Untangling the Ambidexterity Dilemma through Big Data Analytics





Ambidexterity, exploration-exploitation, organizational performance, big data, analytics capability, organization design


Ambidexterity theory suggests that the ability to simultaneously explore and exploit is linked to firm performance, but the empirical evidence to date is mixed. In this study, I review existing research on firm performance in the newspaper industry in order to identify the main causal factors in a single industrial context. Three broad categories emerge: media convergence, organizational ambidexterity, and business model innovation. By incorporating variables and arguments from these categories into a basic performance model, I develop a multi-dimensional conceptual framework of explore and exploit value chains. The article concludes with a discussion of how the explore/exploit framework can be operationalized using big data analytics, and recommendations for future research are offered.

Author Biography

Tor Bøe-Lillegraven, Copenhagen Business School

Tor Bøe-Lillegraven is a PhD scholar (industrial PhD) at Copenhagen School of Business, Department of Strategic Management and Globalization.  Tor holds an ESST (
European Studies of Society, Science, and Technology) International Master degree (2004) from the University of Oslo, as well as a Master of Management from the Norwegian School of business (2010). 

His research interest is primarily in ambidexterity, business model innovation, managing strategic paradoxes as well as how big data analytics can help managers make better business decisions.




How to Cite

Bøe-Lillegraven, T. (2014). Untangling the Ambidexterity Dilemma through Big Data Analytics. Journal of Organization Design, 3(3), 27–37. https://doi.org/10.7146/jod.18173



Research Article