The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Social Influence Effects in Online Product Ratings
Abstract
Websites prominently display consumers’ product ratings, which influence consumers’ buying decisions and willingness to pay. Few insights exist regarding whether a consumer's online product rating is prone to social influence from others’ online ratings. Examining this issue, the authors hypothesize that other consumers’ online ratings moderate the effects of positive and regular negative features of product experience, product failure, and product recovery (to address product failure) on the reviewer's online product rating. The results from a model using 7499 consumers’ online ratings of 114 hotels support the hypotheses. Other consumers’ online ratings weaken the effects of positive and regular negative features of product experience but can either exacerbate or overturn the negative effect of product failure, depending on the quality of product recovery. For marketing theory, the findings indicate that consumers who influence others are themselves influenced by other consumers and that this influence is contingent on their product experience. For managerial practice, the authors offer a method to estimate the effects of product experience characteristics on online product ratings and show that social influence effects make high online product ratings a double-edged sword, exacerbating the negative effect of product failure and strengthening the benefit of product recovery.
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Cites
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“By describing his or her product experience and providing an online product rating, the reviewer is a de facto member of the online reviewer community (social group) (Hennig-Thurau et al. 2004).”
BackgroundThe Service Encounter: Diagnosing Favorable and Unfavorable Incidents
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BackgroundAll in a Day's Work: Boundaries and Micro Role Transitions
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Cited by
Social Media Metrics — A Framework and Guidelines for Managing Social Media
Peters, K., Chen, Y., Kaplan, A. M., Ognibeni, B., & Pauwels, K. (2013) · Journal of Interactive Marketing · doi:10.1016/j.intmar.2013.09.007 · Cited by 657
Voorhees, C. M., Fombelle, P. W., Gregoire, Y., Bone, S., Gustafsson, A., Sousa, R., & Walkowiak, T. (2017) · Journal of Business Research · doi:10.1016/j.jbusres.2017.04.014 · Cited by 489
Unstructured data in marketing
Balducci, B., & Marinova, D. (2018) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-018-0581-x · Cited by 300
Decision difficulty in the age of consumer empowerment
Broniarczyk, S. M., & Griffin, J. G. (2014) · Journal of Consumer Psychology · doi:10.1016/j.jcps.2014.05.003 · Cited by 256
Your Hometown Matters: Popularity-Difference Bias in Online Reputation Platforms
Kokkodis, M., & Lappas, T. (2020) · Information Systems Research · doi:10.1287/isre.2019.0895 · Cited by 48
Metadata
- Authors
- Sridhar, S., & Srinivasan, R.
- Venue
- Journal of Marketing
- Publisher
- SAGE Publications
- Published
- 2012-09
- Volume
- 76
- Issue
- 5
- Pages
- 70-88
- ISSN
- 0022-2429 (ISSN-L)
- 1547-7185
- OpenAlex
- W2172236729
- Cited by
- 375
- References
- 60
- FWCI
- 63.44
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
