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An Analysis of Consumer Preferences for Value-Added Seafood Products Derived from Crawfish

Published online by Cambridge University Press:  15 September 2016

R. Wes Harrison ,
Timothy Stringer  and
Witoon Prinyawiwatkul
R. Wes Harrison
Affiliation:
Department of Agricultural Economics and Agribusiness, Louisiana State University Agricultural Center
Timothy Stringer
Affiliation:
Department of Agricultural Economics and Agribusiness, Louisiana State University Agricultural Center
Witoon Prinyawiwatkul
Affiliation:
Department of Food Science, Louisiana State University Agricultural Center
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Abstract

Conjoint analysis is used to evaluate consumer preferences for three consumer-ready products derived from crawfish. Utility functions are estimated using two-limit tobit and ordered probit models. The results show women prefer a baked nugget or popper type product, whereas 35- to 44-year-old men prefer a microwavable nugget or patty type product. The results also show little difference between part-worth estimates or predicted rankings for the tobit and ordered probit models, implying the results are not sensitive to assumptions regarding the ordinal and cardinal nature of respondent preferences.

Keywords

conjoint analysisconsumer-ready productscrawfishordered probittwo-limit tobit
Type
Articles
Information
Agricultural and Resource Economics Review , Volume 31 , Issue 2 , October 2002 , pp. 157 - 170
Copyright
Copyright © 2002 Northeastern Agricultural and Resource Economics Association 

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References

Acito, F., and Jain, A. K. (1980). “Evaluation of Conjoint Analysis Results: A Comparison of Methods.” Journal of Marketing Research 17, 106–112.Google Scholar
Anderson, J. L., and Bettencourt, S. (1993). “A Conjoint Approach to Model Product Preferences: The New England Market for Fresh and Frozen Salmon.” Marine Resource Economics 8(1), 31–47.Google Scholar
Bacon, J. R., Halbrendt, C. K., and Toensmeyer, U. C. (1991). Journal of Food Distribution Research 22(1), 116–117.Google Scholar
Baker, G. A., and Crosbie, P. J. (1993). “Measuring Food Safety Preferences: Identifying Consumer Segments.” Journal of Agricultural and Resource Economics 18(2), 277–287.Google Scholar
Boyle, K., Holmes, T. P., Teisl, M., and Roe, B. (2001). “A Comparison of Conjoint Analysis Response Formats.” American Journal of Agricultural Economics 83(2), 441–454.CrossRefGoogle Scholar
Bretton-Clark Co. (1988). Conjoint Designer software program. New York: Bretton-Clark Co.Google Scholar
Gates, K. W., and Parker, A. H. (1992). “Characterization of Minced Meat Extracted from Blue Crab Picking Plant By-products.” Journal of Food Science 57, 267–270.Google Scholar
Greene, W. H. (2000). Econometric Analysis, 4th edition. Upper Saddle River, NJ: Prentice-Hall, Inc. Google Scholar
Halbrendt, C. K., Wirth, F. F., and Vaughn, G. F. (1991). “Conjoint Analysis of the Mid-Atlantic Food-Fish Market for Farm-Raised Hybrid Striped Bass.” Southern Journal of Agricultural Economics 23(1), 155–163.Google Scholar
Harrison, R. W., Gillespie, J., and Fields, D. (2001). “Theoretical and Empirical Considerations of Eliciting Preferences and Model Estimation in Conjoint Analysis.” Selected paper presented at the annual meetings of the American Agricultural Economics Association, Chicago, IL.Google Scholar
Harrison, R. W., Özayan, A., and Meyers, S. P. (1998). “A Conjoint Analysis of New Food Products Processed from Underutilized Small Crawfish.” Journal of Agricultural and Applied Economics 30(2), 257–265.CrossRefGoogle Scholar
Holland, D., and Wessells, C. R. (1998). “Predicting Consumer Preferences for Fresh Salmon: The Influence of Safety Inspection and Production Method Attributes.” Agricultural and Resource Economics Review 27(1), 1–14.CrossRefGoogle Scholar
Huang, C. L., and Fu, J. (1995). “Conjoint Analysis of Consumer Preferences and Evaluations of a Processed Meat.” Journal of International Food and Agribusiness Marketing 7, 62–75.Google Scholar
Lee, E., Meyers, S. P., and Godber, J. S. (1993). “A Minced Meat Crabcake from Blue Crab Processing By-products: Development and Sensory Evaluation.” Journal of Food Science 58(1), 12–21.Google Scholar
Long, J. S. (1997). Regression Models for Categorical and Limited Dependent Variables. Thousand Oaks, CA: SAGE Publications.Google Scholar
Louisiana State University, Agricultural Center. (2000). “Louisiana Summary: Agriculture and Natural Resources.” Baton Rouge, LA.Google Scholar
MacKenzie, J. (1990). “Conjoint Analysis of Deer Hunting.” Northeastern Journal of Agricultural and Resource Economics 19(2), 109–117.CrossRefGoogle Scholar
MacKenzie, J. (1993). “A Comparison of Contingent Preference Models.” American Journal of Agricultural Economics 75, 593–603.Google Scholar
Özayan, A. (1997). “Market Analysis of New Minced-Meat Products Made from Undersized Crawfish.” Unpublished M.S. thesis, Louisiana State University, Baton Rouge.Google Scholar
Pigott, G. Μ. (1994). “The Status and Future of Aquatic Food Research in the U.S.” Report presented at the International Seafood Research Meeting held at Mie University, Tsu, Japan.Google Scholar
Prentice, B. E., and Benell, D. (1992). “Determinants of Empty Returns by U.S. Refrigerated Trucks: Conjoint Analysis Approach.” Canadian Journal of Agricultural Economics 40(1), 109–127.Google Scholar
Roe, B., Boyle, K. J., and Teisl, M. F. (1996). “Using Conjoint Analysis to Derive Estimates of Compensating Variation.” Journal of Environmental Management 31(2), 145–159.Google Scholar
Stevens, T. H., Barrett, C., and Willis, C. E. (1997). “Conjoint Analysis of Groundwater Protection Programs.” Agricultural and Resource Economics Review 27(2), 229–246.Google Scholar
Sy, H. A., Faminow, M. D., Johnson, G. V., and Crow, G. (1997). “Estimating the Values of Cattle Characteristics Using an Ordered Probit Model.” American Journal of Agricultural Economics 79(2), 463–476.CrossRefGoogle Scholar
U.S. Department of Commerce, National Oceanic and Atmospheric Administration. (2001). “Fisheries of the United States, 2000.” Fishery Statistics and Economics Division, NOAA, Silver Spring, MD.Google Scholar
Yen, S. T., Dellenbarger, L. E., and Schupp, A. R. (1995). “Determinants of Participation and Consumption: The Case of Crawfish in South Louisiana” Journal of Agricultural and Applied Economics 27(1), 253–262.CrossRefGoogle Scholar
Yoo, D., and Ohta, H. (1995). “Optimal Pricing and Product-Planning for New Multiattribute Products Based on Conjoint Analysis.” International Journal of Production Economics 38, 245–253.Google Scholar
Zar, J. H. (1984). Biostatistical Analysis, 2nd edition. Englewood Cliffs, NJ: Prentice-Hall, Inc. Google Scholar