Abstract
This chapter presents behavioral issues arising from various approaches for including risk and uncertainty in multi-criteria decision analysis (MCDA). The chapter is a behaviorally oriented reassessment and reinterpretation of our earlier reviews on uncertainty modeling in MCDA, updated to include recent developments. We review the limitations of probability models and how these limitations can be partially overcome, while remaining in a conventional probability modeling framework, through the use of debiasing tools. We then focus on an approach outside of the conventional probability framework: the use of scenario planning. While scenario planning is not in its origins a quantitative tool, it is often so adopted in OR, with quantification of alternative performances, preference parameters, and even dubious assignment of scenario probabilities. We discuss different ways in which authors have interpreted these quantities, and assess the behavioral implications of these. Under this heading, we discuss cognitive perceptions of scenarios; the validity of viewing performance under a scenario as a dimension of preference, akin to a criterion; and the implications of treating decision aiding under uncertainty as an extended multi-criterion problem.
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Notes
- 1.
Note that these approaches do not employ probability concepts, although they do include other quantitative features which we outline in the next two sections.
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Durbach, I.N., Stewart, T.J. (2020). Probability and Beyond: Including Uncertainties in Decision Analysis. In: White, L., Kunc, M., Burger, K., Malpass, J. (eds) Behavioral Operational Research. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-25405-6_5
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