Yikun Jiang

Hello! I am a Ph.D. candidate in Economics at the University of California, Berkeley. Prior to my doctoral studies at Berkeley, I completed my bachelor's degree at McGill University and spent one year as a Ph.D. student in Quantitative Marketing at the University of Toronto's Rotman School of Management.

 

My research focuses on understanding individuals' decisions on digital platforms to inform platform strategies. I combine the design and implementation of large-scale field experiments, causal inference, structural modeling, machine learning, and the analysis of unstructured data to answer research questions.

 

In my job market paper, I design and implement a large-scale field experiment on a leading question-and-answer platform, Stack Overflow, where I experimentally vary the recognition among 12,182 contributing individuals. I present the first field experimental evidence in content contribution decisions that quantifies the relative importance of social motivation versus instrumental motivation with a structural model. Using counterfactual simulations, I then explore platform strategies that encourage contributions. Understanding individuals’ content contribution decisions has important managerial implications for various user-generated content platforms.