Professor Kristina Dahlin got her PhD in Organizational Behvior and Theory from the Tepper School at Carnegie Mellon University. Her thesis investigated firm responses to radical innovations in the tennis racket industry.
Kristina's main research interests are in the intersection of technology and business, with forays into social psychology to better understand R&D group behavior. She currently studies technical standards and strategic alliances in high tech industries as well as the perennial problem of how we measure technology and how incorrect measurements lead to incorrect business and policy recommendations.
Kristina is interested in how technology shapes competition and how competition, in turn, shapes technology.
To investigate this, she works on technology, industry, firm and group levels of analysis. Technology-level papers involve how we do and should measure invention novelty to correctly asses its impact on inventors and the economy as well as work studying if there is a difference between patents owned by firms versus by independent inventors (the answer is that on average there is not, but that indpendent inventors are overrepresented at the tail ends of the distribution when we look at how they impact future inventions) . Firm-level papers are either in the learning tradition or focusing on how strategic alliances dampen competition. The leanring papers focus on learning from adverse events.
Two empirical papers analyze train accidents and how and why firms differ in their learning rates from prior experiences. To synthesize what we have learned from a vast body of work on failure and error learning, Kristina recently (2018) published an overview of this literature.
The strategic alliance papers are set in high-tech industries (semi-conductors and telecom). Here we see how multi-market competition and strategic alliances jointly lower competitive pressures on firms. My work on groups uses text analysis to investigate how group composition (educational diversity) impact information use and creativity. More diverse groups will do broader and deeper analysis of complext problems, but only up to a point. When analyzing creativity in problem solving we find that diversity interacts with depth of analysis in a way so that less diverse groups in our sample are the most creative if they spend more effort in problem analysis. Given that group composition often is a given, this has implications for how to cue creativity.
Developing better measures of invention novelty to assess the true risks/rewards for inventors and firms pursuing disruptive inventions
We study choosing a technical standard depends on other factors than installed base and technical performance in US 2G cellular markets
How do informal vs formal regulatory action impact firm learning
The interaction between experience and motivation in determining learning rate
Why do some start-ups neither die nor make it big -- the role of owner preferences.
Dahlin, K., Chuang, Y. and T. Roulet. 2018. Opportunity, motivation and ability to learn from failures and errors: Review, synthesis and ways to move forward Academy of Management Annals. 12(1): 252-277.
Chuang, Y., Dahlin, K., Thomson, K., Lai, Y. and C. Yong. 2018. “Multi-market contact, strategic alliances and firm performance.” Journal of Management. 44(4):1551-1572. doi: 10.1177/0149206315615399.
Susan K. Cohen, Sean T. Hsu, Kristina B. Dahlin. 2016. “With Whom Do Technology Sponsors Partner During Technology Battles? Social Networking Strategies for Unproven (and Proven) Technologies." Organization Science 27(4):846872.
I am open to supervising DPhil students with an interest in work where technology and business overlaps