IDEAS home Printed from https://ideas.repec.org/p/ags/aaea11/103524.html
   My bibliography  Save this paper

Consumer WTP for Blueberry Attributes: A Hierarchical Bayesian Approach in the WTP Space

Author

Listed:
  • Shi, Lijia
  • House, Lisa
  • Gao, Zhifeng

Abstract

A stated preference experiment is conducted to elicit consumer WTPs for various blueberry attributes. The mixed logit model is employed to account for consumer heterogeneity. The model is set up in the WTP space where the distributions of WTPs are directly specified. Considering the high diversity of consumer perception and the remarkable benefits from differential marketing, we apply the hierarchical Bayesian approach and the discussion is based on the individual level WTP estimates. The results show that “local produced” attribute is preferred over simply “produced in the U.S.” by most respondents. By contrast, less than 50% of the respondents are willing to pay premium for organic blueberries. In addition, hardly any relationship between demographics and WTPs is detected. Demographic information seems to have little explanation power for consumer perception in small purchases like fruits or vegetables. In this light, the hierarchical Bayesian approach is critical to the practice of differential marketing strategies.

Suggested Citation

  • Shi, Lijia & House, Lisa & Gao, Zhifeng, 2011. "Consumer WTP for Blueberry Attributes: A Hierarchical Bayesian Approach in the WTP Space," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103524, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea11:103524
    DOI: 10.22004/ag.econ.103524
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/103524/files/AAEA%20paper%20Shi.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.103524?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
    ---><---

    References listed on IDEAS

    as
    1. Johansson-Stenman Olof & Svedsäter Henrik, 2008. "Measuring Hypothetical Bias in Choice Experiments: The Importance of Cognitive Consistency," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 8(1), pages 1-10, September.
    Full references (including those not matched with items on IDEAS)

    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. Frode Alfnes & Chengyan Yue & Helen H. Jensen, 2010. "Cognitive dissonance as a means of reducing hypothetical bias," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 37(2), pages 147-163, June.
    2. Araña, Jorge E. & León, Carmelo J., 2013. "Dynamic hypothetical bias in discrete choice experiments: Evidence from measuring the impact of corporate social responsibility on consumers demand," Ecological Economics, Elsevier, vol. 87(C), pages 53-61.
    3. Svenningsen, Lea S. & Jacobsen, Jette Bredahl, 2018. "Testing the effect of changes in elicitation format, payment vehicle and bid range on the hypothetical bias for moral goods," Journal of choice modelling, Elsevier, vol. 29(C), pages 17-32.
    4. Fredrik Carlsson & Jorge García & Åsa Löfgren, 2010. "Conformity and the Demand for Environmental Goods," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 47(3), pages 407-421, November.
    5. Scharf, Kim; Smith, Sarah, 2010. "Rational Inattention to Subsidies for Charitable Contributions," CAGE Online Working Paper Series 02, Competitive Advantage in the Global Economy (CAGE).
    6. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part I. Macro-scale analysis of literature and integrative synthesis of empirical evidence from applied economics, experimental psychology and neuroimag," Journal of choice modelling, Elsevier, vol. 41(C).
    7. Christian Pfarr & Andreas Schmid & Morten Raun Mørkbak, 2018. "Modelling Heterogeneous Preferences for Income Redistribution–An Application of Continuous and Discrete Distributions," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(2), pages 270-294, June.
    8. Johanna Jussila Hammes, 2021. "The Impact of Career Concerns and Cognitive Dissonance on Bureaucrats’ Use of Benefit-Cost Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 80(2), pages 409-424, October.
    9. Luchini, S. & Watson, V., 2014. "Are choice experiments reliable? Evidence from the lab," Economics Letters, Elsevier, vol. 124(1), pages 9-13.
    10. Craig D. Broadbent, 2014. "Evaluating mitigation and calibration techniques for hypothetical bias in choice experiments," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 57(12), pages 1831-1848, December.
    11. Mørkbak, Morten Raun & Olsen, Søren Bøye & Campbell, Danny, 2014. "Behavioral implications of providing real incentives in stated choice experiments," Journal of Economic Psychology, Elsevier, vol. 45(C), pages 102-116.
    12. Xie, Jing & Gao, Zhifeng & House, Lisa, 2013. "The Puzzle of Valuation Gaps Between Experimental Auction and Real Choice Experiments: Do Purchase Intention and Price Bargaining Preference Matter?," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151282, Agricultural and Applied Economics Association.
    13. Daniel A. Brent & Lata Gangadharan & Anke Leroux & Paul A. Raschky, 2016. "Putting Your Money Where Your Mouth Is," Monash Economics Working Papers 42-16, Monash University, Department of Economics.
    14. Craig E. Landry & Paul Hindsley & Okmyung Bin & Jamie B. Kruse & John C. Whitehead & Ken Wilson, 2011. "Weathering the Storm: Measuring Household Willingness‐to‐Pay for Risk‐Reduction in Post‐Katrina New Orleans," Southern Economic Journal, John Wiley & Sons, vol. 77(4), pages 991-1013, April.
    15. Jussila Hammes , Johanna, 2017. "The impact of career concerns and cognitive dissonance on bureaucrats’ use of cost-benefit analysis," Working papers in Transport Economics 2017:5, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    16. Frode Alfnes & Maren Bachke & Mette Wik, 2012. "Eliciting donor preferences," Artefactual Field Experiments 00098, The Field Experiments Website.
    17. Carlsson, Fredrik & Kataria, Mitesh & Krupnick, Alan & Lampi, Elina & Löfgren, Åsa & Qin, Ping & Sterner, Thomas, 2013. "A fair share: Burden-sharing preferences in the United States and China," Resource and Energy Economics, Elsevier, vol. 35(1), pages 1-17.
    18. Leonardo Becchetti & Vittorio Pelligra & Tommaso Reggiani, 2017. "Information, belief elicitation and threshold effects in the 5X1000 tax scheme: a framed field experiment," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 24(6), pages 1026-1049, December.
    19. Cavallo, Carla & Del Giudice, Teresa & Cicia, Gianni & Di Monaco, Rossella & Caracciolo, Francesco, 2014. "Revealed preference approach for analysing consumer preferences: a choice experiment with a real-life setting," Politica Agricola Internazionale - International Agricultural Policy, Edizioni L'Informatore Agrario, vol. 2014(2).
    20. Fredrik Carlsson, 2010. "Design of Stated Preference Surveys: Is There More to Learn from Behavioral Economics?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 46(2), pages 167-177, June.

    More about this item

    Keywords

    Agribusiness; Consumer/Household Economics; Food Consumption/Nutrition/Food Safety; Marketing;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:aaea11:103524. 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/aaeaaea.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.