The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Human staff vs. service robot vs. fellow customer: Does it matter who helps your customer following a service failure incident?
Abstract
Abstract The key to excellent service delivery is to ensure harmonious interactions between service actors. Therefore, in the event of service failure incidents, an understanding of the roles and interactions of these service actors is critical to achieving positive service outcomes. This research addresses the question: How do interactions between customers and these service actors (human staff/automated technological interface/fellow customer) influence their service experience following a service failure? We draw on role theory and answer this question via three experimental studies. Findings show that customers evaluate their service experience less favourably when receiving service recovery from fellow customers rather than firms (human staff and service robots). Furthermore, a firm’s instrumental recovery, rather than informational recovery, leads to a more favourable service evaluation, although this effect is absent when service recovery was given by fellow customers. Findings provide insights into the role of each actor in determining customer service evaluation.
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Podsakoff, P. M., MacKenzie, S. B., Paine, J. B., & Bachrach, D. G. (2000) · Journal of Management · doi:10.1177/014920630002600307 · Cited by 5,897
Artificial intelligence in service
Huang, M.-H., & Rust, R. T. (2018) · Journal of Service Research · doi:10.1177/1094670517752459 · Cited by 3,978
A Model of Customer Satisfaction with Service Encounters Involving Failure and Recovery
Smith, A. K., Bolton, R. N., & Wagner, J. (1999) · Journal of Marketing Research · doi:10.2307/3152082 · Cited by 2,058
The impact of online reviews on hotel booking intentions and perception of trust
Sparks, B. A., & Browning, V. (2011) · Tourism Management · doi:10.1016/j.tourman.2010.12.011 · Cited by 1,688
Weinstein, N., & Ryan, R. M. (2010) · Journal of Personality and Social Psychology · doi:10.1037/a0016984 · Cited by 1,484
Mende, M., Scott, M. L., van Doorn, J., Grewal, D., & Shanks, I. (2019) · Journal of Marketing Research · doi:10.1177/0022243718822827 · Cited by 1,197
Developing and validating a service robot integration willingness scale
Lu, L., Cai, R., & Gursoy, D. (2019) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2019.01.005 · Cited by 1,013
Service Failure and Recovery: The Impact of Relationship Factors on Customer Satisfaction
Hess Jr., R. L., Ganesan, S., & Klein, N. M. (2003) · Journal of the Academy of Marketing Science · doi:10.1177/0092070302250898 · Cited by 959
Customer experience challenges: Bringing together digital, physical and social realms
Bolton, R. N., McColl-Kennedy, J. R., Cheung, L., Gallan, A., Orsingher, C., Witell, L., & Zaki, M. (2018) · Journal of Service Management · doi:10.1108/josm-04-2018-0113 · Cited by 849
Patterson, P. G., Cowley, E., & Prasongsukarn, K. (2006) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2006.02.004 · Cited by 525
Cited by
Preference for robot service or human service in hotels? Impacts of the COVID-19 pandemic
Kim, S. (., Kim, J., Badu-Baiden, F., Giroux, M., & Choi, Y. (2021) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2020.102795 · Cited by 567
Hotel managers’ perceptions towards the use of robots: A mixed-methods approach
Ivanov, S., Seyitoğlu, F., & Markova, M. (2020) · Information Technology & Tourism · doi:10.1007/s40558-020-00187-x · Cited by 243
Service recovery by AI or human agents: Do failure and strategy context matter?
Fürst, A., Trißler, L., Friedrich, R., & Wirtz, J. (2025) · Journal of Service Management · doi:10.1108/josm-04-2024-0190 · Cited by 42
Metadata
- Authors
- Ho, T. H., Tojib, D., & Tsarenko, Y.
- Venue
- International Journal of Hospitality Management
- Publisher
- Elsevier BV
- Published
- 2020-05
- Volume
- 87
- Pages
- 102501
- ISSN
- 0278-4319 (ISSN-L)
- OpenAlex
- W3010513208
- Cited by
- 189
- References
- 13
- FWCI
- 24.65
- Type
- journal article
- Language
- en
- Open access
- closed
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- Ho, T. H., Tojib, D., & Tsarenko, Y. (2020). Human staff vs. service robot vs. fellow customer: Does it matter who helps your customer following a service failure incident? International Journal of Hospitality Management. https://doi.org/10.1016/j.ijhm.2020.102501
Data sources
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.