IDEAS home Printed from https://ideas.repec.org/a/ags/joaaec/45532.html
   My bibliography  Save this article

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

Author

Listed:
  • Gillespie, Jeffrey M.
  • Lewis, Darius

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.

Suggested Citation

  • Gillespie, Jeffrey M. & Lewis, Darius, 2008. "Processor Willingness to Adopt a Crawfish Peeling Machine: An Application of Technology Adoption under Uncertainty," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 40(1), pages 1-15, April.
  • Handle: RePEc:ags:joaaec:45532
    DOI: 10.22004/ag.econ.45532
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/45532/files/jaae-40-01-369.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.45532?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. R. K. Blamey & J. W. Bennett & M. D. Morrison, 1999. "Yea-Saying in Contingent Valuation Surveys," Land Economics, University of Wisconsin Press, vol. 75(1), pages 126-141.
    2. Darren Hudson & Diane Hite, 2003. "Producer Willingness to Pay for Precision Application Technology: Implications for Government and the Technology Industry," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 51(1), pages 39-53, March.
    3. Kenkel, Philip L. & Norris, Patricia E., 1995. "Agricultural Producers' Willingness To Pay For Real-Time Mesoscale Weather Information," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 20(2), pages 1-17, December.
    4. Steven B. Caudill & Peter A. Groothuis, 2005. "Modeling Hidden Alternatives in Random Utility Models: An Application to "Don’t Know" Responses in Contingent Valuation," Land Economics, University of Wisconsin Press, vol. 81(3).
    5. Alberini, Anna & Boyle, Kevin & Welsh, Michael, 2003. "Analysis of contingent valuation data with multiple bids and response options allowing respondents to express uncertainty," Journal of Environmental Economics and Management, Elsevier, vol. 45(1), pages 40-62, January.
    6. Matin Qaim & Alain de Janvry, 2003. "Genetically Modified Crops, Corporate Pricing Strategies, and Farmers' Adoption: The Case of Bt Cotton in Argentina," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 814-828.
    7. Kinnucan, Henry & Hatch, Upton & Molnar, Joseph J. & Venkateswaran, Meenakshi, 1990. "Scale Neutrality of Bovine Somatotropin: Ex Ante Evidence from the Southeast," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 22(2), pages 1-12, December.
    8. Peter Groothuis & John Whitehead, 2002. "Does don't know mean no? Analysis of 'don't know' responses in dichotomous choice contingent valuation questions," Applied Economics, Taylor & Francis Journals, vol. 34(15), pages 1935-1940.
    9. Ready Richard C. & Whitehead John C. & Blomquist Glenn C., 1995. "Contingent Valuation When Respondents Are Ambivalent," Journal of Environmental Economics and Management, Elsevier, vol. 29(2), pages 181-196, September.
    10. Richard C. Ready & Ståle Navrud & RW. Richard Dubourg, 2001. "How Do Respondents with Uncertain Willingness to Pay Answer Contingent Valuation Questions?," Land Economics, University of Wisconsin Press, vol. 77(3), pages 315-326.
    11. Bryan J. Hubbell & Michele C. Marra & Gerald A. Carlson, 2000. "Estimating the Demand for a New Technology: Bt Cotton and Insecticide Policies," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(1), pages 118-132.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nyaupane, Narayan P. & Gillespie, Jeffrey M., 2011. "Factors Influencing Producers’ Marketing Decisions in the Louisiana Crawfish Industry," Journal of Food Distribution Research, Food Distribution Research Society, vol. 42(2), pages 1-11, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Seon-Ae Kim & Jeffrey M. Gillespie & Krishna P. Paudel, 2008. "Rotational grazing adoption in cattle production under a cost-share agreement: does uncertainty have a role in conservation technology adoption?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 52(3), pages 235-252, September.
    2. Svedsater, Henrik, 2007. "Ambivalent statements in contingent valuation studies: inclusive response formats and giving respondents time to think," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 51(1), pages 1-17.
    3. Patricia Champ & Richard Bishop, 2001. "Donation Payment Mechanisms and Contingent Valuation: An Empirical Study of Hypothetical Bias," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 19(4), pages 383-402, August.
    4. Mark Morrison & Thomas Brown, 2009. "Testing the Effectiveness of Certainty Scales, Cheap Talk, and Dissonance-Minimization in Reducing Hypothetical Bias in Contingent Valuation Studies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 44(3), pages 307-326, November.
    5. Emmanuel Flachaire & Guillaume Hollard, 2007. "Model Selection in Iterative Valuation Questions," Revue d'économie politique, Dalloz, vol. 117(5), pages 853-865.
    6. Richard T. Carson, 2011. "Contingent Valuation," Books, Edward Elgar Publishing, number 2489.
    7. Sabina Shaikh & Lili Sun & G. Cornelis van Kooten, 2005. "The Effect of Uncertainty on Contingent Valuation Estimates: A Comparison," Working Papers 2005-15, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    8. Christian A. Vossler & Robert G. Ethier & Gregory L. Poe & Michael P. Welsh, 2003. "Payment Certainty in Discrete Choice Contingent Valuation Responses: Results from a Field Validity Test," Southern Economic Journal, Southern Economic Association, vol. 69(4), pages 886-902, April.
    9. Joseph Cooper & Daniel Hellerstein, 2009. "Do Government Economists Value AAEA Conferences?," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(4), pages 914-930, December.
    10. Christian A. Vossler & Robert G. Ethier & Gregory L. Poe & Michael P. Welsh, 2003. "Payment Certainty in Discrete Choice Contingent Valuation Responses: Results from a Field Validity Test," Southern Economic Journal, John Wiley & Sons, vol. 69(4), pages 886-902, April.
    11. Nikita Lyssenko & Roberto Mart󹑺-Espiñeira, 2012. "Respondent uncertainty in contingent valuation: the case of whale conservation in Newfoundland and Labrador," Applied Economics, Taylor & Francis Journals, vol. 44(15), pages 1911-1930, May.
    12. Kelvin Balcombe & Iain Fraser, 2009. "Dichotomous-choice contingent valuation with 'dont know' responses and misreporting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1137-1152.
    13. Christian A. Vossler & Robert G. Ethier & Gregory L. Poe & Michael P. Welsh, 2003. "Payment Certainty in Discrete Choice Contingent Valuation Responses: Results from a Field Validity Test," Southern Economic Journal, John Wiley & Sons, vol. 69(4), pages 886-902, April.
    14. Broberg, Thomas & Brännlund, Runar, 2008. "An alternative interpretation of multiple bounded WTP data--Certainty dependent payment card intervals," Resource and Energy Economics, Elsevier, vol. 30(4), pages 555-567, December.
    15. Karen Blumenschein & GlennC. Blomquist & Magnus Johannesson & Nancy Horn & Patricia Freeman, 2008. "Eliciting Willingness to Pay Without Bias: Evidence from a Field Experiment," Economic Journal, Royal Economic Society, vol. 118(525), pages 114-137, January.
    16. Akter, Sonia & Brouwer, Roy & Brander, Luke & van Beukering, Pieter, 2009. "Respondent uncertainty in a contingent market for carbon offsets," Ecological Economics, Elsevier, vol. 68(6), pages 1858-1863, April.
    17. Sun, Lili & van Kooten, G. Cornelis, 2005. "Fuzzy Logic and Preference Uncertainty in Non-market Valuation," Working Papers 37021, University of Victoria, Resource Economics and Policy.
    18. Stithou, Mavra, 2009. "Respondent Certainty and Payment Vehicle Effect in Contingent Valuation: an Empirical Study for the Conservation of Two Endangered Species in Zakynthos Island, Greece," Stirling Economics Discussion Papers 2009-21, University of Stirling, Division of Economics.
    19. Flachaire, Emmanuel & Hollard, Guillaume, 2007. "Starting point bias and respondent uncertainty in dichotomous choice contingent valuation surveys," Resource and Energy Economics, Elsevier, vol. 29(3), pages 183-194, September.
    20. Shaikh, Sabina L. & Sun, Lili & Cornelis van Kooten, G., 2007. "Treating respondent uncertainty in contingent valuation: A comparison of empirical treatments," Ecological Economics, Elsevier, vol. 62(1), pages 115-125, April.

    More about this item

    Keywords

    Agribusiness; Farm Management; Food Consumption/Nutrition/Food Safety; Industrial Organization;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:joaaec:45532. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/saeaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.