Team composition, competencies and performance under conditions of technological change: The case of robotic surgery
We study how team composition affects team performance in the context of surgery teams. Tracking the behavior of surgery teams operating through a new robotic surgery technology, we are interested in understanding how the mix of experiential and vicarious learning affects team performance Experiential learning is historical in the sense that it is based on individual trial-and-error (learning-by-doing) processes. Vicarious learning is social in the sense that it derives from exposure to the experience of others. We study the contextual effects of historical and social learning are interwoven across different types of surgery procedures – and across different types of teams. The specific goal of the project is to understand how team performance and productivity are affected by: (i) The composition of the team, in terms of similarity, familiarity and competences of members; (ii) The range of skills of team members. A leading private university hospital provides the site for the empirical part of our research. We collect data on the more than 100 surgeons ever using the technology in the more than 2000 operations ever performed through the robot surgeon since its introduction. The high-level access granted by this organization to our research team and the nature of the new surgery technology involved, jointly provide an important opportunity to collect and analyze data of unparalleled quality, precision and value for understanding teams and team performance in knowledge-intensive environments. The study provides a unique opportunity to analyze complex data produced by the interaction of social and technological processes in the context of health care organizations.