Artikel

What shapes local innovation policies? Empirical evidence from Japanese cities

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&D) subsidy programs at the city level. Our research fills this gap by using information on R&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&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&D subsidy programs. In contrast, we find that demand-side factors matter more for the design of subsidy programs than supply-side factors.

Sprache
Englisch

Erschienen in
Journal: Administrative Sciences ; ISSN: 2076-3387 ; Volume: 10 ; Year: 2020 ; Issue: 1 ; Pages: 1-22 ; Basel: MDPI

Klassifikation
Öffentliche Verwaltung
Thema
innovation policy
local authority
R&D subsidy
policy design
city
Japan

Ereignis
Geistige Schöpfung
(wer)
Okamuro, Hiroyuki
Nishimura, Junichi
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2020

DOI
doi:10.3390/admsci10010011
Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Okamuro, Hiroyuki
  • Nishimura, Junichi
  • MDPI

Entstanden

  • 2020

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