Skip to main content
SpringerLink
Log in

Collaborative Decision Making for Small Groups Utilizing UTA Methods

  • Chapter
  • First Online:
Book cover Preference Disaggregation in Multiple Criteria Decision Analysis

Part of the book series: Multiple Criteria Decision Making ((MCDM))

Abstract

Decision Aid process involving many stakeholders constitute a complex situation while requires the reconciliation of multiple views, interests and preferences. Multicriteria Disaggregation—Aggregation approaches such as UTA(*) and UTA II support the estimation of additive value preference models utilizing the Decision Makers (DMs) global preferences expressed by the pre-ranking of a limited set of alternative actions evaluated on a consistent family of criteria. This research work presents the exploitation of UTA methods and voting collective functions of Social Choice Theory in order to support decision aid process in a multi-agents decision environment. Also, the RACES systems developed to support small group decision aid process, accompanying the MINORA and MIIDAS system is presented and illustrated through a real world cases study.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Bargagliotti, A. (2009). Aggregation and decision making using ranked data. Mathematical Social Sciences, 58, 354–366.

    Article  Google Scholar 

  • Black, D. (1958). The theory of committees and elections. Cambridge: Cambridge University Press.

    Google Scholar 

  • Borda, J. C. (1781). Memoire sur les elections au scrutin. Histoire de L’Academie Royale des Sciences.

    Google Scholar 

  • Brams, S. J., & Fishburn, P. C. (2002). Voting procedures. In K. J. Arrow, A. K. Sen, & K. Suzumura (Eds.), Handbook of social choice and welfare (Vol. 1). London: Elsevier.

    Google Scholar 

  • Bui, T. X. (1987). Co-oP: A group decision support system for cooperative multiple criteria group decision making. Lecture Notes in Computer Science, 290. Springer, Berlin.

    Google Scholar 

  • Carlsson, C., Ehrenberg, D., Eklund, P., Fedrizzi, M., Gustafsson, P., Lindholm, P., Merkuryeva, G., Riisanen, T., & Ventre, A. G. S. (1992). Consensus in distributed soft environments. European Journal of Operational Research, 61, 165–185.

    Article  Google Scholar 

  • Colson, G., & Mareschal, B. (1994). JUDGES: A descriptive group decision support system for the ranking of the items. Decision Support Systems, 12, 391–404.

    Article  Google Scholar 

  • Condorcet, M. J. (1785). Essai sur l’application de l'analyses a la probabilite des decision rendue a la pluralite des voix. Paris.

    Google Scholar 

  • Cook, W. D., & Seiford, L. M. (1978). Priorities ranking and consensus formation. Management Science, 20(16), 59–73.

    Google Scholar 

  • Dennis, A. R., George, J. F., Jessup, L. M., Nunamaker, J. F., & Vogel, D. (1988). Information technology to support electronic meetings. MIS Quarterly, 12(4), 591–624.

    Article  Google Scholar 

  • Figuera, J., Greco, S., & Slowinski, R. (2009). Building a set of additive value functions representing a reference preorder and intensities of preferences: The GRIP method. European Journal of Operational Research, 195(2), 460–486.

    Article  Google Scholar 

  • Fishburn, P. C. (1970). Conditions for simple majority decision functions with intransitive individual differences. Journal of Economic Theory, 2, 254–367.

    Google Scholar 

  • Fishburn, P. C. (1972). A comparative analysis of group decision methods. Behavioral Science, 16(6), 538–236.

    Article  Google Scholar 

  • Fishburn, P. C., & Brams, S. J. (1981). Approval voting, Condorcet’s principles and Runnpff elections. Public Choice, 36, 89–114.

    Article  Google Scholar 

  • Greco, S., Mousseau, V., & Slowinski, R. (2007). Ordinal regression revisited: multiple criteria ranking using a set of additive value functions. European Journal of Operational Research, 19(2), 415–435.

    Google Scholar 

  • Greco, S., Kedzinski, M., Mousseau, V., & Slowinski, R. (2012). Robust Ordinal regression for multiple criteria group decision, UTA^GMS-GROUP and UTADIS^GMS-GROUP. Decision Support Systems, 52(3), 549–561.

    Article  Google Scholar 

  • Hwang, C.-L., & Lin, M.-J. (1988). Group decision making under multiple criteria in Lectures notes in economics and mathematical systems. Springer, Berlin, Heidelberg.

    Google Scholar 

  • Jacquet-Lagrèze, E. (1982). Binary preference indices: A new look on multicriteria aggregation procedures. European Journal of Operational Research, 10(1), 26–32.

    Article  Google Scholar 

  • Jacquet-Lagreze, E., & Shakun, M. F. (1984). Decision support system for semistructured buying decisions. European Journal of Operational Research, 16(1), 48–56.

    Article  Google Scholar 

  • Jacquet-Lagrèze, E., & Siskos, Y. (1982). Assessing a set of additive utility functions for multicriteria decision making. European Journal of Operational Research, 10(2), 151–164.

    Article  Google Scholar 

  • Jarke, M., Jelassi, M. T., & Shakun, M. F. (1987). MEDIATOR: Towards a negotiation support system. European Journal of Operational Research, 31, 314–333.

    Article  Google Scholar 

  • Keeney, R. L., & Raifa, H. (1976). Decision with multiple objectives: Preferences and value tradeoffs. New York: Wiley.

    Google Scholar 

  • Kendall, M. G. (1970). Rank correlation methods. London: Charles Griffin and Company Limited.

    Google Scholar 

  • Kenemy, J. G., & Snell, J. L. (1972). Mathematical models in the social sciences. Cambridge, MA: The MIT Press.

    Google Scholar 

  • Kersten, G. E. (1985). NEGO-group decision support system. Information Management, 8(5), 237–246.

    Article  Google Scholar 

  • Matsatsinis, N. F., & Delias, P. (2004). A multi-criteria protocol for multi-agent negotiations. In G. A. Vouros, & T. Panayiotopoulos (Eds.), SETN, LNAI 3025 (pp. 103–111). Springer, Berlin, Heidelberg.

    Chapter  Google Scholar 

  • Matsatsinis, N. F., & Samaras, A. P. (1997). Aggregation and disaggregation of preferences for consensus seeking in group decisions. Paper presented at the 46th meeting of the European working group on multicriteria aid for decisions, Ă•, Bastia, France, 23–25 October.

    Google Scholar 

  • Matsatsinis, N. F., & Samaras, A. P. (2001). MCDA and preference disaggregation in group decision support systems. European Journal of Operational Research, 130, 414–429.

    Article  Google Scholar 

  • Miettinen, K., Salminen, P., & Hokkanen, J. (1997). Acceptability analysis for multicriteria problems with multiple decisionmakers. Report 2/1997, University of Jyvaskyla, Department of Mathematics, Laboratory of Scientific Computing, Jyvaskyla.

    Google Scholar 

  • Roy, B. (1985). MĂ©thodologie multicritère d'aide Ă  la DĂ©cision, Economica, Paris.

    Google Scholar 

  • Roy, B. (1990). The outranking approach and the foundations of ELECTRE methods. In C. A. Bana e Costa (Ed.), Reading in multiple criteria decision aid (pp. 155–183). Berlin: Springer.

    Chapter  Google Scholar 

  • Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.

    Google Scholar 

  • Siskos, Y. (1980). Comment modĂ©liser les prĂ©fĂ©rences au moyen de fonctions d’utilitĂ© additives. RAIRO Recherche OpĂ©rationnelle, 14, 53–82.

    Google Scholar 

  • Siskos, Y., & Grigoroudis, E. (2010). New trends in aggregation–disaggregation approaches. In C. Zopounideis & P. M. Pardalos (Eds.), Handbook of multicriteria analysis, applied optimization (Vol. 103). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-540-92828.

    Chapter  Google Scholar 

  • Siskos, Y., & Yannacopoulos, D. (1985). UTASTAR, an ordinal regression method for building additive value functions. Investigacao Operacional, 5(1), 39–53.

    Google Scholar 

  • Siskos, Y., Spyridakos, A., & Yannacopoulos, D. (1993). MINORA: A multicriteria decision aiding system for discrete alternatives. Journal of Information Science and Technology. In Y. Siskos & C. Zopounidis (Eds.), Special issue on multicriteria decision support systems, 2(2), 136–149.

    Google Scholar 

  • Siskos, Y., Spyridakos, A., & Yannacopoulos, D. (1998). Using artificial intelligent techniques into preference disaggregation analysis: The MIIDAS system. European Journal of Operational Research, 113, 281–299.

    Article  Google Scholar 

  • Spyridakos, A. (2012). Aggregation of individual preference models in collaborative decision making through disaggregation-aggregation approach with the RACES system. In A. Respicio & F. Burstein (Eds.), Fusing decision support systems into the fabric of the context (pp. 241–252). Amsterdam: IOS Press.

    Google Scholar 

  • Spyridakos, A., & Yannacopoulos, Y. (2015). Incorporating collective functions to multicriteria disaggregation-aggregation approaches for small group decision making. Annals of Operation Research, 227(1), 119–136.

    Article  Google Scholar 

  • Spyridakos, A., Siskos, Y., Yannacopoulos, D., & Skouris, A. (2001). Multicriteria Job evaluation for large organizations. European Journal of Operational Research, 130, 375–387.

    Article  Google Scholar 

  • Truchon, M., & Gordon, S. (2009). Statistical comparison of aggregation rules for votes. Mathematical Social Sciences, 57, 199–212.

    Article  Google Scholar 

  • Vetchera, R. (1991). Integrating databases and preference evaluations in group decision support – A feedback-oriented approach. Decision Support Systems, 7, 67–77.

    Article  Google Scholar 

  • Yannacopoulos, D., Spyridakos, A., & Tsotsolas, N. (2014). Robustness analysis in multicriteria disaggregation – aggregation approaches for group decision making. Lecture Notes in Business Information Systems, 184, 167–180.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Business and Administration, University of West Attica, Aigaleo, Greece

    Athanasios Spyridakos & Denis Yannacopoulos

Authors
  1. Athanasios Spyridakos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Denis Yannacopoulos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Athanasios Spyridakos .

Editor information

Editors and Affiliations

  1. Technical University of Crete, Chania, Greece

    Nikolaos Matsatsinis

  2. Technical University of Crete, Chania, Greece

    Evangelos Grigoroudis

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Spyridakos, A., Yannacopoulos, D. (2018). Collaborative Decision Making for Small Groups Utilizing UTA Methods. In: Matsatsinis, N., Grigoroudis, E. (eds) Preference Disaggregation in Multiple Criteria Decision Analysis. Multiple Criteria Decision Making. Springer, Cham. https://doi.org/10.1007/978-3-319-90599-0_3

Download citation

Publish with us

Policies and ethics

Search

Navigation