Networks in scientific circles: Influence, productivity and expertise

The objective of this thesis is to describe a set of methods using social and dynamic network analysis technology and tools that are reliable and repeatable in order to aid and improve knowledge management of knowledge-intensive organizations. Scientific and research organizations are knowledge-intensive complex entities that are in the business of creating and disseminating knowledge. I introduce three separate approaches to improving the knowledge management of these types of organizations; understanding the effects of influence on decision-making, identifying the impact of different types of collaboration, and mapping out the knowledge environment of the organization. The first study in this thesis identifies a method by which the personal or egocentric networks of scientists in Science, Technology, Engineering and Mathematics (STEM) fields are examined in order to determine the influences upon their academic and career choice decisions. The results indicate that the methodology can help to identify both the time frames and the persons whose influence helped them to make a choice to go into a STEM field. The second study details a method in which a network of academic scientific researchers in the computer science department of a major U.S. research university is analyzed to determine if there are benefits that accrue to different network positions of the collaborative relationships of researchers. Using output measures from social network analysis as inputs to a linear regression model, results show how this method can determine how various types of collaborative behaviors impact on productivity as measured by the number of peer-reviewed publications. This study expands on the first by looking not simply at the individual level, but also at the academic department level. The third study extends the earlier two studies by outlining a method for identifying, mapping and examining the knowledge environment created by the expertise of academic scientific researchers in order to facilitate project staffing, knowledge management and personnel decisions. University research often requires collaborative efforts, and yet it can be very difficult to identify the experts who have the areas of expertise that are needed for various responsibilities. The methodology outlined in this study helps to perform this task. These studies are important for a number of reasons. Each of the methodologies is unique. Because of their focus on networks of scientific circles, they shed considerable light on the unwritten workings of organizations, and provide new ways of describing and analyzing the social structure of scientists' influence, collaboration and knowledge networks. By using these methods, insight is provided into the ways and means by which individuals can be encouraged to consider scientific careers, the ways in which various types of collaborations can benefit themselves and their organizations, and how to better understand the knowledge environment in which they operate.