Developing a measure of innovation from research in higher education data

The benefit of science is often limited to the contribution to general knowledge. The definition of innovation of research is complex and multidimensional. Size of research expenditure budget and publication and citation metrics are most often used to measure innovation of institutional research. This project aims to construct a measure for innovation of institutional research that has convergent validity with societal benefit from university research. The sample included 143 institutions in the US who responded to the 2014 Association of University Technology Managers (AUTM) Licensing Survey Data on faculty size, research expenditure, publications, citations, intellectual property outcomes, clinical trials registration and results, and contributions to clinical practice guidelines were included. Exploratory Structural Equation Modeling (ESEM) was used to determine the most parsimonious model with all available indicators from the AUTM Licensing Survey Data. A Second-Order Confirmatory Factor Analysis (CFA) was used to validate the ESEM results. Second order CFA confirmed hypothesis of an overall latent factor of research innovation. These results indicate that innovation of institutional research can be evaluated on three factors: contributions to knowledge, public health innovation, and economic impact. There have been no previous efforts to empirically measure the multidimensionality of innovation of institutional research with the inclusion of public health impact.