声誉
计算机科学
偏爱
对比度(视觉)
选择(遗传算法)
堆栈(抽象数据类型)
人工智能
微观经济学
社会学
经济
社会科学
程序设计语言
作者
Lei Xu,Tingting Nian,Luı́s Cabral
出处
期刊:Management Science
[Institute for Operations Research and the Management Sciences]
日期:2020-02-01
卷期号:66 (2): 587-604
被引量:46
标识
DOI:10.1287/mnsc.2018.3264
摘要
Many online platforms rely on users to voluntarily provide content. What motivates users to contribute content for free, however, is not well understood. In this paper, we use a revealed-preference approach to show that career concerns play an important role in user contributions to Stack Overflow, the largest online question-and-answer community. We investigate how activities that can enhance a user’s reputation vary before and after the user finds a new job. We contrast this reputation-generating activity with activities that do not improve a user’s reputation. After finding a new job, users contribute 23.7% less in reputation-generating activity; by contrast, they reduce their non–reputation-generating activity by only 7.4%. These findings suggest that users contribute to Stack Overflow in part because they perceive such contributions as a way to improve future employment prospects. We provide direct evidence against alternative explanations such as integer constraints, skills mismatch, and dynamic selection effects. This paper was accepted by Chris Forman, information systems.
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