How socioeconomic and institutional conditions at the household level shape the environmental effectiveness of governmental payments for ecosystem services program

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Chen, C.; Matzdorf, Bettina; Meyer, C.; König, H.J.; Zhen, L.: How socioeconomic and institutional conditions at the household level shape the environmental effectiveness of governmental payments for ecosystem services program. In: Ecosystems and People 15 (2019), Nr. 1, S. 317-330. DOI: https://doi.org/10.1080/26395916.2019.1676311

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/9837

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Sum total of downloads: 96




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Abstract: 
As the world’s largest payments for ecosystem services (PES) program, China’s Sloping Land Conversion Program (SLCP) is designed to combat soil erosion and land degradation by converting cropland on steep slopes into forests. Operating through an incentive-based approach, the SLCP involved 32 million rural households as core agents. This paper aims to fill a research gap regarding how socioeconomic and institutional conditions influence rural households to reach the primary environmental goals. Using fuzzy-set qualitative comparative analysis (fsQCA), we conclude that at the household level, the different pathways to environmental success or failure have been shaped by socioeconomic and institutional conditions in a combinatory manner rather than single conditions alone. Specifically, the combination of household involvement and effective monitoring plays a fundamental role in capacity-building between government and households. We found that financial incentives have a trade-off effect, as they could not only create a positive interaction but also trigger failure in situations with different conditions. Finally, the potential and limits of QCA were discussed, and we call for a more serious reflection on the added value of QCA as an alternative or complementary method to conventional approaches in environmental governance research.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2019
Appears in Collections:Fakultät für Architektur und Landschaft

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of United States United States 32 33.33%
2 image of flag of Germany Germany 31 32.29%
3 image of flag of China China 7 7.29%
4 image of flag of No geo information available No geo information available 4 4.17%
5 image of flag of Serbia Serbia 3 3.12%
6 image of flag of Czech Republic Czech Republic 3 3.12%
7 image of flag of Russian Federation Russian Federation 2 2.08%
8 image of flag of Poland Poland 2 2.08%
9 image of flag of Brazil Brazil 2 2.08%
10 image of flag of Ukraine Ukraine 1 1.04%
    other countries 9 9.38%

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