A Meta-Analytic Investigation of p-hacking in E-commerce Experimentation

Working Papers

Randomized controlled trials—often called A/B tests in industrial settings—are an increasingly important element in the management many organizations. Such experiments are meant to bring the benefits of scientific rigor and statistical measurement to the domain of managerial decision making. Read More

Strategies for Dynamic Experimentation

Funded Research Proposal

In this project, we seek to update the statistical paradigm for conducting A/B tests in the 21st century. In particular, we plan to develop a statistical framework that takes the guesswork out of deciding when to stop an experiment and to calibrate a firm’s decision thresholds based on their own historical data.Read More

Experimentation and Appropriability in Early-Stage Ventures: Evidence from the U.S. Software Industry

Working Papers

This study examines the tension between learning and appropriability in the experimentation process of early-stage ventures. I build a stylized model to argue that, when formal intellectual property is weak, the learning benefit of experimentation may be offset by its imitation risk. Read More

A Theory of Experimentation in New Ventures

Working Papers

Experimentation has been the center of a fascinating debate among entrepreneurship practitioners throughout the past decade. While intellectually stimulating and practically relevant, this discussion has received little attention from management research, and therefore has no scientific support. Read More

Experimentation, Learning, and Performance: Evidence from a RCT

Working Papers

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