IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v93y2016ipap318-337.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191261516301345
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.trb.2016.07.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bahamonde-Birke, Francisco J., 2018. "Estimating the reference frame: A smooth twice-differentiable utility function for non-compensatory loss-averse decision-making," Journal of choice modelling, Elsevier, vol. 28(C), pages 71-81.
    2. Wong, Stephen D & Chorus, Caspar G & Shaheen, Susan A & Walker, Joan L, 2020. "A Revealed Preference Methodology to Evaluate Regret Minimization with Challenging Choice Sets: A Wildfire Evacuation Case Study," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt2k12q9ph, Institute of Transportation Studies, UC Berkeley.
    3. Hancock, Thomas O. & Hess, Stephane & Choudhury, Charisma F., 2018. "Decision field theory: Improvements to current methodology and comparisons with standard choice modelling techniques," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 18-40.
    4. John Buckell & Vrinda Vasavada & Sarah Wordsworth & Dean A. Regier & Matthew Quaife, 2022. "Utility maximization versus regret minimization in health choice behavior: Evidence from four datasets," Health Economics, John Wiley & Sons, Ltd., vol. 31(2), pages 363-381, February.
    5. van Cranenburgh, Sander & Meyerhoff, Jürgen & Rehdanz, Katrin & Wunsch, Andrea, 2024. "On the impact of decision rule assumptions in experimental designs on preference recovery: An application to climate change adaptation measures," Journal of choice modelling, Elsevier, vol. 50(C).
    6. Stephane Hess & Andrew Daly & Richard Batley, 2018. "Revisiting consistency with random utility maximisation: theory and implications for practical work," Theory and Decision, Springer, vol. 84(2), pages 181-204, March.
    7. van Cranenburgh, Sander & Collins, Andrew T., 2019. "New software tools for creating stated choice experimental designs efficient for regret minimisation and utility maximisation decision rules," Journal of choice modelling, Elsevier, vol. 31(C), pages 104-123.
    8. Bibhuti Sharma & Mark Hickman & Neema Nassir, 2019. "Park-and-ride lot choice model using random utility maximization and random regret minimization," Transportation, Springer, vol. 46(1), pages 217-232, February.
    9. van Cranenburgh, Sander & Chorus, Caspar G., 2018. "Does the decision rule matter for large-scale transport models?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PB), pages 338-353.
    10. van Cranenburgh, Sander & Rose, John M. & Chorus, Caspar G., 2018. "On the robustness of efficient experimental designs towards the underlying decision rule," Transportation Research Part A: Policy and Practice, Elsevier, vol. 109(C), pages 50-64.
    11. Li, Feng & Du, Timon C. & Wei, Ying, 2020. "Enhancing supply chain decisions with consumers’ behavioral factors: An illustration of decoy effect," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    12. Hancock, Thomas O. & Broekaert, Jan & Hess, Stephane & Choudhury, Charisma F., 2020. "Quantum probability: A new method for modelling travel behaviour," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 165-198.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jörg Rieskamp & Jerome R. Busemeyer & Barbara A. Mellers, 2006. "Extending the Bounds of Rationality: Evidence and Theories of Preferential Choice," Journal of Economic Literature, American Economic Association, vol. 44(3), pages 631-661, September.
    2. Ahn, Heinz & Vazquez Novoa, Nadia, 2016. "The decoy effect in relative performance evaluation and the debiasing role of DEA," European Journal of Operational Research, Elsevier, vol. 249(3), pages 959-967.
    3. Nicole Wiebach & Jana L. Diels, 2011. "The impact of context and promotion on consumer responses and preferences in out-of-stock situations," SFB 649 Discussion Papers SFB649DP2011-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. 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.
    5. Bonaccio, Silvia & Reeve, Charlie L., 2006. "Consideration of preference shifts due to relative attribute variability," Organizational Behavior and Human Decision Processes, Elsevier, vol. 101(2), pages 200-214, November.
    6. William M. Hedgcock & Raghunath Singh Rao & Haipeng (Allan) Chen, 2016. "Choosing to Choose: The Effects of Decoys and Prior Choice on Deferral," Management Science, INFORMS, vol. 62(10), pages 2952-2976, October.
    7. repec:cup:judgdm:v:8:y:2013:i:2:p:136-149 is not listed on IDEAS
    8. Castillo, Geoffrey, 2020. "The attraction effect and its explanations," Games and Economic Behavior, Elsevier, vol. 119(C), pages 123-147.
    9. Diels, Jana Luisa & Wiebach, Nicole & Hildebrandt, Lutz, 2013. "The impact of promotions on consumer choices and preferences in out-of-stock situations," Journal of Retailing and Consumer Services, Elsevier, vol. 20(6), pages 587-598.
    10. Mehran Spitmaan & Oihane Horno & Emily Chu & Alireza Soltani, 2019. "Combinations of low-level and high-level neural processes account for distinct patterns of context-dependent choice," PLOS Computational Biology, Public Library of Science, vol. 15(10), pages 1-31, October.
    11. Terry Connolly & Jochen Reb & Edgar E. Kausel, 2013. "Regret salience and accountability in the decoy effect," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 8(2), pages 136-149, March.
    12. Linhai Wu & Pingping Liu & Xiujuan Chen & Wuyang Hu & Xuesen Fan, 2021. "Contents of product attributes and the decoy effect: A study on traceable pork from the perspective of consumer utility," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(4), pages 974-984, June.
    13. Heydari, Pedram, 2021. "Luce arbitrates: Stochastic resolution of inner conflicts," Games and Economic Behavior, Elsevier, vol. 126(C), pages 33-74.
    14. Kumar Padamwar, Pravesh & Kumar Kalakbandi, Vinay & Dawra, Jagrook, 2023. "Deliberation does not make the attraction effect disappear: The role of induced cognitive reflection," Journal of Business Research, Elsevier, vol. 154(C).
    15. Jonathan C. Pettibone, 2012. "Testing the effect of time pressure on asymmetric dominance and compromise decoys in choice," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 7(4), pages 513-523, July.
    16. Nasim Mousavi & Panagiotis Adamopoulos & Jesse Bockstedt, 2023. "The Decoy Effect and Recommendation Systems," Information Systems Research, INFORMS, vol. 34(4), pages 1533-1553, December.
    17. Seidl, C. & Traub, S., 1996. "Rational Choice and the Relevance of Irrelevant Alternatives," Other publications TiSEM 26452450-9ecd-45b4-bc45-b, Tilburg University, School of Economics and Management.
    18. Peng Jing & Mengxuan Zhao & Meiling He & Long Chen, 2018. "Travel Mode and Travel Route Choice Behavior Based on Random Regret Minimization: A Systematic Review," Sustainability, MDPI, vol. 10(4), pages 1-20, April.
    19. Fabio Galeotti & Maria Montero & Anders Poulsen, 2022. "The Attraction and Compromise Effects in Bargaining: Experimental Evidence," Management Science, INFORMS, vol. 68(4), pages 2987-3007, April.
    20. Cheng, Yin-Hui & Chuang, Shih-Chieh & Pei-I Yu, Annie & Lai, Wan-Ting, 2019. "Change in your wallet, change your choice: The effect of the change-matching heuristic on choice," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 67-76.
    21. Bechler, Georg & Steinhardt, Claudius & Mackert, Jochen & Klein, Robert, 2021. "Product line optimization in the presence of preferences for compromise alternatives," European Journal of Operational Research, Elsevier, vol. 288(3), pages 902-917.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transb:v:93:y:2016:i:pa:p:318-337. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.