Identifying the factors influencing farmers’adoption of low-carbon technologies(FA)and understanding their impacts are essential for shaping effective agricultural policies amied at emission reduction and carbon sequ...Identifying the factors influencing farmers’adoption of low-carbon technologies(FA)and understanding their impacts are essential for shaping effective agricultural policies amied at emission reduction and carbon sequestration in China.This study employs a meta-analysis of 122 empirical studies,delves into 23 driving factors affecting FA and addresses the inconsistencies present in the existing literature.We systematically examine the effect size,source of heterogeneity,and time-accumulation effect of the driving factors on FA.We find that significant heterogeneity in the factors influencing FA,except for farming experience,sources of heterogeneity from the survey zone,methodology model,technological attributes,report source,financial support,and the sampling year.Additionally,age,farming experience,and adoption cost negatively correlate with FA.In contrast,educational level,health status,technical training,economic and welfare cognition,land contract,soil quality,terrain,information accessibility,demonstration,government promotion,government regulation,government support,agricultural cooperatives member,peer effect,and agricultural income ratio demonstrate a positive correlation.Especially,demonstration and age show a particularly strong correlation.Finally,the effect of demonstration,age,economic and welfare cognition,farming experience,land contract,soil quality,information accessibility,government promotion,and support,as well as agricultural cooperative membership and peer effects on FA,are generally stable but exhibit varying degrees of attenuation over time.The effect of village cadre,family income,farm scale,gender,health status,technical training,and off-farm work on FA show notable temporal shifts and maintain a weak correlation with FA.This study contributes to shaping China’s current low-carbon agriculture policies across various regions.It encourages policymakers to comprehensively consider the stability of key factors,other potential factors,technological attributes,rural socio-economic context,and their interrelations.展开更多
基金supported by the National Social Science Fund of China(19BGL152)the Sichuan Technology Planning Project,China(2022JDTD0022)the Provincial College Student Innovation and Entrepreneurship Training Program of Sichuan Province,China(S202310626018).
文摘Identifying the factors influencing farmers’adoption of low-carbon technologies(FA)and understanding their impacts are essential for shaping effective agricultural policies amied at emission reduction and carbon sequestration in China.This study employs a meta-analysis of 122 empirical studies,delves into 23 driving factors affecting FA and addresses the inconsistencies present in the existing literature.We systematically examine the effect size,source of heterogeneity,and time-accumulation effect of the driving factors on FA.We find that significant heterogeneity in the factors influencing FA,except for farming experience,sources of heterogeneity from the survey zone,methodology model,technological attributes,report source,financial support,and the sampling year.Additionally,age,farming experience,and adoption cost negatively correlate with FA.In contrast,educational level,health status,technical training,economic and welfare cognition,land contract,soil quality,terrain,information accessibility,demonstration,government promotion,government regulation,government support,agricultural cooperatives member,peer effect,and agricultural income ratio demonstrate a positive correlation.Especially,demonstration and age show a particularly strong correlation.Finally,the effect of demonstration,age,economic and welfare cognition,farming experience,land contract,soil quality,information accessibility,government promotion,and support,as well as agricultural cooperative membership and peer effects on FA,are generally stable but exhibit varying degrees of attenuation over time.The effect of village cadre,family income,farm scale,gender,health status,technical training,and off-farm work on FA show notable temporal shifts and maintain a weak correlation with FA.This study contributes to shaping China’s current low-carbon agriculture policies across various regions.It encourages policymakers to comprehensively consider the stability of key factors,other potential factors,technological attributes,rural socio-economic context,and their interrelations.
