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Shelf sequence and proximity effects on online grocery choices

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Author Info

  • Els Breugelmans

    ()

  • Katia Campo

    ()

  • Els Gijsbrechts

    ()

Abstract

Research on shelf effects in traditional grocery stores shows that a product's absolute and relative shelf position may strongly affect consumer choices. The authors examine whether and how such shelf effects translate to an online grocery context. We find that a product's choice probability increases when presented on the first screen or located near focal items, especially when the latter are out-of-stock. These primacy and proximity effects have stronger impacts on choice decisions when assortments are more difficult to evaluate and when a clear shelf organization facilitates the use of shelf-based choice heuristics. Copyright Springer Science + Business Media, LLC 2007

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File URL: http://hdl.handle.net/10.1007/s11002-006-9002-x
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Bibliographic Info

Article provided by Springer in its journal Marketing Letters.

Volume (Year): 18 (2007)
Issue (Month): 1 (June)
Pages: 117-133

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Handle: RePEc:kap:mktlet:v:18:y:2007:i:1:p:117-133

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Web page: http://www.springerlink.com/link.asp?id=100312

Related research

Keywords: Retailing; Shelf management; Assortment; Online shopping; Choice decision;

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  1. Joffre Swait & Rick L. Andrews, 2003. "Enriching Scanner Panel Models with Choice Experiments," Marketing Science, INFORMS, vol. 22(4), pages 442-460, September.
  2. Jianan Wu & Arvind Rangaswamy, 2003. "A Fuzzy Set Model of Search and Consideration with an Application to an Online Market," Marketing Science, INFORMS, vol. 22(3), pages 411-434, March.
  3. Simonson, Itamar & Winer, Russell S, 1992. " The Influence of Purchase Quantity and Display Format on Consumer Preference for Variety," Journal of Consumer Research, University of Chicago Press, vol. 19(1), pages 133-38, June.
  4. Burke, Raymond R, et al, 1992. " Comparing Dynamic Consumer Choice in Real and Computer-Simulated Environments," Journal of Consumer Research, University of Chicago Press, vol. 19(1), pages 71-82, June.
  5. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
  6. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
  7. Desmet, Pierre & Renaudin, Valérie, 1998. "Estimation of Product Category Sales Responsiveness to Allocated Shelf-Space," Economics Papers from University Paris Dauphine 123456789/1757, Paris Dauphine University.
  8. Rohm, Andrew J. & Swaminathan, Vanitha, 2004. "A typology of online shoppers based on shopping motivations," Journal of Business Research, Elsevier, vol. 57(7), pages 748-757, July.
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