The effect of regional resources on innovation: a firm-centered approach

Abstract

The current environment of high competitiveness has made innovative firms, especially job-creating ones, central to regional economic growth. Most of previous studies have not considered the interactions between internal and regional factors, and has focused on product innovation performance. This paper aims to fill both gaps in the literature on the regional determinants of firm innovation. Assuming a firm-centered approach, the main goal of the paper is to analyse whether the regional resources determine firm innovation either in a direct way or by shaping the effect of the firm’s internal resources. We used multilevel modelling and panel data methodology in a sample of 2141 Spanish manufacturing firms over the period 2008–2014. More specifically, we assume fixed slopes and estimate a three-level logistic random intercept models (observations: level 1; firms: level 2; regions: level 3). Our results show that the internal factors are the cornerstone of firm innovation. Nevertheless, there is also a ‘regional effect’ in the firms’ propensity to innovate. Particularly, the effect of the region’s resources in explaining the differences across firms in product innovation is more substantive than in process innovation. In this last case, regional factors play a subtler role by shaping the effect of its internal drivers. Policy-makers should be conscious of the need of keeping a bottom–up approach (or a firm-centered approach) when designing regional innovation policies. In this respect, policies aimed at promoting the size, export activities and R&D intensity of firms could be effective to increase the number of firms that can benefit from the exploitation of the region’s resources.

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Fig. 1
Fig. 2

Notes

  1. 1.

    Eurostat uses the aggregation of the manufacturing industry according to technological intensity and based on the NACE Rev.2 at the two-digit level.

  2. 2.

    The authors thank an anonymous reviewer for this suggestion.

  3. 3.

    Other different measures of the regional production spillovers through scientific publishing were used. In particular, we used the natural logarithm of the number of WOS (Web of Science) publications per 100 thousand inhabitants, the natural logarithm of the number of SCOPUS publications per 100 thousand inhabitants, and the natural logarithm of the number of SCOPUS publications over the number of professors at the region’s universities. These alternative measures yield similar results to those presented in Tables 5 and 6. These models are not reported for space reasons. They can be obtained from the authors if required.

  4. 4.

    The authors thank an anonymous reviewer for this suggestion.

  5. 5.

    For details see: https://ec.europa.eu/regional_policy/es/policy/how/is-my-region-covered/2007-2013/

  6. 6.

    Those models are not reported for space reasons. They can be obtained from the authors if required.

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Appendix

Appendix

See Figures 3, 4, 5, 6, 7 and 8.

Fig. 3
figure3

Percentage of innovative firms (NIF_TF) in each region by year

Fig. 4
figure4

Percentage of GDP dedicated to R&D (RD_GDP) in each region by year

Fig. 5
figure5

Percentage of workers in R&D (NRDE_TE) in each region by year

Fig. 6
figure6

Number of academic documents published in WOS per university professor (LNWOS_PDI) in each region by year

Fig. 7
figure7

Number of patent applications per 100 thousand inhabitants (LNPAT_100TH) in each region by year

Fig. 8
figure8

Percentage of adult population with higher education (P_POPHE) in each region by year

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Rodríguez-Gulías, M.J., Rodeiro-Pazos, D., Fernández-López, S. et al. The effect of regional resources on innovation: a firm-centered approach. J Technol Transf (2020). https://doi.org/10.1007/s10961-020-09811-8

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Keywords

  • External resources
  • Regional resources
  • Product innovation
  • Process innovation
  • Multilevel
  • Absorptive capacity
  • Interaction effects

JEL Classification

  • O31
  • O38
  • C33
  • R58