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Decision‐makers in organisations and businesses make numerous decisions every day, and these decisions are expected to be based on facts and carried out in a rational manner. However, most decisions are not based on precise information or careful analysis due to several reasons. People are, e.g., unable to behave rationally as a result of their experiences, socialisation, and additionally, because humans possess fairly limited capacities for processing information in an objective manner. In order to circumvent this human incapacity to handle decision situations in a rational manner, especially those involving risk and uncertainty, a widespread suggestion, at least in managerial decision making, is to take advantage of support in the form of decision support systems. One possibility involves decision analytical tools, but they are, almost without exception, not efficiently employed in organisations and businesses. It appears that one reason for this is the high demands the tools place on the decision‐maker in a variety of ways, e.g., by presupposing that reliable input data is obtainable by an exogenous process. Even though the reliability of current decision analytic tools is highly dependent on the quality of the input data, they rarely contain methods for eliciting data from the users. The problem focused on in this thesis is the unavailability and inefficiency of methods for eliciting decision information from the users. The aim is to identify problem areas regarding the elicitation of decision data in real decision making processes, and to propose elicitation methods that take people’s natural choice strategies and natural behaviour into account. In this effort, we have identified a conceptual gap between the decision‐makers, the decision models, and the decision analytical tools, consisting of seven gap components. The gap components are of three main categories (of which elicitation is one). In order to study elicitation problems, a number of empirical studies, involving more than 400 subjects in total, have been carried out in Sweden and Brazil. An iterative research approach has been adopted and a combination of quantitative and qualitative methods has been used. Findings made in this thesis include the fact that decision‐makers have serious problems in many decision situations due to not having access to accurate and relevant data in the first place, and secondly, not having the means for retrieving such data in a proper manner, i.e. lacking elicitation methods for this purpose. Employing traditional elicitation methods in this realm yield results that reveal an inertia gap, i.e. an intrinsic inertia in people’s natural behaviour to shift between differently framed prospects, and different groups of decisionmakers displaying different choice patterns. Since existing elicitation methods are unable to deal with the inertia, we propose a class of methods to take advantage of this natural behaviour, and also suggest a representation for the elicited information. An important element in the proposed class of methods is also that we must be able to fine‐tune methods and measuring instruments in order to fit into different types of decision situations, user groups, and choice behaviours.
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