Investigating Innovation in Free/Libre Open Source Software Development Teams

Summary

We propose a social science study in the context of software development to advance our　understanding of fundamental processes of learning, process change and product innovation in distributed teams. Our study addresses the general research question: How do members of　distributed technology-supported teams of Free/Libre Open Source Software (FLOSS) developers　learn to improve their performance by forming shared mental models, individual roles, informal　norms and formal rules and how do these structures guide effective behaviours leading to　innovations? This question is important because organizational work is increasingly performed　by distributed teams of interdependent knowledge workers. These teams have many benefits, but　the distance (geographic, organizational and social) between members challenges team members　to create the shared　understandings and social structures necessary to be effective. But as yet,　research and practitioner communities know little about the dynamics of learning and innovation　in distributed teams.
To answer our research question, we will conduct a longitudinal in-depth study identifying and comparing the formation, learning and innovation processes of distributed teams of FLOSS　developers. The proposed research will be guided by an advisory board of FLOSS developers to　ensure relevance and to help promote diffusion of our findings into practice. We will study how　these distributed groups develop shared mental models to guide members’ behavior, roles to mediate　access to resources, and norms and rules to shape action, as well as the processes by which　independent, geographically-dispersed individuals are socialized into teams. As a basis for this　study, we develop a conceptual framework that uses a structurational perspective to integrate research on team behaviour, organizational learning, communities of practice and shared mental models. We will utilize qualitative data analysis of team interactions, observation and interview　data to investigate these processes. We will also use social network analysis to study the　socialization process of members and change in roles over time.