IDEAS home Printed from https://ideas.repec.org/a/spr/fuzodm/v20y2021i1d10.1007_s10700-020-09335-8.html
   My bibliography  Save this article

Probabilistic-based expressions in behavioral multi-attribute decision making considering pre-evaluation

Author

Listed:
  • Zhenzhen Ma

    (Beihang University)

  • Jianjun Zhu

    (Nanjing University of Aeronautics and Astronautics)

  • Shitao Zhang

    (Anhui University of Technology)

Abstract

A behavioral multi-attribute decision making (BMADM) problem with probabilistic-based expressions is studied by considering decision-maker’s (DM) risk attitude and pre-evaluation. With consideration of information expressions for uncertainty, probabilistic interval numbers (PINs) and probabilistic linguistic terms (PLTs) are utilized to depict pre-evaluation information with respect to quantitative and qualitative attributes, respectively. Then surrounding the two kinds of probabilistic-based expressions, we propose a BMADM method with DM’s risk attitude being included based on regret theory. First, through taking into account characteristics of risk, we develop a basic utility function and a regret–rejoice function by considering risk-averse, risk-neutral and risk-seeking preference coefficients. Second, risk-based utility functions are examined for measuring PINs and PLTs. The third element is the establishment of optimization models for handling probability incompleteness to fully utilize the information. In the fourth step, a weighted comprehensive risk-based utility measurement is presented as a basis for making a selection. The final phase of the research is the application of the proposed method to one case, along with sensitivity and comparative analyses, as a means of illustrating the applicability and feasibility of the new method.

Suggested Citation

  • Zhenzhen Ma & Jianjun Zhu & Shitao Zhang, 2021. "Probabilistic-based expressions in behavioral multi-attribute decision making considering pre-evaluation," Fuzzy Optimization and Decision Making, Springer, vol. 20(1), pages 145-173, March.
  • Handle: RePEc:spr:fuzodm:v:20:y:2021:i:1:d:10.1007_s10700-020-09335-8
    DOI: 10.1007/s10700-020-09335-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10700-020-09335-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10700-020-09335-8?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. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    2. JosÉ Figueira & Salvatore Greco & Matthias Ehrogott, 2005. "Multiple Criteria Decision Analysis: State of the Art Surveys," International Series in Operations Research and Management Science, Springer, number 978-0-387-23081-8, December.
    3. Loomes, Graham & Sugden, Robert, 1982. "Regret Theory: An Alternative Theory of Rational Choice under Uncertainty," Economic Journal, Royal Economic Society, vol. 92(368), pages 805-824, December.
    4. Berman, Oded & Sanajian, Nima & Wang, Jiamin, 2017. "Location choice and risk attitude of a decision maker," Omega, Elsevier, vol. 66(PA), pages 170-181.
    5. 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..
    6. Huchang Liao & Xiaomei Mi & Zeshui Xu, 2020. "A survey of decision-making methods with probabilistic linguistic information: bibliometrics, preliminaries, methodologies, applications and future directions," Fuzzy Optimization and Decision Making, Springer, vol. 19(1), pages 81-134, March.
    7. David E. Bell, 1982. "Regret in Decision Making under Uncertainty," Operations Research, INFORMS, vol. 30(5), pages 961-981, October.
    8. David E. Bell, 1985. "Disappointment in Decision Making Under Uncertainty," Operations Research, INFORMS, vol. 33(1), pages 1-27, February.
    9. Rabin, Matthew, 1993. "Incorporating Fairness into Game Theory and Economics," American Economic Review, American Economic Association, vol. 83(5), pages 1281-1302, December.
    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. Enrico G. De Giorgi & Thierry Post, 2011. "Loss Aversion with a State-Dependent Reference Point," Management Science, INFORMS, vol. 57(6), pages 1094-1110, June.
    2. Ronald Bosman & Frans Van Winden, 2010. "Global Risk, Investment and Emotions," Economica, London School of Economics and Political Science, vol. 77(307), pages 451-471, July.
    3. Ivan Barreda-Tarrazona & Ainhoa Jaramillo-Gutierrez & Daniel Navarro-Martinez & Gerardo Sabater-Grande, 2014. "The role of forgone opportunities in decision making under risk," Journal of Risk and Uncertainty, Springer, vol. 49(2), pages 167-188, October.
    4. Servaas van Bilsen & Roger J. A. Laeven & Theo E. Nijman, 2020. "Consumption and Portfolio Choice Under Loss Aversion and Endogenous Updating of the Reference Level," Management Science, INFORMS, vol. 66(9), pages 3927-3955, September.
    5. Astrid Hopfensitz & Frans Winden, 2008. "Dynamic Choice, Independence and Emotions," Theory and Decision, Springer, vol. 64(2), pages 249-300, March.
    6. Jiakun Zheng, 2020. "Optimal insurance design under narrow framing," Post-Print hal-04227370, HAL.
    7. Zheng, Jiakun, 2020. "Optimal insurance design under narrow framing," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 596-607.
    8. Zhihua Li & Songfa Zhong, 2023. "Reference Dependence in Intertemporal Preference," Management Science, INFORMS, vol. 69(1), pages 475-490, January.
    9. Graham Loomes & Ganna Pogrebna, 2014. "Testing for independence while allowing for probabilistic choice," Journal of Risk and Uncertainty, Springer, vol. 49(3), pages 189-211, December.
    10. William S. Neilson, 2000. "Victory and Defeat in a Model of Behavior in Games and Toward Risk," Econometric Society World Congress 2000 Contributed Papers 0690, Econometric Society.
    11. Klaus Wälde, 2016. "Emotion Research in Economics," CESifo Working Paper Series 5982, CESifo.
    12. Weber, Bethany J. & Chapman, Gretchen B., 2005. "Playing for peanuts: Why is risk seeking more common for low-stakes gambles?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 97(1), pages 31-46, May.
    13. Herweg, Fabian & Müller, Daniel, 2021. "A comparison of regret theory and salience theory for decisions under risk," Journal of Economic Theory, Elsevier, vol. 193(C).
    14. Pierpaolo Battigalli & Martin Dufwenberg, 2022. "Belief-Dependent Motivations and Psychological Game Theory," Journal of Economic Literature, American Economic Association, vol. 60(3), pages 833-882, September.
    15. Doron Sonsino, 2008. "Disappointment Aversion in internet Bidding-Decisions," Theory and Decision, Springer, vol. 64(2), pages 363-393, March.
    16. Georgalos, Konstantinos & Paya, Ivan & Peel, David, 2024. "The Kőszegi–Rabin expectations-based model and risk-apportionment tasks for elicitation of higher order risk preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 224(C), pages 749-770.
    17. Edouard Kujawski, 2005. "A reference‐dependent regret model for deterministic tradeoff studies," Systems Engineering, John Wiley & Sons, vol. 8(2), pages 119-137.
    18. van Bilsen, Servaas & Laeven, Roger J.A., 2020. "Dynamic consumption and portfolio choice under prospect theory," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 224-237.
    19. Mark Schneider & Robert Day, 2018. "Target-Adjusted Utility Functions and Expected-Utility Paradoxes," Management Science, INFORMS, vol. 64(1), pages 271-287, January.
    20. Tianyang Wang & Robert G. Schwebach & Sriram V. Villupuram, 2022. "Reference point formation: Does the market whisper in the background?," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 45(2), pages 384-421, June.

    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:spr:fuzodm:v:20:y:2021:i:1:d:10.1007_s10700-020-09335-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.