Treatment Heterogeneity and Customer Value in Online Experimentation

Funded Research Proposal

Firms often have many competing innovations that are possible for them to implement, but limited information about which one is likely to yield the highest return. An emerging strategy for evaluating various innovations is A/B testing, which gives firms a data-driven strategy for making strategic innovation decisions. Read More

Entrepreneurship, Experimentation, and Performance: Evidence from the US Software Industry

Funded Research Proposal

Experimentation is the center of a fascinating debate among entrepreneurship practitioners. Inspired by the lean startup, much current practice advocates the intense use of experimentation. Conversely, a large entrepreneurship tradition emphasizes the importance of design and planning. Read More

Experimentation and Project Selection: Screening and Learning

Published Research

We study optimal contracting in a setting that combines experimentation and adverse selection. In our leading example, an entrepreneur (agent) is better informed than the investor (principal) about both the quality the project (risky arm’s distribution) and the entrepreneur’s outside option (payoff of the safe arm).Read More

Analyzing Knowledge Communities Using Foreground and Background Clusters

Published Research

Insight into the growth (or shrinkage) of “knowledge communities” of authors that build on each other’s work can be gained by studying the evolution over time of clusters of documents. We cluster documents based on the documents they cite in common using the Streemer clustering method, which finds cohesive foreground clusters (the knowledge communities) embedded in a diffuse background.Read More