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      Synergy in the Knowledge Base of U.S. Innovation Systems at National, State, and Regional Levels: The Contributions of High-Tech Manufacturing and Knowledge-Intensive Services

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          Abstract

          Synergies among technological opportunities, market perspectives, and geographical endowments can be considered as indicators of systemness. Using information theory, we propose a measure of synergy among size-classes, zip-codes, and NACE-codes for 8.5 million American firms. The synergy at the national level is decomposed at the level of states and Core-Based Statistical Areas (CBSA) as regions. Thereafter, we zoom in to the state of California and in even more detail to Silicon Valley. Our results do not support the assumption of a national system of innovations in the U.S.A. Innovation systems appear to operate at the level of the states, the CBSA regions are too small, so that systemness spills across their borders. Decomposition of the sample in terms of high-tech manufacturing (HTM), medium-high-tech manufacturing (MHTM), knowledge-intensive services (KIS), and high-tech services (HTKIS) does not change this pattern, but refines it. The East Coast--New Jersey, Boston, and New York--and California are the major players, with Texas a third one in the case of HTKIS. At the regional level, Chicago and industrial centers in the Midwest also contribute synergy. Within California, Los Angeles and its environment contribute synergy in the sectors of manufacturing, the San Francisco area in KIS, and Silicon Valley in both, but with synergy mainly generated by manufacturing. Knowledge-intensive services in Silicon Valley spillover to other regions and even globally.

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          Geographies of production: growth regimes in spatial perspective 1-innovation, institutions and social systems

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            Why are some regions more innovative than others? The role of small firms in the presence of large labs

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              Short cycle connectivity

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                Author and article information

                Journal
                30 October 2017
                Article
                1710.11017
                bf412f02-f7b8-4d68-8f9b-4239e9fe967a

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                cs.DL cs.CY

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