IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v35y2001i10p903-928.html
   My bibliography  Save this article

A non-compensatory choice model incorporating attribute cutoffs

Author

Listed:
  • Swait, Joffre

Abstract

This research proposes an extension to the traditional compensatory utility maximization framework which has guided most theoretical and statistical work in choice modeling applications, including those in transportation demand estimation work. Attribute cutoffs are incorporated into the decision problem formulation; it is then argued on extant empirical evidence that individuals may view these constraints as "soft". This leads to the formulation of a penalized utility function that allows for constraint violation, but at a cost to the overall evaluation of the good. The proposed model is able to represent fully compensatory, conjunctive and disjunctive choice strategies, as well as combinations thereof. The properties of the proposed theoretical model are examined and discussed. From the theoretical framework, statistical models of choice behavior are easily derived; in their simplest forms, these models can be estimated using existing software. A Stated Preference choice experiment is analyzed using the proposed model, which is found to be highly consistent with observed choices and superior to a structural two-stage choice set formation model.

Suggested Citation

  • Swait, Joffre, 2001. "A non-compensatory choice model incorporating attribute cutoffs," Transportation Research Part B: Methodological, Elsevier, vol. 35(10), pages 903-928, November.
    • Handle: RePEc:eee:transb:v:35:y:2001:i:10:p:903-928
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191-2615(00)00030-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Grether, David & Wilde, Louis, 1984. "An Analysis of Conjunctive Choice: Theory and Experiments," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 10(4), pages 373-385, March.
    2. 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.
    3. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    4. John Rotondo, 1986. "Technical Note—Price as an Aspect of Choice in EBA," Marketing Science, INFORMS, vol. 5(4), pages 391-402.
    5. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304.
    6. Pollak, Robert A. & Wales, Terence J., 1991. "The likelihood dominance criterion : A new approach to model selection," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 227-242, February.
    7. Ford, J. Kevin & Schmitt, Neal & Schechtman, Susan L. & Hults, Brian M. & Doherty, Mary L., 1989. "Process tracing methods: Contributions, problems, and neglected research questions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 43(1), pages 75-117, February.
    8. Svenson, Ola, 1996. "Decision Making and the Search for Fundamental Psychological Regularities: What Can Be Learned from a Process Perspective?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 65(3), pages 252-267, March.
    9. Swait, Joffre & Ben-Akiva, Moshe, 1987. "Empirical test of a constrained choice discrete model: Mode choice in São Paulo, Brazil," Transportation Research Part B: Methodological, Elsevier, vol. 21(2), pages 103-115, April.
    10. Dennis H. Gensch & Joseph A. Svestka, 1979. "An Exact Hierarchical Algorithm for Determining Aggregate Statistics from Individual Choice Data," Management Science, INFORMS, vol. 25(10), pages 939-952, October.
    11. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    12. Klein, Noreen M & Bither, Stewart W, 1987. "An Investigation of Utility-Directed Cutoff Selection," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(2), pages 240-256, September.
    13. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    14. 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.
    15. Huber, Joel & Klein, Noreen M, 1991. "Adapting Cutoffs to the Choice Environment: The Effects of Attribute Correlation and Reliability," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(3), pages 346-357, December.
    16. Moshe Ben-Akiva & Joffre Swait, 1986. "The Akaike Likelihood Ratio Index," Transportation Science, INFORMS, vol. 20(2), pages 133-136, May.
    Full references (including those not matched with items on IDEAS)

    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. Swait, Joffre, 2001. "Choice set generation within the generalized extreme value family of discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 643-666, August.
    2. Moser, Riccarda & Raffaelli, Roberta, 2014. "Does attribute cut-off elicitation affect choice consistency? Contrasting hypothetical and real-money choice experiments," Journal of choice modelling, Elsevier, vol. 11(C), pages 16-29.
    3. Truong, Thuy D. & Adamowicz, Wiktor L. (Vic) & Boxall, Peter C., 2015. "Modeling non-compensatory preferences in environmental valuation," Resource and Energy Economics, Elsevier, vol. 39(C), pages 89-107.
    4. Yulian Ding & Michele M. Veeman & Wiktor L. Adamowicz, 2012. "The influence of attribute cutoffs on consumers' choices of a functional food," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 39(5), pages 745-769, December.
    5. F Alpizar & F Carlsson & P Martinsson, 2003. "Using Choice Experiments for Non-Market Valuation," Economic Issues Journal Articles, Economic Issues, vol. 8(1), pages 83-110, March.
    6. Siikamaki, Juha & Layton, David F., 2007. "Discrete choice survey experiments: A comparison using flexible methods," Journal of Environmental Economics and Management, Elsevier, vol. 53(1), pages 122-139, January.
    7. Petrolia, Daniel R. & Walton, William C. & Sarah, Acquah, 2014. "A National Survey of Consumer Preferences for Branded Gulf Oysters and Risk Perceptions of Gulf Seafood," Research Reports 190586, Mississippi State University, Department of Agricultural Economics.
    8. Contu, Davide & Strazzera, Elisabetta & Mourato, Susana, 2016. "Modeling individual preferences for energy sources: The case of IV generation nuclear energy in Italy," Ecological Economics, Elsevier, vol. 127(C), pages 37-58.
    9. Joan L. Walker & Moshe Ben-Akiva, 2011. "Advances in Discrete Choice: Mixture Models," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 8, Edward Elgar Publishing.
    10. Leonie Burgess & Deborah J. Street & Rosalie Viney & Jordan Louviere, 2012. "Design of Choice Experiments in Health Economics," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 42, Edward Elgar Publishing.
    11. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    12. Wang, Xuehong & Bennett, Jeff & Xie, Chen & Zhang, Zhitao & Liang, Dan, 2007. "Estimating non-market environmental benefits of the Conversion of Cropland to Forest and Grassland Program: A choice modeling approach," Ecological Economics, Elsevier, vol. 63(1), pages 114-125, June.
    13. Falck-Zepeda, José & Kilkuwe, Enoch & Wesseler, Justus, 2008. "Introducing a genetically modified banana in Uganda: Social benefits, costs, and consumer perceptions," IFPRI discussion papers 767, International Food Policy Research Institute (IFPRI).
    14. Siikamaki, Juha & Layton, David F., 2006. "Discrete Choice Survey Experiments: A Comparison Using Flexible Models," RFF Working Paper Series dp-05-60, Resources for the Future.
    15. Mahmud, Asif & Gayah, Vikash V. & Paleti, Rajesh, 2022. "A latent choice model to analyze the role of preliminary preferences in shaping observed choices," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 95-108.
    16. Herriges, Joseph A. & Phaneuf, Daniel J., 1999. "Controlling for Correlation Across Choice Occasions and Sites in a Repeated Mixed Logit Model of Recreation Demand," Western Region Archives 321717, Western Region - Western Extension Directors Association (WEDA).
    17. Cao, Ying (Jessica) & Cranfield, John & Chen, Chen & Widowski, Tina, 2021. "Heterogeneous informational and attitudinal impacts on consumer preferences for eggs from welfare enhanced cage systems," Food Policy, Elsevier, vol. 99(C).
    18. Basu, Debasis & Hunt, John Douglas, 2012. "Valuing of attributes influencing the attractiveness of suburban train service in Mumbai city: A stated preference approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1465-1476.
    19. Swait, Joffre & Adamowicz, Wiktor, 2001. "Choice Environment, Market Complexity, and Consumer Behavior: A Theoretical and Empirical Approach for Incorporating Decision Complexity into Models of Consumer Choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 86(2), pages 141-167, November.
    20. Solomon Tarfasa & Roy Brouwer, 2013. "Estimation of the public benefits of urban water supply improvements in Ethiopia: a choice experiment," Applied Economics, Taylor & Francis Journals, vol. 45(9), pages 1099-1108, March.

    More about this item

    Statistics

    Access and download statistics

    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:35:y:2001:i:10:p:903-928. 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.