Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/29016
Title: Causal loop diagrams to systematically analyze market power in the Belgian sugar value chain
Authors: BIELY, Katharina 
Erik Mathijs
VAN PASSEL, Steven 
Issue Date: 2019
Publisher: AMER INST MATHEMATICAL SCIENCES-AIMS
Source: AIMS Agriculture and Food, 4(3), p. 711-730
Abstract: It has been acknowledged that power is a fundamental aspect that needs to be considered when performing a value chain analysis. The structure of the value chain is indicative of the power distribution along the chain. By employing systems thinking the structure of the value chain can be further investigated and inferences on market power issues can be made. This novel approach connects value chain research with insights from Industrial Organization (IO) literature. Depending on the case, market power may not be measurable by traditional economic tools. Systems thinking offers an alternative tool, allowing the employment of qualitative and quantitative data, overcoming drawbacks of IO methods and providing more depth to value chain analysis. In this paper the valuable contribution of systems thinking to market power analysis is exemplified by the Belgian sugar beet case. The analysis showed that transportability and perishability of sugar beet are key causes of market failure in the Belgian sugar value chain. Systems thinking can support understanding potential future behavior of the market based on the thorough understanding of the current market structure. We illustrate how to integrate factors determining the market structure into causal loop diagrams. This novel approach allows a comprehensive evaluation and thus opens up market power analysis to interdisciplinary research.
Keywords: market power; systems thinking; causal loop; agriculture; sugar
Document URI: http://hdl.handle.net/1942/29016
ISSN: 2471-2086
e-ISSN: 2471-2086
DOI: 10.3934/agrfood.2019.3.711
ISI #: WOS:000488251600014
Rights: 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
Category: A1
Type: Journal Contribution
Validations: vabb 2022
Appears in Collections:Research publications

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