IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i12p6536-d576756.html
   My bibliography  Save this article

Risk Attitude in Multicriteria Decision Analysis: A Compromise Approach

Author

Listed:
  • Juan Ribes

    (ETSI Informáticos, Campus de Montegancedo, Universidad Politécnica de Madrid, Boadilla del Monte, 28660 Madrid, Spain
    Department of Financial and Actuarial Economics and Statistics, Facultad de Ciencias Económicas y Empresariales, Campus de Somosaguas, Universidad Complutense de Madrid, Pozuelo de Alarcón, 28223 Madrid, Spain
    These authors contributed equally to this work.)

  • Jacinto González-Pachón

    (Department of Artificial Intelligence, Campus de Montegancedo, Universidad Politécnica de Madrid, Boadilla del Monte, 28660 Madrid, Spain
    These authors contributed equally to this work.)

Abstract

In fields on which decisions need to be taken including health, as we are seeing nowadays in the COVID-19 crisis, decision-makers face multiple criteria and results with a random component. In stochastic multicriteria decision-making models, the risk attitude of the decision maker is a relevant factor. Traditionally, the shape of a utility function is the only element that represents the decision maker’s risk attitude. The eduction process of multi-attribute utility functions implies some operational drawbacks, and it is not always easy. In this paper, we propose a new element with which the decision maker’s risk attitude can be implemented: the selection of the stochastic efficiency concept to be used during a decision analysis. We suggest representing the risk attitude as a conflict between two poles: risk neutral attitude, associated with best expectations, and risk aversion attitude, associated with a lower uncertainty. The Extended Goal Programming formulation has inspired the parameter that is introduced in a new risk attitude formulation. This parameter reflects the trade-off between the two classical poles with respect to risk attitude . Thus, we have produced a new stochastic efficiency concept that we call Compromise Efficiency .

Suggested Citation

  • Juan Ribes & Jacinto González-Pachón, 2021. "Risk Attitude in Multicriteria Decision Analysis: A Compromise Approach," IJERPH, MDPI, vol. 18(12), pages 1-14, June.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:12:p:6536-:d:576756
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/12/6536/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/12/6536/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Brunette, Marielle & Jacob, Julien, 2019. "Risk aversion, prudence and temperance: An experiment in gain and loss," Research in Economics, Elsevier, vol. 73(2), pages 174-189.
    2. P. L. Yu, 1973. "A Class of Solutions for Group Decision Problems," Management Science, INFORMS, vol. 19(8), pages 936-946, April.
    3. Dylan Jones & Mehrdad Tamiz, 2010. "Practical Goal Programming," International Series in Operations Research and Management Science, Springer, edition 1, number 978-1-4419-5771-9, September.
    4. André Hajek & Benedikt Kretzler & Hans-Helmut König, 2020. "Multimorbidity, Loneliness, and Social Isolation. A Systematic Review," IJERPH, MDPI, vol. 17(22), pages 1-12, November.
    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. González-Pachón, Jacinto & Romero, Carlos, 2016. "Bentham, Marx and Rawls ethical principles: In search for a compromise," Omega, Elsevier, vol. 62(C), pages 47-51.
    7. Walter Gutjahr & Alois Pichler, 2016. "Stochastic multi-objective optimization: a survey on non-scalarizing methods," Annals of Operations Research, Springer, vol. 236(2), pages 475-499, January.
    8. Megan Cross & Shu-Kay Ng & Paul Scuffham, 2020. "Trading Health for Wealth: The Effect of COVID-19 Response Stringency," IJERPH, MDPI, vol. 17(23), pages 1-15, November.
    9. R. Caballero & E. Cerdá & M. M. Muñoz & L. Rey & I. M. Stancu-Minasian, 2001. "Efficient Solution Concepts and Their Relations in Stochastic Multiobjective Programming," Journal of Optimization Theory and Applications, Springer, vol. 110(1), pages 53-74, July.
    10. Walter J. Gutjahr & Alois Pichler, 2016. "Stochastic multi-objective optimization: a survey on non-scalarizing methods," Annals of Operations Research, Springer, vol. 236(2), pages 475-499, January.
    11. Fouad Ben Abdelaziz & Cinzia Colapinto & Davide La Torre & Danilo Liuzzi, 2020. "A stochastic dynamic multiobjective model for sustainable decision making," Annals of Operations Research, Springer, vol. 293(2), pages 539-556, October.
    12. Brunette, Marielle & Jacob, Julien, 2019. "Risk aversion, prudence and temperance: An experiment in gain and loss," Research in Economics, Elsevier, vol. 73(2), pages 174-189.
    13. González-Pachón, Jacinto & Romero, Carlos, 2011. "The design of socially optimal decisions in a consensus scenario," Omega, Elsevier, vol. 39(2), pages 179-185, April.
    14. Romero, Carlos, 2001. "Extended lexicographic goal programming: a unifying approach," Omega, Elsevier, vol. 29(1), pages 63-71, February.
    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. González-Pachón, Jacinto & Romero, Carlos, 2016. "Bentham, Marx and Rawls ethical principles: In search for a compromise," Omega, Elsevier, vol. 62(C), pages 47-51.
    2. Francisco Salas-Molina & Filippo Bistaffa & Juan A. Rodriguez-Aguilar, 2024. "A General Approach for Computing a Consensus in Group Decision Making That Integrates Multiple Ethical Principles," Papers 2401.07818, arXiv.org, revised Mar 2024.
    3. Tian, Ye & Li, Yudi & Sun, Jian, 2022. "Stick or carrot for traffic demand management? Evidence from experimental economics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 235-254.
    4. Benítez-Fernández, Amalia & Ruiz, Francisco, 2020. "A Meta-Goal Programming approach to cardinal preferences aggregation in multicriteria problems," Omega, Elsevier, vol. 94(C).
    5. Chang, Ching-Ter, 2011. "Multi-choice goal programming with utility functions," European Journal of Operational Research, Elsevier, vol. 215(2), pages 439-445, December.
    6. Konstantinos Georgalos & Ivan Paya & David Peel, 2023. "Higher order risk attitudes: new model insights and heterogeneity of preferences," Experimental Economics, Springer;Economic Science Association, vol. 26(1), pages 145-192, March.
    7. Jones, Dylan, 2011. "A practical weight sensitivity algorithm for goal and multiple objective programming," European Journal of Operational Research, Elsevier, vol. 213(1), pages 238-245, August.
    8. Ivan Paya & David Peel & Konstantinos Georgalos, 2020. "On the Predictions of Cumulative Prospect Theory for Third and Fourth Order Preferences," Working Papers 293574809, Lancaster University Management School, Economics Department.
    9. Amelia Bilbao-Terol & Mariano Jiménez & Mar Arenas-Parra, 2016. "A group decision making model based on goal programming with fuzzy hierarchy: an application to regional forest planning," Annals of Operations Research, Springer, vol. 245(1), pages 137-162, October.
    10. Salas-Molina, Francisco & Bistaffa, Filippo & Rodríguez-Aguilar, Juan A., 2023. "A general approach for computing a consensus in group decision making that integrates multiple ethical principles," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    11. Rohmer, S.U.K. & Gerdessen, J.C. & Claassen, G.D.H., 2019. "Sustainable supply chain design in the food system with dietary considerations: A multi-objective analysis," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1149-1164.
    12. Jones, Dylan & Jimenez, Mariano, 2013. "Incorporating additional meta-objectives into the extended lexicographic goal programming framework," European Journal of Operational Research, Elsevier, vol. 227(2), pages 343-349.
    13. Mila Bravo & Dylan Jones & David Pla-Santamaria & Francisco Salas-Molina, 2022. "Encompassing statistically unquantifiable randomness in goal programming: an application to portfolio selection," Operational Research, Springer, vol. 22(5), pages 5685-5706, November.
    14. Panos Xidonas & Christis Hassapis & George Mavrotas & Christos Staikouras & Constantin Zopounidis, 2018. "Multiobjective portfolio optimization: bridging mathematical theory with asset management practice," Annals of Operations Research, Springer, vol. 267(1), pages 585-606, August.
    15. Hadi Karimi & Sandra D. Ekşioğlu & Michael Carbajales-Dale, 2021. "A biobjective chance constrained optimization model to evaluate the economic and environmental impacts of biopower supply chains," Annals of Operations Research, Springer, vol. 296(1), pages 95-130, January.
    16. Maniezzo, Vittorio & Boschetti, Marco A. & Gutjahr, Walter J., 2021. "Stochastic premarshalling of block stacking warehouses," Omega, Elsevier, vol. 102(C).
    17. Francisco Salas-Molina & Juan Antonio Rodr'iguez Aguilar & Filippo Bistaffa, 2020. "Shared value economics: an axiomatic approach," Papers 2006.00581, arXiv.org.
    18. Jones, Dylan & Firouzy, Sina & Labib, Ashraf & Argyriou, Athanasios V., 2022. "Multiple criteria model for allocating new medical robotic devices to treatment centres," European Journal of Operational Research, Elsevier, vol. 297(2), pages 652-664.
    19. Bottasso, Anna & Duchêne, Sébastien & Guerci, Eric & Hanaki, Nobuyuki & Noussair, Charles N., 2022. "Higher order risk attitudes of financial experts," Journal of Behavioral and Experimental Finance, Elsevier, vol. 34(C).
    20. Hocine, Amine, 2018. "Meta goal programing approach for solving multi-criteria de Novo programing problemAuthor-Name: Zhuang, Zheng-Yun," European Journal of Operational Research, Elsevier, vol. 265(1), pages 228-238.

    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:gam:jijerp:v:18:y:2021:i:12:p:6536-:d:576756. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.