Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-24T14:54:58.233Z Has data issue: false hasContentIssue false
  • English
  • Français

A Conjoint Analysis of Waterfowl Hunting in Louisiana

Published online by Cambridge University Press:  28 April 2015

Christopher Gan  and
E. Jane Luzar
Christopher Gan
Affiliation:
Department of Economics and Marketing, Lincoln University, Canterbury, New Zealand
E. Jane Luzar
Affiliation:
Department of Agricultural Economics and Agribusiness, Louisiana Agricultural Experiment Station, Louisiana State University Agricultural Center, Louisiana State University, Baton Rouge, Louisiana
Get access Rights & Permissions [Opens in a new window]

Abstract

Conjoint analysis, widely used in marketing research, offers an alternative resource valuation approach suited to outdoor recreation activities characterized as multiattribute. Design, implementation, and interpretation of conjoint analysis are reviewed in the context of recreation applications. Conjoint analysis is used in an analysis of waterfowl hunting in Louisiana. Using primary data collected from a survey of waterfowl hunters, ordered logit is used to estimate willingness-to-pay for recreation experience attributes.

Keywords

conjoint analysisrecreation demandwaterfowl huntingvaluation
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 25 , Issue 2 , December 1993 , pp. 36 - 45
Copyright
Copyright © Southern Agricultural Economics Association 1993

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

Addelman, Sidney. “Orthogonal Main-Effect Plans for Asymmetrical Factorial Experiments.” Technometrics. 4:2(1962): 21–46.CrossRefGoogle Scholar
Cattin, Philippe and Wittink, Dick R.. “Commercial Use of Conjoint Analysis: A Survey.” Journal of Marketing. 46(1982): 44–53.CrossRefGoogle Scholar
Cesario, Frank J. and Knetsch, Jack L.. “Time Bias in Recreation Benefit Estimate.” Water Resource Research. 6(1970): 700–704.CrossRefGoogle Scholar
Chapman, Randall G. and Staelin, Richard. “Exploiting Rank Ordered Choice Set Data within the Stochastic Utility Model.” Journal of Marketing. 15:8(1982): 288–301.CrossRefGoogle Scholar
Clawson, Marion and Knetsch, J. L.. Economics of Outdoor Recreation. Baltimore, Maryland: Johns Hopkins University, 1966.Google Scholar
Cox, D. R.The Analysis of Binary Data. London: Chapman and Hall, 1970.Google Scholar
Dillman, D.A.Mail and Telephone Survey. New York: John Wiley and Sons, 1978.Google Scholar
Farber, Stephen. “The Value of Coastal Wetlands for Recreation: An Application of Travel Cost and Contingent Valuation Methodologies.” Journal of Environmental Management. 26:4(1988): 299–312.Google Scholar
Fieller, E.C. “The Distribution of the Index in a Normal Bivariate Population,” Biometrika, 24(1932): 428–440.CrossRefGoogle Scholar
Green, Paul E. and Wind, Yoram. “New Way to Measure Consumers' Judgments.” Harvard Business Review. 53:7(1975): 107-17.Google Scholar
Green, Paul E. “On the Design of Choice Experiments Involving Multifactor Alternatives.” Journal of Consumer Research. 1:9(1974): 61–68.CrossRefGoogle Scholar
Green, Paul E. and Srinivasan, V.. “Conjoint Analysis in Consumer Research: Issues and Outlook.” Journal of Consumer Research. 5:9(1978): 103–123.CrossRefGoogle Scholar
Green, Paul E., and Rao, Vithala. R.. “Conjoint Measurement for Quantifying Judgmental Data.” Journal of Marketing Research. 8:8(1971): 355–363.Google Scholar
Green, Paul E., and Wind, Yoram. Multiattribute Decisions In Marketing: A Measurement Approach. Hinsdale, Illinois: The Dryden Press, 1973.Google Scholar
Goodman, Allen C. “Identifying Willingness-to-Pay for Heterogeneous Goods with Factorial Survey Methods.” Journal of Environmental Economics and Management. 16(1989): 58–79.CrossRefGoogle Scholar
Hair, J.F., Anderson, R.E., Tatham, R.L., and Black, W.C.. Multivariate Data Analysis with Readings. New York, New York: Macmillan Publishing Company, 1991.Google Scholar
Halbrendt, C.K., Wirth, F.F., and Vaughn, G.F.. “Conjoint Analysis of the Mid-Atlantic Food-Fish Market for Farm-Raised Hybrid Striped Bass.” Southern Journal of Agricultural Economics. 23:1(1991):155–164.Google Scholar
Harrell, Frank E. Jr. “The Logist Procedure.” SUGI Manual SAS Institute, Cary, NC, 1980.Google Scholar
Judge, George G, Hill, R. Cater, Griffiths, William E., Lutkepohl, Helmut, and Lee, Tsoung-Chao. Introduction to the Theory and Practice of Econometrics. New York: John Wiley and Sons, 1988.CrossRefGoogle Scholar
Knetsch, J. L. “Outdoor Recreation Demands and Benefits.” Land Economics. 39(1963): 387–396.CrossRefGoogle Scholar
Louisiana Department of Wildlife and Fisheries. Wildlife Resources of Louisiana. Baton Rouge, Louisiana, 1987.Google Scholar
McFadden, Daniel. “Conditional Logit Analysis of Qualitative Choice Behavior.” In Zarembka, P. (ed.), Frontiers in Econometrics. New York: Academic Press, 1974, pp. 105–142.Google Scholar
Mackenzie, John. “Valuation of Open Space as a Composite Environmental Good via Conjoint Analysis.” Paper Presented at the Annual American Agricultural Economics Association Meeting, Manhattan, Kansas, August 1991.Google Scholar
Mackenzie, John. “Conjoint Analysis of Waterfowl Hunting As A Composite Recreation Good.” Paper Presented at the Annual American Economics Association Meeting, Vancouver, Canada, August 1990.Google Scholar
Maddala, G. S.Limited Dependent and Qualitative Variables in Econometrics. Cambridge, MA: Cambridge University Press, 1983.CrossRefGoogle Scholar
Miller, Jon R. and Hay, Michael J.. “Determinants of Hunter Participation: Duck Hunting in the Mississippi Flyway.” American Journal of Agricultural Economics. 63:4(1981): 677–684.CrossRefGoogle Scholar
Pindyck, Robert S. and Rubinfeld, Daniel L.. Econometric Models and Economic Forecasts. New York: McGraw-Hill Book Company, 1976.Google Scholar
Saxton, Arnold, Frederick, Rebecca, and Wright, Vernon. Department of Experimental Statistics, Louisiana State University, Baton Rouge, Louisiana, 1990. Personal Communication.Google Scholar
White, K.E., Haun, S.A., Horsman, N.G., and Wong, S.D.. SHAZAM Econometrics Computer Program. New York: McGraw-Hill Book Company, 1988.Google Scholar