Research

Thank you for your interests in my research!

I have been interested in exploring several fundamental issues of organizational learning, and elaborating on their implications for strategic management. My research portfolio comprises 3 main related streams of research, as shown in the graph below.

First, I have been intrigued by the so-called ‘credit assignment problem' - how do people and firms learn when there is no immediate outcome feedback? Building on ideas of reinforcement learning from Machine Learning and Cognitive Science, I examine how firms and individuals can use alternative, model-based feedback to guide their actions. My second stream of work examines the implications of credit assignment for Strategic Management. I ask: How would the credit assignment challenge impact when and where could firms discover strategic opportunities where resources are potentially mis-valued? What is the appropriate role of luck in performance evaluation, inference and learning? It is a theoretically important and fundamental problem which I started to delve into in my dissertation, and my most cited paper (SMJ 2003; WoS 231; Google 654) comes from these two streams of work.

Third, building on both classics such as March (1991) and recent advances in the network sciences, I have developed models of organizational learning that incorporate an important organizational feature - individuals are embedded in interpersonal organizational networks and as such, their learning is shaped by network characteristics. How much cross-group linkings is optimal? Will ‘hubby’ networks outperform more democratic ones? How will information flow filtered through organizational hierarchy impact the efficacy of organizational learning and performance? This first paper from this newer stream became my second most cited paper (OS 2010, WoS 165; Google 476).

A distinct feature of my intellectual perspective is that it is inter disciplinary. In addition to ideas from my own field (i.e. Strategy), I have always been fascinated by ideas from related disciplines such as computer science, cognitive science and behavioral decision making. My dissertation was very influenced by a book from computer science titled Reinforcement Learning by Robert Sutton and Andrew Barton (1998). Another significant influence was the behavioral decision making tradition started by Daniel Kahneman and Amos Tversky, and this interest was also why I became involved in founding a new, Behavioral Strategy Interest Group in 2013. Ideas that people and firms may not be rational, and that their systematic biases and pathologies may point to potential arbitrage opportunities for Strategists are a recurrent, underlying theme in my published work. This multi-disciplinary orientation is motivated by an interest and desire to read and think broadly, and it is what makes research exciting and fun for me. In terms of methodology – I use primarily computer simulations, but have also used lab experiments, as well as large sample, field data.

Here is a graphical illustration of my evolving research streams - enjoy!

You can find my research statement here.