IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v18y1999i4p527-546.html
   My bibliography  Save this article

The Variety of an Assortment

Author

Listed:
  • Stephen J. Hoch

    (The Wharton School, University of Pennsylvania, 1400 Steinberg-Dietrich Hall, Philadelphia, Pennsylvania 19104-6371)

  • Eric T. Bradlow

    (The Wharton School, University of Pennsylvania, 1400 Steinberg-Dietrich Hall, Philadelphia, Pennsylvania 19104-6371)

  • Brian Wansink

    (School of Business, University of Illinois at Urbana-Champaign, Champaign, Illinois 61820-6980)

Abstract

Consumers rank variety of assortment right behind location and price when naming reasons why they patronize their favorite stores. Consumers care about variety because they are more likely to find what they want when going to a store that offers more varied assortments. When tastes are not well formed or are dynamic, perceived variety matters even more because of the desire to become educated about what is available while maintaining flexibility. Variety perception also matters when the variety-seeking motive operates. Retailers care about variety because customers value variety. Therefore, it is important to understand how people perceive the variety contained in an assortment and how these perceptions influence satisfaction and store choice. Remarkably, except for a recent study by Broniarczyk et al. (1998), there has been no research aimed at understanding the variety perception process itself. We offer a general mathematical model of variety based on the information structure of an assortment, defined both by the multiattribute structure of the objects and their spatial locations. We impose a psychologically plausible set of restrictions on the general model and obtain a class of simpler estimable models of perceived variety. We utilize the model to develop assortments that vary widely in terms of their information structure and study the influence of three factors on variety perceptions: (a) information structure of each assortment (i.e., the attribute level differences between objects); (b) level of organization of the objects and hence their relative spatial positions; and (c) task orientations, promoting either analytic or holistic processing. We also investigate the influence of variety perception and organization on stated satisfaction and store choice. To summarize our major findings: 1. Information structure has a big impact on variety perceptions, though diminishing returns accompany increases in the number of attributes on which object pairs differ. 2. People are more influenced by local information structure (adjacent objects) than nonlocal information structure. Proximity matters. 3. Organization of the display can either increase or decrease variety perceptions. When people engage in analytic processing, organized displays appear to offer more variety. When processing is holistic, random displays are seen as more varied. 4. Both variety perceptions and organization drive stated satisfaction and store choice. People are more satisfied with and likely to choose stores carrying those assortments that are perceived as offering high variety and that are displayed in an organized rather than random manner. Our work provides a basic framework for thinking about variety. By helping retailers to understand the factors that drive variety perception, it may be possible to design more efficient, lower cost assortments without reducing variety perceptions and the probability of future store visits.

Suggested Citation

  • Stephen J. Hoch & Eric T. Bradlow & Brian Wansink, 1999. "The Variety of an Assortment," Marketing Science, INFORMS, vol. 18(4), pages 527-546.
  • Handle: RePEc:inm:ormksc:v:18:y:1999:i:4:p:527-546
    DOI: 10.1287/mksc.18.4.527
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.18.4.527
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mksc.18.4.527?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. Little, John D C & Shapiro, Jeremy F, 1980. "A Theory for Pricing Nonfeatured Products in Supermarkets," The Journal of Business, University of Chicago Press, vol. 53(3), pages 199-209, July.
    2. William J. Baumol & Edward A. Ide, 1956. "Variety in Retailing," Management Science, INFORMS, vol. 3(1), pages 93-101, October.
    3. Kreps, David M, 1979. "A Representation Theorem for "Preference for Flexibility"," Econometrica, Econometric Society, vol. 47(3), pages 565-577, May.
    4. McAlister, Leigh, 1982. "A Dynamic Attribute Satiation Model of Variety-Seeking Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(2), pages 141-150, 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. Aydinli, Aylin & Gu, Yangjie & Pham, Michel Tuan, 2017. "An experience-utility explanation of the preference for larger assortments," International Journal of Research in Marketing, Elsevier, vol. 34(3), pages 746-760.
    2. Tom Fangyun Tan & Serguei Netessine & Lorin Hitt, 2017. "Is Tom Cruise Threatened? An Empirical Study of the Impact of Product Variety on Demand Concentration," Information Systems Research, INFORMS, vol. 28(3), pages 643-660, September.
    3. Yan, Huan & Chang, En-Chung & Chou, Ting-Jui & Tang, Xiaofei, 2015. "The over-categorization effect: How the number of categorizations influences shoppers' perceptions of variety and satisfaction," Journal of Business Research, Elsevier, vol. 68(3), pages 631-638.
    4. Liang Guo, 2006. "—Removing the Boundary Between Structural and Reduced-Form Models," Marketing Science, INFORMS, vol. 25(6), pages 629-632, 11-12.
    5. Liang Guo, 2010. "Capturing Consumption Flexibility in Assortment Choice from Scanner Panel Data," Management Science, INFORMS, vol. 56(10), pages 1815-1832, October.
    6. Liang Guo, 2006. "Consumption Flexibility, Product Configuration, and Market Competition," Marketing Science, INFORMS, vol. 25(2), pages 116-130, 03-04.
    7. Thunström, Linda & Nordström, Jonas & Shogren, Jason F., 2015. "Certainty and overconfidence in future preferences for food," Journal of Economic Psychology, Elsevier, vol. 51(C), pages 101-113.
    8. Christopher P. Chambers & Federico Echenique & Eran Shmaya, 2014. "The Axiomatic Structure of Empirical Content," American Economic Review, American Economic Association, vol. 104(8), pages 2303-2319, August.
    9. Evan Piermont, 2021. "Hypothetical Expected Utility," Papers 2106.15979, arXiv.org, revised Jul 2021.
    10. André Lapied & Thomas Rongiconi, 2013. "Ambiguity as a Source of Temptation: Modeling Unstable Beliefs," Working Papers halshs-00797631, HAL.
    11. Vassili Vergopoulos, 2014. "A Behavioral Definition of States of the World," Documents de travail du Centre d'Economie de la Sorbonne 14047, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    12. Eddie Dekel & Barton L. Lipman & Aldo Rustichini, 2009. "Temptation-Driven Preferences," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(3), pages 937-971.
    13. Liu, Jingting, 2016. "Covered in Gold: Examining gold consumption by middle class consumers in emerging markets," International Business Review, Elsevier, vol. 25(3), pages 739-747.
    14. Andreoni, James & Serra-Garcia, Marta, 2021. "Time inconsistent charitable giving," Journal of Public Economics, Elsevier, vol. 198(C).
    15. Andreas Herrmann & Michael D. Johnson, 1999. "Die Kundenzufriedenheit als Bestimmungsfaktor der Kundenbindung," Schmalenbach Journal of Business Research, Springer, vol. 51(6), pages 579-598, June.
    16. Bryan, Gharad & Karlan, Dean & Nelson, Scott, 2009. "Commitment Contracts," Working Papers 73, Yale University, Department of Economics.
    17. Andrew Rhodes & Jidong Zhou, 2019. "Consumer Search and Retail Market Structure," Management Science, INFORMS, vol. 67(6), pages 2607-2623, June.
    18. Youichiro Higashi & Kazuya Hyogo, 2012. "Lexicographic expected utility with a subjective state space," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 49(1), pages 175-192, January.
    19. Barbera, S. & Bossert, W. & Pattanaik, P.K., 2001. "Ranking Sets of Objects," Cahiers de recherche 2001-02, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    20. Jaehwan Kim & Greg M. Allenby & Peter E. Rossi, 2002. "Modeling Consumer Demand for Variety," Marketing Science, INFORMS, vol. 21(3), pages 229-250, December.

    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:inm:ormksc:v:18:y:1999:i:4:p:527-546. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.