4.2 Article

Spatial dependence of family farms' adoption behavior of green control techniques in China

Journal

AGROECOLOGY AND SUSTAINABLE FOOD SYSTEMS
Volume 45, Issue 5, Pages 767-789

Publisher

TAYLOR & FRANCIS INC
DOI: 10.1080/21683565.2020.1841707

Keywords

Family farm; Green control techniques; Spatial spillover effect; Bayesian spatial Durbin probit model

Funding

  1. National Natural Science Foundation of China [71803096]
  2. Humanity and Social Science of Ministry of Education Foundation of China [18YJA790024]
  3. Shandong Province Natural Science Foundation of China [ZR2018MG009]

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The study found that the adoption behavior of green control techniques among neighboring family farmers is spatially correlated, with significant positive effects on the GCT adoption behaviors of family farms, mainly influenced by the direct effects of characteristic variables.
Based on field survey data from 443 family farms in Shandong and Henan Provinces, the green control techniques(GCT) adoption behavior of family farms was measured in terms of adoption or non-adoption. Based on the global Moran's I test, the Bayesian spatial Durbin probit model(BSDPM) was constructed, the appropriate spatial weight matrix was set, the optimal model for parameter estimation was selected, and the direct and spatial spillover effects of family farm characteristics on GCTs adoption behavior of family farms were decomposed by means of the partial differential method. The results show that the GCTs adoption behaviors of adjacent family farmers are spatially correlated and strongest when they are within 2.0 km of each other. Farm leaders' educational level, degree of risk preference, financial status, number of laborers, understanding of GCTs and of the dangers of chemical pesticides, knowledge of other GCT adopters, frequency of communication with neighbors, participation in technical training and the strength of media publicity have significantly positive effects on the GCT adoption behaviors of family farms, which are mainly influenced by the direct effects of characteristic variables. However, the spatial spillover effects of neighboring family farmers' participation in technical training, number of laborers, and financial status cannot be ignored. This result provides not only theoretical support for the demonstration and extension of the effectiveness of GCTs but also a reference for the selection of family farms as model households.

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