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Modeling the decoy effect with context-RUM Models: Diagrammatic analysis and empirical evidence from route choice SP and mode choice RP case studies

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  • Guevara, C. Angelo
  • Fukushi, Mitsuyoshi

Abstract

Evidence outside transportation has suggested that the introduction of a decoy to the choice-set could increase the share of other alternatives. This evidence breaks the regularity assumption, which is at the root of the classical Random Utility Maximization (RUM) model with utilities that ignore the choice context. This article assesses the suitability of various context-RUM choice models that could overcome this limitation. For this we use a diagrammatic analysis, as well as Stated Preference (SP) and Revealed Preference (RP) transportation choice evidence. We begin confirming that the reported decoy outcomes cannot be replicated with the classical RUM models and that such a goal could be achieved instead using a set of five context-RUM models. We then show, for the first time, that the Asymmetrically Dominated (AD) and Compromise (CP) decoy effects were present in an SP route choice setting. We also show that, for a subset of individuals, the relative strength of the different decoy types was coherent with a Data Generation Process (DGP) defined by the Random Regret Minimization (RRM) or by the Regret by Aspects (RBA) parsimonious models. Then, we use cross-validation analysis where we found that RRM and RBA were superior to a classical Logit for all decoy types. Nevertheless, the ad-hoc Emergent Value (EV) model was consistently superior to all models suggesting that, although the parsimonious models may in theory replicate all decoy types, they seem to still make an incomplete representation of the DGP behind the overall decoy effect. We finally consider an RP mode choice experiment with which we detect, for the first time, an AD decoy effect in this choice setting. We also use this experiment to illustrate how to handle the decoy phenomena in a real context with various alternatives and variables. The article concludes summarizing the main contributions of this research and suggesting future lines of investigation for it.

Suggested Citation

  • Guevara, C. Angelo & Fukushi, Mitsuyoshi, 2016. "Modeling the decoy effect with context-RUM Models: Diagrammatic analysis and empirical evidence from route choice SP and mode choice RP case studies," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 318-337.
    • Handle: RePEc:eee:transb:v:93:y:2016:i:pa:p:318-337
    DOI: 10.1016/j.trb.2016.07.012
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    1. Simonson, Itamar, 1989. "Choice Based on Reasons: The Case of Attraction and Compromise Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 16(2), pages 158-174, September.
    2. Quinn McNemar, 1947. "Note on the sampling error of the difference between correlated proportions or percentages," Psychometrika, Springer;The Psychometric Society, vol. 12(2), pages 153-157, June.
    3. Caspar Chorus & Michel Bierlaire, 2013. "An empirical comparison of travel choice models that capture preferences for compromise alternatives," Transportation, Springer, vol. 40(3), pages 549-562, May.
    4. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    5. Quiggin, John, 1994. "Regret Theory with General Choice Sets," Journal of Risk and Uncertainty, Springer, vol. 8(2), pages 153-165, March.
    6. Joel L. Horowitz, 1983. "Statistical Comparison of Non-Nested Probabilistic Discrete Choice Models," Transportation Science, INFORMS, vol. 17(3), pages 319-350, August.
    7. Ariely, Dan & Wallsten, Thomas S., 1995. "Seeking Subjective Dominance in Multidimensional Space: An Explanation of the Asymmetric Dominance Effect," Organizational Behavior and Human Decision Processes, Elsevier, vol. 63(3), pages 223-232, September.
    8. Pettibone, Jonathan C. & Wedell, Douglas H., 2000. "Examining Models of Nondominated Decoy Effects across Judgment and Choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 81(2), pages 300-328, March.
    9. Highhouse, Scott, 1996. "Context-Dependent Selection: The Effects of Decoy and Phantom Job Candidates," Organizational Behavior and Human Decision Processes, Elsevier, vol. 65(1), pages 68-76, January.
    10. Chorus, Caspar G. & Arentze, Theo A. & Timmermans, Harry J.P., 2008. "A Random Regret-Minimization model of travel choice," Transportation Research Part B: Methodological, Elsevier, vol. 42(1), pages 1-18, January.
    11. Huber, Joel & Puto, Christopher, 1983. "Market Boundaries and Product Choice: Illustrating Attraction and Substitution Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 10(1), pages 31-44, June.
    12. van Cranenburgh, Sander & Guevara, Cristian Angelo & Chorus, Caspar G., 2015. "New insights on random regret minimization models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 91-109.
    13. Huber, Joel & Payne, John W & Puto, Christopher, 1982. "Adding Asymmetrically Dominated Alternatives: Violations of Regularity and the Similarity Hypothesis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(1), pages 90-98, June.
    14. Wedell, Douglas H. & Pettibone, Jonathan C., 1996. "Using Judgments to Understand Decoy Effects in Choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 67(3), pages 326-344, September.
    15. Leong, Waiyan & Hensher, David A., 2012. "Embedding multiple heuristics into choice models: An exploratory analysis," Journal of choice modelling, Elsevier, vol. 5(3), pages 131-144.
    Full references (including those not matched with items on IDEAS)

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