IDEAS home Printed from https://ideas.repec.org/a/spr/grdene/v28y2019i3d10.1007_s10726-019-09616-7.html
   My bibliography  Save this article

Solving voting system by data envelopment analysis for assessing sustainability of suppliers

Author

Listed:
  • Mohammad Izadikhah

    (Islamic Azad University)

  • Reza Farzipoor Saen

    (Islamic Azad University)

Abstract

Recently, sustainable supply chain management has attracted the attention of scholars and practitioners. Data envelopment analysis (DEA) is a useful tool for evaluating sustainability of suppliers. Ranking a system of voting is an important topic in DEA. Many firms apply voting systems to rank candidates. Generally, these kinds of methods rank candidates by their associated weights. In this paper, to increase discrimination power among candidates, a novel model for obtaining a suitable value of discriminating factor is proposed. Then, using the optimal value of the discriminating factor, a new model for calculating preference scores of candidates is presented. This model evaluates candidates based on different set of weights. To evaluate candidates based on common set of weights, using concept of ideal point, two new multiple objective programming models are proposed. The proposed method is applied for selecting the most sustainable suppliers that supply self-supporting cable for a power distribution company. Results show that candidates might be affected by changing the set of weights. Using our proposed models, full rankings are obtained.

Suggested Citation

  • Mohammad Izadikhah & Reza Farzipoor Saen, 2019. "Solving voting system by data envelopment analysis for assessing sustainability of suppliers," Group Decision and Negotiation, Springer, vol. 28(3), pages 641-669, June.
    • Handle: RePEc:spr:grdene:v:28:y:2019:i:3:d:10.1007_s10726-019-09616-7
    DOI: 10.1007/s10726-019-09616-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10726-019-09616-7
    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/s10726-019-09616-7?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. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    2. Hatefi, S.M. & Torabi, S.A., 2010. "A common weight MCDA-DEA approach to construct composite indicators," Ecological Economics, Elsevier, vol. 70(1), pages 114-120, November.
    3. Calzada-Infante, Laura & Lozano, Sebastián, 2016. "Analysing Olympic Games through dominance networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1215-1230.
    4. Liu, Fuh-Hwa Franklin & Hai, Hui Lin, 2005. "The voting analytic hierarchy process method for selecting supplier," International Journal of Production Economics, Elsevier, vol. 97(3), pages 308-317, September.
    5. Paul D. Ballew & Robert H. Schnorbus, 1994. "The impact of the auto industry on the economy," Chicago Fed Letter, Federal Reserve Bank of Chicago, issue Mar.
    6. Pavel Yu. Chebotarev & Elena Shamis, 1998. "Characterizations of scoring methodsfor preference aggregation," Annals of Operations Research, Springer, vol. 80(0), pages 299-332, January.
    7. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    8. A. Davoodi & H. Rezai, 2012. "Common set of weights in data envelopment analysis: a linear programming problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 355-365, June.
    9. Sitarz, Sebastian, 2012. "Mean value and volume-based sensitivity analysis for Olympic rankings," European Journal of Operational Research, Elsevier, vol. 216(1), pages 232-238.
    10. Llamazares, Bonifacio & Pea, Teresa, 2009. "Preference aggregation and DEA: An analysis of the methods proposed to discriminate efficient candidates," European Journal of Operational Research, Elsevier, vol. 197(2), pages 714-721, September.
    11. Sinuany-Stern, Zilla & Friedman, Lea, 1998. "DEA and the discriminant analysis of ratios for ranking units," European Journal of Operational Research, Elsevier, vol. 111(3), pages 470-478, December.
    12. Obata, Tsuneshi & Ishii, Hiroaki, 2003. "A method for discriminating efficient candidates with ranked voting data," European Journal of Operational Research, Elsevier, vol. 151(1), pages 233-237, November.
    13. Ebrahimnejad, Ali & Tavana, Madjid & Santos-Arteaga, Francisco J., 2016. "An integrated data envelopment analysis and simulation method for group consensus ranking," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 119(C), pages 1-17.
    14. Bai, Chunguang & Sarkis, Joseph, 2010. "Integrating sustainability into supplier selection with grey system and rough set methodologies," International Journal of Production Economics, Elsevier, vol. 124(1), pages 252-264, March.
    15. Caporaletti, L. E. & Dulá, J. H. & Womer, N. K., 1999. "Performance evaluation based on multiple attributes with nonparametric frontiers," Omega, Elsevier, vol. 27(6), pages 637-645, December.
    16. Cook, Wade D. & Kress, Moshe, 1991. "A multiple criteria decision model with ordinal preference data," European Journal of Operational Research, Elsevier, vol. 54(2), pages 191-198, September.
    17. Wu, Desheng & Olson, David L., 2008. "Supply chain risk, simulation, and vendor selection," International Journal of Production Economics, Elsevier, vol. 114(2), pages 646-655, August.
    18. Wu, Jie & Chu, Junfei & Sun, Jiasen & Zhu, Qingyuan, 2016. "DEA cross-efficiency evaluation based on Pareto improvement," European Journal of Operational Research, Elsevier, vol. 248(2), pages 571-579.
    19. Cook, Wade D. & Zhu, Joe, 2007. "Within-group common weights in DEA: An analysis of power plant efficiency," European Journal of Operational Research, Elsevier, vol. 178(1), pages 207-216, April.
    20. Green, Rodney H. & Doyle, John R. & Cook, Wade D., 1996. "Preference voting and project ranking using DEA and cross-evaluation," European Journal of Operational Research, Elsevier, vol. 90(3), pages 461-472, May.
    21. Wade D. Cook & Moshe Kress, 1990. "A Data Envelopment Model for Aggregating Preference Rankings," Management Science, INFORMS, vol. 36(11), pages 1302-1310, November.
    22. Mohammad Izadikhah & Reza Farzipoor Saen & Kourosh Ahmadi, 2017. "How to Assess Sustainability of Suppliers in the Presence of Dual-Role Factor and Volume Discounts? A Data Envelopment Analysis Approach," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(03), pages 1-25, June.
    23. Talluri, Srinivas & Narasimhan, Ram & Nair, Anand, 2006. "Vendor performance with supply risk: A chance-constrained DEA approach," International Journal of Production Economics, Elsevier, vol. 100(2), pages 212-222, April.
    24. Kleinsorge, Ilene K. & Schary, Philip B. & Tanner, Ray D., 1992. "Data Envelopment Analysis for monitoring customer-supplier relationships," Journal of Accounting and Public Policy, Elsevier, vol. 11(4), pages 357-372.
    25. Mahdiloo, Mahdi & Saen, Reza Farzipoor & Lee, Ki-Hoon, 2015. "Technical, environmental and eco-efficiency measurement for supplier selection: An extension and application of data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 168(C), pages 279-289.
    26. Ruiz, José L. & Sirvent, Inmaculada, 2016. "Common benchmarking and ranking of units with DEA," Omega, Elsevier, vol. 65(C), pages 1-9.
    27. Hashimoto, Akihiro, 1997. "A ranked voting system using a DEA/AR exclusion model: A note," European Journal of Operational Research, Elsevier, vol. 97(3), pages 600-604, March.
    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. Amin Mahmoudi & Mehdi Abbasi & Xiaopeng Deng, 2022. "Evaluating the Performance of the Suppliers Using Hybrid DEA-OPA Model: A Sustainable Development Perspective," Group Decision and Negotiation, Springer, vol. 31(2), pages 335-362, April.
    2. Patricija Bajec & Danijela Tuljak-Suban & Eva Zalokar, 2021. "A Distance-Based AHP-DEA Super-Efficiency Approach for Selecting an Electric Bike Sharing System Provider: One Step Closer to Sustainability and a Win–Win Effect for All Target Groups," Sustainability, MDPI, vol. 13(2), pages 1-24, January.
    3. Katerina Fotova Čiković & Ivana Martinčević & Joško Lozić, 2022. "Application of Data Envelopment Analysis (DEA) in the Selection of Sustainable Suppliers: A Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(11), pages 1-30, 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. Madjid Tavana & Mehdi Soltanifar & Francisco J. Santos-Arteaga, 2023. "Analytical hierarchy process: revolution and evolution," Annals of Operations Research, Springer, vol. 326(2), pages 879-907, July.
    2. Mohammad Izadikhah & Reza Farzipoor Saen & Razieh Roostaee, 2018. "How to assess sustainability of suppliers in the presence of volume discount and negative data in data envelopment analysis?," Annals of Operations Research, Springer, vol. 269(1), pages 241-267, October.
    3. Mohammad Izadikhah & Reza Farzipoor Saen, 2020. "Ranking sustainable suppliers by context-dependent data envelopment analysis," Annals of Operations Research, Springer, vol. 293(2), pages 607-637, October.
    4. Pishchulov, Grigory & Trautrims, Alexander & Chesney, Thomas & Gold, Stefan & Schwab, Leila, 2019. "The Voting Analytic Hierarchy Process revisited: A revised method with application to sustainable supplier selection," International Journal of Production Economics, Elsevier, vol. 211(C), pages 166-179.
    5. Soltanifar, Mehdi & Shahghobadi, Saeid, 2013. "Selecting a benevolent secondary goal model in data envelopment analysis cross-efficiency evaluation by a voting model," Socio-Economic Planning Sciences, Elsevier, vol. 47(1), pages 65-74.
    6. Mohammad Izadikhah & Reza Farzipoor Saen & Kourosh Ahmadi, 2017. "How to Assess Sustainability of Suppliers in the Presence of Dual-Role Factor and Volume Discounts? A Data Envelopment Analysis Approach," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(03), pages 1-25, June.
    7. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    8. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    9. Paolo Viappiani, 2024. "Volumetric Aggregation Methods for Scoring Rules with Unknown Weights," Post-Print hal-04440153, HAL.
    10. Llamazares, Bonifacio & Peña, Teresa, 2013. "Aggregating preferences rankings with variable weights," European Journal of Operational Research, Elsevier, vol. 230(2), pages 348-355.
    11. Ebrahimnejad, Ali & Tavana, Madjid & Santos-Arteaga, Francisco J., 2016. "An integrated data envelopment analysis and simulation method for group consensus ranking," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 119(C), pages 1-17.
    12. Mohammad Izadikhah & Reza Farzipoor Saen, 2023. "Developing a linear stochastic two-stage data envelopment analysis model for evaluating sustainability of supply chains: a case study in welding industry," Annals of Operations Research, Springer, vol. 322(1), pages 195-215, March.
    13. Bonifacio Llamazares, 2016. "Ranking Candidates Through Convex Sequences of Variable Weights," Group Decision and Negotiation, Springer, vol. 25(3), pages 567-584, May.
    14. Jie Wu & Junfei Chu & Qingyuan Zhu & Pengzhen Yin & Liang Liang, 2016. "DEA cross-efficiency evaluation based on satisfaction degree: an application to technology selection," International Journal of Production Research, Taylor & Francis Journals, vol. 54(20), pages 5990-6007, October.
    15. Obata, Tsuneshi & Ishii, Hiroaki, 2003. "A method for discriminating efficient candidates with ranked voting data," European Journal of Operational Research, Elsevier, vol. 151(1), pages 233-237, November.
    16. Tüselmann, Heinz & Sinkovics, Rudolf R. & Pishchulov, Grigory, 2016. "Revisiting the standing of international business journals in the competitive landscape," Journal of World Business, Elsevier, vol. 51(4), pages 487-498.
    17. Foroughi, A.A. & Tamiz, M., 2005. "An effective total ranking model for a ranked voting system," Omega, Elsevier, vol. 33(6), pages 491-496, December.
    18. Alikhani, Reza & Torabi, S. Ali & Altay, Nezih, 2019. "Strategic supplier selection under sustainability and risk criteria," International Journal of Production Economics, Elsevier, vol. 208(C), pages 69-82.
    19. Pankaj Dutta & Bharath Jaikumar & Manpreet Singh Arora, 2022. "Applications of data envelopment analysis in supplier selection between 2000 and 2020: a literature review," Annals of Operations Research, Springer, vol. 315(2), pages 1399-1454, August.
    20. Afsharian, Mohsen & Ahn, Heinz & Harms, Sören Guntram, 2021. "A review of DEA approaches applying a common set of weights: The perspective of centralized management," European Journal of Operational Research, Elsevier, vol. 294(1), pages 3-15.

    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:grdene:v:28:y:2019:i:3:d:10.1007_s10726-019-09616-7. 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.