Putting university research in context: Assessing alternative measures of production and diffusion at Stanford

Scholars widely acknowledge that university research is critical to innovation and entrepreneurship. Much of the literature on university research, however, evokes a linear model from “science to products” and focuses, therefore, upon a limited set of indicators such as patents and licenses. Such a perspective runs the danger of missing the myriad ways in which science and commerce are intertwined and the myriad ways in which these activities might be assessed. In this paper, I address the question of how different measures reflect different perspectives and biases by investigating the production and diffusion of research associated with one of Stanford University's most prolific interdisciplinary centers, the Center for Computer Research in Music and Acoustics (CCRMA). I draw upon a unique data set that captures activities and engagement surrounding CCRMA for its 30-year history through a wide variety of measures, ranging from publication citations to industrial affiliates to personnel mobility. Employing the analytic categories of “description” and “enactment,” and distinguishing between “indicators” and “pathways,” I show how different measures reflect different activities and learning processes, and how they dramatically alter perceptions of active individuals, organizational reach, and timing and sequencing of activities. Building on these findings, I present a more complete model of university research production and diffusion, I discuss how alternative measures challenge certain assumptions in the literature, and I suggest concrete policy initiatives to improve our measurement and assessment of university research.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► University research is vital to innovation, but measuring its production and diffusion is difficult. ► I examine 30 years of student and faculty activity at a Stanford research center through a wide range of novel metrics. ► I distinguish between “pathways” and “indicators” and between “enactment” and “description”. ► The measures reveal differences in magnitude, organizational demography, timing, and sequencing. ► The findings encourage a more nuanced view of university research that challenges some existing academic studies.