Mendy Tönsfeuerborn’s research while affiliated with RWTH Aachen University and other places

The Entscheidungsnavi is an open-source decision support system based on multi-attribute utility theory, that offers various methods for dealing with uncertainties. To model decisions with uncertainties, decision-makers can use two categories: Forecast and Parameter Uncertainties. Forecast Uncertainty is modeled with (combined) influence factors using discrete, user-defined probability distributions or predefined ‘worst-median-best’ distributions. Parameter Uncertainty allows imprecision for utilities, objective weights, and probability distributions. To analyze these uncertainties, the Entscheidungsnavi offers several methods and tools, like a robustness check, based on (Monte Carlo) simulations and a sensitivity analysis. The objective weight analysis provides insights into the effects of different objective weight combinations. Indicator impacts, tornado diagrams, and risk profiles visualize the impact of uncertainties in a decision under risk. Risk profiles also enable a check for stochastic and simulation dominance. This article presents the complete range of methods for dealing with uncertainties in the Entscheidungsnavi using a hypothetical case study.

Decisions with multiple objectives are challenging for many individuals. The decision problem has to be structured appropriately (decision frontend) and the decision makers` preferences have to be elicited and aggregated (decision backend). There are dozens of decision support systems helping decision makers to deal with their decision problems and thereby promote the quality of one concrete decision. However, most of them require expertise in decision making. Furthermore, they neglect the improvement of decision-making skills, which lead to better and higher quality decisions in general, for decision makers with little expertise and experience. In this paper, we introduce the Entscheidungsnavi, a freely available decision support system for multi-criteria decision making, which combines the basic functionalities of a decision support system with a training to improve the user`s decision-making skills. Based on the concepts of value-focused thinking, multi-attribute utility theory and various debiasing techniques, the decision maker can practice his proactive decision-making skills by going through three main phases: structuring the decision situation, developing the consequence table, evaluating the alternatives. Moreover, we report on the experience gained so far from using the Entscheidungsnavi and what conclusions can be drawn from it.