【公开学术报告】Dynamics in Online Knowledge Contributions- Evidence from a Field Experiment

Dynamics in Online Knowledge Contributions- Evidence from a Field Experiment

Guest Speaker: Yikun JIANG (UC Berkeley)

Date & Time: Tuesday, October 29, 2024, 10:00 - 11:30 am (Beijing Time)

Zoom Meeting ID: 86302742875 (Password: 441732)

Join via the Link: https://us02web.zoom.us/j/86302742875

ABSTRACT

With the prominence of user-generated content platforms, online knowledge platforms have experienced substantial growth. However, it is unclear why individuals voluntarily contribute knowledge, and how platform strategies can facilitate individuals’ contributions through non-monetary incentives. I develop a stylized model of individual knowledge contributions where individuals have social motivation to gain reputation and instrumental motivation to obtain functionality privileges on the platform. Based on the model, I design and implement a large-scale field experiment, involving 12,128 individuals on one of the largest online question-and-answer platforms. I sample and manually treat participating platform individuals daily over the course of four and a half months. The treatment gives one anonymous upvote to eligible answers from one of my own accounts, exogenously shifting individuals’ social and instrumental motivations. I then track comprehensive data on individuals’ subsequent behavior on the platform daily for four months. I find that the treatment significantly increases an individual’s probability of contributing additional answers by around 15% of the baseline, and the difference between the control and treatment groups persists over time. The treatment effect is the most pronounced for individuals with low-to-moderate answering experience or reputation and is slightly stronger for those who are close to obtaining additional privileges after the treatment. The overall quality and effort of future answers remain stable. Using data from the field experiment, I structurally estimate the model of contribution decisions to quantify the relative importance of social and instrumental motivation. Simulation results suggest that social motivation is more important, and platform strategies that boost social motivation are more effective in encouraging contributions.

Keywords: Consumer Dynamics; Innovation; Field Experiment; User-Generated Contents; Online Knowledge Platforms; Online Reputation; Platform Design; Social Preferences