More Stars or More Reviews?
Abstract
The large majority of reputation systems use features such as star ratings and reviews to give users a reputation in online peer-to-peer markets. Both have been shown to be effective for signaling trustworthiness. However, the exact extent to which these features can change perceptions of users' trustworthiness remains an open question. Using data from an online experiment conducted on Airbnb users, we investigate which of the two types of reputation information --average star rating or the number of reviews --is more important for signaling a user's trustworthiness. We find that the relative effectiveness of ratings and reviews differ depending on whether reputation has a strong or a weak differentiation power. Our findings show that reputation effects are contingent on and susceptible to the context created by the alternative choices presented to users, highlighting how reputation information is displayed can drastically alter their efficacy for engendering trust.
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Good on-site reputation is an effective trust signal in online transactions.
“Indeed, as previous research has shown, ''good'' on-site reputation is an effective trust signal in online transactions (Dellarocas et al. 2009; Qiu et al. 2018; Tadelis 2016).”
From In Stars We Trust – A Note on Reputation Portability Between Digital Platforms (2022) · cites this paper as Qiu et al. 2018
Prior research's positive relation between the number of ratings and trust was constrained to good/excellent ratings only.
“While prior research has suggested a positive relation between the number of ratings and trust, it is important that these findings were constrained to good/excellent ratings only (Cabral and Hortac ¸su 2010; Qiu et al. 2018).”
From In Stars We Trust – A Note on Reputation Portability Between Digital Platforms (2022) · cites this paper as Qiu et al. 2018
Cites
Resnick, P., Kuwabara, K., Zeckhauser, R., & Friedman, E. (2000) · Communications of the ACM · doi:10.1145/355112.355122 · Cited by 2,190 · cited 1× · see citing works
“A decision which influ-enced primarily by traditional peer-to-peer (p2p) markets such as eBay [21].”
BackgroundTrust and reputation in the sharing economy: The role of personal photos in Airbnb
Ert, E., Fleischer, A., & Magen, N. (2016) · Tourism Management · doi:10.1016/j.tourman.2016.01.013 · Cited by 1,295 · see citing works
The value of reputation on eBay: A controlled experiment
Resnick, P., Zeckhauser, R., Swanson, J., & Lockwood, K. (2006) · Experimental Economics · doi:10.1007/s10683-006-4309-2 · Cited by 1,118 · see citing works
Reputation and Feedback Systems in Online Platform Markets
Tadelis, S. (2016) · Annual Review of Economics · doi:10.1146/annurev-economics-080315-015325 · Cited by 524 · see citing works
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When Do People Trust Their Social Groups?
Ma, X., Cheng, J., Iyer, S., & Naaman, M. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300297 · Cited by 41 · see citing works
Reputation portability – quo vadis?
Hesse, M., & Teubner, T. (2020) · Electronic Markets · doi:10.1007/s12525-019-00367-6 · Cited by 39 · see citing works
Where the host is part of the deal: Social and economic value in the platform economy
Dann, D., Teubner, T., Adam, M. T. P., & Weinhardt, C. (2020) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2019.100923 · Cited by 33 · see citing works
In Stars We Trust – A Note on Reputation Portability Between Digital Platforms
Hesse, M., Teubner, T., & Adam, M. T. P. (2022) · Business & Information Systems Engineering · doi:10.1007/s12599-021-00717-9 · Cited by 16 · see citing works
“…rating score and number of reviews received, as the latter may strengthen the effects of good/bad rating scores (positivity/negativity effects; Khare et al. 2011) and previous research suggested a positive relation between number of reviews and trust (Cabral and Hortaçsu 2010; Qiu et al. 2018).”
BackgroundMethodResult
- Authors
- Qiu, W., Parigi, P., & Abrahao, B.
- Affiliations
- Stanford University (US)
- Airbnb (United States) (US)
- New York University Shanghai & Stanford University, Stanford, CA, USA
- Venue
- Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2018-04-19
- Pages
- 1-11
- OpenAlex
- W2799074526
- Cited by
- 37
- References
- 4
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 4 · 2023: 2 · 2022: 9 · 2021: 3 · 2020: 6 · 2019: 7 · 2018: 1
- FWCI
- 18.82
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Funders
- NSF (1257138)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Sharing Economy and Platforms
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Sociology and Political Science › Access Control and Trust
- Keywords
- reputation systems, star ratings, peer-to-peer markets, Airbnb, online trust
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