User acceptance of knowledge-based system recommendations: Explanations, arguments, and fit

Justin Scott Giboney, Susan A Brown, Paul Benjamin Lowry, Jay F Nunamaker

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

Knowledge-based systems (KBS) can potentially enhance individual decision-making. Yet, recommendations from KBS continue to be met with resistance. This is particularly troubling in the context of deception detection (e.g., border control), in which humans are accurate only about half the time. In this study, we examine how the fit between KBS explanations and users' internal explanations influences acceptance of KBS recommendations. We leverage cognitive fit theory (CFT) to explain why fit is important for user acceptance of KBS evaluations. We also compare the predictions of CFT to those of the person-environment fit (PEF) paradigm. The two theories make conflicting predictions about the outcomes of fit when it comes to KBS explanations. CFT predicts that explanations with a higher cognitive fit will have more influence and be evaluated faster whereas PEF predicts that individuals will take more time in evaluating explanations with greater fit. In our deception detection scenario, we find support for CFT in the sense that people are influenced more by cognitively fitting explanations, however PEF is supported in the sense that people take more time to evaluate the explanation.

Original languageEnglish (US)
Pages (from-to)1-10
Number of pages10
JournalDecision Support Systems
Volume72
DOIs
StatePublished - 2015

Fingerprint

Knowledge based systems
Deception
Decision Making
User acceptance
Knowledge-based systems
Knowledge-based Systems
Acceptance
Decision making
Person-environment fit
Person

Keywords

  • Cognitive fit
  • Explanations
  • Recommendations
  • User acceptance

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Information Systems and Management
  • Arts and Humanities (miscellaneous)
  • Developmental and Educational Psychology

Cite this

User acceptance of knowledge-based system recommendations : Explanations, arguments, and fit. / Giboney, Justin Scott; Brown, Susan A; Lowry, Paul Benjamin; Nunamaker, Jay F.

In: Decision Support Systems, Vol. 72, 2015, p. 1-10.

Research output: Contribution to journalArticle

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