The focus of my research agenda lies at the intersection of innovation, organizational search, cognition, and social dynamics, like politics and status hierarchies. In particular, I investigate fundamental questions like how organizations search, explore, and find novel ideas. How do external pressures alter firms’ search process and the knowledge pursued? How are breakthrough ideas unusual? Why do we persist in exploring ideas despite failures? How do scientists and entrepreneurs think and make decisions? What role do social dynamics play, and what determines the nature of the discoveries companies bring to society?

I have developed a research portfolio that follows two different yet complementary directions to address these questions. The first strand of my research focuses on innovation, organizational search, and decision-making during discovery processes. In the second strand, I explore social dynamics – such as politics and social status – and their consequences in search directions and individual behaviors.

In my research, I span diverse data sources and assorted quantitative methods, ranging from patents and drug development to data on firms' political activity and sports data. I have been employing causal or quasi-causal inferences like difference-in-differences and regression discontinuity designs, event-history analysis, sequence analysis, and applied (supervised) machine learning.

Ultimately, I like to think of myself as an educated wonderer for interesting answers to relevant questions.

Job Market Paper

From Failure to Success:

Dual-Space Persistency in Discovery Process

Abstract. How can organizations turn a failed idea into a success? There is a longstanding agreement in management literature that failures should be tolerated to achieve innovative breakthroughs. However, less is known about how organizational search processes unfold after having encountered an early failure and how organizations can persist in searching within the same idea in order to fix it. This study builds on cognitive research on scientific reasoning to introduce a theory of persistent search during a discovery process. This theory argues that organizations search for the latent value of an idea by generating alternatives (i.e., hypotheses on how the idea works) and experimenting with them. Biases characterize discovery search processes in both the alternatives and the experiments. After a failure, solely persisting in searching for evidence is detrimental, but a coupled persistent search in the evidence space and the hypotheses space can improve the likelihood of reaching a successful result for the failed idea. The theory is tested by using a unique dataset of dynamic portfolios of firms’ ideas built on drug-development data.

The effect of dual-space persistency on the probability of achieving a successful drug approval.