IDEAS home Printed from https://ideas.repec.org/a/cys/ecocyb/v50y2017i3p73-90.html
   My bibliography  Save this article

The Application of OWAs in Expertise Processes: The Development of a Model for the Quantification of Hidden Quality Costs

Author

Listed:
  • Manuel E. SANSALVADOR

    (Department of Economic and Financial Studies Miguel Hernández University - Elche (Alicante). Spain)

  • José M. BROTONS

    (Department of Economic and Financial Studies Miguel Hernández University - Elche (Alicante). Spain)

Abstract

This paper will introduce a fuzzy model for the quantification of hidden quality costs based on the aggregation of subjective information. The proposed model will be able to properly aggregate and summarize subjective opinions expressed by experts about the costs to be quantified, thereby achieving an adequate level of objectivity. To do so,a Probabilistic Uncertain Ordered Weighted Average operator is used, establishing as weighting factors both the confidence the organization has in each expert and, thanks to an original and specifically designed tool, the company’s position on Crosby’s well-known Quality Management Maturity Grid. Finally, in order to refine the results, the values obtained will undergo Contra-Expertise through Ordered Weighted Average Expertons. Once the theoretical model has been described, it will be applied to a case study: the quantification of the cost of loss of image in one insurance brokerage firm.

Suggested Citation

  • Manuel E. SANSALVADOR & José M. BROTONS, 2017. "The Application of OWAs in Expertise Processes: The Development of a Model for the Quantification of Hidden Quality Costs," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(3), pages 73-90.
  • Handle: RePEc:cys:ecocyb:v:50:y:2017:i:3:p:73-90
    as

    Download full text from publisher

    File URL: ftp://www.eadr.ro/RePEc/cys/ecocyb_pdf/ecocyb3_2017p73-90.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zarghami, Mahdi & Szidarovszky, Ferenc, 2009. "Revising the OWA operator for multi criteria decision making problems under uncertainty," European Journal of Operational Research, Elsevier, vol. 198(1), pages 259-265, October.
    2. Zimmermann, H. -J., 2000. "An application-oriented view of modeling uncertainty," European Journal of Operational Research, Elsevier, vol. 122(2), pages 190-198, April.
    3. Sadiq, Rehan & Tesfamariam, Solomon, 2007. "Probability density functions based weights for ordered weighted averaging (OWA) operators: An example of water quality indices," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1350-1368, November.
    4. Dong, Yucheng & Xu, Yinfeng & Li, Hongyi & Feng, Bo, 2010. "The OWA-based consensus operator under linguistic representation models using position indexes," European Journal of Operational Research, Elsevier, vol. 203(2), pages 455-463, June.
    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. Carlos Llopis-Albert & José M. Merigó & Huchang Liao & Yejun Xu & Juan Grima-Olmedo & Carlos Grima-Olmedo, 2018. "Water Policies and Conflict Resolution of Public Participation Decision-Making Processes Using Prioritized Ordered Weighted Averaging (OWA) Operators," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(2), pages 497-510, January.
    2. Dias, Luis C. & Climaco, Joao N., 2005. "Dealing with imprecise information in group multicriteria decisions: a methodology and a GDSS architecture," European Journal of Operational Research, Elsevier, vol. 160(2), pages 291-307, January.
    3. Yan, Hong-Bin & Ma, Tieju & Huynh, Van-Nam, 2017. "On qualitative multi-attribute group decision making and its consensus measure: A probability based perspective," Omega, Elsevier, vol. 70(C), pages 94-117.
    4. Amin Vafadarnikjoo & Madjid Tavana & Tiago Botelho & Konstantinos Chalvatzis, 2020. "A neutrosophic enhanced best–worst method for considering decision-makers’ confidence in the best and worst criteria," Annals of Operations Research, Springer, vol. 289(2), pages 391-418, June.
    5. Kikuchi, Shinya & Chakroborty, Partha, 2006. "Place of possibility theory in transportation analysis," Transportation Research Part B: Methodological, Elsevier, vol. 40(8), pages 595-615, September.
    6. Sun, Bingzhen & Ma, Weimin, 2015. "An approach to consensus measurement of linguistic preference relations in multi-attribute group decision making and application," Omega, Elsevier, vol. 51(C), pages 83-92.
    7. González-Arteaga, T. & Alcantud, J.C.R. & de Andrés Calle, R., 2016. "A cardinal dissensus measure based on the Mahalanobis distance," European Journal of Operational Research, Elsevier, vol. 251(2), pages 575-585.
    8. Weijun Xu & Xin Chen & Yucheng Dong & Francisco Chiclana, 2021. "Impact of Decision Rules and Non-cooperative Behaviors on Minimum Consensus Cost in Group Decision Making," Group Decision and Negotiation, Springer, vol. 30(6), pages 1239-1260, December.
    9. Fu, Chao & Yang, Shanlin, 2011. "An attribute weight based feedback model for multiple attributive group decision analysis problems with group consensus requirements in evidential reasoning context," European Journal of Operational Research, Elsevier, vol. 212(1), pages 179-189, July.
    10. Yazidi, Anis & Ivanovska, Magdalena & Zennaro, Fabio M. & Lind, Pedro G. & Viedma, Enrique Herrera, 2022. "A new decision making model based on Rank Centrality for GDM with fuzzy preference relations," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1030-1041.
    11. Abdelkader Baaziz & Luc Quoniam, 2013. "Réduire les risques des décisions stratégiques dans les nouveaux environnements concurrentiels incertains : Cas des Entreprises Publiques Algériennes," Post-Print hal-00822969, HAL.
    12. Janssen, J.A.E.B. & Krol, M.S. & Schielen, R.M.J. & Hoekstra, A.Y. & de Kok, J.-L., 2010. "Assessment of uncertainties in expert knowledge, illustrated in fuzzy rule-based models," Ecological Modelling, Elsevier, vol. 221(9), pages 1245-1251.
    13. Bowen Zhang & Yucheng Dong & Enrique Herrera-Viedma, 2019. "Group Decision Making with Heterogeneous Preference Structures: An Automatic Mechanism to Support Consensus Reaching," Group Decision and Negotiation, Springer, vol. 28(3), pages 585-617, June.
    14. Zeshui Xu & Wei Zhou, 2017. "Consensus building with a group of decision makers under the hesitant probabilistic fuzzy environment," Fuzzy Optimization and Decision Making, Springer, vol. 16(4), pages 481-503, December.
    15. Zhang, Hengjie & Dong, Yucheng & Xiao, Jing & Chiclana, Francisco & Herrera-Viedma, Enrique, 2021. "Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    16. Paulo Afonso & Vishad Vyas & Ana Antunes & Sérgio Silva & Boris P. J. Bret, 2021. "A Stochastic Approach for Product Costing in Manufacturing Processes," Mathematics, MDPI, vol. 9(18), pages 1-23, September.
    17. Gao, Jianwei & Li, Ming & Liu, Huihui, 2015. "Generalized ordered weighted utility averaging-hyperbolic absolute risk aversion operators and their applications to group decision-making," European Journal of Operational Research, Elsevier, vol. 243(1), pages 258-270.
    18. Kijazi, Martin Herbert & Kant, Shashi, 2011. "Social acceptability of alternative forest regimes in Mount Kilimanjaro, Tanzania, using stakeholder attitudes as metrics of uncertainty," Forest Policy and Economics, Elsevier, vol. 13(4), pages 242-257, April.
    19. Fu, Chao & Yang, Shanlin, 2012. "An evidential reasoning based consensus model for multiple attribute group decision analysis problems with interval-valued group consensus requirements," European Journal of Operational Research, Elsevier, vol. 223(1), pages 167-176.
    20. Jia-Li Chang & Hui Li & Jian Wu, 2023. "How Tourist Group Books Hotels Meeting the Majority Affective Expectations: A Group Selection Frame with Kansei Text Mining and Consensus Coordinating," Group Decision and Negotiation, Springer, vol. 32(2), pages 327-358, April.

    More about this item

    Keywords

    Quality Management; Quality Cost; Fuzzy Logic; Ordered Weighted Average; Case Study;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M49 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Other

    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:cys:ecocyb:v:50:y:2017:i:3:p:73-90. 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: Corina Saman (email available below). General contact details of provider: https://edirc.repec.org/data/feasero.html .

    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.