When AI-based services fail: examining the effect of the self-AI connection on willingness to share negative word-of-mouth after service failures: examining the effect of the self-AI connection on willingness to share negative word-of-mouth after service failures

Bo Huang, Matthew Philp

Research output: Journal PublicationArticlepeer-review

39 Citations (Scopus)

Abstract

Recent proliferation of artificial intelligence (AI) in service encounters gives rise to questions on how consumers respond to these novel technologies. This study seeks to examine the influence of AI service failures on consumers’ propensity to share negative word-of-mouth. Three experiments demonstrate that consumers are less willing to share negative word-of-mouth after a service failure caused by an AI recommendation system, in contrast to a human employee, despite there being no difference in the failure, firm blame, or dissatisfaction with the failure. Further investigation suggests that this effect is driven by consumers’ perceived connection with the AI that uses their past behavior to predict their future preferences. The conclusions shed light on the overall understanding of consumer-AI interactions. The results also provide managerial implications for firms to implement AI effectively and carefully in their service offerings.

Original languageEnglish
Pages (from-to)877-899
Number of pages23
JournalService Industries Journal
Volume41
Issue number13-14
DOIs
Publication statusPublished - 2021
Externally publishedYes

Keywords

  • Artificial intelligence
  • service failure
  • negative world-of-mouth
  • self-enhancement
  • attribution

ASJC Scopus subject areas

  • Strategy and Management
  • Management of Technology and Innovation

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