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Service Robots Rising: How Humanoid Robots Influence Service Experiences and Elicit Compensatory Consumer Responses
Open accessAbstract
Interactions between consumers and humanoid service robots (HSRs; i.e., robots with a human-like morphology such as a face, arms, and legs) will soon be part of routine marketplace experiences. It is unclear, however, whether these humanoid robots (compared with human employees) will trigger positive or negative consequences for consumers and companies. Seven experimental studies reveal that consumers display compensatory responses when they interact with an HSR rather than a human employee (e.g., they favor purchasing status goods, seek social affiliation, and order and eat more food). The authors investigate the underlying process driving these effects, and they find that HSRs elicit greater consumer discomfort (i.e., eeriness and a threat to human identity), which in turn results in the enhancement of compensatory consumption. Moreover, this research identifies boundary conditions of the effects such that the compensatory responses that HSRs elicit are (1) mitigated when consumer-perceived social belongingness is high, (2) attenuated when food is perceived as more healthful, and (3) buffered when the robot is machinized (rather than anthropomorphized).
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“In marketing, various forms of mechanical AI have been used to provide a standardization benefit; for example, collaborative robots (cobots) help with packaging (Colgate et al. 1996), drones distribute physical goods, self-service robots deliver service, and service robots automate social presence in frontline (Mende et al. 2019; van Doorn et al. 2017).”
From A strategic framework for artificial intelligence in marketing (2021) · cites this paper as Mende et al. 2019
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“It has been found that perceived interactivity will affect users' purchase intention (Ilicic and Webster, 2011; Mende et al., 2019).”
From Understanding user switch of information seeking: From search engines to generative AI (2026) · cites this paper as Mende et al., 2019
Experimental — accuracy not yet measuredIn the citing paper
“In recent years, AI applications have been also started to become an integral part of the city.”
From The sustainability of artificial intelligence: an urbanistic viewpoint from the lens of smart and sustainable cities (2020) · cites this paper as [12]
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Metadata
- Authors
- Mende, M., Scott, M. L., van Doorn, J., Grewal, D., & Shanks, I.
- Affiliations
- Florida State University (US)
- Corresponding author
- Mende, Martin
- Venue
- Journal of Marketing Research
- Publisher
- SAGE Publications
- Published
- 2019-04-22
- Volume
- 56
- Issue
- 4
- Pages
- 535-556
- ISSN
- 0022-2437 (ISSN-L)
- 1547-7193
- OpenAlex
- W2941128398
- Cited by
- 1,197
- References
- 111
- Citations by year
- 2026: 213 · 2025: 236 · 2024: 210 · 2023: 173 · 2022: 168 · 2021: 109 · 2020: 70 · 2019: 18
- FWCI
- 41.64
- Type
- journal article
- Language
- en
- Open access
- green
- research.rug.nl
- Locations
- Journal of Marketing Research (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Funders
- Marketing Science Institute
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior in Brand Consumption and Identification
- Keywords
- humanoid service robots, compensatory consumption, eeriness, status goods, social affiliation, dietary intake, anthropomorphism, social belonging, service experience
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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