Knowledge matters: Restrictiveness and performance with decision support

摘要

We study 56 subjects of varying knowledge in a preferential choice task, aided by one of two Decision Support Systems (DSS) of different restrictiveness: an eliminative tool (ELIM) and a parametric search tool (PS). Using a novel measure for performance based on Data Envelopment Analysis (DEA), we find that the gains due to effort are greater with the less restrictive DSS. Surprisingly knowledge has a negative effect on performance, an effect exacerbated with the less restrictive DSS. We interpret our results in terms of knowledge-effort substitution and the nature of knowledge relative to the restrictiveness of the DSS.