Abstracts

Investment in Research and Development (R&D) is necessary for innovation, allowing an organization to maintain a competitive edge. The U.S. Federal Government invests billions of dollars, primarily in basic research technologies to help fill the pipeline for other organizations to take the technology into commercialization. However, it is not about just investing in innovation, it is about converting that research into application. A cursory review of the research proposal evaluation criteria suggests that there is little to no emphasis placed on the transfer of research results. This effort is motivated by a need to move research into application. One segment that is facing technology challenges is the energy sector. Historically, the electric grid has been stable and predictable; therefore, there were no immediate drivers to innovate. However, an aging infrastructure, integration of renewable energy, and aggressive energy efficiency targets are motivating the need for research and to put promising results into application. Many technologies exist or are in development but the rate at which they are being adopted is slow. The goal of this research is to develop a decision model that can be used to identify the technology transfer potential of a research proposal. An organization can use the model to select the proposals whose research outcomes are more likely to move into application. The model begins to close the chasm between research and applicationotherwise known as the valley of death. A comprehensive literature review was conducted to understand when the idea of technology application or transfer should begin. Next, the attributes that are necessary for successful technology transfer were identified. The emphasis of successful technology transfer occurs when there is a productive relationship between the researchers and the technology recipient. A hierarchical decision model, along with desirability curves, was used to understand the complexities of the researcher and recipient relationship, specific to technology transfer. In this research, the evaluation criteria of several research organizations were assessed to understand the extent to which the success attributes that were identified in literature were considered when reviewing research proposals. While some of the organizations included a few of the success attributes, none of the organizations considered all of the attributes. In addition, none of the organizations quantified the value of the success attributes. The effectiveness of the model relies extensively on expert judgments to complete the model validation and quantification. Subject matter experts ranging from senior executives with extensive experience in technology transfer to principal research investigators from national labs, universities, utilities, and non-profit research organizations were used to ensure a comprehensive and cross-functional validation and quantification of the decision model. The