Monetary rewards or comment recognition? The difference between the two types of feedback in online Q&A community

Purpose An in-depth exploration of difference in the motivational effects of various types of feedback can better address the challenges faced by knowledge contributions. Drawing upon the self-determination theory (SDT), this study examines the relative effects of asker monetary rewards and peer comment recognition in the short term, the heterogeneous effects across different social status levels and their long-term impact over time. Design/methodology/approach Based on panel data from an online financial knowledge Q&A community, this study employs a fixed-effects Poisson regression for empirical analysis. In addition, it also conducts instrumental variable regression and a series of robustness tests. Findings The results indicate the following: (1) Peer comment recognition has a positive effect on knowledge contributions, whereas asker monetary rewards have a negative impact. (2) In the short-term, the relative effect of asker monetary rewards is stronger, but this effect changes as the social status of the user increases. (3) There is no evidence of an offsetting effect between asker monetary rewards and peer comment recognition. (4) The impact of both asker monetary rewards and peer comment recognition on continuous knowledge contributions decreases over time, but the influence of the latter lasts longer. Originality/value Previous studies on monetary rewards and peer recognition have focused primarily on their direct effects. This research explores the differences in external incentives by examining the sources, types and timing of feedback, providing a more comprehensive understanding of the mechanisms that drive continuous knowledge contribution. It also offers a more valuable insights for the management of knowledge Q&A communities.

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Publication Details

Journal
Information Technology and People
Published
2025-04-09
DOI
https://doi.org/10.1108/itp-01-2024-0128
Primary Topic
Expert finding and Q&A systems
Type
article
Field-Weighted Citation Impact
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article

Monetary rewards or comment recognition? The difference between the two types of feedback in online Q&A community

Xipeng Liu, Jinpeng Liu, Xinmiao Li
Information Technology and People
Expert finding and Q&A systems
article

Monetary rewards or comment recognition? The difference between the two types of feedback in online Q&A community

Xipeng Liu, Jinpeng Liu, Xinmiao Li
article en

Abstract

Purpose An in-depth exploration of difference in the motivational effects of various types of feedback can better address the challenges faced by knowledge contributions. Drawing upon the self-determination theory (SDT), this study examines the relative effects of asker monetary rewards and peer comment recognition in the short term, the heterogeneous effects across different social status levels and their long-term impact over time. Design/methodology/approach Based on panel data from an online financial knowledge Q&A community, this study employs a fixed-effects Poisson regression for empirical analysis. In addition, it also conducts instrumental variable regression and a series of robustness tests. Findings The results indicate the following: (1) Peer comment recognition has a positive effect on knowledge contributions, whereas asker monetary rewards have a negative impact. (2) In the short-term, the relative effect of asker monetary rewards is stronger, but this effect changes as the social status of the user increases. (3) There is no evidence of an offsetting effect between asker monetary rewards and peer comment recognition. (4) The impact of both asker monetary rewards and peer comment recognition on continuous knowledge contributions decreases over time, but the influence of the latter lasts longer. Originality/value Previous studies on monetary rewards and peer recognition have focused primarily on their direct effects. This research explores the differences in external incentives by examining the sources, types and timing of feedback, providing a more comprehensive understanding of the mechanisms that drive continuous knowledge contribution. It also offers a more valuable insights for the management of knowledge Q&A communities.

Information Technology and PeopleVol. 39(2)
Shanghai University of Finance and Economics (CN)
Openalex Percentile: Top 91%
Expert finding and Q&A systems
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Monetary rewards or comment recognition? The difference between the two types of feedback in online Q&A community — Xipeng Liu, Jinpeng Liu, et al. · Information Technology and People (2025) | TGRS Research Map | TGRS