Minimally Restrictive Decision Support Systems

Abstract

Decision-making behavior is heterogeneous. We therefore suggest building a decision support system for online purchase decisions that can support various different decision strategies and also allows users to mix them. We design this minimally restrictive system by decomposing different strategies into their component steps and implementing aids for supporting these steps. We empirically compare this system to a typical one, which restricts the users by supporting only one normative, utility-maximizing strategy. Users perceive the minimally restrictive system as requiring lesser effort and being more enjoyable to use than the typical decision support system. Furthermore, they exhibit a higher intention to re-use the minimally restrictive system. However, there is no difference with respect to the perceived usefulness. Our results imply that webstores should implement minimally restrictive systems not only because of high user satisfaction, but also because analyzing clicks on the aids provides information as to which strategies are being used.

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