TY - GEN
T1 - More stars or more reviews? Differential effects of reputation on trust in the sharing economy
AU - Qiu, Will
AU - Parigi, Palo
AU - Abrahao, Bruno
N1 - Funding Information:
We thank the anonymous reviewers for their detailed and helpful feedback. This work is supported by National Science Foundation Grant 1257138.
Publisher Copyright:
© 2018 Copyright is held by the owner/author(s).
PY - 2018/4/20
Y1 - 2018/4/20
N2 - 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.
AB - 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.
KW - Airbnb
KW - Reputation and rating systems
KW - Sharing economy
KW - Trust
UR - http://www.scopus.com/inward/record.url?scp=85046969384&partnerID=8YFLogxK
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U2 - 10.1145/3173574.3173727
DO - 10.1145/3173574.3173727
M3 - Conference contribution
AN - SCOPUS:85046969384
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
T2 - 2018 CHI Conference on Human Factors in Computing Systems, CHI 2018
Y2 - 21 April 2018 through 26 April 2018
ER -