What motivates farmers to participate in sustainable agriculture? Evidence and policy implications
Authors: Yan Ma ab; Liding Chen ab; Xinfeng Zhao ab; Haifeng Zheng ab;Yihe L

a
| Affiliations: | a State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China |
| b Graduate School of Chinese Academy of Sciences, Beijing, China |
DOI: 10.1080/13504500903319047
Publication Frequency: 6 issues per year
Published in:
International Journal of Sustainable Development & World Ecology, Volume
16, Issue
6 December 2009 , pages 374 - 380
Abstract Sustained growth in agricultural productivity has become an ideal model and a political goal of agricultural development in China. Local participation is essential for the implementation of sustainable agriculture strategy. We conducted a case study in Hailun County, an important grain production base in China, to find ways to motivate farmers to participate in sustainable agriculture. We obtained data from semi-structured interviews of 98 households using participatory rural appraisal methods. Logistic regression models were used to explore factors that underlie farmers' attitudes towards agricultural production and their environmental awareness. Results indicated that low agricultural economic efficiency could result in less enthusiasm for agriculture among local farmers. This is a potential risk for China's food security and sustainable agricultural development. The backward development of the rural economy limited improvement of farmers' environmental awareness. Moreover, poor rural labour quality implied a lack of local participation in sustainable agriculture. Suggestions for sustainable agricultural development include establishment of a reasonable market and agricultural subsidy mechanisms, basic and vocational education for young adults, effective agricultural instruction and environmental education agencies and two-way communication mechanisms.
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Keywords: local people; attitudes; agricultural production; environmental awareness; logistic regression; China
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