Configuration analysis of factors influencing carbon emissions from provincial agriculture in China under the TOE framework:combining NCA and fsQCA methods*

Developing low-carbon agriculture is an inevitable requirement for achieving sustainable agricultural development, and assessing the linkage effect of factors influencing agricultural carbon emissions is a necessary approach for developing low-carbon agriculture. Herein, on the basis of the “Technology-Organization-Environment” framework, we constructed a theoretical framework of factors influencing carbon emissions from Chinese provincial agriculture, with the aim of clarifying the complex causal relationships among these factors. Having calculated the total agricultural carbon emissions of Chinese provinces (autonomous regions and municipalities, excluding Hong Kong, Macao, Taiwan and Xizang, the same below) in 2017 using an input–output method, and subsequently calculating the intensity of agricultural carbon emissions in these provinces, we analyzed the necessity of single factors for agricultural low-carbon emissions or non-low-carbon emissions based on Necessary Condition Analysis, and analyzed the adequacy of multi-factors for agricultural low-carbon emissions or non-low-carbon emissions by performing fuzzy set Qualitative Comparative Analysis, which enabled us to assess the complex configuration relationships between influencing factors and agricultural carbon emissions. By combining Necessary Condition Analysis with fuzzy set Qualitative Comparative Analysis, we accordingly established that agricultural mechanization, agricultural financial support, agricultural technician, environmental regulation, and rationalization of the agricultural industrial structure are non-essential conditions for agricultural low-carbon emissions or non-low-carbon emissions. On the basis of a fuzzy set of Qualitative Comparative Analysis, we identified three influencing pathways for generating agricultural low-carbon emissions, which are summarized as machinery leading, machinery and structure collaborating, and structure and environment collaborating types, as determined by summing up core factors. The solution coverage of the three influencing pathways was found to be 0.611, which indicates that more than half of the provinces with agricultural low-carbon emissions can be explained. In addition, we identified two influencing pathways contributing to agricultural non-low-carbon emissions, which are summarized as machinery and structure absenting, and machinery and environment absenting types, as determined by summing up core factors. The solution coverage of the two influencing pathways was 0.427, which indicates that almost half of the provinces with agricultural non-low-carbon emissions can be explained. Finally, on the basis of a comprehensive assessment of the pathways influencing agricultural low-carbon emissions and non-low-carbon emissions, we established that agricultural mechanization, rationalization of the agricultural industrial structure, and environmental regulations are key factors influencing agricultural carbon emissions. The three influencing pathways for generating agricultural low-carbon emissions include at least one of the three key influencing factors, and the two influencing pathways contributing to non-low-carbon emissions lack two of the three key influencing factors. Consequently, our findings indicate that the development of low-carbon agriculture can only be achieved by ensuring the mutual promotion of technology, organization, and environment. These findings provide a new perspective for examining carbon emissions, and expand the scope of the “Technology-Organization-Environment” framework. Moreover, our findings highlight the diverse approaches that can be adopted to develop low-carbon agriculture in the Chinese provinces.