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Cited by 603

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Global production networks and the extractive sector: governing resource-based development

Open access
Bridge, G.·2008·Journal of Economic Geography

Abstract

This article explores the opportunities a GPN approach provides for understanding the network configurations and regional development impacts associated with extractive industries. The article elaborates two core claims: (i) that the application of the GPN analytical framework provides a way to make progress in a stalled policy debate regarding the linkages between resource extraction and socio-economic development (popularly known as the ‘resource curse thesis’); and (ii) that the encounter between GPN and a natural resource-based sector introduces distinctive issues—associated with the materiality and territoriality of extractive commodities—that, to date, GPN has not considered fully. The article examines the global production network for oil as an empirical case of how extractive industries can provide (limited) opportunities for socio-economic development.

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Crossref · 10.1093/jeg/lbn009

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Metadata

Authors
Bridge, G.
Venue
Journal of Economic Geography
Published
2008-02-29
Volume
8
Issue
3
Pages
389-419
ISSN
  • 1468-2702 (ISSN-L)
  • 1468-2710
OpenAlex
W2127947455
Cited by
603
References
3
FWCI
28.31
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Global production networks and the extractive sector: governing resource-based development. https://app.cochat.ai/papers/10.1093/jeg/lbn009
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Bridge, G. (2008). Global production networks and the extractive sector: governing resource-based development. Journal of Economic Geography. https://doi.org/10.1093/jeg/lbn009

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.