Type of Document Dissertation Author Jang, Hoseok Author's Email Address email@example.com URN etd-11152010-141557 Title Examining Organization Learning in Public Sector Organizations: From the Perspective of Florida Municipal Governments Degree Doctor of Philosophy Department Public Administration and Policy, School of Advisory Committee
Advisor Name Title Frances Stokes Berry Committee Chair Kaifeng Yang Committee Member Lance deHaven-Smith Committee Member Koji Ueno University Representative Keywords
- Single-loop Learning
- Double-loop Learning
- Performance Management
- Local Governments
Date of Defense 2010-10-19 Availability unrestricted AbstractPublic sector organizations currently operate in an environment of change and choice (Berry, 2007). In particular, the complex governance and unpredictable nature of the contemporary public sector environment have challenged governments’ attempts to improve their performance and accountability. Organizational learning is the key to performance improvement in changing and uncertain environments (Argyris and Schon, 1996; Schein, 1993) because it is based on new knowledge development or performance information use, which in turn enables managers to make better decisions to improve performance. In this respect, organizational learning is an important component of the current performance management reforms or managing for results, which focus on collecting, distributing, and using performance information to improve government organizations’ performance. Although organizational learning is a critical domain in performance management, empirical understanding of organizational learning in the public sector settings is limited. Thus, this study attempts to advance both theoretical and empirical research on organizational learning in the public sector, using data from the Organizational Learning and Performance Management Survey 2010: Florida Municipal Governments.
The overall research question of this dissertation is: what factors influence organizational learning in Florida municipal governments? In particular, this study attempts to assess if there are differences in the antecedents of single-loop and double-loop learning. In this study, therefore, we use two dependent variables which consist of indicators for single-loop and double-loop learning respectively, in our models to examine a facilitative environment or condition for organizational learning. To answer this research question, based on past research, this study develops a theory composed of six factors to assess what seems to impact single and double-loop learning based on: 1) structural factors, 2) cultural factors, 3) learning forums, 4) performance management systems, 5) network characteristics, and 6) external stakeholder’s participation.
We found strong support for our organizational learning models, and variables representing each of the six theoretical factors were significant. Research results indicated that there are some different patterns of effects and different impacts for single-loop and double-loop learning. The goal and mission orientation, strategic planning, external networks, and political officials’ participation are facilitative factors to double-loop learning but do not have a significant relationship to single-loop learning, while the utilization of IT is important to single-loop learning but not to double-loop learning. Moreover, the impacts of decentralization, risk-taking culture, and learning forums are stronger in double-loop learning than in single-loop learning, while the impact of internal network is greater on single-loop learning than on double-loop learning. Low formalization, resources, and benchmarking, however, were unexpectedly found to have negative relationships with at least one type of organizational learning. Moreover, we found the mediating effect of single-loop learning on double-loop learning.
Overall, the findings provide insight into antecedents of and strategies for fostering single-loop and double-loop learning, and ultimately performance improvement of local governments.
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