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The Use of Ranking Veto Concept to Mitigate the Compensatory Effects of Additive Aggregation in Group Decisions on a Water Utility Automation Investment

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  • Suzana de Suzana Dantas Daher

    (Federal University of Pernambuco)

  • Adiel Teixeira Almeida

    (Federal University of Pernambuco)

Abstract

The use of additive models for aggregating group decisions implies they have a compensatory effect in the process of aggregating all decision makers’ (DMs’) preferences. In this kind of model, the final result may produce some extremely undesirable alternatives for one or more DMs. Such alternatives may emerge with a higher ranking than desirable ones, thus generating conflicts and regrets. To overcome this problem the concept of ranking veto is introduced based on a reduction factor combined with the utility of the alternative in order to penalize conflicting alternatives and reduce disagreements in an additive model. A water utility problem was considered as a numerical application to illustrate the model. A decision group method based on MAUT, utility thresholds and a reduction factor is proposed to support group decision in selecting regions that will receive investments in automation over the next 4 years.

Suggested Citation

  • Suzana de Suzana Dantas Daher & Adiel Teixeira Almeida, 2012. "The Use of Ranking Veto Concept to Mitigate the Compensatory Effects of Additive Aggregation in Group Decisions on a Water Utility Automation Investment," Group Decision and Negotiation, Springer, vol. 21(2), pages 185-204, March.
    • Handle: RePEc:spr:grdene:v:21:y:2012:i:2:d:10.1007_s10726-011-9266-2
    DOI: 10.1007/s10726-011-9266-2
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    Cited by:

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    2. Roszkowska, Ewa & Wachowicz, Tomasz, 2015. "Application of fuzzy TOPSIS to scoring the negotiation offers in ill-structured negotiation problems," European Journal of Operational Research, Elsevier, vol. 242(3), pages 920-932.
    3. Medeiros, C.P. & Alencar, M.H. & de Almeida, A.T., 2017. "Multidimensional risk evaluation of natural gas pipelines based on a multicriteria decision model using visualization tools and statistical tests for global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 268-276.
    4. Ali Azarnivand & Mohammad Ebrahim Banihabib, 2017. "A Multi-level Strategic Group Decision Making for Understanding and Analysis of Sustainable Watershed Planning in Response to Environmental Perplexities," Group Decision and Negotiation, Springer, vol. 26(3), pages 629-648, May.
    5. Adiel T. de Almeida-Filho & Madson B. S. Monte & Danielle C. Morais, 2017. "A Voting Approach Applied to Preventive Maintenance Management of a Water Supply System," Group Decision and Negotiation, Springer, vol. 26(3), pages 523-546, May.
    6. Garcez, Thalles Vitelli & de Almeida, Adiel Teixeira, 2014. "A risk measurement tool for an underground electricity distribution system considering the consequences and uncertainties of manhole events," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 68-80.
    7. Madson B. S. Monte & Adiel T. Almeida-Filho, 2016. "A Multicriteria Approach Using MAUT to Assist the Maintenance of a Water Supply System Located in a Low-Income Community," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(9), pages 3093-3106, July.
    8. Danielle Costa Morais & Adiel Teixeira Almeida & José Rui Figueira, 2014. "A Sorting Model for Group Decision Making: A Case Study of Water Losses in Brazil," Group Decision and Negotiation, Springer, vol. 23(5), pages 937-960, September.
    9. Adiel T. Almeida & Danielle C. Morais, 2014. "New Methods and Models of Group Decision and Negotiation Presented in Recife," Group Decision and Negotiation, Springer, vol. 23(3), pages 349-353, May.
    10. de Almeida Filho, Adiel T. & Clemente, Thárcylla R.N. & Morais, Danielle Costa & de Almeida, Adiel Teixeira, 2018. "Preference modeling experiments with surrogate weighting procedures for the PROMETHEE method," European Journal of Operational Research, Elsevier, vol. 264(2), pages 453-461.

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