Analytics Challenge Webinar Series - Monetary Incentives and Knowledge Spillover: Evidence from a Natural Experiment
Supporting the below United Nations Sustainable Development Goals:支持以下聯合國可持續發展目標:支持以下联合国可持续发展目标:
We examine how the introduction of monetary incentives by a knowledge-sharing platform affects the non-rewarded knowledge activity on the platform. Our setting is a question-and-answer platform that provides monetary incentives for holding live talks. Using a combination of coarsened exact matching and difference-in-differences estimation techniques, we find that the launch of the paid feature creates a positive spillover effect on the hosts’ free contributions, specifically, 9.4%–40.8% more answers, in the short run when compared with non-hosts. The paid feature did not result in any significant change in the quality of answers. We suggest reputation building is one plausible mechanism underlying the spillover. Additional analyses reveal the spillover effect is negative for short-lived hosts in the long run, indicating possible crowding out of free contributions. The positive spillover effect for long-lived hosts lasts longer but is also reduced over time. Our findings suggest that introducing monetary incentives can be a viable business model for knowledge platforms to stimulate user contributions in both paid and related unpaid activities. Yet, platform owners should be cautious about the potential negative spillover after users stop participating in the paid activity and develop effective strategies to maintain users’ long-term interests in the paid program.
This is part 5 of a 5-part webinar series featuring leading academic experts in big data analytics, information systems, machine learning, data mining, and large-scale data processing. Students participating in the CBSA-Wisers Analytics Challenge @HKUST 2021/22 are highly encouraged to attend the webinars.
For more information about this webinar, please visit: https://cbsa.hkust.edu.hk/analytics-challenge-webinar-part-5-of-5
Ms. Wern Ngo by email: wernngo@ust.hk