Date of Award

Summer 2012

Document Type


Degree Name

Doctor of Philosophy (PhD)


Engineering Management

Committee Director

Rafael Landaeta

Committee Member

C. Ariel Pinto

Committee Member

Andreas Tolk

Committee Member

Jeffery A. Temple


Risk management (RM) and Knowledge management (KM) have mostly been treated as separate management philosophies. Risk management is a widely taught topic in academia and is practiced in industry. Knowledge management is being taught at increasingly more colleges and many companies are discovering a need for managing knowledge. This dissertation shows that some research has been conducted to apply the principles of knowledge management in establishing risk management plans. To a lesser extent there has been research conducted to apply the philosophies of risk management to identifying knowledge gaps and maintaining corporate knowledge. Both risk management and knowledge management are broad fields. The literature review uncovers the planning, identification, analyzing, handling, documenting, and monitoring of risks as key areas of consideration for risk management. It additionally reveals knowledge transfer in the form of lessons learned, best practices and near misses as a focal investigation point for knowledge management. The question answered in this dissertation is "Does knowledge transfer have a positive impact on risk management capabilities?"

A conceptual model of the relationships across knowledge transfer and risk management was built and six hypotheses were identified and statistically tested using data collected from the project environment. A data collection instrument was developed, vetted through peer review, and distributed using the Internet. Ninety complete responses were collected and provided the raw data to statistically test the validity of the measures and the hypotheses. The results support the general hypothesis that an increase in knowledge transfer will have a positive impact on risk management capabilities in projects. Another significant result is the amount, direction, and strengths of the significant statistical correlations found in this research across the measures of inter- and intra-knowledge transfer in projects and project risk management. The results of this research show that of the knowledge transfer methods considered in this study (i.e., best practices, lessons learned, and near misses) best practices have the highest number of significant statistical correlations across the measures used, including the strongest correlation found in this investigation. Additionally, it was also noted in the results that inter-knowledge transfer was significantly correlated with 70% more risk management measures than intra knowledge transfer. These results have implications for academics and engineering managers and suggest areas for future research.