Path selection and efficiency increase mechanism of farmers’ adoption of environmentally friendly technologies: an empirical analysis

DONG Ying1 MU Yueying2

(1.College of Economics & Management, South China Agricultural University)
(2.College of Economics and Management, China Agricultural University)

【Abstract】Based on an analysis of the path selection and efficiency increase mechanism of farmers’ adoption of environmentally friendly technology, this paper constructs a Cov-AHP-MFA integrated technology efficiency evaluation model, and uses the survey data collected from 959 farmer households in the main greenhouse vegetable production areas of Huang-Huai-Hai and Bohai Rim regions to conduct an empirical estimation and a comparative analysis. The main conclusions are as follows. First, farmers with different path selection of doption of environmentally friendly technologies by themselves or service participation face different production frontiers; technology adoption intensity of farmers who participate in services provision has a significant U relationship with their production frontier. They have the potential to deepen the adoption of technology and expand frontier. Farmers who adopt technology by themselves rely on technology experience to mitigate the loss of technical inefficiency. Second, the marketing channels service based on environmentally-friendly technical advantages can significantly improve the TGR, but the purchase of relative technical goods or services reduces the farmers’ TGR. Third, the comprehensive meta-frontier production efficiency of farmers who participate in services provision is 5.79% higher than farmers who adopt technology by themselves, where the technical skill diffusion under learning by doing and the model effect is the main mechanism to improve production efficiency.

【Keywords】 adoption of environmentally friendly technologies; path selection; efficiency increase mechanism; Cov-AHP-MFA Model;

【DOI】

【Funds】 Youth Project of National Natural Science Foundation of China (71803052) General Project of National Natural Science Foundation of China (71773121) Modern Agricultural Industry Technology System (BAIC01-2018) Key Project of National Social Science Fund of China (18ZDA074)

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    Footnote

    [1]. ① It specifically refers to the technology of returning greenhouse vegetable straw to the field. This technology is helpful to greatly reduce the use of pesticides and fertilizers, increase soil organic matter and biological activity, and improve soil water and fertilizer conservation capacity. [^Back]

    [2]. ① Agricultural membrane is an important input material in greenhouse vegetable production, including plastic membrane and greenhouse membrane. However, the replacement of plastic membrane and greenhouse membrane does not follow the production cycle and is not taken as an input factor for production, which mainly reflects the completeness of facilities. Moreover, plastic membrane is the main supporting material for furrow irrigation technology under membrane, which should not be repeated in the production model, thus affecting the results of empirical calculation. Therefore, the input cost per mu is included in the equation to reflect the input density and guarantee level of material capital. [^Back]

    References

    1. Cai, R. Chinese Rural Economy (中国农村经济), (1) (2011).

    2. Chen, F., Zhang, C., Luo, Y. et al. Journal of Agrotechnical Economics (农业技术经济), (5) (2016).

    3. Deng, X., Mu, Y. & Qian, J. On Economic Problems (经济问题), (5) (2011).

    4. Dong, Y. & Mu, Y. Journal of Beijing Institute of Technology (Social Sciences Edition) (北京理工大学学报(社会科学版)), (6) (2016).

    5. Ge, J. & Zhou, S. Journal of Nanjing Agricultural University (Social Sciences Edition) (南京农业大学学报(社会科学版)), (2) (2012).

    6. Guo, L. China Rural Survey (中国农村观察), (5) (2003).

    7. Huang, Z. & Gao, Y. Chinese Rural Economy (中国农村经济), (7) (2012).

    8. Li, X. & Mu, Y. China Population Resources and Environment (中国人口·资源与环境), (5) (2013a).

    9. Li, X. & Mu, Y. Journal of Nanjing Agricultural University (Social Sciences Edition) (南京农业大学学报(社会科学版)), (4) (2013b).

    10. Li, N., Wang, L. & Zhou, W. Management of Agricultural Science and Technology (农业科技管理), (6) (2002).

    11. Liang, Q. & Huang, Z. Economist (经济学家), (12) (2011).

    12. Liu, X., Zhang, Y. & Yao, S. Mathematics in Practice and Theory (数学的实践与认识), (24) (2017).

    13. Luo, J., Guo, H., Jia, F. et al. Journal of Management Case Studies (管理案例研究与评论), (2) (2015).

    14. Lyu, J., Jin, X. & Han, X. Journal of Arid Land Resources and Environment (干旱区资源与环境), (10) (2016).

    15. Pan, J. China Rural Survey (中国农村观察), (6) (2011).

    16. Wang, J. & Huo, X. China Rural Survey (中国农村观察), (3) (2013).

    17. Wang, S., Jin, Y. & Han, H. Journal of Agrotechnical Economics (农业技术经济), (8) (2017).

    18. Wu, B., Liu, J., Xu, X. et al. Journal of Agrotechnical Economics (农业技术经济), (8) (2016).

    19. Xie, Z. The Journal of Quantitative & Technical Economics (数量经济技术经济研究), (8) (2015).

    20. Xu, Z. & Lyu, K. Chinese Rural Economy (中国农村经济), (3) (2018).

    21. Yang, L., Zhang, Y. & Xu, H. Transactions of the Chinese Society of Agricultural Engineering (农业工程学报), (6) (2003).

    22. Ito Junichi, Bao, Z. & Su, Q. China Rural Survey (中国农村观察), (5) (2011).

    23. Zhang, H., Luo, J. & Hao, Y. Chinese Rural Economy (中国农村经济), (1) (2017).

    24. Zhang, S., Dong, J. & Sun, Z. Journal of Agrotechnical Economics (农业技术经济), (11) (2016).

    25. Zhou, Y. & Hu, L. Chinese Rural Economy (中国农村经济), (6) (2016).

    26. Aldana U, Useche P., 2011, “Sequential Adoption of Package Technologies: The Dynamics of Stacked Trait Corn Adoption”, American Journal of Agricultural Economics, 93 (1): 130–143.

    27. Battese G E, Rao D S P, O’Donnell C J., 2004, “A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies”, Journal of Productivity Analysis, 21 (1): 91–103.

    28. Cai Q, Zhu Y, Chen Q, 2015, “Can social networks increase households’ contribution to public-good provision in rural China?: The case of small hydraulic facilities construction”, China Agricultural Economic Review, 8 (1): 178–184.

    29. Deng H, Huang J, Xu Z, et al., 2010, “Policy support and emerging farmer professional cooperatives in rural China”, China Economic Review, 21 (4): 495–507.

    30. Huang C J, Huang T H, Liu N H., 2014, “A new approach to estimating the metafrontier production function based on a stochastic frontier framework”, Journal of Productivity Analysis, 42 (3): 241–254.

    31. Ma W, Abdulai A, Goetz R., 2017, “Agricultural Cooperatives and Investment in Organic Soil Amendments and Chemical Fertilizer in China”, American Journal of Agricultural Economics, 100 (2).

    32. Naziri D, Aubert M, Codron J M, et al., 2014, “Estimating the Impact of Small-Scale Farmer Collective Action on Food Safety: The Case of Vegetables in Vietnam”, Journal of Development Studies, 50 (5): 715–730.

    33. Noltze M, Schwarze S, Qaim M., 2013, “Impacts of natural resource management technologies on agricultural yield and household income: The system of rice intensification in Timor Leste”, Ecological Economics, 85 (2): 59–68.

    34. O’Donnell C J, Rao D S P, Battese G E., 2008, “Metafrontier frameworks for the study of firm-level efficiencies and technology ratios”, Empirical Economics, 34 (2):231–255.

    35. Yang H., 2013, “Farmer cooperatives as intermediaries for agricultural and rural development in China”, Fatigue & Fracture of Engineering Materials & Structures, 37 (3): 231–231.

This Article

ISSN:1006-4583

CN: 11-3586/F

Vol , No. 02, Pages 34-48

March 2019

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Article Outline

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Abstract

  • 1 Introduction
  • 2 Mechanism analysis and research framework
  • 3 Data and empirical model construction
  • 4 Empirical results and comparative analysis
  • 5 Conclusions and policy recommendations
  • Footnote

    References