Exploring Determinants of and Barriers to Climate-Smart Agricultural Technologies Adoption in Chinese Cooperatives: A Hybrid Study

The loss of agricultural production due to climate change and natural disasters has attracted widespread attention. Climate-smart agricultural technologies (CSATs) are attracting attention as a solution to address climate change while achieving sustainable agricultural development. However, in the Chinese context, research on cooperatives’ intention to adopt such technologies is relatively limited. This study investigated the factors influencing the behavioral intentions of Chinese farmers’ cooperatives to adopt CSATs using a behavioral reasoning theory (BRT) framework. A structured questionnaire was administered to 308 participants using purposive sampling techniques. For data analysis, an artificial neural network (ANN) and fuzzy set qualitative comparative analysis (fsQCA) complemented the disjointed two-stage partial least squares structural equation modeling (PLS-SEM) approach to ensure the robustness of the results and provide important practical insights. The results suggest that values (perceived value of government environmental concern, value of openness to change) shape the determinants of and barriers to CSAT adoption by cooperatives, but do not have a direct impact on behavioral intentions. The “determinants” all positively influenced adoption behavioral intentions, with “agricultural extension and advisory service” having the greatest impact on behavioral intentions, followed by “opinion leaders’ recommendation” and “policy support”. Among the “barriers”, only “perceived risk” and behavioral intention were negatively correlated. Behavioral intention to adopt CSATs by cooperatives has a positive effect on willingness to pay, which motivated cooperatives to pay more to acquire the technology. Based on the findings, this study provides theoretical insights for researchers and policy implications for governments, agricultural organizations, policymakers, and agri-technology companies.