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Processor Willingness to Adopt a Crawfish Peeling Machine: An Application of Technology Adoption under Uncertainty

Published online by Cambridge University Press:  26 January 2015

Jeffrey Gillespie
Affiliation:
Department of Agricultural Economics and Agribusiness, Louisiana State University, Baton Rouge, LA 70803
Darius Lewis
Affiliation:
U.S. Department of Agriculture, National Agricultural Statistics Service, Lansing, MI

Abstract

Crawfish processors' ex ante adoption rates of three hypothetical crawfish peeling machines are assessed using a polychotomous-choice elicitation format. Adoption rates would likely range from 23% to 70%, depending upon which machine was offered and whether it was purchased or leased. Processors most likely to adopt are determined using ordered probit analysis. Likely adopters would be larger, more diversified processors with greater resources and longer planning horizons.

Type
Articles
Copyright
Copyright © Southern Agricultural Economics Association 2008

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References

Alberini, A., Boyle, K., and Welsh, M.Analysis of Contingent Valuation Data with Multiple Bids and Response Options Allowing Respondents to Express Uncertainty.” Journal of Environmental Economics and Management 45,1(2003): 40–62.Google Scholar
Arrow, K., Solow, R., Prtney, P.R., Learner, E.E., Radner, R., and Schuman, H.Report of the NOAA Panel on Contingent Valuation.” Federal Register 58(1993):4601–14.Google Scholar
Blarney, R.K., Bennett, J.W., and Morrison, M.D.Yea Saying in Contingent Valuation Surveys.” Land Economics 75(1999): 126–41.Google Scholar
Boehlje, M.D., and Eidman, V.R. Farm Management. New York: John Wiley & Sons, 1984.Google Scholar
Caudill, S.B., and Groothuis, P.A.Modeling Hidden Alternatives in Random Utility Models: An Application to “Don't Know” Responses in Contingent Valuation.” Land Economics 81, 3(2005):445–54.Google Scholar
Champ, P.A., Bishop, R.C., Brown, T.C., and McCollum, D.W.Using Donation Mechanisms to Value Nonuse Benefits from Public Goods.” Journal of Environmental Economics and Management 33(1997):151–62.Google Scholar
Feder, G., Just, R.E., and Zilberman, D.Adoption of Agricultural Innovations in Developing Countries: A Survey.” Economic Development and Cultural Change 33(1985):255–98.Google Scholar
Gillespie, J.M., and Capdeboscq, M. Factors to Be considered in the Crawfish Peeling Machine Decision. Baton Rouge, LA: Dept. of Agricultural Economics and Agribusiness, Louisiana State University Agricultural Center, D.A.E. Research Report 705, 1996.Google Scholar
Gillespie, J.M., and Lewis, D. Crawfish Processor Preferences for a Crawfish Peeling Machine. Baton Rouge, LA: Louisiana State University Agricultural Center, Bulletin 885, 2005.Google Scholar
Greene, W.H. Econometric Analysis, 5th ed. Upper Saddle River, NJ: Prentice-Hall, 2003.Google Scholar
Groothuis, P.A., and Whitehead, J.C.Does Don't Know Mean No? Analysis of ‘Don't Know’ Responses in Dichotomous Choice Contingent Valuation Questions.” Applied Economics 34(2002): 1935–40.Google Scholar
Hubbell, B.J., Marra, M.C., and Carlson, G.A.Estimating the Demand for a New Technology: BT Cotton and Insecticide Policies.” American Journal of Agricultural Economics 82(February 2000): 118132.Google Scholar
Hudson, D., and Hite, D.Production Willingness to Pay for Precision Application Technology: Implications for Government and the Technology Industry.” Canadian Journal of Agricultural Economics 51(2003):3953.CrossRefGoogle Scholar
Kenkel, P.L., and Norris, P.E.Agricultural Producers' Willingness to Pay for Real-Time Meso scale Weather Information.” Journal of Agricultural and Resource Economics 20,2(1995): 356–72.Google Scholar
Kinnucan, H., Hatch, U., Molnar, J.J., and Venkateswaran, M.Scale Neutrality of Bovine Somatotropin: Ex Ante Evidence from the Southeast.” Southern Journal of Agricultural Economics 22,2(December 1990):112.Google Scholar
Li, C.Z., and Mattson, L.Discrete Choice under Preference Uncertainty: An Improved Structural Model for Contingent Valuation.” Journal of Environmental Economics and Management 28(1995):256–69.Google Scholar
Marra, M.C., and Carlson, G.A.Agricultural Technology and Risk, Chapter 15.” The Role of Risk in Agriculture. Just, R. and Pope, R. eds. Norwell, MA: Kluwer Academic Publications, 2002.Google Scholar
Qiam, M., and de Janvry, A.Genetically Modified Crops, Corporate Pricing Strategies, and Farmers' Adoption: The Case of BT Cotton in Argentina.” American Journal of Agricultural Economics 85(2003):814–28.Google Scholar
Ready, R.C., Navrud, S., and Dubourg, W.R.How Do Respondents with Uncertain Willingness to Pay Answer contingent Valuation Questions?Land Economics 77(2001):315-26.Google Scholar
Ready, R.C., Whitehead, J.C., and Blomquist, G.C.Contingent Valuation When Respondents are Ambivalent.” Journal of Environmental Economics and Management 29(1995):181–96.CrossRefGoogle Scholar
Crawfish Tail Meat from China: Investigation No. 731-TA-752 (Review). Washington, DC: U.S. International Trade Commission, Publication 3614, July 2003.Google Scholar
van Kooten, G.C., Krcmar, E., and Bulte, E.H.Preference Uncertainty in Non-Market Valuation: A Fuzzy Approach.” American Journal of Agricultural Economics 83(2001):487500.Google Scholar
Wang, H.Treatment of Don't Know Responses in Contingent Valuation Surveys: A Random Valuation Model.” Journal of Environmental Economics and Management 32(1997):219–32.Google Scholar
Whitehead, J.C., Blomquist, G.C., Ready, R.C., and Huang, J.Construct Validity of Dichotomous and Polychotomous Choice Contingent Valuation Questions.” Environmental and Resource Economics 11(1998):107–11.Google Scholar