Developing A Model To Measure Public Sector Knowledge Management Performance Using The Analytic Network Process

Date of Award


Degree Name

Doctor of Philosophy


Public Affairs and Administration

First Advisor

Vincent Reitano, Ph.D.

Second Advisor

Matthew S. Mingus, Ph.D.

Third Advisor

Brian S. Horvitz, Ph.D.


Analytic network process (ANP), KM performance measurement, knowledge management (KM), public sector


Knowledge Management (KM) is a relatively a nascent field under the discipline of public administration. Specifically, KM performance measurement in the public sector is one of the areas that, to some extent, received less attention from scholars. This study aims to develop a model to measure KM performance in the public sector. The model of this dissertation is derived from system theories, where KM is depicted as a system consisting of intertwined and interacting elements. The proposed model is hypothesized to measure KM through evaluating knowledge resources, knowledge processes, and environmental factors identified as a prerequisite to the success of KM in the public sector.

This study identified the following clusters of KM success factors: Knowledge Resources, Knowledge Processes, Leadership, Organizational Culture, Organizational Structure, and KM Capabilities. Each of those clusters is comprised of elements labeled as nodes. In total, twenty-six KM success factors were identified. The KM success factors were perceived to have a causal effect relationship as a system. This dissertation used the Analytic Network Process (ANP) to evaluate the size of the influence of each KM success factor. Pairwise comparisons were conducted by surveying five academic experts. The judgments of those experts were utilized to evaluate the influence weight of each factor. The highest weighted KM success factors included Top Management Support, Teamwork Spirit, Working in Networks, and Financial Resources.

Access Setting

Dissertation-Open Access

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