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Psychometrika

, Volume 61, Issue 3, pp 485–508 | Cite as

A stochastic multidimensional unfolding approach for representing phased decision outcomes

  • Wayne S. DeSarbo
  • Donald R. Lehmann
  • Gregory Carpenter
  • Indrajit Sinha
Article

Abstract

This paper presents a stochastic multidimensional unfolding (MDU) procedure to spatially represent individual differences in phased or sequential decision processes. The specific application or scenario to be discussed involves the area of consumer psychology where consumers form judgments sequentially in their awareness, consideration, and choice set compositions in a phased or sequential manner as more information about the alternative brands in a designated product/service class are collected. A brief review of the consumer psychology literature on these nested congnitive sets as stages in phased decision making is provided. The technical details of the proposed model, maximum likelihood estimation framework, and algorithm are then discussed. A small scale Monte Carlo analysis is presented to demonstrate estimation proficiency and the appropriateness of the proposed model selection heuristic. An application of the methodology to capture awareness, consideration, and choice sets in graduate school applicants is presented. Finally, directions for future research and other potential applications are given.

Key words

consumer psychology multidimensional scaling maximum likelihood consideration sets multidimensional unfolding successive categories analysis 

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Copyright information

© The Psychometric Society 1996

Authors and Affiliations

  • Wayne S. DeSarbo
    • 4
  • Donald R. Lehmann
    • 1
  • Gregory Carpenter
    • 2
  • Indrajit Sinha
    • 3
  1. 1.Marketing DepartmentColumbia UniversityUSA
  2. 2.Marketing DepartmentNorthwestern UniversityUSA
  3. 3.Marketing DepartmentTemple UniversityUSA
  4. 4.Department of Marketing, Smeal School of BusinessPennsylvania State UniversityUniversity Park

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