Diversity and Reach of Penn State Extension Programs and Effect of Brokerage and Network Position on Extension Program Outcomes through Social Network AnalysiS (SNA)
Open Access
- Author:
- Kumar Chaudhary, Anil
- Graduate Program:
- Agricultural and Extension Education
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- July 11, 2014
- Committee Members:
- Rama B Radhakrishna, Thesis Advisor/Co-Advisor
Edgar Paul Yoder, Thesis Advisor/Co-Advisor
Wenpin Tsai, Thesis Advisor/Co-Advisor - Keywords:
- Social Network Analysis (SNA)
Cooperative Extension
Reach
Programs
Stakeholders
Brokerage
Degree Centrality - Abstract:
- This study was designed to understand the diversity and reach of Cooperative Extension programs in Pennsylvania delivered by Penn State Extension and the influence of network variables (brokerage and centrality) on program outcomes (program business performance and demand for the program) using Social Network Analysis (SNA). The study was conducted at Penn State Extension (PSE), the outreach wing of the College of Agricultural Sciences at the Pennsylvania State University. The population for this study consisted of all the programs offered by Penn State Extension and the program stakeholders. The sampling method used for this study was a ‘census’ of all programs and their stakeholders. The study utilized the SNA methodology and ex-post facto research design. The independent variables used in the study were the network variables, which included five types of brokers (liaison, gatekeeper, representative, itinerant, and coordinator), and degree centrality of Extension programs. There were two dependent variables, change in program business performance and change in demand for the programs. The independent variables were analyzed using UCINET 6 and network maps were drawn using NetDraw’s spring embedding algorithm. Data were analyzed using the Statistical Package for Social Sciences (SPSS 21). Binary logistic regression was used to test the hypotheses. The study had four hypotheses regarding influence of network variables (degree centrality, gatekeeper brokerage, consultant brokerage, and liaison brokerage) on Extension program outcomes (program business performance and demand for the programs). Results showed that network of Penn State Extension is widespread and programs are well connected to stakeholders in the form of number of stakeholders and connections of programs to stakeholders. Analysis using backward Wald binary logistic regression revealed that all the independent variables together (degree centrality, gatekeeper brokerage, consultant brokerage, and liaison brokerage) were statistically significant in predicting the business performance of programs but were unable to significantly explain the change in demand for the programs. Only degree centrality statistically predicted the change in business performance of programs but it had no relationship with demand for Extension programs. None of the other variables significantly predicted the change in business performance or demand for the programs. Overall, it can be concluded that, SNA is useful to understand the outreach of Extension and in understanding various outcomes of Extension programs. Based on the findings of the study, it is recommended that emphasis be placed to encourage collaboration among various programs, a need for systematic and accurate data collection and management that provides reliable data for all Extension activities. Further, it is recommended that future research be conducted by using the egocentric network to understand the all actors involved in Penn State Extension.