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20-04-2022

Language matters: humanizing service robots through the use of language during the COVID-19 pandemic

Authors: Smriti Kumar, Elizabeth G. Miller, Martin Mende, Maura L. Scott

Published in: Marketing Letters | Issue 4/2022

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Abstract

Service robots are emerging quickly in the marketplace (e.g., in hotels, restaurants, and healthcare), especially as COVID-19-related health concerns and social distancing guidelines have affected people’s desire and ability to interact with other humans. However, while robots can increase efficiency and enable service offerings with reduced human contact, prior research shows a systematic consumer aversion toward service robots relative to human service providers. This potential dilemma raises the managerial question of how firms can overcome consumer aversion and better employ service robots. Drawing on prior research that supports the use of language for building interpersonal relationships, this research examines whether the type of language (social-oriented vs. task-oriented language) a service robot uses can improve consumer responses to and evaluations of the focal service robot, particularly in light of consumers’ COVID-19-related stress. The results show that consumers respond more favorably to a service robot that uses a social-oriented (vs. task-oriented) language style, particularly when these consumers experience relatively higher levels of COVID-19-related stress. These findings contribute to initial empirical evidence in marketing for the efficacy of leveraging robots’ language style to improve customer evaluations of service robots, especially under stressful circumstances. Overall, the results from two experimental studies not only point to actionable managerial implications but also to a new avenue of research on service robots that examines customer-robot interactions through the lens of language and in contexts that can be stressful for consumers (e.g., healthcare or some financial service settings).

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Appendix
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Footnotes
1
Language style concerns stylistic aspects of an interchange, such as choice of tone, genre-appropriate lexis and syntax, and genre-appropriate terms of address or use of honorifics (Spencer-Oatey 2000).
 
2
Related to a growing discussion about the relevance of null hypothesis significance testing (e.g., Amrhein, Greenland, and McShane 2019), we do not introduce formal hypotheses; instead, we propose our theorizing and, consistent with the recent literature, assess p-values “continuously rather than in a dichotomous or threshold-ed manner” (McShane et al., 2019, p. 236); that is, we consider p-values as measuring the compatibility between our theorizing and data (Greenland 2019).
 
3
As expected, an exploratory factor analysis with the five measures (intention to sign up, service quality, likelihood of recommending the program, interest in the program, interest in learning more about the program) yielded a single factor (which accounted for 85.73% of the variance).
 
4
We note one unexpected significant contrast for the human service provider (Fig. 2B). We speculate that interacting with a human provider allows consumers to be more comfortable with the task-oriented language (i.e., the human-to-human interaction may compensate for the more task-oriented language). Furthermore, the contrast is driven by consumers who are relatively more stressed, which may help explain why they would be more accepting of the task-oriented language as long as the service provider is another human; however, when they interact with a mechanical robot, consumers prefer the machine to “compensate” through a social-oriented language.
 
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Metadata
Title
Language matters: humanizing service robots through the use of language during the COVID-19 pandemic
Authors
Smriti Kumar
Elizabeth G. Miller
Martin Mende
Maura L. Scott
Publication date
20-04-2022
Publisher
Springer US
Published in
Marketing Letters / Issue 4/2022
Print ISSN: 0923-0645
Electronic ISSN: 1573-059X
DOI
https://doi.org/10.1007/s11002-022-09630-x