PUBLIC VALUE MAPPING:
Developing A Non-Economic Model of the
PI: Daniel Sarewitz, Arizona State University
Co-PI: Barry Bozeman, University of Georgia
Science and innovation policies (SIPs) aim at mobilizing knowledge in support of a wide range of societal aspirations and values. However, analytical tools and models for the assessment of SIPs focus predominantly on economic values. Analytical tools for assessing social impacts of science tend to be anchored in microeconomics (e.g. benefit-cost analysis). The assumptions upon which economics of innovation models and attendant tools are based inevitably affect SIP assessments and choices. For example, the tendency to focus on “science and technology as the engine of economic growth” has contributed in part to the limited attention to equity in the distribution of the impacts of research activities (Woodhouse and Sarewitz, 2007). Values not easily expressed in economic terms receive less attention simply owing to the absence of compelling and concrete ways of thinking about them.
Nearly all observers, including economists, recognize that some social values are not well accounted for by economic models and measures. The influence of economic models in SIP is in part explained by limited progress in developing ways to conceptualize those science- and innovation-related values not easily expressed in monetary terms. The purpose of the proposed research is to further develop a public-values-based model for SIP. At the core of our work are two fundamental questions: What are the public values that justify particular SIPs, and what is the capacity of a given SIP to yield outcomes that support and advance those values?
The research will operationalize these questions and apply them to the development of a SIP decision model using a method that we call Public Value Mapping (PVM). Core assumptions of PVM are: (1) that it is possible to identify public values, including ones not well captured by economic constructs; (2) just as one can assess market failure, “public value failure” occurs when neither the market nor the public sector provides goods and services required to achieve designated public values; and (3) innovation can be characterized not only in terms of contributions to economic growth and productivity but also in terms of public values achieved.
The proposed work entails theory development as well as case studies to advance and test the PVM model. Four case studies (as well as three additional studies funded from other sources) will be inter-linked by a common analytical framework, bringing multiple perspectives to the analysis. Case studies are designed specifically to draw from current PVM theory while also testing and improving the theory. Each case begins with an explicit statement of the public values analyzed, and proceeds to “map” progress toward public values by modeling the distinctive innovation process in which each case is embedded. Integration of case studies will add empirical robustness to the PVM model.
A new model of innovation based on widely shared, non-economic values—public values—would represent a major intellectual advance in the study and analysis of science and innovation policies. The proposed research will: (1) advance understanding of the links between SIPs and public values; (2) further develop Public Value Mapping in terms of a “churn model” of innovation (Bozeman and Rogers, 2003) emphasizing the social impacts of innovations and the capacity of innovation systems to create new beneficial impacts; and (3) develop the PVM model as a new theoretically and empirically grounded foundation for assessing and designing SIPs.
The new model of innovation will provide SIP analysts a theoretical and methodological foundation for assessing and informing science and innovation investment and institutional design decisions, using public values as the measure of success. The model is also meant to be a crucial first step toward developing public-values-oriented SIP decision tools that could be widely deployed in SIP decision making processes.
Public Value Mapping: Assessing the Non-Economic Value of R&D