RISS 검색 - 국내학술지논문 상세보기

다국어 초록 (Multilingual Abstract)

[Background] Local public technology centers, administrated by the prefectural and municipal government, have engaged in technological support for small local firms. The initiation of this regional innovation policy dates back to the modern economic growth in the 1880s. Local public technology centers offer various kinds of technological services such as testing, inspection, usage of experimental equipments, workshops for technology diffusion, technological consultation, funded research and joint research. They also conduct their own research, patent inventions and license out their patents chiefly to small local firms. Recently two structural changes forced local public technology centers to redefine their strategies in regional innovation systems. First, after a prolonged recession in the 1990s, the local authorities became highly cost-conscious, which led them to cut centers` budgets and to evaluate them more rigorously. Second, the reform of national innovation systems, symbolized by the incorporation of national universities in 2004, made knowledge interactions between small local firms and national universities more active, which has created a new source of knowledge for small local firms that performed R&D. [Purpose] Under such circumstances, local public technology centers are required to establish their own strategies that match the characteristics of regional innovation systems. Since local public technology centers are administrated by local authorities, their strategy development represents regional innovation policy. Their strategies are predicted to be most effective when they are developed in accordance with the characteristics of regional innovation systems. Using a comprehensive database on local public technology centers, this study aims to quantitatively examine whether regional innovation policy represented as centers` resource allocation strategies during 2000 and 2008 is contingent on, or regardless of, the characteristics of regional innovation systems. [Structure] First, I established the model to describe the characteristics of regional innovation systems. The model conceptualizes the local market for public technological services, such as technological consultation, workshops for diffusion of new technologies, material inspection, and joint research, from demand-side and supply-side perspectives. Demand-side factors are represented as the absorptive capacity of small local firms. Regions with more R&D-active small firms would exhibit more needs for high-quality public knowledge and more interactive channels, such as joint research, for knowledge transfer. Supply-side factors are represented as the activeness of national universities in the region to interact with small local firms via joint research. Regions with a national university willing to interact with small local firms would require local public technology centers to establish distinct strategies that do not overlap with the universities` role in the local market for public technological services. Second, I identified two key strategies that characterize technology transfer channels offered by local public technology centers. Based on factor analysis, various technological services provided by centers were integrated into two factors: the tendency to enhance the centers` own research capabilities; and the tendency to directly support small local firms. Then, I developed theoretical predictions about the relationships between regional innovation policy represented as resource allocation strategies of the centers and the characteristics of regional innovation systems where the center is located. Third, using a comprehensive dataset of local public technology centers, a statistical analysis was conducted to test whether centers` strategies were developed so that they would match the characteristics of regional innovation systems. [Method] Based on the model that describes the characteristics of regional innovation systems, I introduced a proxy variable for demand-side factors of the local market for public technological services, i.e., the ratio of R&D-active small firms to the whole small firms in the region. A proxy variable for supply-side factors was the ratio of joint research projects between small local firms and national universities to all joint research projects conducted by national universities in the region. Two proxy variables were enabled to draw a scatter chart, where vertical axis denotes demand-side factors and horizontal axis denotes supply-side factors, representing the location of the 47 local authorities in Japan. [Result] Four quadrants were identified by dividing a scatter chart by introducing averages of demand- and supply-side factors in the chart. For instance, a region (prefecture) in Quadrant II has small local firms with above-average absorptive capacity while universities in that region have below-average activity in knowledge interactions with small local firms. This implies that in such region, local public technology centers with high-quality technological knowledge can act as a significant spillover pool for small R&D-intensive firms in that region. An analysis of variance was conducted to test whether local public technology centers` strategies adopted between 2000 and 2008 aligned with the regional environmental characteristics identified as four quadrants. The results show that there is no statistically significant difference in centers` resource allocation strategies according to the characteristics of regional innovation systems. This implies that local public technology centers` resources may not have been fully utilized as an engine for regional economic development. [Contributions] Theoretical and policy implications derived from empirical results are as follows. First, based on the previous literature on regional knowledge spillovers, a model to describe the characteristics of regional innovation systems was developed. The model pictures the local market for public technological services from demand-side and supply-side perspectives. Linked to two distinct centers` strategies identified by factor analysis, this model enables us to infer theoretical relationships between regional innovation policy represented as resource allocation strategies of local public technology centers and the characteristics of regional innovation systems, which can be quantitatively examined. The newly developed model to understand regional innovation systems and empirical approach to examine the relationships between regional innovation policy and regional innovation systems can be applied to the assessment of regional innovation policy in other geographies. This constitutes the strength of the study. Second, with a comprehensive dataset of the centers, the aforementioned approach enabled us to quantitatively evaluate regional innovation policy on local public technology centers for the first time. This makes a clear contrast to the existing studies on local public technology centers based on case studies, where the generality of their implications are limited. Although local public technology centers have been considered to play an important role in regional economic development, the results suggest that they need to make their strategies more efficient so that their resources will be allocated in concord with the characteristics of the regional innovation system. The policy implications of this study are that local authorities and local public technology centers should precisely recognize their relative advantage in the region. Then it would be possible for them to rebuild guidelines that would help local public technology centers to contribute to the regional economic development in a more relevant manner.

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참고문헌 (Reference)

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