Introduction

It is with great pleasure that I introduce this Economic Development Quarterly symposium consisting primarily of research funded by the U.S. Department of Commerce Economic Development Administration (EDA) Research and National Technical Assistance grant program. EDA has a long history of funding high-quality economic development–oriented research. It has been my pleasure to be involved in EDA’s research program during the past 6 years, when the contributions presented in this symposium were conceptualized, initiated, and completed. The fundamental difficulties, in my view, with social science research as used in public policy analysis, program evaluation, and performance measurement lie in both the influence of strong normative presumptions assuming program effectiveness and the frequent lack of common definitions. The first difficulty arises from the political nature of preference aggregation in the public sector and the influence of “iron triangles” on the policy analysis, program evaluation, and performance measurement. Much of the social science research produced or funded by government and interested nonprofit entities proceeds from, and seeks to validate, the assumption that can be encapsulated in the often heard phrase “we know our program works,” an approach that might be tendentiously characterized as “face validity. ” As a result, social science researchers seeking funding from government agencies and interested nonprofits are faced with a conundrum that arguably biases research methods and findings. Research reports are reviewed most commonly by normative standards of interested parties and report language not infrequently negotiated. The fundamental flaw in this approach is that it fails to produce the best possible insights into programmatic and funding decision making. As a social scientist and practitioner, I wanted the best possible information, stripped insofar as possible of normative presumptions, to access the analytical power of social science to inform decision making. The peer review process has long served this function in the academic world because it brings to bear the methodological and contextual awareness of seasoned researchers to the review process. The education, training, and experience of these social scientists allows them to offer critiques to their colleagues that others, lacking their expertise and independence, cannot or will not. The result is higher quality research and the deeper, more meaningful, insights that are critical to programmatic improvement and the credibility of outcome reporting. To address the second challenge, the lack of common definitions, I pursued what I called an “integrated research agenda. ” Agenda integration implies several dimensions. First, it is important to leverage the modest research funds available by ensuring, to the extent possible, that common definitions and understandings of the literature exist, tying the various research activities together. Second, the integrated agenda bridges what is sometimes called the theory–practice gap and embodies my understanding of “good theory. ” Good theory should have both theoretic and pragmatic utility; it should stand up to the peer review process, build on our existing knowledge, add to our understanding of economic development, and should produce practitioner accessible reports and tools that improve the practice of economic development. The articles in this symposium represent the integrated research agenda spectrum. Their appearance in this journal indicates that the work passed rigorous peer review. The inclusion of research not funded by EDA underlines the embedding in the broader economic development research context. It is important to note that the research partnerships employed in some of the articles demonstrate that peer review quality research can span the divide that so often characterizes the academic–practitioner relationship. Hopefully, the broad economic development–relevant linkages characterize the work appearing in this symposium underlines that reality. Karen Chapple and her colleagues employ a regional innovation systems perspective to argue that “green innovation complicates traditional models of innovation and economic development. ” Exploring the situation from a “regional innovation systems” perspective, the piece makes some important distinctions, including the variable role of regulation and reinforcing our understanding that “[i]nnovation doesn’t necessarily foster growth. ” Chapple’s emphasis on systems and network thinking is consistent with other articles in the symposium and the broader literature now expanding Porter’s original business clusters insights (Porter, 1990) to provide more nuanced understandings