IDEAS home Printed from https://ideas.repec.org/a/wly/navres/v36y1989i4p359-372.html
   My bibliography  Save this article

Identifying and ranking a most preferred subset of alternatives in the presence of multiple criteria

Author

Listed:
  • M. Murat Köksalan

Abstract

In this article an interactive method is developed to identify and rank a most preferred subset, T, of alternatives assuming that the decision maker has an implicit quasiconcave nondecreasing utility function. The method requires the decision maker to compare pairs of selected alternatives. Based on the responses of the decision maker, convex cones are constructed to eliminate alternatives that are proved to be inferior to alternatives in set T. The method aims at keeping the number of pairwise comparisons small. Computational experience with the method indicates that the required number of pairwise comparisons to form set T is usually small. However, the number of pairwise comparisons needed to confirm that this set is best may be large.

Suggested Citation

  • M. Murat Köksalan, 1989. "Identifying and ranking a most preferred subset of alternatives in the presence of multiple criteria," Naval Research Logistics (NRL), John Wiley & Sons, vol. 36(4), pages 359-372, August.
    • Handle: RePEc:wly:navres:v:36:y:1989:i:4:p:359-372
    DOI: 10.1002/1520-6750(198908)36:43.0.CO;2-9
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/1520-6750(198908)36:43.0.CO;2-9
    Download Restriction: no
    File URL: https://libkey.io/10.1002/1520-6750(198908)36:43.0.CO;2-9?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. Green, Paul E & Srinivasan, V, 1978. "Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(2), pages 103-123, Se.
    2. Siskos, J., 1982. "A way to deal with fuzzy preferences in multi-criteria decision problems," European Journal of Operational Research, Elsevier, vol. 10(3), pages 314-324, July.
    3. Pekka Korhonen & Jyrki Wallenius & Stanley Zionts, 1984. "Solving the Discrete Multiple Criteria Problem using Convex Cones," Management Science, INFORMS, vol. 30(11), pages 1336-1345, November.
    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. Koksalan, Murat & Ulu, Canan, 2003. "An interactive approach for placing alternatives in preference classes," European Journal of Operational Research, Elsevier, vol. 144(2), pages 429-439, January.
    2. Canan Ulu & Murat Köksalan, 2001. "An interactive procedure for selecting acceptable alternatives in the presence of multiple criteria," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(7), pages 592-606, October.

    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. Koksalan, Murat & Ulu, Canan, 2003. "An interactive approach for placing alternatives in preference classes," European Journal of Operational Research, Elsevier, vol. 144(2), pages 429-439, January.
    2. Ishizaka, Alessio & Siraj, Sajid, 2018. "Are multi-criteria decision-making tools useful? An experimental comparative study of three methods," European Journal of Operational Research, Elsevier, vol. 264(2), pages 462-471.
    3. Canan Ulu & Murat Köksalan, 2001. "An interactive procedure for selecting acceptable alternatives in the presence of multiple criteria," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(7), pages 592-606, October.
    4. Winfried Steiner & Harald Hruschka, 2002. "A Probabilistic One-Step Approach to the Optimal Product Line Design Problem Using Conjoint and Cost Data," Review of Marketing Science Working Papers 1-4-1003, Berkeley Electronic Press.
    5. Merja Halme & Kari Linden & Kimmo Kääriä, 2009. "Patients’ Preferences for Generic and Branded Over-the-Counter Medicines," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 2(4), pages 243-255, December.
    6. Kadziński, MiŁosz & Greco, Salvatore & SŁowiński, Roman, 2012. "Extreme ranking analysis in robust ordinal regression," Omega, Elsevier, vol. 40(4), pages 488-501.
    7. 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.
    8. Haaijer, Marinus E., 1996. "Predictions in conjoint choice experiments : the x-factor probit model," Research Report 96B22, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    9. Fusco, Elisa, 2023. "Potential improvements approach in composite indicators construction: The Multi-directional Benefit of the Doubt model," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    10. Xue, Hong & Mainville, Denise Y. & You, Wen & Nayga, Rodolfo M., Jr., 2009. "Nutrition Knowledge, Sensory Characteristics and Consumers’ Willingness to Pay for Pasture-Fed Beef," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49277, Agricultural and Applied Economics Association.
    11. Barbara Baarsma, 2003. "The Valuation of the IJmeer Nature Reserve using Conjoint Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 25(3), pages 343-356, July.
    12. Zanakis, Stelios H. & Mandakovic, Tomislav & Gupta, Sushil K. & Sahay, Sundeep & Hong, Sungwan, 1995. "A review of program evaluation and fund allocation methods within the service and government sectors," Socio-Economic Planning Sciences, Elsevier, vol. 29(1), pages 59-79, March.
    13. Kowalska-Pyzalska, Anna & Michalski, Rafał & Kott, Marek & Skowrońska-Szmer, Anna & Kott, Joanna, 2022. "Consumer preferences towards alternative fuel vehicles. Results from the conjoint analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    14. Kim, Junghun & Seung, Hyunchan & Lee, Jongsu & Ahn, Joongha, 2020. "Asymmetric preference and loss aversion for electric vehicles: The reference-dependent choice model capturing different preference directions," Energy Economics, Elsevier, vol. 86(C).
    15. Horna, J. Daniela & Smale, Melinda & von Oppen, Matthias, 2005. "Private Participation In Agricultural Extension In Nigeria And Benin: Determining The Willingness To Pay For Information," 2005 Annual meeting, July 24-27, Providence, RI 19401, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. John Liechty & Duncan Fong & Eelko Huizingh & Arnaud Bruyn, 2008. "Hierarchical Bayesian conjoint models incorporating measurement uncertainty," Marketing Letters, Springer, vol. 19(2), pages 141-155, June.
    17. Christian P Theurer & Andranik Tumasjan & Isabell M Welpe, 2018. "Contextual work design and employee innovative work behavior: When does autonomy matter?," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-35, October.
    18. Kannika Thampanishvong, 2013. "Determinants of Flash Flood Evacuation Choices and Assessment of Preferences for Flash Flood Warning Channels: The Case of Thailand," EEPSEA Research Report rr2013034, Economy and Environment Program for Southeast Asia (EEPSEA), revised Mar 2013.
    19. Teichert, Thorsten Andreas, 1997. "Schätzgenauigkeit von Conjoint-Analysen," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 444, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    20. Theodoros Evgeniou & Constantinos Boussios & Giorgos Zacharia, 2005. "Generalized Robust Conjoint Estimation," Marketing Science, INFORMS, vol. 24(3), pages 415-429, May.

    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:36:y:1989:i:4:p:359-372. 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.