Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-27T21:53:49.649Z Has data issue: false hasContentIssue false

Comparing Consumer Preferences for Livestock Production Process Attributes Across Products, Species, and Modeling Methods

Published online by Cambridge University Press:  12 June 2017

Abstract

Consumer preferences for four livestock products were investigated to determine consumer willingness to pay (WTP) for livestock production process attributes. We use an inferred method of attribute nonattendance (ANA) using the coefficient of variation on individual specific parameter estimates to assess the variability of preference intensity for various product characteristics. We find that accounting for ANA did not significantly impact mean estimates of WT P. Implications of our findings on the reliability of existing work in the area of consumer preferences for animal welfare attributes are discussed.

Type
Emerging Scholar Papers
Copyright
Copyright © Southern Agricultural Economics Association 2014

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

Adamowicz, W., Louviere, J., and Williams, M.. “Combining Revealed and Stated Preference Methods for Valuing Environmental Amenities.” Journal of Environmental Economics and Management 26(1994): 271-92.Google Scholar
Alfnes, F.Stated Preferences for Imported and Hormone-Treated Beef: Application of a Mixed Logit Model.” European Review of Agricultural Economics 31(2004): 1937.Google Scholar
Bech, M. and Gyrd-Hansen, D.. “Effects Coding in Discrete Choice Experiments.” Health Economics 14(2005): 1079-83.CrossRefGoogle ScholarPubMed
Bonnet, C., and Simioni, M.. “Assessing Consumer Response to Protected Designation of Origin Labelling: A Mixed Multinomial Logit Approach.” European Review of Agriculture Economics 28(2001): 433-49.Google Scholar
Carlsson, F., Frykblom, P., and Lagerkvist, C.J.. “Consumer Willingness to Pay for Farm Animal Welfare: Mobine Abattoirs versus Transportation to Slaughter.” European Review of Agriculture Economics 34(2007a):321—44.Google Scholar
Carlsson, F.. “Farm Animal Welfare-Testing for Market Failure.” Journal of Agricultural and Applied Economics 39(2007b): 6173.Google Scholar
Cicia, G., Del Guidice, T., and Scarpa, R.. “Consumers’ Perception of Quality in Organic Food: A Random Utility Model under Preference Heterogeneity and Choice Correlation from Rank Orderings.” British Food Journal 104(2002): 200-13.CrossRefGoogle Scholar
Fleming, C.M., and Bowden, M.. “Web-Based Surveys as an Alternative to Traditional Mail Methods.” Journal of Environmental Management 90(2009): 284-92.Google Scholar
Gao, Z., and Schroeder, T.C.. “Effects of Label Information on Consumer Willingness-to-Pay for Food Attributes.” American Journal of Agricultural Economics 91(2009): 795809.CrossRefGoogle Scholar
Greene, W.H. NLOGIT Version 5 Reference Guide. Plainview, NY: Econometric Software, Inc., 2012.Google Scholar
Hensher, D., and Greene, W.. “Non-Attendance and Dual Processing of Common-Metric Attributes in Choice Analysis: A Latent Class Specification.” Empirical Economics 39(2010): 413-26.Google Scholar
Hensher, D.A., Rose, J., and Greene, W.H.. “The Implications on Willingness to Pay of Respondents Ignoring Specific Attributes.” Transportation 32(2005): 203222.Google Scholar
Hess, S., and Hensher, D.A.. “Using Conditioning on Observed Choices to Retrieve Individual-Specific Attribute Processing Strategies.” Transportation Research Part B: Methodological 44(2010):781-90.Google Scholar
Hole, A.A Comparison of Approaches to Estimating Confidence Intervals for Willingness to Pay Measures.” Health Economics 16(2007):827-40.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
Layton, D., and Hensher, D.A.. 2008. Aggregationof Common-metric Attributes in Preference Revelation in Choice Experimentsand Implications for Willingness to Pay. Institute of Transportand Logistics Studies, The Australian Key Centre in Transport and LogisticsManagement, The University of Sydney, Sydney, Australia. ISSN 1832-570X.Google Scholar
Lijenstolpe, C.Evaluating Animal Welfare with Choice Experiments: An Application to Swedish Pig Production.” Agribusiness 21(2008): 6784.Google Scholar
Loureiro, M.L., and Umberger, W.J.. “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 32(2007): 496514.Google Scholar
Louviere, J.J., Islam, T., Wasi, N., Street, D., and Burgess, L.. “Designing Discrete Choice Experiments: Do Optimal Designs Come at a Price?The Journal of Consumer Research 35(2008): 360-75.Google Scholar
Lusk, J.L.Effects of Cheap Talk on Consumer Willingness-to-Pay for Golden Rice.” American Journal of Agricultural Economics 85(2003): 840-56.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(2005): 771785.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.Google Scholar
Lusk, J.L., Roosen, J., and Fox, J.. “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): 1629.Google Scholar
Marta-Pedroso, C., Freitas, H., and Domingos, T.. “Testing for the Survey Mode Effect on Contingent Valuation Data Quality: A Case Study of Web Based versus In-Person Interviews.” Ecological Economics 62(2007): 388-98.Google Scholar
McKendree, M.G.S., Olynk, N. Widmar, D.L. Ortega, , and Foster, K.A.. “Consumer Preferences for Verified Pork-Rearing Practices in the Production of Ham Products.” Journal of Agricultural and Resource Economics 38(2013):1—20.Google Scholar
Nocella, G., Boecker, A., Hubbard, L., and Scarpa, R.. “Eliciting Consumer Preferences for Certified Animal-Friendly Foods: Can Elements of the Theory of Planned Behavior Improve Choice Experiment Analysis?Psychology and Marketing 29(2012):850-68.CrossRefGoogle Scholar
Nocella, G., Hubbard, L.Lionel, and Scarpa, R.. “Farm Animal Welfare, Consumer Willingness to Pay, and Trust: Results of a Cross-National Survey.” Applied Economic Perspectives and Policy 32(2010):275-97.Google Scholar
Olynk, N.J., and Ortega, D.L.. “Consumer Preferences for Verified Dairy Cattle Management Practices in the Production of Yogurt and Ice Cream.” Food Control 30(2013): 298305.Google Scholar
Olynk, N.J., Tonsor, G.T., and Wolf, C.A.. “Consumer Willingness to Pay for Livestock Credence Attribute Claim Verification.” Journal of Agricultural and Resource Economics 35(2010): 261-80.Google Scholar
Olsen, S.B.Choosing between Internet and Mail Survey Modes for Choice Experiment Surveys Considering Non-Market Goods.” Environmental and Resource Economics 44(2009): 591610.Google Scholar
Ortega, D.L., Holly, H. L. Wu, Wang, and Olynk, N.. “Modeling Heterogeneity in Consumer Preferences for Select Food Safety Attributes in China.” Food Policy 36(2011): 318-24.Google Scholar
Poe, G.L., Giraud, K.L., and Loomis, J.B.. “Computational Methods for Measuring the Difference of Empirical Distributions.” American Journal of Agricultural Economics 87(2005): 353365.Google Scholar
Scarpa, R., T.J.Gilbride, , Campbell, D., and Hensher, D.A.. “Modeling Attribute Non-Attendance inChoice Experiments for Rural Landscape Valuation.” EuropeanReview of Agriculture Economics 36,2(2009):151-74.Google Scholar
Scarpa, R., and Rose, J.M.. “Design Efficiency for Non-Market Evaluation with Choice Modelling: How to Measure It, What to Report and Why.” The Australian Journal of Agricultural and Resource Economics 52(2008):253—82.Google Scholar
Scarpa, R., Zanoli, R., Bruschi, V., and Naspetti, S.. “Inferred and Stated Attribute Non-Attendance in Food Choice Experiments.” American Journal of Agricultural Economics 95,1(2013):165—80.CrossRefGoogle Scholar
Schenker, N., and Gentleman, J.F.. “On Judging Significance of Difference by Examining the Overlap between Confidence Intervals.” The American Statistician 53(2001):182—86.Google Scholar
Tonsor, G.T., Olynk, N., and Wolf, C.. “Consumer Preferences for Animal Welfare Attributes: The Case of Gestation Crates.” Journal of Agricultural and Applied Economics 41(2009):713—30.Google Scholar
Tonsor, G.T., Schroeder, T.C., Fox, J.A., and Biere, A.. “European Preferences for Beef Steak Attributes.” Journal of Agricultural and Resource Economics 30(2005): 367-80.Google Scholar
Tonsor, G.T., and Wolf, C.A.. “Drivers of Resident Support for Animal Care Oriented Ballot Initiatives.” Journal of Agricultural and Applied Economics 42(2010): 419-28.CrossRefGoogle Scholar
Tonsor, G.T., Wolf, C., and Olynk, N.. “Consumer Voting and Demand Behavior Regarding Swine Gestation Crates.” Food Policy 34(2009): 492-98.Google Scholar
Train, K.Recreation Demand Models with Taste Differences over People.” Land Economics 74(1998):230-39.Google Scholar
Train, K.E. 2003. Discrete Choice Methods with Simulation. Cambridge, UK: Cambridge University Press.Google Scholar
U.S. Department of Agriculture/Grain Inspection, Packers and Stockyards Administration. “Federal Grain Inspection Service Directive No.9180.79.Google Scholar
Appendix 1: Process Verified Program,” USDA/ GISPA, January 17, 2007. Internet site: www.gipsa.usda.gov/fgis/insp_weigh/inspwgh/pvp/9180-79.pdf (Accessed January 12, 2012).Google Scholar
Vermuelen, B., Goos, P., Scarpa, R., and Vandebroek, M.. “Bayesian Conjoint Choice Designs for Measuring Willingness to Pay.” Environmental and Resource Economics 48(2011):129-49.Google Scholar
Wolf, C.A., Tonsor, G.T., and Olynk, N.J.. “Understanding U.S. Consumer Demand for Milk Production Attributes.” Journal of Agricultural and Resource Economics 36(2011): 326-42.Google Scholar