Promoting rural households' energy use for cooking: Using Internet

互联网 业务 能量(信号处理) 环境经济学 营销 农业经济学 经济增长 计算机科学 经济 万维网 统计 数学
作者
He Jia,Qing Chen,Shili Guo,Wenfeng Zhou,Xin Deng,Dingde Xu
出处
期刊:Technological Forecasting and Social Change [Elsevier]
卷期号:184: 121971-121971 被引量:17
标识
DOI:10.1016/j.techfore.2022.121971
摘要

Clean energy is expected to both reduce carbon emissions and enhance well-being, and ‘Internet + energy consumption’ has become a key to facilitating the transformation of energy use for cooking among Chinese farmers. However, few studies have analyzed the relationship between the two based on large-scale micro-data systems. Based on data from the China Labor Force Dynamics Survey (CLDS) for 2012, 2014, and 2016, a conditional mixed estimation method (CMP) was used to empirically analyze the impact of Internet use on farmers' clean energy use for cooking, and a mediation effect method was used to further analyze its mechanism of action. The results found that (1) between 2012 and 2016, the energy mix of farmers' cooking was gradually optimized and the proportion of clean energy use increased significantly. (2) Internet use can significantly promote the use of clean energy for cooking by expanding social networks, affecting the use of clean energy for others in social networks and improving the stability of non-farm employment. (3) After considering the health level of farmers and regional heterogeneity, the promotion effect still exists, but farmers with higher health levels and located in the eastern region can better use the Internet to achieve household clean energy conversion. This study is helpful to understand the changes of farmers' cooking energy decisions in the Internet era. • The energy structure of rural household cooking is gradually turning clean. • The conditional mixed estimation (CMP) was used to deal with endogeneity. • Internet is information transmission carrier, communication media and technological progress. • The impact of the Internet on energy decision-making cannot be ignored. • This impact is related to social networks and non-farm employment.
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