones, Z., and Poole, N.. “A Repositioning Strategy for Olive Oil in the UK Market.” Agribusiness: An International Journal 18(2002):163-80.CrossRefGoogle Scholar
Mathews, K.H. Jr.Antimicrobial Drug Use and Veterinary Costs in U.S. Livestock Production. Washington, DC: U.S. Department of Agriculture, Economic Research Service, Agriculture Information Bulletin No. 766, 2001.Google Scholar
Mathews, K.H. Jr., Buzby, J.C., and Tollefson, L.R.. Livestock Drugs: More Questions Than Answers? Washington, DC: U.S. Department of Agriculture, Economic Research Service, Agricultural Outlook, September 2001.Google Scholar
Mitchell, L. “Impact of Consumer Demand for Animal Welfare on Global Trade.” Changing Structure of Global Food Consumption and Trade. Regmi, A., ed. Washington, DC: U.S. Department of Agriculture, Economic Research Service, Agriculture and Trade Report WRS No. 01-1, 2001.Google Scholar
Moore, W.L. “A Cross-Validity Comparison of Rating-Based and Choice-Based Conjoint Analysis Models.” International Journal of Research in Marketing 21(2004):299–312.CrossRefGoogle Scholar
Nayga, R.M. Jr., “Sociodemographic Influences on Consumer Concern for Food Safety: The Case of Irradiation, Antibiotics, Hormones, and Pesticides.” Review of Agricultural Economics 18(1996):467-75.Google Scholar
Nayga, R.M. Jr., Poghosyan, A., and Nichols, J.P.. “Will Consumers Accept Irradiated Food Products?” International Journal of Consumer Studies 28(2004):178-85.CrossRefGoogle Scholar
Nayga, R.M. Jr., Woodward, R., and Aiew, W.. “Willingness to Pay for Reduced Risk of Foodborne Illness: A Nonhypothetical Field Experiment.” Canadian Journal of Agricultural Economics 54(2006):461-75.CrossRefGoogle Scholar
Olsen, R.J. “Note on the Uniqueness of the Maximum Likelihood Estimator for the Tobit Model.” Econometrica 46(1978):1211-5.CrossRefGoogle Scholar
Pew Initiative on Food and Biotechnology. Public Sentiment about Genetically Modified Foods, September 2003 Update. Internet site: http://pewagbiotech.org/research/2003update/ (Accessed July 17, 2006).Google Scholar
Reibstein, D., Bateson, J.E.G., and Boulding, W.. “Conjoint Analysis Reliability: Empirical Findings.” Marketing Science 7(1988):271-86.CrossRefGoogle Scholar
Rosett, R.N., and Nelson, F.D.. “Estimation of the Two-Limit Probit Regression Model.” Econometrica 43(1975):141-6.CrossRefGoogle Scholar
SAS Institute Inc. SAS Online Doc® 9.1. North Carolina: SAS Institute, 2003.Google Scholar
Shogren, J., Fox, J., Hayes, D., and Roosen, J.. “Observed Choices for Food Safety in Retail, Survey, and Auction Markets.” American Journal of Agricultural Economics 81(1999):1192-9.CrossRefGoogle Scholar
Smith, J.L., Drum, D.J., Dai, Y., Kim, J.M., Sanchez, S., Maurer, J.J., Hofacre, C.L., and Lee, M.D.. “Impact of Antimicrobial Usage on Antimicrobial Resistance in Commensal Escherichia coli Strains Colonizing Broiler Chickens.” Applied and Environmental Microbiology 73(2007):1404-14.CrossRefGoogle ScholarPubMed
U.S. Department of Agriculture—Economic Research Service (USDA-ERS). Internet site: http://www.ers.usda.gov/data/BiotechCrops/ExtentofAdoptionTablel.htm (Accessed October 20, 2003a).Google Scholar
U.S. Department of Agriculture—Economic Research Service (USDA-ERS). Internet site: http://www.ers.usda.gov/Ambewaves/november03/Features/futureofbiotech.htm (Accessed November 20, 2003b).Google Scholar
U.S. Department of Agriculture—Food Safety and Inspection Service (USDA-FSIS). Internet site: http://www.fsis.usda.gov/oa/pubs/lablterm.htm (Accessed August 4, 2004).Google Scholar
U.S. Department of Agriculture—National Agricultural Statistics Service (USDA-NASS). Agricultural Statistics Summary/Cash Receipts from Marketing:1998-2002. Internet site: http://www.nass.usda.gov/de/new2703.pdf (Accessed May 20, 2003a).Google Scholar
U.S. Department of Agriculture—National Agricultural Statistics Service (USDA-NASS). Agricultural Statistics Summary/Poultry Highlights. Internet site: http://www.nass.usda.gov/de/agstat.htm (Accessed May 20, 2003b).Google Scholar
van der Pol, M., and Ryan, M.. “Using Conjoint Analysis to Establish Consumer Preferences for Fruit and Vegetables.” British Food Journal 98(1996):5–12.CrossRefGoogle Scholar
Voelckner, F. “An Empirical Comparison of Methods for Measuring Consumers’ Willingness to Pay.” Marketing Letters 17(2006):137-49.CrossRefGoogle Scholar
Weise, E. “‘Natural’ Chickens Take Flight.” USA-Today. Internet site: http://www.usatoday.com/news/health/2006-01-23-natural-chickens_x.htm (Accessed August 6, 2006).Google Scholar
West, G.E., Gendron, C., Larue, B., and Lambert, R.. “Consumers’ Valuation of Functional Properties of Foods: Results from a Canada-wide Survey.” Canadian Journal of Agricultural Economics 50(2002):541-58.CrossRefGoogle Scholar
Wittink, D.R., and Cattin, P.. “Commercial Use of Conjoint Analysis: An Update.” Journal of Marketing 53(1989):91-6.CrossRefGoogle Scholar