Panel Paper: What Is a “Good” Social Network for a System? Knowledge Flow and Organizational Change

Saturday, November 10, 2012 : 2:05 PM
Poe (Sheraton Baltimore City Center Hotel)

*Names in bold indicate Presenter

Kenneth Frank, Michigan State University, Ann Krause, University of Toledo and William Penuel, University of Colorado, Boulder

Background and Overview

This study addresses the connection between knowledge flow, social network structure, and organizational change.  In particular, we relate organizational change to the potential for resource flows between subgroups in organizations.  More specifically, we use rich data from attempted implementations of reform in 21 different schools to test two organizational-level hypotheses about the relationship between knowledge flows, networks, and level of implementation.  Our first hypothesis extrapolates findings of effects of knowledge flow on individual behavior to the organizational level: the more expansive the flow of knowledge to potential recipient subgroups the greater will be the systemic implementation of practices dependent on the knowledge. The second builds on the idea that superior knowledge flows will come from subgroups in which interactions are focused on relevant productive activities: the more knowledge is restricted to flow from subgroups with greater expertise, the greater will be the systemic implementation of practices dependent on that knowledge. 

Research Approach and Data

Our sample consists of 21 schools (largely elementary) from a single state in the U.S. Pacific West region that were engaged in a reform initiative intended to have a school-wide influence on teachers’ practices.  We administered a questionnaire to all staff with responsibilities for classroom teaching in fall 2004 (time 1) and again in spring 2005 (time 2). The survey included sociometric items asking staff to indicate the others in the school whom they considered close colleagues and who helped them implement the school-wide initiative. The overall average response rate was 83.6% in fall 2004, and 80.4% in spring 2005.

Our dependent variable is the level of implementation of the reform based on teachers’ survey responses about how their local school-wide initiative affected their practices.  Our primary independent measures of interest involve the entropy of knowledge flows between subgroups.   Subgroups were identified by applying the Kliquefinder clustering algorithm (Frank, 1995) on the teacher network data within each school.  To characterize the potential for knowledge flow through this social structure, we employ Shannon’s (1948) measures of entropy of communication, which were adapted from measures of entropy in the physical sciences.  Conceptually, Shannon’s entropy measures reflect the extent to which a resource such as knowledge has the potential to flow evenly over possible links in a system. The more channels over which resources may flow, the greater the entropy in the system because there is less certainty about the link over which any given resource will flow.


Our key finding is that the more restricted the knowledge flows from potential provider subgroups, the greater the organizational change.  More specifically, we find no effect of the distribution of resources to subgroup recipients.  Instead we find an effect based on how resources are distributed from potential providers.  And here we find less is more; the more restricted the providers of knowledge, the greater the systemic change.