IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i4p1291-d142536.html
   My bibliography  Save this article

Green Logistic Provider Selection with a Hesitant Fuzzy Linguistic Thermodynamic Method Integrating Cumulative Prospect Theory and PROMETHEE

Author

Listed:
  • Huchang Liao

    (Business School, Sichuan University, Chengdu 610064, China
    Department of Computer Science and Artificial Intelligence, University of Granada, E-18071 Granada, Spain)

  • Di Wu

    (Business School, Sichuan University, Chengdu 610064, China)

  • Yulong Huang

    (Business School, Sichuan University, Chengdu 610064, China)

  • Peijia Ren

    (Business School, Sichuan University, Chengdu 610064, China)

  • Zeshui Xu

    (Business School, Sichuan University, Chengdu 610064, China)

  • Mohit Verma

    (CSIR-Structural Engineering Research Centre, Chennai 600113, India)

Abstract

In the process of evaluating the green levels of cold-chain logistics providers, experts may hesitate between several linguistic terms rather than give precise values over the alternatives. Due to the potential profit and risk of business decisions, decision-making information is often based on experts’ expectations of programs and is expressed as hesitant fuzzy linguistic terms. The consistency of evaluation information of an alternative can reflect the clarity of the alternative in the mind of experts and its own controversy. This paper proposes a method to use the value transfer function in the cumulative prospect theory to convert the original hesitant fuzzy linguistic terms into evaluation information based on reference points. We also introduce the parameters related to the disorder of the system in the hesitant fuzzy thermodynamic method to describe the quantity and quality characteristics of the alternatives. In these kinds of multi-criteria decision-making problems, the weights of criteria are of great importance for decision-making results. Considering the conflicting cases among criteria, the weights were obtained by utilizing the PROMETHEE method. An illustrative example concerning green logistics provider selection was operated to show the practicability of the proposed method.

Suggested Citation

  • Huchang Liao & Di Wu & Yulong Huang & Peijia Ren & Zeshui Xu & Mohit Verma, 2018. "Green Logistic Provider Selection with a Hesitant Fuzzy Linguistic Thermodynamic Method Integrating Cumulative Prospect Theory and PROMETHEE," Sustainability, MDPI, vol. 10(4), pages 1-16, April.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:1291-:d:142536
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/4/1291/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/10/4/1291/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aguezzoul, Aicha, 2014. "Third-party logistics selection problem: A literature review on criteria and methods," Omega, Elsevier, vol. 49(C), pages 69-78.
    2. 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.
    3. 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..
    4. Ankit Bansal & Pravin Kumar, 2013. "3PL selection using hybrid model of AHP-PROMETHEE," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 14(3), pages 373-397.
    5. Zhang, Jiekuan & Zhang, Yan, 2018. "Carbon tax, tourism CO2 emissions and economic welfare," Annals of Tourism Research, Elsevier, vol. 69(C), pages 18-30.
    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. Guohua Qu & Rudan Xue & Tianjiao Li & Weihua Qu & Zeshui Xu, 2020. "A Stochastic Multi-Attribute Method for Measuring Sustainability Performance of a Supplier Based on a Triple Bottom Line Approach in a Dual Hesitant Fuzzy Linguistic Environment," IJERPH, MDPI, vol. 17(6), pages 1-26, March.
    2. Szabolcs Duleba & Sarbast Moslem, 2018. "Sustainable Urban Transport Development with Stakeholder Participation, an AHP-Kendall Model: A Case Study for Mersin," Sustainability, MDPI, vol. 10(10), pages 1-14, October.
    3. Jianghong Zhu & Yanlai Li, 2018. "Green Supplier Selection Based on Consensus Process and Integrating Prioritized Operator and Choquet Integral," Sustainability, MDPI, vol. 10(8), pages 1-22, August.
    4. Prabha Bhola & Alexandros-Georgios Chronis & Panos Kotsampopoulos & Nikos Hatziargyriou, 2023. "Business Model Selection for Community Energy Storage: A Multi Criteria Decision Making Approach," Energies, MDPI, vol. 16(18), pages 1-30, September.
    5. Aleksandra Król & Jerzy Księżak & Elżbieta Kubińska & Stelios Rozakis, 2018. "Evaluation of Sustainability of Maize Cultivation in Poland. A Prospect Theory—PROMETHEE Approach," Sustainability, MDPI, vol. 10(11), pages 1-19, November.
    6. Chia-Nan Wang & Yih-Tzoo Chen & Chun-Chun Tung, 2021. "Evaluation of Wave Energy Location by Using an Integrated MCDM Approach," Energies, MDPI, vol. 14(7), pages 1-14, March.
    7. R. Krishankumar & K. S. Ravichandran & J. Premaladha & Samarjit Kar & Edmundas Kazimieras Zavadskas & Jurgita Antucheviciene, 2018. "A Decision Framework under a Linguistic Hesitant Fuzzy Set for Solving Multi-Criteria Group Decision Making Problems," Sustainability, MDPI, vol. 10(8), pages 1-21, July.
    8. Ying Luo & Xudong Chen & Liming Yao, 2021. "Flood disaster resilience evaluation of Chinese regions: integrating the hesitant fuzzy linguistic term sets with prospect theory," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(1), pages 667-690, January.
    9. Xiaobing Yu & Hong Chen & Zhonghui Ji, 2019. "Combination of Probabilistic Linguistic Term Sets and PROMETHEE to Evaluate Meteorological Disaster Risk: Case Study of Southeastern China," Sustainability, MDPI, vol. 11(5), pages 1-13, March.
    10. Burak, Selmin & Samanlioglu, Funda & Ülker, Duygu, 2022. "Evaluation of irrigation methods in Söke Plain with HF-AHP-PROMETHEE II hybrid MCDM method," Agricultural Water Management, Elsevier, vol. 271(C).
    11. Rujee Rodcha & Nitin K. Tripathi & Rajendra Prasad Shrestha, 2019. "Comparison of Cash Crop Suitability Assessment Using Parametric, AHP, and FAHP Methods," Land, MDPI, vol. 8(5), pages 1-22, May.
    12. Junping Tian & Zheng Huo & Fengjiao Ma & Xing Gao & Yanbin Wu, 2019. "Application and Selection of Remediation Technology for OCPs-Contaminated Sites by Decision-Making Methods," IJERPH, MDPI, vol. 16(11), pages 1-15, May.

    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. van den Bergh, J.C.J.M. & Botzen, W.J.W., 2015. "Monetary valuation of the social cost of CO2 emissions: A critical survey," Ecological Economics, Elsevier, vol. 114(C), pages 33-46.
    2. Shoji, Isao & Kanehiro, Sumei, 2016. "Disposition effect as a behavioral trading activity elicited by investors' different risk preferences," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 104-112.
    3. Jonathan Meng & Feng Fu, 2020. "Understanding Gambling Behavior and Risk Attitudes Using Cryptocurrency-based Casino Blockchain Data," Papers 2008.05653, arXiv.org, revised Aug 2020.
    4. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    5. Boone, Jan & Sadrieh, Abdolkarim & van Ours, Jan C., 2009. "Experiments on unemployment benefit sanctions and job search behavior," European Economic Review, Elsevier, vol. 53(8), pages 937-951, November.
    6. Castro, Luciano de & Galvao, Antonio F. & Kim, Jeong Yeol & Montes-Rojas, Gabriel & Olmo, Jose, 2022. "Experiments on portfolio selection: A comparison between quantile preferences and expected utility decision models," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    7. Jos'e Cl'audio do Nascimento, 2019. "Behavioral Biases and Nonadditive Dynamics in Risk Taking: An Experimental Investigation," Papers 1908.01709, arXiv.org, revised Apr 2023.
    8. Francesco GUALA, 2017. "Preferences: Neither Behavioural nor Mental," Departmental Working Papers 2017-05, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    9. Bin Zou, 2017. "Optimal Investment In Hedge Funds Under Loss Aversion," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-32, May.
    10. Itzhak Gilboa & Andrew Postlewaite & Larry Samuelson & David Schmeidler, 2019. "What are axiomatizations good for?," Theory and Decision, Springer, vol. 86(3), pages 339-359, May.
    11. Wiafe, Osei K. & Basu, Anup K. & Chen, En Te, 2020. "Portfolio choice after retirement: Should self-annuitisation strategies hold more equities?," Economic Analysis and Policy, Elsevier, vol. 65(C), pages 241-255.
    12. Nicholas Barberis, 2012. "A Model of Casino Gambling," Management Science, INFORMS, vol. 58(1), pages 35-51, January.
    13. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    14. Goytom Abraha Kahsay & Daniel Osberghaus, 2018. "Storm Damage and Risk Preferences: Panel Evidence from Germany," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(1), pages 301-318, September.
    15. Carolin Bock & Maximilian Schmidt, 2015. "Should I stay, or should I go? – How fund dynamics influence venture capital exit decisions," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 68-82, November.
    16. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2013. "Risk-averse and Risk-seeking Investor Preferences for Oil Spot and Futures," Documentos de Trabajo del ICAE 2013-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Aug 2013.
    17. Paredes-Frigolett, Harold, 2016. "Modeling the effect of responsible research and innovation in quadruple helix innovation systems," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 126-133.
    18. Karle, Heiko & Schumacher, Heiner & Vølund, Rune, 2023. "Consumer loss aversion and scale-dependent psychological switching costs," Games and Economic Behavior, Elsevier, vol. 138(C), pages 214-237.
    19. Christian Gollier & James Hammitt & Nicolas Treich, 2013. "Risk and choice: A research saga," Journal of Risk and Uncertainty, Springer, vol. 47(2), pages 129-145, October.
    20. Carter, Steven & McBride, Michael, 2013. "Experienced utility versus decision utility: Putting the ‘S’ in satisfaction," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 42(C), pages 13-23.

    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:10:y:2018:i:4:p:1291-:d:142536. 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.