Type of Document	Dissertation
Author	Choi, Sang Ok
URN	etd-07112005-104000
Title	Network Analysis of Workforce Development Programs
Degree	Doctor of Philosophy
Department	Public Administration and Policy, School of
Advisory Committee	Advisor Name Title Ralph S. Brower Committee Chair Frances S. Berry Committee Member Mary E. Guy Committee Member Robert E. Crew, Jr. Committee Member
Keywords	Public Management Network Analysis Workforce Development Program Public Administration
Date of Defense	2005-07-01
Availability	unrestricted
Abstract Network structure is one explanatory variable to explain network performance, but its effect may be uncertain. Much research, however, has not attempted to combine network structures with other characteristics of networks – e.g., network social capital, network management, or network learning – that may explain network performance. The consideration of other network characteristics as well as the combination of network structure with other factors cannot be ignored. This study proposed four network characteristics and presented an integrated model of network performance. The model included unique aspects (structure, content, process, and management) of networks from four network perspectives. This study first examined simple relationships between each characteristic and network performance, and then extended intermediated effects of each characteristic on others. This study used 136 workforce development networks for this analysis with a social network analysis program (UCINET 6.0) and the LISREL 8.0 program. Fifteen of the twenty-five hypotheses proposed were supported. Key research findings are as follows: more diverse service networks or less centralized networks are more likely to lead to better network performance; there is a positive relationship between network social capital and network performance; service provider network learning had a positive effect on network performance; there is a positive relationship between network management and network performance; a more adaptive service provider network is more likely to have more effective network management network and to influence employer network learning processes.. This study also provided managerial implications for workforce development managers that relatively equal distributed networks (loose/decentralized network) and more cohesive networks may be one of strategic choices for maintaining workforce development program stability or increasing the network capacity. From the results of the comprehensive data analysis and procedures, this study concludes that in successful workforce development programs, a more thorough understanding of network characteristics of workforce development programs should be made.
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