Service robots, agency and embarrassing service encounters

Valentina Pitardi*, Jochen Wirtz, Stefanie Paluch, Werner H. Kunz

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

121 Citations (Scopus)

Abstract

Purpose: Extant research mainly focused on potentially negative customer responses to service robots. In contrast, this study is one of the first to explore a service context where service robots are likely to be the preferred service delivery mechanism over human frontline employees. Specifically, the authors examine how customers respond to service robots in the context of embarrassing service encounters. Design/methodology/approach: This study employs a mixed-method approach, whereby an in-depth qualitative study (study 1) is followed by two lab experiments (studies 2 and 3). Findings: Results show that interactions with service robots attenuated customers' anticipated embarrassment. Study 1 identifies a number of factors that can reduce embarrassment. These include the perception that service robots have reduced agency (e.g. are not able to make moral or social judgements) and emotions (e.g. are not able to have feelings). Study 2 tests the base model and shows that people feel less embarrassed during a potentially embarrassing encounter when interacting with service robots compared to frontline employees. Finally, Study 3 confirms that perceived agency, but not emotion, fully mediates frontline counterparty (employee vs robot) effects on anticipated embarrassment. Practical implications: Service robots can add value by reducing potential customer embarrassment because they are perceived to have less agency than service employees. This makes service robots the preferred service delivery mechanism for at least some customers in potentially embarrassing service encounters (e.g. in certain medical contexts). Originality/value: This study is one of the first to examine a context where service robots are the preferred service delivery mechanism over human employees.

Original languageEnglish
Peer-reviewed scientific journalJournal of Service Management
Number of pages26
ISSN1757-5818
DOIs
Publication statusPublished - 05.10.2021
MoE publication typeA1 Journal article - refereed

Keywords

  • 512 Business and Management
  • service robots
  • artificial intelligence
  • agency
  • embarrassment
  • service encounter

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