JOURNAL ARTICLE
Power in Global Commodity Chains. Introducing Commodity Chain Mapping as a Method for Analysing Complex Spatialities.
Published In: Historical Social Research, 2025, v. 50, n. 4. P. 344 1 of 3
Database: Sociology Source Ultimate 2 of 3
Authored By: Espeter, Lara M. 3 of 3
Abstract
»Macht in globalen Warenketten. Einführung des Commodity Chain Mappings als Methode zur Analyse komplexer Raumanordnungen«. Based on a world-systems approach, I focus in this article on spatialities that go beyond territorial thinking: commodity chains. Therefore, I ask how these can be captured methodologically. In this article, I outline a method for reducing the complexity of large-scale spatialities dominated by the spatial logic of routes, such as commodity chains. This is necessary in order to be able to work with and analyse such complex chains of interdependence empirically. I illustrate this by examining the commodity chain of cut flowers from Kenya to Germany. Complexity reduction aims at identifying the power structures within the commodity chain in order to be able to examine global inequalities in subsequent work. In this way I demonstrate the complexity of such spatial structures and systematically reduce them to their power structure within the modern world-system. To do this, I operationalise power (according to Marx and Wallerstein), which makes it possible to analyse the power structure inherent in the commodity chain. In light of this, I propose a framework with which complex spatial arrangements such as global commodity chains can be surveyed and analysed in the future. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Historical Social Research. 2025/10, Vol. 50, Issue 4, p344
- Document Type:Article
- Subject Area:Biography
- Publication Date:2025
- ISSN:0172-6404
- DOI:10.12759/hsr.50.2025.52
- Accession Number:189424767
- Copyright Statement:Copyright of Historical Social Research is the property of GESIS - Leibniz-Institute for the Social Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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