Abstract
Despite the many advantages that decision support systems (DSSs) provide to decision makers, acceptance of advice from these systems has remained relatively low. In this study, we leverage theoretical insights from the literature to build a DSS that is behaviorally similar to its user, with the aim of increasing acceptance of DSS advice. To test whether users would be more accepting of advice from a behaviorally-similar DSS, we conducted a field experiment in a complex semi-structured decision context. The results of our experiment provide empirical evidence that a behaviorally-similar DSS can increase acceptance of advice in semi-structured decision-making contexts.
| Original language | English |
|---|---|
| Pages (from-to) | 10-25 |
| Number of pages | 16 |
| Journal | Data Base |
| Volume | 53 |
| Issue number | 3 |
| DOIs | |
| State | Published - Aug 2022 |
Keywords
- artificial neural network
- behavioral similarity
- decision support system
- dss advice acceptance
- field experiment
- it artifacts as social actors
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