Journal article

Modeling Ecological Success of Common Pool Resource Systems Using Large Datasets


Authors listFrey, Ulrich J.; Rusch, Hannes

Publication year2014

Pages93-103

JournalWorld Development

Volume number59

ISSN0305-750X

DOI Linkhttps://doi.org/10.1016/j.worlddev.2014.01.034

PublisherElsevier


Abstract
The influence of many factors on ecological success in common pool resource management is still unclear. This may be due to methodological issues. These include causal complexity, a lack of large-N-studies, and non-linear relationships between factors. We address all three issues with a new methodological approach, artificial neural networks, which is discussed in detail. It allows us to develop a model with comparably high predictive power. In addition, two success factors are analyzed: legal security and institutional fairness. Both factors show a positive impact on success in irrigation and fisheries supporting the view that there are sector-independent success factors. (C) 2014 Elsevier Ltd. All rights reserved.



Citation Styles

Harvard Citation styleFrey, U. and Rusch, H. (2014) Modeling Ecological Success of Common Pool Resource Systems Using Large Datasets, World Development, 59, pp. 93-103. https://doi.org/10.1016/j.worlddev.2014.01.034

APA Citation styleFrey, U., & Rusch, H. (2014). Modeling Ecological Success of Common Pool Resource Systems Using Large Datasets. World Development. 59, 93-103. https://doi.org/10.1016/j.worlddev.2014.01.034



Keywords


common pool resourcesComplexityINSTITUTIONSlarge-NNEURAL-NETWORKSnon-linearitySOCIAL-ECOLOGICAL SYSTEMS

Last updated on 2025-02-04 at 02:15