IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i11p4606-d367432.html
   My bibliography  Save this article

Multi-Criteria Decision Making of Contractor Selection in Mass Rapid Transit Station Development Using Bayesian Fuzzy Prospect Model

Author

Listed:
  • Min-Yuan Cheng

    (Department of Civil and Construction Engineering, National Taiwan University of Science and Technology, Taipei 10672, Taiwan)

  • Shu-Hua Yeh

    (Department of Civil and Construction Engineering, National Taiwan University of Science and Technology, Taipei 10672, Taiwan)

  • Woei-Chyi Chang

    (Department of Civil Engineering, Construction Engineering and Management Division, National Taiwan University, Taipei 10617, Taiwan)

Abstract

In Taiwan, the most advantageous tender in governmental procurement is the selection of a general contractor based on a score or ranking evaluated by a committee. Due to personal, subjective preferences, the contractor selection of committee members may be different, causing cognitive difference between the results of the members’ selection and the preliminary opinions provided by the working group. Integrated, multi-criteria decision making techniques, combined with preference relation, Bayesian, fuzzy utility, and prospect theories are used to assess factors weighing up the duration/cost/quality, probability of external information, and utility function system. The paper proposes a Bayesian fuzzy prospect model for group decision making, based on probability and utility multiplied relation, and taking the sustainable development factors into consideration. This study aims to provide committees with an objective model to select the best contractor for public construction projects. The results of this study can avoid the lowest bidder being selected; besides, the score gap of contractor selection can be increased, and the difference between the top three contractors’ scores can be decreased as well. In addition to proposing an innovative decision-making system of contractor selection and an index weight-assessing system for sustainable development, this model will be widely applied and sustainably updated for other cases.

Suggested Citation

  • Min-Yuan Cheng & Shu-Hua Yeh & Woei-Chyi Chang, 2020. "Multi-Criteria Decision Making of Contractor Selection in Mass Rapid Transit Station Development Using Bayesian Fuzzy Prospect Model," Sustainability, MDPI, vol. 12(11), pages 1-32, June.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:11:p:4606-:d:367432
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/11/4606/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/11/4606/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zydrune Morkunaite & Romualdas Bausys & Edmundas Kazimieras Zavadskas, 2019. "Contractor Selection for Sgraffito Decoration of Cultural Heritage Buildings Using the WASPAS-SVNS Method," Sustainability, MDPI, vol. 11(22), pages 1-25, November.
    2. Rick Best & Craig Langston, 2006. "Evaluation of construction contractor performance: a critical analysis of some recent research," Construction Management and Economics, Taylor & Francis Journals, vol. 24(4), pages 439-445.
    3. Weber, Charles A. & Current, John R. & Benton, W. C., 1991. "Vendor selection criteria and methods," European Journal of Operational Research, Elsevier, vol. 50(1), pages 2-18, January.
    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. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    6. 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.
    7. Agnieszka Leśniak & Filip Janowiec, 2019. "Risk Assessment of Additional Works in Railway Construction Investments Using the Bayes Network," Sustainability, MDPI, vol. 11(19), pages 1-15, September.
    8. Yi Zhang, 2020. "Construction of Bid Evaluation Index System in Government Public Project Green Procurement in China Based on D-S Evidence Theory," Sustainability, MDPI, vol. 12(2), pages 1-15, January.
    9. Herrera-Viedma, E. & Herrera, F. & Chiclana, F. & Luque, M., 2004. "Some issues on consistency of fuzzy preference relations," European Journal of Operational Research, Elsevier, vol. 154(1), pages 98-109, April.
    10. Qingpeng Cao & Moses Olabhele Esangbedo & Sijun Bai & Caroline Olufunke Esangbedo, 2019. "Grey SWARA-FUCOM Weighting Method for Contractor Selection MCDM Problem: A Case Study of Floating Solar Panel Energy System Installation," Energies, MDPI, vol. 12(13), pages 1-30, June.
    11. Zenonas Turskis & Nikolaj Goranin & Assel Nurusheva & Seilkhan Boranbayev, 2019. "A Fuzzy WASPAS-Based Approach to Determine Critical Information Infrastructures of EU Sustainable Development," Sustainability, MDPI, vol. 11(2), pages 1-25, January.
    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. Khoso, Ali Raza & Yusof, Aminah Md & Chen, Zhen-Song & Skibniewski, Mirosław J. & Chin, Kwai-Sang & Khahro, Shabir Hussain & Sohu, Samiullah, 2022. "Comprehensive analysis of state-of-the-art contractor selection models in construction environment-A critical review and future call," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    2. Gerda Ana Melnik-Leroy & Gintautas Dzemyda, 2021. "How to Influence the Results of MCDM?—Evidence of the Impact of Cognitive Biases," Mathematics, MDPI, vol. 9(2), pages 1-25, January.
    3. Aziz Naghizadeh Vardin & Ramin Ansari & Mohammad Khalilzadeh & Jurgita Antucheviciene & Romualdas Bausys, 2021. "An Integrated Decision Support Model Based on BWM and Fuzzy-VIKOR Techniques for Contractor Selection in Construction Projects," Sustainability, MDPI, vol. 13(12), pages 1-28, June.

    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. Alarie, Yves & Dionne, Georges, 2005. "Testing explanations of preference reversal: A model," Working Papers 05-2, HEC Montreal, Canada Research Chair in Risk Management.
    2. Mohammed Abdellaoui & Olivier L’Haridon & Horst Zank, 2010. "Separating curvature and elevation: A parametric probability weighting function," Journal of Risk and Uncertainty, Springer, vol. 41(1), pages 39-65, August.
    3. Foster, Gigi & Frijters, Paul & Schaffner, Markus & Torgler, Benno, 2018. "Expectation formation in an evolving game of uncertainty: New experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 379-405.
    4. Che-Yuan Liang, 2017. "Optimal inequality behind the veil of ignorance," Theory and Decision, Springer, vol. 83(3), pages 431-455, October.
    5. Xue Dong He & Sang Hu & Jan Obłój & Xun Yu Zhou, 2017. "Technical Note—Path-Dependent and Randomized Strategies in Barberis’ Casino Gambling Model," Operations Research, INFORMS, vol. 65(1), pages 97-103, February.
    6. Kerim Keskin, 2016. "Inverse S-shaped probability weighting functions in first-price sealed-bid auctions," Review of Economic Design, Springer;Society for Economic Design, vol. 20(1), pages 57-67, March.
    7. Ariane Charpin, 2018. "Tests des modèles de décision en situation de risque. Le cas des parieurs hippiques en France," Revue économique, Presses de Sciences-Po, vol. 69(5), pages 779-803.
    8. Bocqueho, Geraldine & Jacquet, Florence & Reynaud, Arnaud, 2011. "Expected Utility or Prospect Theory Maximizers? Results from a Structural Model based on Field-experiment Data," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114257, European Association of Agricultural Economists.
    9. Philip Bromiley, 2009. "A Prospect Theory Model of Resource Allocation," Decision Analysis, INFORMS, vol. 6(3), pages 124-138, September.
    10. Freudenreich, Hanna & Musshoff, Oliver & Wiercinski, Ben, 2017. "The Relationship between Farmers' Shock Experiences and their Uncertainty Preferences - Experimental Evidence from Mexico," GlobalFood Discussion Papers 256212, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    11. Syngjoo Choi & Jeongbin Kim & Eungik Lee & Jungmin Lee, 2022. "Probability Weighting and Cognitive Ability," Management Science, INFORMS, vol. 68(7), pages 5201-5215, July.
    12. repec:diw:diwwpp:dp1879 is not listed on IDEAS
    13. Thomas Epper & Helga Fehr-Duda & Adrian Bruhin, 2011. "Viewing the future through a warped lens: Why uncertainty generates hyperbolic discounting," Journal of Risk and Uncertainty, Springer, vol. 43(3), pages 169-203, December.
    14. Mohammed Abdellaoui & Horst Zank, 2023. "Source and rank-dependent utility," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 75(4), pages 949-981, May.
    15. Basieva, Irina & Khrennikova, Polina & Pothos, Emmanuel M. & Asano, Masanari & Khrennikov, Andrei, 2018. "Quantum-like model of subjective expected utility," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 150-162.
    16. Kontek, Krzysztof, 2009. "Are People Really Risk Seeking for Losses?," MPRA Paper 19326, University Library of Munich, Germany.
    17. LiCalzi, Marco & Sorato, Annamaria, 2006. "The Pearson system of utility functions," European Journal of Operational Research, Elsevier, vol. 172(2), pages 560-573, July.
    18. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2013. "Salience and Consumer Choice," Journal of Political Economy, University of Chicago Press, vol. 121(5), pages 803-843.
    19. Epper, Thomas & Fehr-Duda, Helga, 2017. "A Tale of Two Tails: On the Coexistence of Overweighting and Underweighting of Rare Extreme Events," Economics Working Paper Series 1705, University of St. Gallen, School of Economics and Political Science.
    20. Sanjit Dhami & Narges Hajimoladarvish, 2020. "Mental Accounting, Loss Aversion, and Tax Evasion: Theory and Evidence," CESifo Working Paper Series 8606, CESifo.
    21. Nikolaus Schweizer & Nora Szech, 2018. "Optimal Revelation of Life-Changing Information," Management Science, INFORMS, vol. 64(11), pages 5250-5262, November.

    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:jsusta:v:12:y:2020:i:11:p:4606-:d:367432. 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.