Firm strategies in scientific labor markets
Bandyopadhyay, Kirsten Analise
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This dissertation expands on the economic geography literature on how and why innovation clusters spatially by taking a closer look at two correlated phenomena: regional specialization and firm clustering. While existing studies note that innovative regions are often highly specialized and highly clustered, further research is needed on the relative contributions of specialization and clustering to regional innovation. I examine these contributions by focusing on one key element of any regional innovation project: the labor market for scientific and technical professionals. The foundation for this study is a typology of regions based on regional specialization and firm clustering. I use this typology to answer one key research question: how specialization and clustering affect wages and recruitment methods in science-based industries. I create my typology using firm location data from the Photonics Buyers’ Guide, a leading trade publication in the photonics industry; I use the standardized location quotient and the average nearest neighbor distance as metrics of regional specialization and firm clustering, respectively. I investigate small firms’ labor market strategies using job search and wage data from the 2011 and 2012 SPIE salary surveys of employees in the photonics industry. I also examine how people-based and place-based policies for strengthening scientific and technical labor markets change when viewed through the lens of specialization and clustering. I selected the photonics industry as an example of a science-based industry for three reasons: its diversity of applications, its policy importance, and its unique colocation of design and manufacturing. Regional specialization and firm clustering, while correlated, do not always go hand in hand. By disentangling the effects of specialization versus clustering, this dissertation contributes to the literature on the spatial analysis of innovation. It also offers policymakers a heuristic for deciding on the importance of being known for a particular industry (regional specialization) and creating dense innovation districts (firm clusters) through preferential zoning or other mechanisms.