Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-30T20:56:28.688Z Has data issue: false hasContentIssue false
  • English
  • Français

Willingness-to-Pay for Beef Quality Attributes: A LatentSegmentation Analysis of Korean Grocery Shoppers

Published online by Cambridge University Press:  26 January 2015

Chanjin Chung ,
Brian C. Briggeman  and
Sungill Han
Chanjin Chung
Affiliation:
Department of Agricultural Economics, Oklahoma State University, Stillwater, Oklahoma
Brian C. Briggeman
Affiliation:
Department of Agricultural Economics, Kansas State University, Manhattan, Kansas
Sungill Han
Affiliation:
Department of Livestock Business Management and Marketing Economics, Konkuk University, Seoul, Korea
Get access Rights & Permissions [Opens in a new window]

Abstract

A latent segmentation modeling is used in this study to identify theheterogeneity of willingness-to-pay estimates for quality attributes andcountry-of-origin in the Korean beef market. Three distinctive groups ofgrocery shoppers are identified based on their level of concern (very,moderately, and not too concerned) about the use of antibiotics andgenetically modified organism feed ingredients in beef production. Resultsindicate that the very concerned group values such attributes asantibiotics-free, genetically modified organism-free, and domesticproduction the most among the three groups. Results also suggest that themost important factor in determining grocery shoppers' willingness-to-pay iscountry-of-origin for all three groups.

Keywords

latent segmentationwillingness-to-pay for beef attributesconjoint analysischoice experimentheterogeneity of preferenceQ110Q130Q180
Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 44 , Issue 4 , November 2012 , pp. 447 - 459
Copyright
Copyright © Southern Agricultural Economics Association 2012

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

Abidoye, B.O., Bulut, H., Lawrence, J.D., Mennecke, B., and Townsend, A.M. “U.S. Consumers' Valuation of Quality Attributes in Beef Products.” Journal of Agricultural and Applied Economics 43,1(2011):1–12.S1074070800004016Google Scholar
Boxall, P.C., and Adamowicz, W.L. “Understanding Heterogeneous Preference in Random Utility Models: A Latent Class Approach.” Environmental and Resource Economics 23(2002):421–46.10.1023/A:1021351721619Google Scholar
Briggeman, B.C. and Henderson, J. “The Slow Road Back for the U.S. Livestock Industry.” The Main Street Economist 4,4(2009):1–5.Google Scholar
Carson, R.T., Louviere, J.J., and Wasi, N. “A Cautionary Note on Designing Discrete Choice Experiments: A Comment on Lusk and Norwood's ‘Effect of Experiment Design on Choice-Based Conjoint Valuation Estimates’.” American Journal of Agricultural Economics 91,4(2009):1056–63.10.1111/j.1467-8276.2009.01309.xGoogle Scholar
Chung, C., Han, S., and Boyer, T. “Valuing Quality Attributes and Country Equity in the Korean Beef Market.” Journal of Agricultural Economics 60,3(2009):682–98.10.1111/j.1477-9552.2009.00218.xGoogle Scholar
Food Marketing Institute. Trends in the United States—Consumer Attitudes and the Supermarket. Washington, DC: Research Department, Food Marketing Institute, 2004.Google Scholar
Hynes, S., Hanley, N., and Scarpa, R. “Effects on Welfare Measures of Alternative Means of Accounting for Preference Heterogeneity in Recreational Demand Models.” American Journal of Agricultural Economics 90,4(2008):1011–27.10.1111/j.1467-8276.2008.01148.xGoogle Scholar
Kamakura, W.A., Wedel, M., and Agrawal, J. “Concomitant Variable Latent Class Models for Conjoint Analysis.” International Journal of Research in Marketing 11(1994):451–64.10.1016/0167-8116(94)00004-2Google Scholar
Katsaras, N., Wolfson, P., Kinsey, J., and Senauer, B. “Data Mining: A Segmentation Analysis of U.S. Grocery Shoppers.” Working Paper 01-01. The Retail Food Industry Center, University of Minnesota, 2001.Google Scholar
Korean Census Bureau. Korean Population Census. 2010. Internet site: http://kosis.kr/ (Accessed November 15, 2011).Google Scholar
Krinsky, I., and Robb, A.L. “On Approximating the Statistical Properties of Elasticities.” The Review of Economics and Statistics 64(1986):715–19.Google Scholar
Lusk, J.L., and Norwood, F.B. “Effect of Experimental Design on Choice-Based Conjoint Valuation Estimates.” American Journal of Agricultural Economics 87,3(2005):771–85.10.1111/j.1467-8276.2005.00761.xGoogle Scholar
Lusk, J.L., and Parker, N. “Consumer Preferences for Amount and Type of Fat in Ground Beef.” Journal of Agricultural and Applied Economics 41,1(2009):75–90.S107407080000256XGoogle Scholar
Mennecke, B., Townsend, A., Hayes, D.J., and Lonergan, S. “A Study of Factors that Influence Attitudes Toward Beef Products Using the Conjoint Market Analysis Tool.” Working Paper 06-WP 425. Center for Agricultural and Rural Development, Iowa State University, 2006. Internet site: www.card.iastate.edu (Accessed October 5, 2011).Google Scholar
Morey, E., Thacher, J., and Breffle, W. “Using Angler Characteristics and Attitudinal Data to Identify Environmental Preference Classes: A Latent-Class Model.” Environmental and Resource Economics 34(2006):91–115.10.1007/s10640-005-3794-7Google Scholar
Park, J., Jung, K., and Kim, M. Economic Evaluation of Korean Pork Checkoff Programs. Seoul, Korea: Korean Pork Checkoff Council and Korean Checkoff Research Institute, 2007.Google Scholar
Patunru, A.A., Braden, J.B., and Chattopadhyay, S. “Who Cares About Environmental Stigmas and Does It Matter? A Latent Segmentation Analysis of State Preferences for Real Estate.” American Journal of Agricultural Economics 89,3(2007):712–26.10.1111/j.1467-8276.2007.00988.xGoogle Scholar
Peterson, H.H., and Yoshida, K. “Quality Perception and Willingness-to-Pay for Imported Rice in Japan.” Journal of Agricultural and Applied Economics 36,1(2004):123–41.Google Scholar
Pouta, E., Heikkiläa, J.S., Forsman-Hugga, I.M., and Mäkeläb, J. “Consumer Choice of Broiler Meat: The Effects of Country of Origin and Production Methods.” Food Quality and Preference 21,5(2010):539–46.10.1016/j.foodqual.2010.02.004Google Scholar
Ramaswamy, V., and Cohen, S.H. “Latent Class Models for Conjoint Analysis.” Conjoint Measurement: Methods and Applications, 4th ed. Gustafsson, A., Herrmann, A., and Huber, F., eds. Berlin/Heidelberg: Springer, 2007.Google Scholar
Rho, K., Han, S., and Chung, C. Economic Evaluation of Korean Beef Checkoff Programs. Seoul, Korea: Korean Beef Checkoff Council, 2007.Google Scholar
Rigby, D., and Burton, M. “Preference Heterogeneity and GM Food in the UK.” European Review of Agriculture Economics 32,2(2005):269–88.10.1093/eurrag/jbi009Google Scholar
Ruto, E., Garrod, G., and Scarpa, R. “Valuing Animal Genetic Resources: A Choice Modeling Application to Indigenous Cattle in Kenya.” Agricultural Economics 38(2008):89–98.Google Scholar
Scarpa, R., and Thiene, M. “Destination Choice Models for Rock-Climbing in the North-Eastern Alps: A Latent-Class Approach Based on Intensity of Preferences.” Land Economics 85,3(2005):426–44.Google Scholar
Train, K. Discrete Choice Methods with Simulation. New York: Cambridge University Press, 2003.Google Scholar
Umberger, W.J., Feuz, D.M., Calkins, C.R., and Killinger-Mann, K. “U.S. Consumer Preferences and Willingness to Pay for Domestic Corn-Fed Beef versus International Grass-Fed Beef Measured Through an Experiment Auction.” Agribusiness 18,4(2002):491–504.10.1002/agr.10034Google Scholar
U.S. Meat Export Federation. International Market – Korea. Internet site: http://www.usmef.org/tradelibrary/korea.asp (Accessed November 15, 2011).Google Scholar
Verlegh, P.W.J., and Steenkamp, J.E.M. “A Review and Meta-Analysis of Country-of-Origin Research.” Journal of Economic Psychology 20(1999):521–46.10.1016/S0167-4870(99)00023-9Google Scholar
Wedel, M., and Kamakura, W. Market Segmentation: Conceptual and Methodological Foundations, 2nd ed. Norwell, MA: Kluwer Academic Publishers, 2000.Google Scholar