The Impact of Behavioral Similarity on DSS Advice Acceptance

Merle Campbell, Mark Keil, Maheshwar Boodraj

Research output: Contribution to journalArticlepeer-review

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 languageEnglish
Pages (from-to)10-25
Number of pages16
JournalData Base for Advances in Information Systems
Volume53
Issue number3
DOIs
StatePublished - 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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