Abstract
This chapter is about the decision aiding process. In professional contexts, there are cases of decision problems which require using formal processes and methods. In the first part of the chapter, we identify and describe the essential steps of a decision aiding process. In the second part, we discuss four practical questions that have to be tackled by an analyst in charge of a decision aiding process.
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References
Balestra, G., & Tsoukiàs, A. (1990). Multi-criteria analysis expert knowledge represented by artificial intelligence formalisms. Journal of Operational Research Society, 41, 419–430.
Bana e Costa, C. (1996). Les problématiques de l’aide à la décision: vers l’enrichissement de la trilogie choix-tri-rangement. RAIRO/ Recherche Opérationnelle, 30(2), 191–216.
Bana e Costa, C., & Vansnick, J. (1994). MACBETH – An interactive path towards the construction of cardinal value fonctions. International Transactions in Operational Research, 1, 489–500.
Barthelemy, J., Bisdorff, R., & Coppin, G. (2002). Human centered processes and decision support systems. European Journal of Operational Research, 136, 233–252.
Bell, D., Raiffa, H., & Tversky, A. (Eds.) (1988). Decision making: descriptive, normative, and prescriptive interactions. Cambridge: Cambridge University Press.
Belton, V., & Stewart, T. (2002). Muliple criteria decision analysis: An integrated approach. Dordrecht: Kluwer Academic.
Blum, A., Jackson, J., Sandholm, T., & Zinkevich, M. (2004). Preference elicitation and query learning. Journal of Machine Learning Research, 5, 649–667.
Bouyssou, D., Marchant, T., Pirlot, M., Perny, P., Tsoukiàs, A., & Vincke, P. (2000). Evaluation and decision models: A critical perspective. Dordrecht: Kluwer Academic.
Bouyssou, D., Marchant, T., Pirlot, M., Perny, P., Tsoukiàs, A., & Vincke, P. (2006). Evaluation and decision models with multiple criteria: Stepping stones for the analyst. International Series in Operations Research and Management Science (vol. 86, 1st ed.). Boston: Springer. ISBN 0-387-31098-3.
Brown, R. (1989). Toward a prescriptive science and technology of decision aiding. Annals of Operations Research, 19, 467–483.
Brown, R. (2005). The operation was a success but the patient died: Aider priorities influence decision aid usefulness. Interfaces, 36, 511–521.
Colorni, A., & Tsoukiàs, A. (2013). What is a decision problem? Preliminary Statements, Proceedings of ADT 2013, LNAI 8176, Springer Verlag, Berlin, 139–153.
Dean, J., & Sharfman, M. (1996). Does decision process matter? A study of strategic decision-making effectiveness. Academy of Management Journal, 39, 368–396.
Dias, L. C., & Mousseau, V. (2006 April). Inferring ELECTRE’s veto-related parameters from outranking examples. European Journal of Operational Research, 170(1), 172–191.
Elbanna, S. (2006). Strategic decision-making: Process perspectives. International Journal of Management Reviews, 8, 1–20.
Fürnkranz, J., & Hüllermeier, E. (2010). Preference learning. Berlin: Springer.
Gass, S. (2009). Ethical guidelines and codes in operations research. Omega, 37, 1044–1050.
Greco, S., Mousseau, V., & Slowinski, R. (2008 December). Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions. European Journal of Operational Research, 191(2), 415–435.
Guitouni, A., & Martel, J. (1998 September). Tentative guidelines to help choosing an appropriate MCDA method. European Journal of Operational Research, 109(2), 501–521.
Ha, V., & Haddawy, P. (2003). Similarity of personal preferences: Theoretical foundations and empirical analysis. Artificial Intelligence, 146, 149–173.
Haddaway, P., Ha, V., Restificar, A., Geisler, B., & Miyamoto, J. (2003). Preference elicitation via theory refinement. Journal of Machine Learning Research, 4, 317–337.
Huber, G. (1991). Organizational learning: The contributing processes and the literatures. Organization Science, 2, 88–115.
Hüllermeier, E., & Brinker, K. (2008). Learning valued preference structures for solving classification problems. Fuzzy Sets and Systems, 159, 2337–2352.
Hüllermeier, E., Fürnkranz, J., Cheng, W., & Brinker, K. (2008). Label ranking by learning pairwise preferences. Artificial Intelligence, 172, 1897–1917.
Humphreys, P., Svenson, O., & Vári, A. (1983). Analysis and aiding decision processes. Amsterdam: North-Holland.
Jacquet-Lagrèze, E., & Siskos, Y. (1982). Assessing a set of additive utility functions for multicriteria decision making: the UTA method. European Journal of Operational Research, 10, 151–164.
Jacquet-Lagrèze, E., & Siskos, Y. (2001 April). Preference disaggregation: 20 years of MCDA experience. European Journal of Operational Research, 130(2), 233–245.
Kahneman, D., & Tversky, A. (2000). Choice, values, frames. Cambridge: Cambridge University Press.
Landry, M., Banville, C., & Oral, M. (1996). Model legitimisation in operational research. European Journal of Operational Research, 92, 443–457.
Landry, M., Malouin, J., & Oral, M. (1983). Model validation in operations research. European Journal of Operational Research, 14, 207–220.
Marchant, T. (2003). Towards a theory of MCDM: stepping away from social choice theory. Mathematical Social Sciences, 45, 343–363.
Mintzberg, H., Raisinghani, D., & Théoret, A. (1976). The structure of unstructured decision processes. Administrative Science Quarterly, 21, 246–272.
Moscarola, J. (1984). Organizational decision processes and ORASA intervention. In R. Tomlinson & I. Kiss (Eds.), Rethinking the process of operational research and systems analysis (pp. 169–186). Oxford: Pergamon Press.
Nutt, P. (1984). Types of organizational decision processes. Administrative Science Quarterly, 19, 414–450.
Nutt, P. (1993). The formulation processes and tactics used in organizational decision making. Organization Science, 4, 226–251.
Ostanello, A. (1990). Action evaluation and action structuring - Different decision aid situations reviewed through two actual cases. In C. Bana e Costa (Ed.), Readings in multiple criteria decision aid (pp. 36–57). Berlin: Springer.
Ouerdane, W. (2009). Multiple Criteria Decision Aiding: a dialectical perspective. PhD thesis, Université Paris-Dauphine.
Ozernoy, V. (1992). Choosing the best multiple criteria decision-making method. Information Systems and Operational Research, 30(2), 159–171.
Rivett, P. (1994). The craft of decision modelling. New York: Wiley.
Rosenhead, J. (1989). Rational analysis of a problematic world. New York: Wiley. 2nd revised edition in 2001.
Roy, B. (1993). Decision science or decision-aid science? European Journal of Operational Research, 66, 184–203.
Roy, B. (1994). On operational research and decision aid. European Journal of Operational Research, 73, 23–26.
Roy, B., & Bouyssou, D. (1993). Aide Multicritère à la Décision: Méthodes et Cas. Paris: Economica.
Saaty, T. (1980). The analytic hierarchy process, planning, priority setting, resource allocation. New York: McGraw-Hill.
Salo, A., & Hamalainen, R. (1992). Preference assessment by imprecise ratio statements. Operations Research, 40(6), 1053–1061.
Salo, A., & Hamalainen, R. (2001 November). Preference ratio in multiattribute evaluation (PRIME) - elicitation and decision procedures under incomplete information. IEEE Transactions on Systems, Man and Cybernetics: Part A, 31(6), 533–545.
Sandholm, T., & Boutilier, C. (2006). Preference elicitation in combinatorial auctions. In P.Cramton, Y. Shoham, & R. Steinberg (Eds.), Combinatorial auctions (pp. 233–264). Boston: MIT Press.
Schrenk, L. (1969). Aiding the decision maker - a decision process model. Ergonomics, 12, 543–557.
Simon, H. (1954). A behavioral model of rational choice. Quarterly Journal of Economics, 69, 99–118.
Stamelos, I., & Tsoukiàs, A. (2003). Software evaluation problem situations. European Journal of Operational Research, 145, 273–286 (2003)
Svenson, O. (1979). Process description of decision making. Organizational Behavior and Human Performance, 23, 86–112.
Svenson, O. (1996). Decision making and the search for fundamental psychological regularities: what can we learn from a process perspective? Organisational Behaviour and Human Decision Processes, 65, 252–267.
Teisman, G. (2000). Models for research into decision-making processes: On phases, streams and decision-making rounds. Public Administration: Journal of the Royal Institute of Public Administration, 78, 937–956.
Tsoukiàs, A. (2007). On the concept of decision aiding process. Annals of Operations Research, 154, 3–27.
Vlek, C. (1984). What constitutes a good decision?: A panel discussion among Ward Edwards, István Kiss, Giandomenico Majone and Masanao Toda. Acta Psychologica, 56, 5–27.
von Winterfeldt, D., & Edwards, W. (1986). Decision analysis and behavorial research. Cambridge: Cambridge University Press.
Wang, J. (1994). Artificial neural networks versus natural neural networks: a connectionist paradigm for preference assessment. Decision Support Systems, 11, 415–429.
Williams, H. (1990). Model building in mathematical programming (3rd ed.). New York: Wiley.
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Bouyssou, D., Marchant, T., Pirlot, M., Tsoukiàs, A., Vincke, P. (2015). Aiding to Decide: Concepts and Issues. In: Bisdorff, R., Dias, L., Meyer, P., Mousseau, V., Pirlot, M. (eds) Evaluation and Decision Models with Multiple Criteria. International Handbooks on Information Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46816-6_2
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