Mona Riabacke

State-of-the-Art Prescriptive Criteria Weight Elicitation

Comparatively few of the vast amounts of decision analytical methods suggested have been widely spread in actual practice. Some approaches have nevertheless been more successful in this respect than others. Quantitative decision making has moved from the study of decision theory founded on a single criterion towards decision support for more realistic decision-making situations with multiple, often conflicting, criteria. Furthermore, the identified gap between normative and descriptive theories seems to suggest a shift to more prescriptive approaches. However, when decision analysis applications are used to aid prescriptive decision-making processes, additional demands are put on these applications to adapt to the users and the context. In particular, the issue of weight elicitation is crucial. There are several techniques for deriving criteria weights from preference statements. This is a cognitively demanding task, subject to different biases, and the elicited values can be heavily dependent on the method of assessment. There have been a number of methods suggested for assessing criteria weights, but these methods have properties which impact their applicability in practice. This paper provides a survey of state-of-the-art weight elicitation methods in a prescriptive setting.

Transparent Public Decision Making - Discussion and Case Study in Sweden

The Swedish city of Orebro has since long faced complex problems with poor water quality in a local river. This problem is a typical example of a regional decision problem, since there are several different stakeholders that might be affected, and there are different views on the need for, and effect of, different measures. The problems also strongly relate to the environmental condition of the river and involve other municipalities as well. In this chapter, we describe how to address this problem using an implementation of a systematic democratic decision process for enhancing the transparency and the decision quality in itself. The process is in conformity with common democratic processes, but with higher emphasis on accuracy and precision and on the interaction between civil servants and decision makers. A main issue here is to clearly separate the various views involved in these processes from the actual facts and, at the same time, facilitate input from various stakeholders. Therefore, we allow for modelling of outcomes based on different preferences and facilitate an elicitation process where views are extracted and combined with basic data from the background investigations preceding the decision. The process is divided into two stages. The first one is emphasized in this chapter and concerns the internal democracy, i.e. the formulation and refinement of the original and extended decision problems and the interaction between politicians and civil servants, while the second stage deals with the external democracy, i.e. the communication with the public, where communication channels directed towards citizens will be formed.

A Prescriptive Approach for Eliciting Imprecise Weight Statements in an MCDA Process

In this article, we discuss decision making involving multiple objectives (MCDA) and especially the lack of more prescriptively useful elicitation methods for weights within MCDA. We highlight the discrepancy between how elicitation is handled in current decision analysis applications and the abilities of real decision-makers to provide what is required from them. Based on theory and highlighted problems with current methods, we propose a novel approach for weight elicitation which relaxes the need for numeric preciseness from decision-makers and reduces some of the practical issues related to such processes. The method is tested in a comparative study, as well as employed in a real-life case study.

Weighting Under Ambiguous Preferences and Imprecise Differences in a Cardinal Rank Ordering Process

The limited amount of good tools for supporting elicitation of preference information in multi-criteria decision analysis (MCDA) causes practical problem. In our experiences, this can be remedied by allowing more relaxed input statements from decision-makers, causing the elicitation process to be less cognitively demanding. Furthermore, it should not be too time consuming and must be able to actually use of the information the decision-maker is able to supply. In this paper, we propose a useful weight elicitation method for MAVT/MAUT decision making, which builds on the ideas of rank-order methods, but increases the precision by adding numerically imprecise cardinal information as well.

Cardinal and Rank Ordering of Criteria — Addressing Prescription within Weight Elicitation

Weight elicitation methods in multi-criteria decision analysis (MCDA) are often cognitively demanding, require too much precision, time and effort. Some of the issues may be remedied by connecting elicitation methods to an inference engine facilitating a quick and easy method for decision-makers to use weaker input statements, yet being able to utilize these statements in a method for decision evaluation. In this paper, we propose a fast and practically useful weight elicitation method, answering to many of the requirements. The method builds on the ideas of rank-order methods, but can also take imprecise cardinal information into account. The method is subsequently employed in two real-life case studies and compared to a case where a simple ratio weight procedure using exact input statements was employed.

Consensus by Simulation: a Flood Model for Participatory Policy Making

An overall goal of the Upper Tisza flood risk management project was to design a flood management policy that shared liability for disaster losses between the central government and individual households in a way that was considered acceptable by all the stakeholders. A participatory approach was adopted, where a flood simulation model was used interactively to support the process. In this chapter, we describe the design, implementation and use of the dynamic and spatially explicit flood simulation model, which incorporated novel elements like micro-level representation and Monte Carlo techniques. The model was provided with an interactive graphical interface designed to facilitate its use as a decision support tool in a participatory setting with multiple users. During this process, the model supported comparisons between pre-defined policy options, as well as the design of a new policy option on which consensus was finally reached.