Judgments in the Sharing Economy: The Effect of User-Generated Trust and Reputation Information on Decision-Making Accuracy and Bias

The growing ecosystem of peer-to-peer enterprise – the Sharing Economy (SE) – has brought with it a substantial change in how we access and provide goods and services. Within the SE, individuals make decisions based mainly on user-generated trust and reputation information (TRI). Recent research ind...

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Autores principales:	Mircea Zloteanu, Nigel Harvey, David Tuckett, Giacomo Livan
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	accuracy bias digital identity reputation sharing economy trustworthiness Psychology BF1-990
Acceso en línea:	https://doaj.org/article/f90ce445c1994a28b088d85d30fb0e4d
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spelling	oai:doaj.org-article:f90ce445c1994a28b088d85d30fb0e4d2021-11-16T16:31:58ZJudgments in the Sharing Economy: The Effect of User-Generated Trust and Reputation Information on Decision-Making Accuracy and Bias1664-107810.3389/fpsyg.2021.776999https://doaj.org/article/f90ce445c1994a28b088d85d30fb0e4d2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fpsyg.2021.776999/fullhttps://doaj.org/toc/1664-1078The growing ecosystem of peer-to-peer enterprise – the Sharing Economy (SE) – has brought with it a substantial change in how we access and provide goods and services. Within the SE, individuals make decisions based mainly on user-generated trust and reputation information (TRI). Recent research indicates that the use of such information tends to produce a positivity bias in the perceived trustworthiness of fellow users. Across two experimental studies performed on an artificial SE accommodation platform, we test whether users’ judgments can be accurate when presented with diagnostic information relating to the quality of the profiles they see or if these overly positive perceptions persist. In study 1, we find that users are quite accurate overall (70%) at determining the quality of a profile, both when presented with full profiles or with profiles where they selected three TRI elements they considered useful for their decision-making. However, users tended to exhibit an “upward quality bias” when making errors. In study 2, we leveraged patterns of frequently vs. infrequently selected TRI elements to understand whether users have insights into which are more diagnostic and find that presenting frequently selected TRI elements improved users’ accuracy. Overall, our studies demonstrate that – positivity bias notwithstanding – users can be remarkably accurate in their online SE judgments.Mircea ZloteanuMircea ZloteanuNigel HarveyDavid TuckettGiacomo LivanGiacomo LivanFrontiers Media S.A.articleaccuracybiasdigital identityreputationsharing economytrustworthinessPsychologyBF1-990ENFrontiers in Psychology, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	accuracy bias digital identity reputation sharing economy trustworthiness Psychology BF1-990
spellingShingle	accuracy bias digital identity reputation sharing economy trustworthiness Psychology BF1-990 Mircea Zloteanu Mircea Zloteanu Nigel Harvey David Tuckett Giacomo Livan Giacomo Livan Judgments in the Sharing Economy: The Effect of User-Generated Trust and Reputation Information on Decision-Making Accuracy and Bias
description	The growing ecosystem of peer-to-peer enterprise – the Sharing Economy (SE) – has brought with it a substantial change in how we access and provide goods and services. Within the SE, individuals make decisions based mainly on user-generated trust and reputation information (TRI). Recent research indicates that the use of such information tends to produce a positivity bias in the perceived trustworthiness of fellow users. Across two experimental studies performed on an artificial SE accommodation platform, we test whether users’ judgments can be accurate when presented with diagnostic information relating to the quality of the profiles they see or if these overly positive perceptions persist. In study 1, we find that users are quite accurate overall (70%) at determining the quality of a profile, both when presented with full profiles or with profiles where they selected three TRI elements they considered useful for their decision-making. However, users tended to exhibit an “upward quality bias” when making errors. In study 2, we leveraged patterns of frequently vs. infrequently selected TRI elements to understand whether users have insights into which are more diagnostic and find that presenting frequently selected TRI elements improved users’ accuracy. Overall, our studies demonstrate that – positivity bias notwithstanding – users can be remarkably accurate in their online SE judgments.
format	article
author	Mircea Zloteanu Mircea Zloteanu Nigel Harvey David Tuckett Giacomo Livan Giacomo Livan
author_facet	Mircea Zloteanu Mircea Zloteanu Nigel Harvey David Tuckett Giacomo Livan Giacomo Livan
author_sort	Mircea Zloteanu
title	Judgments in the Sharing Economy: The Effect of User-Generated Trust and Reputation Information on Decision-Making Accuracy and Bias
title_short	Judgments in the Sharing Economy: The Effect of User-Generated Trust and Reputation Information on Decision-Making Accuracy and Bias
title_full	Judgments in the Sharing Economy: The Effect of User-Generated Trust and Reputation Information on Decision-Making Accuracy and Bias
title_fullStr	Judgments in the Sharing Economy: The Effect of User-Generated Trust and Reputation Information on Decision-Making Accuracy and Bias
title_full_unstemmed	Judgments in the Sharing Economy: The Effect of User-Generated Trust and Reputation Information on Decision-Making Accuracy and Bias
title_sort	judgments in the sharing economy: the effect of user-generated trust and reputation information on decision-making accuracy and bias
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/f90ce445c1994a28b088d85d30fb0e4d
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Judgments in the Sharing Economy: The Effect of User-Generated Trust and Reputation Information on Decision-Making Accuracy and Bias

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