Drivers of Farmers’ Behavior toward Compensation Scheme for Cultivated Land Protection in Chengdu Pilot Area, China
Ecological environment compensation has been increasingly applied to promote positive behavior among farmers toward protecting the quantity, quality, and ecological environment of cultivated land. Studying farmers’ behavior affected by economic incentive is necessary to promote sustainable developme...
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Taylor & Francis Group
2021
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oai:doaj.org-article:c069e231d8b74b81b9b16d19feb6caf82021-12-02T19:19:18ZDrivers of Farmers’ Behavior toward Compensation Scheme for Cultivated Land Protection in Chengdu Pilot Area, China2332-887810.1080/20964129.2021.1978330https://doaj.org/article/c069e231d8b74b81b9b16d19feb6caf82021-10-01T00:00:00Zhttp://dx.doi.org/10.1080/20964129.2021.1978330https://doaj.org/toc/2332-8878Ecological environment compensation has been increasingly applied to promote positive behavior among farmers toward protecting the quantity, quality, and ecological environment of cultivated land. Studying farmers’ behavior affected by economic incentive is necessary to promote sustainable development policies for cultivated land protection. In this study, we investigated the current situation regarding economic incentive policies for cultivated land protection, which has attracted the attention of Chinese government in recent years. Then, we focused on the earliest pilot scheme (i.e., the Cultivated Land Protection Fund, CLPF) implemented in the west of China since 2008 to empirically analyze farmers’ behavior. Statistical analysis and path analysis methods were applied, with data collected from 296 questionnaires. Our results showed that positive actions, including the enhancement of initiatives to protect cultivated land, the improvement of the ecological environment of cultivated land, and the investment in agricultural infrastructure, have been adopted by farmers since the implementation of the CLPF. Furthermore, farmers’ individual characteristics (gender, education level, labor force size, cultivated land area, migration out of traditional farming areas, and average annual household income) impacted significantly and directly on farmers’ behavior. In terms of the cognitive characteristics that had a direct impact on farmers’ behavior, the extent of farmers’ knowledge of the policy was the most important factor. On the premise of comprehensive consideration of the diversity of farmers’ livelihoods, new communication technologies and sufficient funds, we suggested that a long-term and sustainable project should be established at the national level to effectively compensate farmers.Haipeng NiuDongyang XiaoSuxia ZhaoTaylor & Francis Grouparticlefarmers’ behaviorecological environment compensationinfluencing factorscultivated land protectionEcologyQH540-549.5ENEcosystem Health and Sustainability, Vol 0, Iss 0 (2021) |
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farmers’ behavior ecological environment compensation influencing factors cultivated land protection Ecology QH540-549.5 |
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farmers’ behavior ecological environment compensation influencing factors cultivated land protection Ecology QH540-549.5 Haipeng Niu Dongyang Xiao Suxia Zhao Drivers of Farmers’ Behavior toward Compensation Scheme for Cultivated Land Protection in Chengdu Pilot Area, China |
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Ecological environment compensation has been increasingly applied to promote positive behavior among farmers toward protecting the quantity, quality, and ecological environment of cultivated land. Studying farmers’ behavior affected by economic incentive is necessary to promote sustainable development policies for cultivated land protection. In this study, we investigated the current situation regarding economic incentive policies for cultivated land protection, which has attracted the attention of Chinese government in recent years. Then, we focused on the earliest pilot scheme (i.e., the Cultivated Land Protection Fund, CLPF) implemented in the west of China since 2008 to empirically analyze farmers’ behavior. Statistical analysis and path analysis methods were applied, with data collected from 296 questionnaires. Our results showed that positive actions, including the enhancement of initiatives to protect cultivated land, the improvement of the ecological environment of cultivated land, and the investment in agricultural infrastructure, have been adopted by farmers since the implementation of the CLPF. Furthermore, farmers’ individual characteristics (gender, education level, labor force size, cultivated land area, migration out of traditional farming areas, and average annual household income) impacted significantly and directly on farmers’ behavior. In terms of the cognitive characteristics that had a direct impact on farmers’ behavior, the extent of farmers’ knowledge of the policy was the most important factor. On the premise of comprehensive consideration of the diversity of farmers’ livelihoods, new communication technologies and sufficient funds, we suggested that a long-term and sustainable project should be established at the national level to effectively compensate farmers. |
format |
article |
author |
Haipeng Niu Dongyang Xiao Suxia Zhao |
author_facet |
Haipeng Niu Dongyang Xiao Suxia Zhao |
author_sort |
Haipeng Niu |
title |
Drivers of Farmers’ Behavior toward Compensation Scheme for Cultivated Land Protection in Chengdu Pilot Area, China |
title_short |
Drivers of Farmers’ Behavior toward Compensation Scheme for Cultivated Land Protection in Chengdu Pilot Area, China |
title_full |
Drivers of Farmers’ Behavior toward Compensation Scheme for Cultivated Land Protection in Chengdu Pilot Area, China |
title_fullStr |
Drivers of Farmers’ Behavior toward Compensation Scheme for Cultivated Land Protection in Chengdu Pilot Area, China |
title_full_unstemmed |
Drivers of Farmers’ Behavior toward Compensation Scheme for Cultivated Land Protection in Chengdu Pilot Area, China |
title_sort |
drivers of farmers’ behavior toward compensation scheme for cultivated land protection in chengdu pilot area, china |
publisher |
Taylor & Francis Group |
publishDate |
2021 |
url |
https://doaj.org/article/c069e231d8b74b81b9b16d19feb6caf8 |
work_keys_str_mv |
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