The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Service robots, customers and service employees: what can we learn from the academic literature and where are the gaps?
Open accessAbstract
Purpose: Robots are predicted to have a profound impact on the service sector. The emergence of robots has attracted increasing interest from business scholars and practitioners alike. In this article, we undertake a systematic review of the business literature about the impact of service robots on customers and employees with the objective of guiding future research. Design/methodology/approach: We analyzed the literature on service robots as they relate to customers and employees in business journals listed in the Financial Times top 50 journals plus all journals covered in the cross-disciplinary SERVSIG literature alerts. Findings: The analysis of the identified studies yielded multiple observations about the impact of service robots on customers (e.g. overarching frameworks on acceptance and usage of service robots; characteristics of service robots and anthropomorphism; and potential for enhanced and deteriorated service experiences) and service employees (e.g. employee benefits such as reduced routine work, enhanced productivity and job satisfaction; potential negative consequences such as loss of autonomy and a range of negative psychological outcomes; opportunities for human–robot collaboration; job insecurity; and robot-related up-skilling and development requirements). We also conclude that current research on service robots is fragmented, is largely conceptual in nature and focused on the initial adoption stage. We feel that more research is needed to build an overarching theory. In addition, more empirical research is needed, especially on the long(er)-term usage service robots on actual behaviors, the well-being and potential downsides and (ethical) risks for customers and service employees. Research limitations/implications: Our review focused on the business and service literature. Future work may want to include additional literature streams, including those in computer science, engineering and information systems. Originality/value: This article is the first to synthesize the business and service literature on the impact of service robots on customers and employees.
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Cites
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“Here, Wirtz and Zeithaml (2018) draw on the technology acceptance model (Davis, 1989) and role theory (Solomon et al., 1985) to focus on needs and role congruency.”
BackgroundSynthesizing information systems knowledge: A typology of literature reviews
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Background
Cited by
Budhwar, P., Malik, A., De Silva, M. T. T., & Thevisuthan, P. (2022) · The International Journal of Human Resource Management · doi:10.1080/09585192.2022.2035161 · Cited by 723
Mariani, M. M., Perez‐Vega, R., & Wirtz, J. (2022) · Psychology & Marketing · doi:10.1002/mar.21619 · Cited by 631
Self-citationArtificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda
Mustak, M., Salminen, J., Plé, L., & Wirtz, J. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2020.10.044 · Cited by 555
Self-citationKim, J., Giroux, M., & Lee, J. C. (2021) · Psychology & Marketing · doi:10.1002/mar.21498 · Cited by 353
AI Customer Service: Task Complexity, Problem-Solving Ability, and Usage Intention
Xu, Y., Shieh, C.-H., van Esch, P., & Ling, I.-L. (2020) · Australasian Marketing Journal · doi:10.1016/j.ausmj.2020.03.005 · Cited by 346
Metadata
- Authors
- Lu, V. N., Wirtz, J., Kunz, W. H., Paluch, S., Gruber, T., Martins, A., & Patterson, P. G.
- Venue
- Journal of Service Theory and Practice
- Publisher
- Emerald
- Published
- 2020-04-04
- Volume
- 30
- Issue
- 3
- Pages
- 361-391
- ISSN
- 2055-6225 (ISSN-L)
- OpenAlex
- W3003753339
- Cited by
- 596
- References
- 16
- FWCI
- 27.47
- Type
- journal article
- Language
- en
- Open access
- green
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- Lu, V. N., Wirtz, J., Kunz, W. H., Paluch, S., Gruber, T., Martins, A., & Patterson, P. G. (2020). Service robots, customers and service employees: what can we learn from the academic literature and where are the gaps? Journal of Service Theory and Practice. https://doi.org/10.1108/jstp-04-2019-0088
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.