Mehmet Gençer is currently a professor of Organization Studies at the Izmir University of Economics, Department of Business Administration. After a training in Electrical and Electronics Engineering (BSc, MSc, 1986-1994), Physics (1986-1989), and Developmental Economics (1995-1996), he has practiced software development and software project management at private companies in Turkey (1994-1999) and US (1994-2001). Soon after joining the Computer Science department at Istanbul Bilgi University in 2002 as a lecturer, he has started his PhD at the Social Sciences Institute’s Organization Studies programme in 2004, which he has finished in 2009. Since then he has been teaching across undergraduate and graduate programs in business, informatics, and computing. His main research focus has been on the social and organizational aspects of innovation in general, and software industry cases in particular. Based on structural features of organizing and knowledge exchange, his studies are concerned with nature and efficiency of collaboration and social networks in innovation, knowledge creation and transfer across individuals and firms; with cases in software, technology, and manufacturing industries. Prof. Gençer has published several research articles in various journals including Technology Analysis and Strategic Management, and The Journal of Organizational Change Management, in addition to book chapters and proceedings. Mehmet Gençer’s research approach reflect the inter-disciplinary character of his background: in computing and computational methods, and in organization studies. With this dual background, his research involves application of computational methods to empirical studies regarding collective production and innovation ecosystems, how do such systems sustain, and how people and organizations manage to collaborate and gain advantage in such systems, or why they fail. Subject of these work includes structural features of organizing and knowledge exchange, nature and efficiency of collaboration in knowledge creation and transfer across individuals and firms, and evolution of community features and dynamics over time. Analysis of social networks has a special place in his approach as it is a truly computational methodology for exploring the social structure of innovation.