The DOI matches its Crossref record; 113 of the 113 references it cites were found in a registry or an index.
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
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“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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Cites
Development and validation of brief measures of positive and negative affect: The PANAS scales.
Watson, D., Clark, L. A., & Tellegen, A. (1988) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.54.6.1063 · Cited by 32,433
Dimensions of Brand Personality
Aaker, J. L. (1997) · Journal of Marketing Research · doi:10.2307/3151897 · Cited by 7,843
Self-discrepancy: A theory relating self and affect.
Higgins, E. T. (1987) · Psychological Review · doi:10.1037/0033-295x.94.3.319 · Cited by 7,219
Understanding customer experience throughout the customer journey
Lemon, K. N., & Verhoef, P. C. (2016) · Journal of Marketing · doi:10.1509/jm.15.0420 · Cited by 5,765
On seeing human: A three-factor theory of anthropomorphism
Epley, N., Waytz, A., & Cacioppo, J. T. (2007) · Psychological Review · doi:10.1037/0033-295x.114.4.864 · Cited by 4,069 · cited 2×
“Humans have a deeply rooted tendency to anthropomorphize objects; they “imbue the real or imagined behavior of nonhuman agents with human-like characteristics, motivations, intentions, or emotions,” which influences how they interact with those agents (Epley, Waytz, and Cacioppo 2007, p. 864).”
BackgroundAn index and test of linear moderated mediation
Hayes, A. F. (2015) · Multivariate Behavioral Research · doi:10.1080/00273171.2014.962683 · Cited by 3,979
Essentials of Behavioral Research: Methods and Data Analysis
Rosenthal, R., & Rosnow, R. L. (1984) · Cited by 3,925
The Uncanny Valley [From the Field]
Mori, M., MacDorman, K., & Kageki, N. (2012) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2012.2192811 · Cited by 3,542
Binge eating as escape from self-awareness
Heatherton, T. F., & Baumeister, R. F. (1991) · Psychological Bulletin · doi:10.1037/0033-2909.110.1.86 · Cited by 2,259
Meuter, M. L., Bitner, M. J., Ostrom, A. L., & Brown, S. W., III (2005) · Journal of Marketing · doi:10.1509/jmkg.69.2.61.60759 · Cited by 1,799
Research works printed but not linked: 6
- 10.1177/002224379703400304 · DOI
- Diller Antoni, 2011, How to Detect an Android
- Frey Carl Benedikt, Osborne Michael A. (2013), “The Future of Employment: How Susceptible Are Jobs to Computerization,” working paper, Oxford Martin School, University of Oxford.
- Kanda Takayuki, 2013, Human–Robot Interaction in Social Robotic
- Kätsyri Jari, 2015, Frontiers in Psychology, 6, 390
- Rubin Charles T., 2003, The New Atlantis, 88
Cited by
Sorted by citations
How artificial intelligence will change the future of marketing
Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-019-00696-0 · Cited by 2,875
A strategic framework for artificial intelligence in marketing
Huang, M.-H., & Rust, R. T. (2021) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-020-00749-9 · Cited by 2,059
“In the frontend, service robots can interact with scale and consistency (Wirtz et al. 2018), and can automate social presence in the frontline (Mende et al. 2019; van Doorn et al. 2017).”
BackgroundBlut, M., Wang, C., Wünderlich, N. V., & Brock, C. (2021) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-020-00762-y · Cited by 1,194
Consumers and artificial intelligence: An experiential perspective
Puntoni, S., Reczek, R. W., Giesler, M., & Botti, S. (2021) · Journal of Marketing · doi:10.1177/0022242920953847 · Cited by 1,547
Engaged to a Robot? The Role of AI in Service
Huang, M.-H., & Rust, R. T. (2021) · Journal of Service Research · doi:10.1177/1094670520902266 · Cited by 1,185
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
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