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Flexibility in Consumer Purchasing for Uncertain Future Tastes


  • John W. Walsh

    (University of Pennsylvania)


Consumers often simultaneously purchase multiple units in the same product category. Whether they are best off purchasing an assortment of alternatives or an equal number of one alternative is addressed in this paper. Models of an expected-utility-maximizing consumer are developed, and it is shown that an assortment may have greater expected utility than an equal number of any one alternative. The rationale is that the assortment allows the consumer to choose from inventory the alternative most appropriate for a consumption occasion using preference information not available at the purchase occasion. It is also shown that, when consuming alternatives from inventory, the consumer may forego the alternative offering the most utility in the expectation that it will yield even more utility in the future.

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  • John W. Walsh, 1995. "Flexibility in Consumer Purchasing for Uncertain Future Tastes," Marketing Science, INFORMS, vol. 14(2), pages 148-165.
  • Handle: RePEc:inm:ormksc:v:14:y:1995:i:2:p:148-165

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    References listed on IDEAS

    1. Hauser, John R. & Urban, Glen L., 1975. "A normative methodology for modeling consumer response to innovation," Working papers 785-75., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Griffin, Abbie. & Hauser, John R., 1991. "The marketing and R & D interface," Working papers #48-91. Working paper (Sl, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    3. Green, Paul E & Srinivasan, V, 1978. " Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Oxford University Press, vol. 5(2), pages 103-123, Se.
    4. George P. Huber, 1974. "Multi-Attribute Utility Models: A Review of Field and Field-Like Studies," Management Science, INFORMS, vol. 20(10), pages 1393-1402, June.
    5. John R. Hauser, 1977. "Testing the Accuracy," Discussion Papers 286, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
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    Cited by:

    1. Linda Court Salisbury & Fred M. Feinberg, 2010. "Alleviating the Constant Stochastic Variance Assumption in Decision Research: Theory, Measurement, and Experimental Test," Marketing Science, INFORMS, vol. 29(1), pages 1-17, 01-02.
    2. Jordan Louviere & Kenneth Train & Moshe Ben-Akiva & Chandra Bhat & David Brownstone & Trudy Cameron & Richard Carson & J. Deshazo & Denzil Fiebig & William Greene & David Hensher & Donald Waldman, 2005. "Recent Progress on Endogeneity in Choice Modeling," Marketing Letters, Springer, vol. 16(3), pages 255-265, December.
    3. Liang Guo, 2006. "—Removing the Boundary Between Structural and Reduced-Form Models," Marketing Science, INFORMS, vol. 25(6), pages 629-632, 11-12.
    4. P. B. Seetharaman & Hai Che, 2009. "Price Competition in Markets with Consumer Variety Seeking," Marketing Science, INFORMS, vol. 28(3), pages 516-525, 05-06.
    5. Liu, Jing & Shively, Gerald E. & Binkley, James K., 2014. "Access to variety contributes to dietary diversity in China," Food Policy, Elsevier, vol. 49(P1), pages 323-331.
    6. Jaehwan Kim & Greg M. Allenby & Peter E. Rossi, 2002. "Modeling Consumer Demand for Variety," Marketing Science, INFORMS, pages 229-250.
    7. Pradeep K. Chintagunta & Harikesh S. Nair, 2011. "Structural Workshop Paper --Discrete-Choice Models of Consumer Demand in Marketing," Marketing Science, INFORMS, vol. 30(6), pages 977-996, November.
    8. Liang Guo, 2010. "Capturing Consumption Flexibility in Assortment Choice from Scanner Panel Data," Management Science, INFORMS, vol. 56(10), pages 1815-1832, October.
    9. Allender, William J. & Richards, Timothy J., 2009. "Measures of Brand Loyalty," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49536, Agricultural and Applied Economics Association.
    10. Jean-Pierre Dubé, 2004. "Multiple Discreteness and Product Differentiation: Demand for Carbonated Soft Drinks," Marketing Science, INFORMS, vol. 23(1), pages 66-81, September.
    11. 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.
    12. Liu, Jing & Shively, Gerald & Binkley, James K., 2013. "Dietary Diversity in Urban and Rural China: An Endogenous Variety Approach," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149624, Agricultural and Applied Economics Association.
    13. Randolph E. Bucklin & Sunil Gupta, 1999. "Commercial Use of UPC Scanner Data: Industry and Academic Perspectives," Marketing Science, INFORMS, vol. 18(3), pages 247-273.
    14. Liang Guo, 2006. "Consumption Flexibility, Product Configuration, and Market Competition," Marketing Science, INFORMS, vol. 25(2), pages 116-130, 03-04.
    15. Barbara E. Kahn & Mary Frances Luce, 2003. "Understanding High-Stakes Consumer Decisions: Mammography Adherence Following False-Alarm Test Results," Marketing Science, INFORMS, vol. 22(3), pages 393-410, April.
    16. Wang, Heli & Chen, Wei-Ru, 2010. "Is firm-specific innovation associated with greater value appropriation? The roles of environmental dynamism and technological diversity," Research Policy, Elsevier, vol. 39(1), pages 141-154, February.
    17. repec:kap:mktlet:v:28:y:2017:i:4:d:10.1007_s11002-017-9438-1 is not listed on IDEAS
    18. Liang Guo, 2009. "Service Cancellation and Competitive Refund Policy," Marketing Science, INFORMS, vol. 28(5), pages 901-917, 09-10.
    19. 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.

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    buyer behavior; choice models;


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