IDEAS home Printed from https://ideas.repec.org/a/spr/decfin/v43y2020i2d10.1007_s10203-020-00291-x.html
   My bibliography  Save this article

Incoherence measures and relations between coherence conditions for pairwise comparisons

Author

Listed:
  • Matteo Brunelli

    (University of Trento)

  • Bice Cavallo

    (University of Naples Federico II)

Abstract

Coherence of preferences, and the measurement of its violation, has been a long-standing issue in decision analysis. This paper continues the inquiry into coherence conditions for pairwise comparisons following a distance-based approach, in which the deviations from coherence conditions are measured on a continuous scale. Firstly, we consider eight coherence conditions already introduced in the literature and provide a complete study on their inclusion relations. Then, we consider four of these conditions and introduce optimization problems to quantify the extent of their violation.

Suggested Citation

  • Matteo Brunelli & Bice Cavallo, 2020. "Incoherence measures and relations between coherence conditions for pairwise comparisons," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 43(2), pages 613-635, December.
    • Handle: RePEc:spr:decfin:v:43:y:2020:i:2:d:10.1007_s10203-020-00291-x
    DOI: 10.1007/s10203-020-00291-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10203-020-00291-x
    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/s10203-020-00291-x?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Irving H. Lavalle & Peter C. Fishburn, 1987. "Decision Analysis Under States-Additive SSB Preferences," Operations Research, INFORMS, vol. 35(5), pages 722-735, October.
    2. Thomas Saaty & Luis Vargas, 2012. "The possibility of group choice: pairwise comparisons and merging functions," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 38(3), pages 481-496, March.
    3. Angilella, Silvia & Mazzù, Sebastiano, 2015. "The financing of innovative SMEs: A multicriteria credit rating model," European Journal of Operational Research, Elsevier, vol. 244(2), pages 540-554.
    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. Bice Cavallo & Alessio Ishizaka, 2023. "Evaluating scales for pairwise comparisons," Annals of Operations Research, Springer, vol. 325(2), pages 951-965, June.
    2. Matteo Brunelli & Michele Fedrizzi & Salvatore Greco & José Rui Figueira & Roman Słowiński, 2020. "A special issue on multi-criteria decision aiding," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 43(2), pages 557-558, December.
    3. Brunelli, Matteo & Fedrizzi, Michele, 2024. "Inconsistency indices for pairwise comparisons and the Pareto dominance principle," European Journal of Operational Research, Elsevier, vol. 312(1), pages 273-282.

    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. Agnieszka Kuś & Dorota Grego-Planer, 2021. "A Model of Innovation Activity in Small Enterprises in the Context of Selected Financial Factors: The Example of the Renewable Energy Sector," Energies, MDPI, vol. 14(10), pages 1-17, May.
    2. Jain, Richa & Reindorp, Matthew & Chockalingam, Arun, 2023. "Buyer-backed purchase-order financing for SME supplier with uncertain yield," European Journal of Operational Research, Elsevier, vol. 307(2), pages 758-772.
    3. Jingjing Long & Cuiqing Jiang & Stanko Dimitrov & Zhao Wang, 2022. "Clues from networks: quantifying relational risk for credit risk evaluation of SMEs," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-41, December.
    4. Wang, Jing & Wang, Kai & Li, Xiang & Zhao, Ruiqing, 2022. "Suppliers’ trade credit strategies with transparent credit ratings: Null, exclusive, and nonchalant provision," European Journal of Operational Research, Elsevier, vol. 297(1), pages 153-163.
    5. Pawel Tadeusz Kazibudzki, 2023. "The uncertainty related to the inexactitude of prioritization based on consistent pairwise comparisons," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-30, September.
    6. Pranith K. Roy & Krishnendu Shaw, 2023. "A credit scoring model for SMEs using AHP and TOPSIS," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 372-391, January.
    7. Javier León & Justo Puerto & Begoña Vitoriano, 2020. "A Risk-Aversion Approach for the Multiobjective Stochastic Programming Problem," Mathematics, MDPI, vol. 8(11), pages 1-26, November.
    8. Juan Aguarón & María Teresa Escobar & José María Moreno-Jiménez, 2016. "The precise consistency consensus matrix in a local AHP-group decision making context," Annals of Operations Research, Springer, vol. 245(1), pages 245-259, October.
    9. Diana Barro & Marco Corazza & Gianni Filograsso, 2023. "A ESG rating model for European SMEs using multi-criteria decision aiding," Working Papers 2023: 27, Department of Economics, University of Venice "Ca' Foscari".
    10. Marcello Pagnini & Paola Rossi & Valerio Vacca & Lucia dalla Pellegrina & Serena Frazzoni & Zeno Rotondi & Andrea Vezzulli, 2017. "Access to Credit for Small Innovative Businesses," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 46(3), pages 411-458, November.
    11. Denis Bouyssou & Marc Pirlot, 2008. "On some ordinal models for decision making under uncertainty," Annals of Operations Research, Springer, vol. 163(1), pages 19-48, October.
    12. Corazza, Marco & Funari, Stefania & Gusso, Riccardo, 2016. "Creditworthiness evaluation of Italian SMEs at the beginning of the 2007–2008 crisis: An MCDA approach," The North American Journal of Economics and Finance, Elsevier, vol. 38(C), pages 1-26.
    13. Marco Corazza & Giovanni Fasano & Stefania Funari & Riccardo Gusso, 2017. "PSO-based tuning of MURAME parameters for creditworthiness evaluation of Italian SMEs," Working Papers 04, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
    14. Sarah Ben Amor & Fateh Belaid & Ramzi Benkraiem & Boumediene Ramdani & Khaled Guesmi, 2023. "Multi-criteria classification, sorting, and clustering: a bibliometric review and research agenda," Annals of Operations Research, Springer, vol. 325(2), pages 771-793, June.
    15. Maria A. S. Xavier & Fernando A. F. Ferreira & José P. Esperança, 2021. "An intuition-based evaluation framework for social credit applications," Annals of Operations Research, Springer, vol. 296(1), pages 571-590, January.
    16. Echchakoui Said, 2019. "Salespeople’s reward preference methodological analysis," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(1), pages 24-39, March.
    17. Pranith Kumar Roy & Krishnendu Shaw, 2022. "Developing a multi-criteria sustainable credit score system using fuzzy BWM and fuzzy TOPSIS," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 5368-5399, April.
    18. A. Seetharaman & Vikas Kumar Sahu & A. S. Saravanan & John Rudolph Raj & Indu Niranjan, 2017. "The Impact of Risk Management in Credit Rating Agencies," Risks, MDPI, vol. 5(4), pages 1-16, September.
    19. Carlo Alberto Magni & Stefano Malagoli & Andrea Marchioni & Giovanni Mastroleo, 2020. "Rating firms and sensitivity analysis," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(12), pages 1940-1958, December.
    20. Chen, Rongda & Chen, Xinhao & Jin, Chenglu & Chen, Yiyang & Chen, Jiayi, 2020. "Credit rating of online lending borrowers using recovery rates," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 204-216.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

    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:spr:decfin:v:43:y:2020:i:2:d:10.1007_s10203-020-00291-x. 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.