TY - JOUR
T1 - Factors affecting farmers' risk perceptions regarding biomass supply: A case study of the national bioenergy industry in northeast China
AU - Wang, Lingling
AU - Watanabe, Tsunemi
N1 - Publisher Copyright:
© 2016 Elsevier Ltd
PY - 2016/12/15
Y1 - 2016/12/15
N2 - To solve the insufficiency of biomass supply in the biomass power industry of China, this study developed a conceptual model of farmers' risk perceptions on straw supply (FROSS) activities by integrating influencing factors, namely, socio-demographic characteristics, policy guidance factors, economic factors, and trust factors, into the model (Wang, 2015). The FROSS model was empirically tested in a survey on the risk perceptions of 275 farmers living around a biomass power plant in northeast China. The results of multiple regression analyses on the influencing factors indicate that the proposed model accounts for 67.4% of the variance in farmers' risk perceptions. The factors that dominantly influence farmers' risk perceptions were then identified, after which factor analysis that was conceptualized along personal- and environment-related risk perceptions was carried out. The influencing factors predict more than 80% of personal-related risk perceptions but only 16.2% of environment-related risk perceptions. Focusing on the initial stages of analyzing the factors that affect farmers' risk perceptions regarding straw supply activities improves our understanding of straw demand risks in China's biomass power industry. The implications of the results are discussed.
AB - To solve the insufficiency of biomass supply in the biomass power industry of China, this study developed a conceptual model of farmers' risk perceptions on straw supply (FROSS) activities by integrating influencing factors, namely, socio-demographic characteristics, policy guidance factors, economic factors, and trust factors, into the model (Wang, 2015). The FROSS model was empirically tested in a survey on the risk perceptions of 275 farmers living around a biomass power plant in northeast China. The results of multiple regression analyses on the influencing factors indicate that the proposed model accounts for 67.4% of the variance in farmers' risk perceptions. The factors that dominantly influence farmers' risk perceptions were then identified, after which factor analysis that was conceptualized along personal- and environment-related risk perceptions was carried out. The influencing factors predict more than 80% of personal-related risk perceptions but only 16.2% of environment-related risk perceptions. Focusing on the initial stages of analyzing the factors that affect farmers' risk perceptions regarding straw supply activities improves our understanding of straw demand risks in China's biomass power industry. The implications of the results are discussed.
UR - http://www.scopus.com/inward/record.url?scp=84995544835&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2016.08.065
DO - 10.1016/j.jclepro.2016.08.065
M3 - Article
AN - SCOPUS:84995544835
SN - 0959-6526
VL - 139
SP - 517
EP - 526
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
ER -