The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Industrial districts as ‘learning regions’: A condition for prosperity
Open accessAbstract
The article discusses the future of industrial districts in a post‐Fordist ‘learning economy’. It argues that the core of the question is related to the collective learning capacity of small and medium sized enterprises in industrial districts. In the article factors enabling and constraining the formation of a sufficient learning capacity are discussed. Special attention is paid to the role and function of the specific ‘Marshallian’ characteristics of industrial districts in securing a successful transformation of the districts into ‘learning regions’.
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Citations
Cites
Storper, M. (1995) · European Urban and Regional Studies · doi:10.1177/096977649500200301 · Cited by 1,595
Cited by
The Geography of Innovation: Regional Innovation Systems
Asheim, B. T., & Gertler, M. S. (2009) · The Oxford Handbook of Innovation · doi:10.1093/oxfordhb/9780199286805.003.0011 · Cited by 1,447
Self-citation(2014) · Cited by 950
Boschma, R. A., & ter Wal, A. L. J. (2007) · Industry & Innovation · doi:10.1080/13662710701253441 · Cited by 657
Gatekeepers of Knowledge within Industrial Districts: Who They Are, How They Interact
Morrison, A. (2008) · Regional Studies · doi:10.1080/00343400701654178 · Cited by 441
Firms in Territories: A Relational Perspective*
Dicken, P., & Malmberg, A. (2001) · Economic Geography · doi:10.1111/j.1944-8287.2001.tb00169.x · Cited by 411
Metadata
- Authors
- Asheim, B. T.
- Venue
- European Planning Studies
- Publisher
- Informa UK Limited
- Published
- 1996-08
- Volume
- 4
- Issue
- 4
- Pages
- 379-400
- ISSN
- 0965-4313 (ISSN-L)
- 1469-5944
- OpenAlex
- W2079982544
- Cited by
- 749
- References
- 1
- FWCI
- 45.75
- Type
- journal article
- Language
- en
- Open access
- green
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- Asheim, B. T. (1996). Industrial districts as ‘learning regions’: A condition for prosperity. European Planning Studies. https://doi.org/10.1080/09654319608720354
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
