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Matching reality: A basket and expenditure based choice experiment with sensory preferences

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  • Neill, Clinton L.
  • Lahne, Jacob

Abstract

This article introduces a basket and expenditure based choice experiment design to elicit consumer preferences for multiple products. This design is utilized to imitate a more realistic shopping scenario for consumers when choosing among many different products simultaneously. This approach allows participants to choose both multiple items, in this case vegetables, and related quantities/expenditures to place in a basket of goods. We provide an application of the experimental design to a vegetable choice experiment. This is done in conjunction with a sensory experiment to provide a contextual component to the experiment and econometric model. This type of experiment lends itself to the use of the Multiple Discrete-Continuous Extreme Value (MDCEV) class of models. More specifically, we use the extended version of the MDCEV model proposed by Palma and Hess (2020) that relaxes the need for a budget while also accounting for substitution and complementarity among products. We find that the proposed design and class of econometric methods present a flexible way to analyze consumer choice when the desire is to elicit preferences for a basket of goods rather than simple discrete alternatives or attributes.

Suggested Citation

  • Neill, Clinton L. & Lahne, Jacob, 2022. "Matching reality: A basket and expenditure based choice experiment with sensory preferences," Journal of choice modelling, Elsevier, vol. 44(C).
  • Handle: RePEc:eee:eejocm:v:44:y:2022:i:c:s1755534522000264
    DOI: 10.1016/j.jocm.2022.100369
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    1. Maynard, Leigh J. & Hartell, Jason G. & Meyer, A. Lee & Hao, Jianqiang, 2004. "An experimental approach to valuing new differentiated products," Agricultural Economics, Blackwell, vol. 31(2-3), pages 317-325, December.
    2. Vasquez Lavin, Felipe & Hanemann, W. Michael, 2008. "Functional Forms in Discrete/Continuous Choice Models With General Corner Solution," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt7z25t659, Department of Agricultural & Resource Economics, UC Berkeley.
    3. Ariely, Dan & Levav, Jonathan, 2000. "Sequential Choice in Group Settings: Taking the Road Less Traveled and Less Enjoyed," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 27(3), pages 279-290, December.
    4. Timothy Richards & Koichi Yonezawa & Sophie Winter, 2015. "Cross-category effects and private labels," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 42(2), pages 187-216.
    5. Timothy J. Richards & Lisa Mancino, 2014. "Demand for food-away-from-home: a multiple-discrete–continuous extreme value model," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(1), pages 111-133, February.
    6. Bonnet, Céline & Richards, Timothy J., 2016. "Models of Consumer Demand for Differentiated Products," TSE Working Papers 16-741, Toulouse School of Economics (TSE).
    7. Neill, Clinton L. & Holcomb, Rodney B., 2019. "Does a food safety label matter? Consumer heterogeneity and fresh produce risk perceptions under the Food Safety Modernization Act," Food Policy, Elsevier, vol. 85(C), pages 7-14.
    8. Neill, Clinton L. & Williams, Ryan B., 2016. "Consumer Preference For Alternative Milk Packaging: The Case Of An Inferred Environmental Attribute," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 48(3), pages 241-256, August.
    9. Brock,W.A. & Durlauf,S.N., 2003. "Multinomial choice with social interactions," Working papers 1, Wisconsin Madison - Social Systems.
    10. Jayson L. Lusk & John A. Fox & Ted C. Schroeder & James Mintert & Mohammad Koohmaraie, 2001. "In-Store Valuation of Steak Tenderness," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 539-550.
    11. Megan E. Waldrop & Jill J. McCluskey, 2019. "Does information about organic status affect consumer sensory liking and willingness to pay for beer?," Agribusiness, John Wiley & Sons, Ltd., vol. 35(2), pages 149-167, April.
    12. Gurmu, Shiferaw & Trivedi, Pravin K., 1992. "Overdispersion tests for truncated Poisson regression models," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 347-370.
    13. Axsen, Jonn & Orlebar, Caroline & Skippon, Stephen, 2013. "Social influence and consumer preference formation for pro-environmental technology: The case of a U.K. workplace electric-vehicle study," Ecological Economics, Elsevier, vol. 95(C), pages 96-107.
    14. Kelvin Lancaster, 1990. "The Economics of Product Variety: A Survey," Marketing Science, INFORMS, vol. 9(3), pages 189-206.
    15. Wales, T. J. & Woodland, A. D., 1983. "Estimation of consumer demand systems with binding non-negativity constraints," Journal of Econometrics, Elsevier, vol. 21(3), pages 263-285, April.
    16. Gregory Howard & Brian E. Roe & Matthew G. Interis & Jay Martin, 2020. "Addressing Attribute Value Substitution in Discrete Choice Experiments to Avoid Unintended Consequences," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 77(4), pages 813-838, December.
    17. repec:ken:wpaper:0901 is not listed on IDEAS
    18. Caputo, Vincenzina & Lusk, Jayson L., 2022. "The Basket-Based Choice Experiment: A Method for Food Demand Policy Analysis," Food Policy, Elsevier, vol. 109(C).
    19. Richards, Timothy J. & Gómez, Miguel I. & Pofahl, Geoffrey, 2012. "A Multiple-discrete/Continuous Model of Price Promotion," Journal of Retailing, Elsevier, vol. 88(2), pages 206-225.
    20. Jayson L. Lusk & Ted C. Schroeder & Glynn T. Tonsor, 2014. "Editor's choice Distinguishing beliefs from preferences in food choice," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(4), pages 627-655.
    21. Thiele, S. & Weiss, C., 2003. "Consumer demand for food diversity: evidence for Germany," Food Policy, Elsevier, vol. 28(2), pages 99-115, April.
    22. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
    23. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    24. Tozer, Peter R. & Galinato, Suzette P. & Ross, Carolyn F. & Miles, Carol A. & McCluskey, Jill J., 2015. "Sensory Analysis and Willingness to Pay for Craft Cider," Journal of Wine Economics, Cambridge University Press, vol. 10(3), pages 314-328, December.
    25. Zijun Wang & David A. Bessler, 2006. "Price and quantity endogeneity in demand analysis: evidence from directed acyclic graphs," Agricultural Economics, International Association of Agricultural Economists, vol. 34(1), pages 87-95, January.
    26. Bhat, Chandra R. & Castro, Marisol & Pinjari, Abdul Rawoof, 2015. "Allowing for complementarity and rich substitution patterns in multiple discrete–continuous models," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 59-77.
    27. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
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    Cited by:

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    3. Hernandez, Jose Ignacio & van Cranenburgh, Sander & Chorus, Caspar & Mouter, Niek, 2023. "Data-driven assisted model specification for complex choice experiments data: Association rules learning and random forests for Participatory Value Evaluation experiments," Journal of choice modelling, Elsevier, vol. 46(C).

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    More about this item

    Keywords

    Consumer choice; Sensory; Basket and expenditure based choice experiment; Vegetables;
    All these keywords.

    JEL classification:

    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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