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Tunnel Vision: Local Behavioral Influences on Consumer Decisions in Product Search

Author

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  • Gerald Häubl

    (School of Business, University of Alberta, Edmonton, Alberta T6G 2R6, Canada)

  • Benedict G. C. Dellaert

    (Department of Business Economics, Erasmus School of Economics, Erasmus University Rotterdam, 3000 DR Rotterdam, The Netherlands)

  • Bas Donkers

    (Department of Business Economics, Erasmus School of Economics, Erasmus University Rotterdam, 3000 DR Rotterdam, The Netherlands)

Abstract

We introduce and test a behavioral model of consumer product search that extends a baseline normative model of sequential search by incorporating nonnormative influences that are local in the sense that they reflect consumers' undue sensitivity to recently encountered alternatives. We propose two types of such local behavioral influences that, at each stage of a search process, can manifest themselves both in which of the products inspected up to that point is deemed to be the most preferred one (the product comparison decision) and whether to terminate the search at that stage (the stopping decision). The first of these influences is that consumers respond excessively to the attractiveness of the currently inspected product, at the expense of all others (“focalism”). The second proposed behavioral influence is that consumers overreact to the difference in attractiveness between the current product and the one encountered just prior to it (“local contrast”). Converging evidence from two experiments, which combine to guarantee both high internal and high external validity, provides support for the proposed behavioral influences. Our findings demonstrate that consumers' product comparison and stopping decisions in sequential product search are jointly governed by normative principles and by the proposed local behavioral influences.

Suggested Citation

  • Gerald Häubl & Benedict G. C. Dellaert & Bas Donkers, 2010. "Tunnel Vision: Local Behavioral Influences on Consumer Decisions in Product Search," Marketing Science, INFORMS, vol. 29(3), pages 438-455, 05-06.
  • Handle: RePEc:inm:ormksc:v:29:y:2010:i:3:p:438-455
    DOI: 10.1287/mksc.1090.0525
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    1. Rothschild, Michael, 1974. "Searching for the Lowest Price When the Distribution of Prices Is Unknown," Journal of Political Economy, University of Chicago Press, vol. 82(4), pages 689-711, July/Aug..
    2. Robert J. Meyer, 1982. "A Descriptive Model of Consumer Information Search Behavior," Marketing Science, INFORMS, vol. 1(1), pages 93-121.
    3. Wiktor Adamowicz & David Bunch & Trudy Cameron & Benedict Dellaert & Michael Hanneman & Michael Keane & Jordan Louviere & Robert Meyer & Thomas Steenburgh & Joffre Swait, 2008. "Behavioral frontiers in choice modeling," Marketing Letters, Springer, vol. 19(3), pages 215-228, December.
    4. A G Phipps & R J Meyer, 1985. "Normative versus Heuristic Models of Residential Search Behavior: An Empirical Comparison," Environment and Planning A, , vol. 17(6), pages 761-776, June.
    5. Adam, Klaus, 2001. "Learning While Searching for the Best Alternative," Journal of Economic Theory, Elsevier, vol. 101(1), pages 252-280, November.
    6. Bettman, James R & Luce, Mary Frances & Payne, John W, 1998. "Constructive Consumer Choice Processes," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(3), pages 187-217, December.
    7. Houser, Daniel & Winter, Joachim, 2004. "How Do Behavioral Assumptions Affect Structural Inference? Evidence from a Laboratory Experiment," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 64-79, January.
    8. Schotter, Andrew & Braunstein, Yale M, 1981. "Economic Search: An Experimental Study," Economic Inquiry, Western Economic Association International, vol. 19(1), pages 1-25, January.
    9. Stigler, George J., 2011. "Economics of Information," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 5, pages 35-49.
    10. Hey, John D., 1982. "Search for rules for search," Journal of Economic Behavior & Organization, Elsevier, vol. 3(1), pages 65-81, March.
    11. Donald B. Rosenfield & Roy D. Shapiro & David A. Butler, 1983. "Optimal Strategies for Selling an Asset," Management Science, INFORMS, vol. 29(9), pages 1051-1061, September.
    12. Daniel McFadden, 1986. "The Choice Theory Approach to Market Research," Marketing Science, INFORMS, vol. 5(4), pages 275-297.
    13. Brannon, James I. & Gorman, Michael F., 2002. "The effects of information costs on search and convergence in experimental markets," Journal of Economic Behavior & Organization, Elsevier, vol. 47(4), pages 375-390, April.
    14. Rami Zwick & Amnon Rapoport & Alison King Chung Lo & A. V. Muthukrishnan, 2003. "Consumer Sequential Search: Not Enough or Too Much?," Marketing Science, INFORMS, vol. 22(4), pages 503-519, October.
    15. Sonnemans, Joep, 1998. "Strategies of search," Journal of Economic Behavior & Organization, Elsevier, vol. 35(3), pages 309-332, April.
    16. Harrison, Glenn W & Morgan, Peter, 1990. "Search Intensity in Experiments," Economic Journal, Royal Economic Society, vol. 100(401), pages 478-486, June.
    17. Brian T. Ratchford & Narasimhan Srinivasan, 1993. "An Empirical Investigation of Returns to Search," Marketing Science, INFORMS, vol. 12(1), pages 73-87.
    18. Tülin Erdem & Michael Keane & T. Öncü & Judi Strebel, 2005. "Learning About Computers: An Analysis of Information Search and Technology Choice," Quantitative Marketing and Economics (QME), Springer, vol. 3(3), pages 207-247, September.
    19. Bikhchandani, Sushil & Sharma, Sunil, 1996. "Optimal search with learning," Journal of Economic Dynamics and Control, Elsevier, vol. 20(1-3), pages 333-359.
    20. Moon, Philip & Martin, Andrew, 1996. "The search for consistency in economic search," Journal of Economic Behavior & Organization, Elsevier, vol. 29(2), pages 311-321, March.
    21. Sonnemans, Joep, 2000. "Decisions and strategies in a sequential search experiment," Journal of Economic Psychology, Elsevier, vol. 21(1), pages 91-102, February.
    22. S. Christian Albright, 1977. "A Bayesian Approach to a Generalized House Selling Problem," Management Science, INFORMS, vol. 24(4), pages 432-440, December.
    23. Cox, James C & Oaxaca, Ronald L, 1989. "Laboratory Experiments with a Finite-Horizon Job-Search Model," Journal of Risk and Uncertainty, Springer, vol. 2(3), pages 301-329, September.
    24. Kogut, Carl A., 1990. "Consumer search behavior and sunk costs," Journal of Economic Behavior & Organization, Elsevier, vol. 14(3), pages 381-392, December.
    25. Michael Rothschild, 1974. "Searching for the Lowest Price When the Distribution of Prices Is Unknown: A Summary," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 1, pages 293-294, National Bureau of Economic Research, Inc.
    26. Gerald Häubl & Valerie Trifts, 2000. "Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids," Marketing Science, INFORMS, vol. 19(1), pages 4-21, May.
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    Cited by:

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    3. Fisher, Geoffrey, 2021. "A multiattribute attentional drift diffusion model," Organizational Behavior and Human Decision Processes, Elsevier, vol. 165(C), pages 167-182.
    4. Miura, Takahiro & Inukai, Keigo & Sasaki, Masaru, 2019. "Testing the Reference-Dependent Model: A Laboratory Search Experiment," IZA Discussion Papers 12378, Institute of Labor Economics (IZA).
    5. Yadav, Manjit S. & de Valck, Kristine & Hennig-Thurau, Thorsten & Hoffman, Donna L. & Spann, Martin, 2013. "Social Commerce: A Contingency Framework for Assessing Marketing Potential," Journal of Interactive Marketing, Elsevier, vol. 27(4), pages 311-323.
    6. Dellaert, B.G.C. & Baker, T. & Johnson, E.J., 2017. "Partitioning Sorted Sets: Overcoming Choice Overload while Maintaining Decision Quality," ERIM Report Series Research in Management 18-2, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    7. Xiaoyuan Wang & Yan Liu, 2020. "Explaining Consumer Heterogeneity in Structural State-Dependence," Sustainability, MDPI, vol. 12(7), pages 1-13, March.
    8. Haas, Alexander & Kenning, Peter, 2014. "Utilitarian and Hedonic Motivators of Shoppers’ Decision to Consult with Salespeople," Journal of Retailing, Elsevier, vol. 90(3), pages 428-441.
    9. Dimitrios Tsekouras & Benedict G. C. Dellaert & Bas Donkers & Gerald Häubl, 2020. "Product set granularity and consumer response to recommendations," Journal of the Academy of Marketing Science, Springer, vol. 48(2), pages 186-202, March.
    10. Fan, Xiaoqing & Zhang, Jianxiong & Yao, Yao & Wei, Liqun, 2024. "Social responsibility disclosure format in a supply chain," Omega, Elsevier, vol. 126(C).
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    13. Raluca Ursu & Stephan Seiler & Elisabeth Honka, 2023. "The Sequential Search Model: A Framework for Empirical Research," CESifo Working Paper Series 10264, CESifo.
    14. Wang, Yichuan & Yu, Chiahui, 2017. "Social interaction-based consumer decision-making model in social commerce: The role of word of mouth and observational learning," International Journal of Information Management, Elsevier, vol. 37(3), pages 179-189.
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