The Effect of Advice Valence on the Perceived Credibility of Data Analytics

Clara Xiaoling Chen, Ryan Hudgins, William F. Wright

Research output: Contribution to journalArticlepeer-review


We use an experiment to examine how advice valence (i.e., whether the advice suggests good news or bad news) affects the perceived source credibility of data analytics compared to human experts as a result of motivated reasoning. We predict that individuals will perceive data analytics as less credible than human experts, but only when the advice suggests bad news. Using a forecasting task in which individuals are seeking advice from either a human expert or data analytics, we find evidence consistent with our prediction. Furthermore, we find that this effect is mediated by the perceived competence of the advice source. We contribute to the nascent accounting literature on data analytics by providing evidence on a potential impediment to successfully transitioning to the use of analytics for decision-making in organizations.

Original languageEnglish (US)
Pages (from-to)97-116
Number of pages20
JournalJournal of Management Accounting Research
Issue number2
StatePublished - Jun 1 2022


  • advice
  • data analytics
  • motivated reasoning
  • source credibility

ASJC Scopus subject areas

  • Business and International Management
  • Accounting


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