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

心理学 计算机科学 数学
作者
Jinpeng Liu,Xinmiao Li,Xipeng Liu
出处
期刊:Information Technology & People [Emerald Publishing Limited]
卷期号:39 (2): 906-933
标识
DOI:10.1108/itp-01-2024-0128
摘要

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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Thousand完成签到,获得积分10
1秒前
赵琪发布了新的文献求助10
1秒前
负责身影发布了新的文献求助10
1秒前
思源应助幽默的煎饼采纳,获得30
1秒前
XF关注了科研通微信公众号
1秒前
KXX发布了新的文献求助10
1秒前
忧虑的凡儿关注了科研通微信公众号
2秒前
2秒前
2秒前
2秒前
MONO完成签到,获得积分10
2秒前
2秒前
sym522完成签到,获得积分10
2秒前
李健的小迷弟应助hongjie_w采纳,获得10
2秒前
标致幻然发布了新的文献求助10
3秒前
3秒前
Akim应助AZOEZ采纳,获得10
3秒前
3秒前
3秒前
阿北完成签到,获得积分10
4秒前
4秒前
困困包发布了新的文献求助10
4秒前
充电宝应助花椒采纳,获得10
5秒前
小二郎应助岁岁平安采纳,获得10
5秒前
Betty发布了新的文献求助10
5秒前
北极光完成签到,获得积分10
6秒前
斯文败类应助tccccc采纳,获得10
6秒前
7秒前
7秒前
spzdss完成签到,获得积分10
7秒前
Yy发布了新的文献求助10
7秒前
wzy发布了新的文献求助10
7秒前
pastor完成签到,获得积分10
8秒前
Thousand发布了新的文献求助10
8秒前
ding应助wsy采纳,获得10
8秒前
Owen应助lijiabo采纳,获得10
9秒前
两点五发布了新的文献求助10
9秒前
box1221发布了新的文献求助10
9秒前
木心长发布了新的文献求助10
9秒前
9秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Effective Clinical Neurologist 3ed 500
The Great Hymn to Šamaš 500
Positive Obsession: The Life and Times of Octavia E. Butler 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7697835
求助须知:如何正确求助?哪些是违规求助? 9257752
关于积分的说明 20010068
捐赠科研通 7272438
什么是DOI,文献DOI怎么找? 3293108
关于科研通互助平台的介绍 2448600
邀请新用户注册赠送积分活动 2299177