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Cited by 715

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

Service robot implementation: a theoretical framework and research agenda

Open access
Belanche, Daniel, Casaló, Luis V., Flavián, Carlos, Schepers, Jeroen·2020·The Service Industries Journal
DOI 10.1080/02642069.2019.1672666
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Abstract

Service robots and artificial intelligence promise to increase productivity and reduce costs, prompting substantial growth in sales of service robots and research dedicated to understanding their implications. Nevertheless, marketing research on this phenomenon is scarce. To establish some fundamental insights related to this research domain, the current article seeks to complement research on robots’ human-likeness with investigations of the factors that service managers must choose for the service robots implemented in their service setting. A three-part framework, comprised of robot design, customer features, and service encounter characteristics, specifies key factors within each category that need to be analyzed together to determine their optimal adaptation to different service components. Definitions and overlapping concepts are clarified, together with previous knowledge on each variable and research gaps that need to be solved. This framework and the final research questions provide a research agenda to guide scholars and help practitioners implement service robots successfully.

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Metadata

Authors
Belanche, D., Casaló, L. V., Flavián, C., & Schepers, J.
Venue
The Service Industries Journal
Publisher
Informa UK Limited
Published
2019-10-03
Volume
40
Issue
3-4
Pages
203-225
ISSN
  • 0264-2069 (ISSN-L)
  • 1743-9507
DOI
10.1080/02642069.2019.1672666
OpenAlex
W2978077952
Cited by
715
References
13
FWCI
24.75
Type
journal article
Language
en
Open access
hybrid

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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.