IDEAS home Printed from https://ideas.repec.org/a/wly/navres/v43y1996i4p519-531.html
   My bibliography  Save this article

An extreme‐point approach for obtaining weighted ratings in qualitative multicriteria decision making

Author

Listed:
  • Wade D. Cook
  • Moshe Kress

Abstract

Many attempts have been made in the past to obtain estimates for the weights and ratings values of a multicriteria linear utility function. In particular, the problem arises when both criteria importance and alternatives' ratings are expressed in a qualitative ordinal manner. This article proposes an extreme‐point approach for obtaining the overall ratings in the presence of ordinal preferences both for the criteria importance and the alternatives' rankings. In particular it is shown that Borda's method of scores is obtained as a special case. © 1996 John Wiley & Sons, Inc.

Suggested Citation

  • Wade D. Cook & Moshe Kress, 1996. "An extreme‐point approach for obtaining weighted ratings in qualitative multicriteria decision making," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(4), pages 519-531, June.
  • Handle: RePEc:wly:navres:v:43:y:1996:i:4:p:519-531
    DOI: 10.1002/(SICI)1520-6750(199606)43:43.0.CO;2-A
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/(SICI)1520-6750(199606)43:43.0.CO;2-A
    Download Restriction: no

    File URL: https://libkey.io/10.1002/(SICI)1520-6750(199606)43:43.0.CO;2-A?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
    ---><---

    References listed on IDEAS

    as
    1. Cook, Wade D. & Kress, Moshe, 1994. "A multiple-criteria composite index model for quantitative and qualitative data," European Journal of Operational Research, Elsevier, vol. 78(3), pages 367-379, November.
    2. Rietveld, Piet & Ouwersloot, Hans, 1992. "Ordinal data in multicriteria decision making, a stochastic dominance approach to siting nuclear power plants," European Journal of Operational Research, Elsevier, vol. 56(2), pages 249-262, January.
    3. Roubens, Marc, 1982. "Preference relations on actions and criteria in multicriteria decision making," European Journal of Operational Research, Elsevier, vol. 10(1), pages 51-55, May.
    4. 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.
    5. Korhonen, Pekka J., 1986. "A hierarchical interactive method for ranking alternatives with multiple qualitative criteria," European Journal of Operational Research, Elsevier, vol. 24(2), pages 265-276, February.
    6. Murat Köksalan & Mark H. Karwan & Stanley Zionts, 1988. "An approach for solving discrete alternative multiple criteria problems involving ordinal criteria," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(6), pages 625-641, December.
    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. Wade D. Cook & Moshe Kress, 1990. "A Data Envelopment Model for Aggregating Preference Rankings," Management Science, INFORMS, vol. 36(11), pages 1302-1310, November.
    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. 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.
    2. Thomas L. Saaty, 2013. "The Modern Science of Multicriteria Decision Making and Its Practical Applications: The AHP/ANP Approach," Operations Research, INFORMS, vol. 61(5), pages 1101-1118, October.
    3. Sahar Ahmadvand & Mir Saman Pishvaee, 2018. "An efficient method for kidney allocation problem: a credibility-based fuzzy common weights data envelopment analysis approach," Health Care Management Science, Springer, vol. 21(4), pages 587-603, December.
    4. Shaher Z. Zahran & Jobair Bin Alam & Abdulrahem H. Al-Zahrani & Yiannis Smirlis & Stratos Papadimitriou & Vangelis Tsioumas, 2020. "Analysis of port efficiency using imprecise and incomplete data," Operational Research, Springer, vol. 20(1), pages 219-246, March.
    5. Friedman, Lea & Sinuany-Stern, Zilla, 1997. "Scaling units via the canonical correlation analysis in the DEA context," European Journal of Operational Research, Elsevier, vol. 100(3), pages 629-637, August.
    6. Reuben Elan & Verma Bharat Bhushan & Bhat Ramesh, 2001. "Hospital Efficiency: An Empirical Analysis of District and Grant-in-Aid Hospitals in Gujarat," IIMA Working Papers WP2001-07-05, Indian Institute of Management Ahmedabad, Research and Publication Department.
    7. 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.
    8. Leskinen, Pekka & Kangas, Annika S. & Kangas, Jyrki, 2004. "Rank-based modelling of preferences in multi-criteria decision making," European Journal of Operational Research, Elsevier, vol. 158(3), pages 721-733, November.
    9. Qing Wang & Zhaojun Liu & Yang Zhang, 2017. "A Novel Weighting Method for Finding Common Weights in DEA," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(05), pages 1-21, October.
    10. Nazila Aghayi & Madjid Tavana & Mohammad Ali Raayatpanah, 2016. "Robust efficiency measurement with common set of weights under varying degrees of conservatism and data uncertainty," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 10(3), pages 385-405.
    11. Laurens Cherchye & Willem Moesen & Nicky Rogge & Tom Puyenbroeck, 2007. "An Introduction to ‘Benefit of the Doubt’ Composite Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 82(1), pages 111-145, May.
    12. 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.
    13. I. Contreras & S. Lozano & M. A. Hinojosa, 2021. "A bargaining approach to determine common weights in DEA," Operational Research, Springer, vol. 21(3), pages 2181-2201, September.
    14. 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.
    15. Robert Huggins & Hiro Izushi, 2009. "Regional Benchmarking in a Global Context: Knowledge, Competitiveness, and Economic Development," Economic Development Quarterly, , vol. 23(4), pages 275-293, November.
    16. William W. Cooper & Kyung Sam Park & Gang Yu, 2001. "An Illustrative Application of Idea (Imprecise Data Envelopment Analysis) to a Korean Mobile Telecommunication Company," Operations Research, INFORMS, vol. 49(6), pages 807-820, December.
    17. Kim, Nam Hyok & He, Feng & Kwon, O Chol, 2023. "Combining common-weights DEA window with the Malmquist index: A case of China’s iron and steel industry," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    18. Cook, Wade D. & Doyle, John & Green, Rodney & Kress, Moshe, 1997. "Multiple criteria modelling and ordinal data: Evaluation in terms of subsets of criteria," European Journal of Operational Research, Elsevier, vol. 98(3), pages 602-609, May.
    19. Ioannis E. Tsolas, 2020. "Financial Performance Assessment of Construction Firms by Means of RAM-Based Composite Indicators," Mathematics, MDPI, vol. 8(8), pages 1-16, August.
    20. Nasim Nasrabadi & Akram Dehnokhalaji & Pekka Korhonen & Jyrki Wallenius, 2019. "Using convex preference cones in multiple criteria decision making and related fields," Journal of Business Economics, Springer, vol. 89(6), pages 699-717, August.

    More about this item

    Statistics

    Access and download statistics

    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:wly:navres:v:43:y:1996:i:4:p:519-531. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1520-6750 .

    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.