Junichi Nishimura

<title>Abstract</title> This paper examines the making of university and industry research collaboration from the perspective of matching theory. Our analysis, based on an original survey in Japan, aims at identifying the mechanism of matching. The major findings are as follows. There is significant evidence for positive assortative matching at the project level: a researcher with better seeds or better needs gives a higher value to the partner’s research capability and the goodness-of-fit between the project and the partner’s capability in selecting its partner. The projects with the partners selected for research capability and goodness-of-fit are associated with high university and industry research collaboration performance. Furthermore, own contact is most used for positive assortative matching. These results indicate the importance of deep field knowledge and tacit knowledge of the researcher in the search process. These findings suggest that technology transfer policy would need to pay significant attention to the contribution of the decentralized matching process.

<title>Abstract</title> Regional innovation policies have been implemented in several countries. In Japan, controlled decentralization of traditionally centralized innovation policy is ongoing, so that we can observe multilevel policy mix of public R&amp;D (research and development) subsidies by national, prefecture, and city governments. However, empirical studies on multilevel R&amp;D support using panel data and considering municipality level have been scarce. Based on original survey data and financial data of manufacturing small and medium enterprises (SMEs), we estimate their total factor productivity (TFP) and empirically investigate the effects of public R&amp;D subsidies by national, prefecture, and city governments. We employ firm-level fixed-effect panel estimation in order to control for the effects of any unobservable time-invariant factors. We find that multilevel subsidies (especially those involving city subsidies) complementarily and persistently increase recipients’ TFP. These results suggest significant advantages of multilevel policy mix, especially those involving city subsidies.

Increasing attention has been paid to regional innovation systems. However, previous studies have so far only focused on (the regional impact of) national policies or specific regions. Despite increasing attention to regional and local innovation policies, no studies have been carried out to date on the factors of implementation and design of local research and development (R&amp;D) subsidy programs at the city level. Our research fills this gap by using information on R&amp;D subsidy programs from local authorities in Japan collected via websites and our original survey. Thus, our research aims at empirically investigating the determinants of both implementation and design of local R&amp;D subsidy programs at the city level (length and upper limit of subsidies, and flexibility of subsidy conditions) considering both demand- and supply-side factors. We employ probit models for basic empirical estimations and provide some robustness checks. The empirical results suggest that, after controlling for city type and population size, supply-side factors including local government conditions significantly affect the implementation of public R&amp;D subsidy programs. In contrast, we find that demand-side factors matter more for the design of subsidy programs than supply-side factors.

We evaluate the three bio-cluster projects in Japan initiated by the Ministry of Economy, Trade and Industry since 2001 in terms of university-industry collaboration (UIC), using 3,020 biotechnology patents of 344 firms. We identify UIC patents by investigating the affiliations of 4,263 inventors in detail. The estimation results can be summarized as follows. First, the value of collaborative patents applied by cluster participants is higher than other types of collaborative patents. Second, the value of patents applied by cluster participants gets higher since the cluster projects started in 2001. Third, in particular, the patents applied by UIC within bioclusters become more valuable. These results imply that firms participating in the bio-cluster projects improve their quality-adjusted R & D productivity through UIC within clusters.