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Consideration-set heuristics

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  • Hauser, John R.

Abstract

Consumers often choose products by first forming a consideration set and then choosing from among considered products. When there are many products to screen (or many features to evaluate), it is rational for consumers to use consider-then-choose decision processes and to do so with heuristic decision rules. Managerial decisions (product development, marketing communications, etc.) depend upon the ability to identify and react to consumers' heuristic consideration-set rules. We provide managerial examples and review the state-of-the-art in the theory and measurement of consumers' heuristic consideration-set rules. Advances in greedoid methods, Bayesian inference, machine-learning, incentive alignment, measurement formats, and unstructured direct elicitation make it feasible and cost-effective to understand, quantify, and simulate “what-if” scenarios for a variety of heuristics. These methods now apply to a broad set of managerial problems including applications in complex product categories with large numbers of product features and feature-levels.

Suggested Citation

  • Hauser, John R., 2014. "Consideration-set heuristics," Journal of Business Research, Elsevier, vol. 67(8), pages 1688-1699.
  • Handle: RePEc:eee:jbrese:v:67:y:2014:i:8:p:1688-1699
    DOI: 10.1016/j.jbusres.2014.02.015
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    References listed on IDEAS

    as
    1. Anja Dieckmann & Katrin Dippold & Holger Dietrich, 2009. "Compensatory versus noncompensatory models for predicting consumer preferences," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 4(3), pages 200-213, April.
    2. Punj, Girish N & Staelin, Richard, 1983. " A Model of Consumer Information Search Behavior for New Automobiles," Journal of Consumer Research, Oxford University Press, vol. 9(4), pages 366-380, March.
    3. Nedungadi, Prakash, 1990. " Recall and Consumer Consideration Sets: Influencing Choice without Altering Brand Evaluations," Journal of Consumer Research, Oxford University Press, vol. 17(3), pages 263-276, December.
    4. Vroomen, Bjorn & Hans Franses, Philip & van Nierop, Erjen, 2004. "Modeling consideration sets and brand choice using artificial neural networks," European Journal of Operational Research, Elsevier, vol. 154(1), pages 206-217, April.
    5. Robin Hogarth & Natalia Karelaia, 2004. "Simple models for multi-attribute choice with many alternatives: When it does and does not pay to face tradeoffs with binary attributes," Economics Working Papers 739, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 2005.
    6. Olivier Toubia & Duncan I. Simester & John R. Hauser & Ely Dahan, 2003. "Fast Polyhedral Adaptive Conjoint Estimation," Marketing Science, INFORMS, vol. 22(3), pages 273-303.
    7. Lohse, Gerald L. & Johnson, Eric J., 1996. "A Comparison of Two Process Tracing Methods for Choice Tasks," Organizational Behavior and Human Decision Processes, Elsevier, vol. 68(1), pages 28-43, October.
    8. Timothy J. Gilbride & Greg M. Allenby, 2004. "A Choice Model with Conjunctive, Disjunctive, and Compensatory Screening Rules," Marketing Science, INFORMS, vol. 23(3), pages 391-406, October.
    9. Peter C. Fishburn, 1974. "Exceptional Paper--Lexicographic Orders, Utilities and Decision Rules: A Survey," Management Science, INFORMS, vol. 20(11), pages 1442-1471, July.
    10. Nils Reisen & Ulrich Hoffrage & Fred W. Mast, 2008. "Identifying decision strategies in a consumer choice situation," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 3(8), pages 641-658, December.
    11. Robin M. Hogarth & Natalia Karelaia, 2005. "Simple Models for Multiattribute Choice with Many Alternatives: When It Does and Does Not Pay to Face Trade-offs with Binary Attributes," Management Science, INFORMS, vol. 51(12), pages 1860-1872, December.
    12. Nitin Mehta & Surendra Rajiv & Kannan Srinivasan, 2003. "Price Uncertainty and Consumer Search: A Structural Model of Consideration Set Formation," Marketing Science, INFORMS, vol. 22(1), pages 58-84, June.
    13. Timothy J. Gilbride & Greg M. Allenby, 2006. "Estimating Heterogeneous EBA and Economic Screening Rule Choice Models," Marketing Science, INFORMS, vol. 25(5), pages 494-509, September.
    14. Dennis H. Gensch, 1987. "A Two-Stage Disaggregate Attribute Choice Model," Marketing Science, INFORMS, vol. 6(3), pages 223-239.
    15. Hauser, John R & Wernerfelt, Birger, 1990. " An Evaluation Cost Model of Consideration Sets," Journal of Consumer Research, Oxford University Press, vol. 16(4), pages 393-408, March.
    16. Lynch, John G, Jr & Srull, Thomas K, 1982. " Memory and Attentional Factors in Consumer Choice: Concepts and Research Methods," Journal of Consumer Research, Oxford University Press, vol. 9(1), pages 18-37, June.
    17. Janiszewski, Chris, 1993. " Preattentive Mere Exposure Effects," Journal of Consumer Research, Oxford University Press, vol. 20(3), pages 376-392, December.
    18. Michael Yee & Ely Dahan & John R. Hauser & James Orlin, 2007. "Greedoid-Based Noncompensatory Inference," Marketing Science, INFORMS, vol. 26(4), pages 532-549, 07-08.
    19. Eric J. Johnson & John W. Payne, 1985. "Effort and Accuracy in Choice," Management Science, INFORMS, vol. 31(4), pages 395-414, April.
    20. Peter E. Rossi & Greg M. Allenby, 2003. "Bayesian Statistics and Marketing," Marketing Science, INFORMS, vol. 22(3), pages 304-328, July.
    21. Daria Dzyabura & John R. Hauser, 2011. "Active Machine Learning for Consideration Heuristics," Marketing Science, INFORMS, vol. 30(5), pages 801-819, September.
    22. Moore, William L. & Semenik, Richard J., 1988. "Measuring preferences with hybrid conjoint analysis: The impact of a different number of attributes in the master design," Journal of Business Research, Elsevier, vol. 16(3), pages 261-274, May.
    23. John R. Hauser & Kenneth J. Wisniewski, 1982. "Dynamic Analysis of Consumer Response to Marketing Strategies," Management Science, INFORMS, vol. 28(5), pages 455-486, May.
    24. Arndt Bröder & Ben Newell, 2008. "Challenging some common beliefs: Empirical work within the adaptive toolbox metaphor," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 3, pages 205-214, March.
    25. Swait, Joffre & Ben-Akiva, Moshe, 1987. "Incorporating random constraints in discrete models of choice set generation," Transportation Research Part B: Methodological, Elsevier, vol. 21(2), pages 91-102, April.
    26. Bettman, James R & Luce, Mary Frances & Payne, John W, 1998. " Constructive Consumer Choice Processes," Journal of Consumer Research, Oxford University Press, vol. 25(3), pages 187-217, December.
    27. Ganzach, Yoav & Czaczkes, Benjamin, 1995. "On Detecting Nonlinear Noncompensatory Judgment Strategies: Comparison of Alternative Regression Models," Organizational Behavior and Human Decision Processes, Elsevier, vol. 61(2), pages 168-176, February.
    28. Laura Martignon & Ulrich Hoffrage, 2002. "Fast, frugal, and fit: Simple heuristics for paired comparison," Theory and Decision, Springer, vol. 52(1), pages 29-71, February.
    29. Min Ding & Young-Hoon Park & Eric T. Bradlow, 2009. "Barter Markets for Conjoint Analysis," Management Science, INFORMS, vol. 55(6), pages 1003-1017, June.
    30. Gensch, Dennis H. & Soofi, Ehsan S., 1995. "An information-theoretic two-stage, two-decision rule, choice model," European Journal of Operational Research, Elsevier, vol. 81(2), pages 271-280, March.
    31. Olivier Toubia & John Hauser & Rosanna Garcia, 2007. "Probabilistic Polyhedral Methods for Adaptive Choice-Based Conjoint Analysis: Theory and Application," Marketing Science, INFORMS, vol. 26(5), pages 596-610, 09-10.
    32. Min Ding & Rajdeep Grewal & John Liechty, 2005. "Incentive-aligned conjoint analysis," Framed Field Experiments 00139, The Field Experiments Website.
    33. Chu, P. C. & Spires, Eric E., 2003. "Perceptions of accuracy and effort of decision strategies," Organizational Behavior and Human Decision Processes, Elsevier, vol. 91(2), pages 203-214, July.
    34. Shugan, Steven M, 1980. " The Cost of Thinking," Journal of Consumer Research, Oxford University Press, vol. 7(2), pages 99-111, Se.
    35. Rajeev Kohli & Kamel Jedidi, 2007. "Representation and Inference of Lexicographic Preference Models and Their Variants," Marketing Science, INFORMS, vol. 26(3), pages 380-399, 05-06.
    36. repec:eee:ijrema:v:30:y:2013:i:2:p:101-113 is not listed on IDEAS
    37. Peter J. Lenk & Wayne S. DeSarbo & Paul E. Green & Martin R. Young, 1996. "Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs," Marketing Science, INFORMS, vol. 15(2), pages 173-191.
    38. Bettman, James R & Park, C Whan, 1980. " Effects of Prior Knowledge and Experience and Phase of the Choice Process on Consumer Decision Processes: A Protocol Analysis," Journal of Consumer Research, Oxford University Press, vol. 7(3), pages 234-248, December.
    39. Wayne DeSarbo & Donald Lehmann & Gregory Carpenter & Indrajit Sinha, 1996. "A stochastic multidimensional unfolding approach for representing phased decision outcomes," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 485-508, September.
    40. Nakamura, Yutaka, 2002. "Lexicographic quasilinear utility," Journal of Mathematical Economics, Elsevier, vol. 37(3), pages 157-178, May.
    41. Theodoros Evgeniou & Constantinos Boussios & Giorgos Zacharia, 2005. "Generalized Robust Conjoint Estimation," Marketing Science, INFORMS, vol. 24(3), pages 415-429, May.
    42. Amos Tversky & Itamar Simonson, 1993. "Context-Dependent Preferences," Management Science, INFORMS, vol. 39(10), pages 1179-1189, October.
    43. George J. Stigler, 1961. "The Economics of Information," Journal of Political Economy, University of Chicago Press, vol. 69, pages 213-213.
    44. 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.
    Full references (including those not matched with items on IDEAS)

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    2. Sonntag, Axel, 2015. "Search costs and adaptive consumers: Short time delays do not affect choice quality," Journal of Economic Behavior & Organization, Elsevier, vol. 113(C), pages 64-79.
    3. Scholz, Michael & Dorner, Verena & Schryen, Guido & Benlian, Alexander, 2017. "A configuration-based recommender system for supporting e-commerce decisions," European Journal of Operational Research, Elsevier, vol. 259(1), pages 205-215.
    4. Pedro Longart & Eugenia Wickens & Ali Bakir, 2016. "Consumer Decision Process in Restaurant Selection: An Application of the Stylized EKB Model," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 28(2), pages 173-190.
    5. Loock, Moritz & Hinnen, Gieri, 2015. "Heuristics in organizations: A review and a research agenda," Journal of Business Research, Elsevier, vol. 68(9), pages 2027-2036.
    6. Li, Lianhua & Adamowicz, Wiktor & Swait, Joffre, 2015. "The effect of choice set misspecification on welfare measures in random utility models," Resource and Energy Economics, Elsevier, vol. 42(C), pages 71-92.
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