Affiliation:
1. University of Missouri–Columbia
2. Texas Tech University
Abstract
Case-based reasoning (CBR) research has compared CBR output to other decision support methods such as statistics. This study differs by evaluating the effect of CBR as an input to judgment. We develop psychological theory concerning the use of CBR and its attenuation of biases that impair the use of statistical advice. Study 1 finds participants shown CBR cases made judgments closer to regression advice than do participants shown only regression advice. Study 2 finds that regression and CBR were used to corroborate each other. Participants used central tendency and dispersion information from CBR cases when this information was apparent in the cases. However, such use was not always normative. Results support including multiple decision aiding features in decision support systems (DSS).
Publisher
American Accounting Association
Subject
Management of Technology and Innovation,Information Systems and Management,Human-Computer Interaction,Accounting,Information Systems,Software,Management Information Systems
Cited by
5 articles.
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