Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/311905 
Erscheinungsjahr: 
2022
Quellenangabe: 
[Journal:] Electronic Markets [ISSN:] 1422-8890 [Volume:] 32 [Issue:] 3 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2022 [Pages:] 1169-1185
Verlag: 
Springer, Berlin, Heidelberg
Zusammenfassung: 
Online review systems try to motivate reviewers to invest effort in writing reviews, as their success crucially depends on the helpfulness of such reviews. Underlying cognitive mechanisms, however, might influence future reviewing effort. Accordingly, in this study, we analyze whether existing reviews matter for future textual reviews. From analyzing a dataset from Google Maps covering 40 sights across Europe with over 37,000 reviews, we find that textual reviewing effort, as measured by the propensity to write an optional textual review and (textual) review length, is negatively related to the number of existing reviews. However, and against our expectations, reviewers do not increase textual reviewing effort if there is a large discrepancy between the existing rating valence and their own rating. We validate our findings using additional review data from Yelp. This work provides important implications for online platforms with review systems, as the presentation of review metrics matters for future textual reviewing effort.
Schlagwörter: 
Online reviews
Reviewing effort
Online review platform
Existing reviews
JEL: 
L81
L86
Persistent Identifier der Erstveröffentlichung: 
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Dokumentart: 
Article
Dokumentversion: 
Published Version

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