Open AccessFarmers’ Willingness to Adopt Clean Energy—Survey in Northeastern China
Author(s) -
Xuesong Li,
Yaowu Dong
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/510/2/022044
Subject(s) - china , government (linguistics) , agricultural economics , socioeconomic status , willingness to pay , business , maturity (psychological) , population , agricultural science , socioeconomics , standard of living , economic growth , marketing , economics , geography , psychology , sociology , demography , philosophy , linguistics , developmental psychology , environmental science , archaeology , microeconomics , market economy
Among 1.38 billion people in China, approximately forty-two percent of the population reside in rural areas. Farmers’ willingness to adopt clean energy is crucial to policy makers, planners and business developers as China will begin its Paris Agreement implementation in 2020. For Chinese government, switching energy sources will be a monumental task. To understand farmers’ opinions, 527 farmers were surveyed in Jilin Province of Northeast China, and nearly 83% of them burn coal and dried stalk/straw to heat homes and cook food. Their willingness to adopt clean energy is assessed in four different areas: attitude towards behavior, subjective norms, perceived behavioral control, and socioeconomic characteristics. A binary logistic regression model is establish with one dependent variable (willingness to adopt clean energy) and twelve independent variables: 1. Quality of life, 2. Monthly expenses, 3. Environment benefits, 4. Government commitments, 5. Appraisal from neighbors and friends, 6. Local clean energy market maturity, 7. Switching costs, 8. Savings in labors, 9. Technical guidance and periodical maintenance instructions, 10. Age, 11. Education level, and 12. Household annual income. Our results indicate that nine variables (X 1 – X 5 , X 7 – X 9 and X 12 ) have apparent impacts on the farmers’ willingness to adopt clean energies. The impacts from X 1 , X 3 – X 5 , X 8 – X 9 and X 12 are positive, while that from X 2 and X 7 are negative. Implications of the results are discussed, along with policy suggestions.