Innovation and Regional Development

Author:

Kijek TomaszORCID,Kijek ArkadiuszORCID,Matras-Bolibok AnnaORCID

Abstract

AbstractInnovation is considered to be highly localized process. It does not appear in space uniformly, but is predominantly spatially concentrated (Crevoisier, 2004). A number of diverse theoretical and empirical frameworks have been developed to analyze spatial dimension of innovation. The theoretical approach to the relationship between innovation and local spaces was initially demonstrated in the concepts of ‘new industrial districts’ and ‘innovative milieu’. The first of them, inspired by the Marshall’s industrial district, was introduced by Becattini (Sforzi, 2015) to emphasize the dynamic linkages between the socio-cultural features of a productive community and the rate of growth of both its productivity and innovativeness (Becattini, 2002). Many theoretical considerations and empirical contributions reveal the impact of belonging to industrial districts on innovation performance (Boix et al., 2018; Boix-Domenech et al., 2019; Cainelli, 2008; Cainelli & De Liso, 2005; Muscio, 2006; Parra-Requena et al., 2020). The existence of dynamic efficiency in industrial districts in the form of positive innovation differentials with regard to the economy average, assigned to the existence of Marshallian external economies (economies of localization) is described by Boix and Galletto (2009) as an ‘I-district effect’.

Publisher

Springer International Publishing

Reference132 articles.

1. Abreu, M., Grinevich, V., Kitson, M., & Savona, M. (2008). Absorptive capacity and regional patterns of innovation. Department for Innovation, Universities & Skills. Accessed from http://webarchive.nationalarchives.gov.uk/20100503135839/dius.gov.uk/policies/innovation/white-paper

2. Alecke, B., Blien, U., Frieg, L., Otto, A., & Untiedt, G. (2010). Ex post evaluation of Cohesion Policy programmes 2000–2006 financed by the European Regional Development Fund, Work Package 6c: Enterprise support - An exploratory study using counterfactual methods on available data from Germany; Final Report [Working paper]. Accessed from https://fis.uni-bamberg.de/handle/uniba/39281

3. Andersson, M., & Karlsson, C. (2007). Knowledge in regional economic growth—The role of knowledge accessibility. Industry and Innovation, 14(2), 129–149. https://doi.org/10.1080/13662710701252450

4. Antonelli, C., & Colombelli, A. (2017). The locus of knowledge externalities and the cost of knowledge. Regional Studies, 51(8), 1151–1164. https://doi.org/10.1080/00343404.2017.1331294

5. Antonelli, C., & Gehringer, A. (2015). Knowledge externalities and demand pull: The European evidence. Economic Systems, 39(4), 608–631. https://doi.org/10.1016/j.ecosys.2015.03.001

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3