%0 Journal Article
%K Building energy use
%K EM-STIRPAT model
%K SEM model
%K Entropy weight method
%A Changqing Lin
%A Yafeng Gao
%A Jinxin Huang
%A Dachuan Shi
%A Wei Feng
%A Qiaoyue Liu
%A Xiuyuan Du
%B Sustainable Production and Consumption
%D 2020
%G eng
%P 308 - 323
%R 10.1016/j.spc.2020.07.014
%T A novel numerical model for investigating macro factors influencing building energy consumption intensity
%V 24
%8 01/2020
%! Sustainable Production and Consumption
%X <p>Building energy use accounts for 40% of the primary energy consumed worldwide. Therefore, it is essential to explore the key influencing factors and the associated interactions among these factors in order to achieve energy-saving goals. In practical scenarios, the sample size is always limited; thus, conventional models are unable to analyze the interactions among factors, or their results are unstable. To resolve this issue, this paper proposes a method that combines the improved stochastic impacts by regression on population, affluence, and technology (EM-STIRPAT) model and a structural equation modeling (SEM) model using the entropy weight method. The results obtained by analyzing the building energy use in Beijing, which was considered as a case study, indicate that economic level, technical level, industry structure, and education structure have a significant positive impact on building energy consumption intensity (BECI). Based on this analysis, it was found that 94% of the technical level and 39% of the economic level indirectly affect BECI through the energy structure. In addition, through a scenario analysis, it was found that future changes in the age structure of the population will have a smaller impact on BECI than changes in the education structure. Finally, based on the results of this study, policymaking recommendations to reduce building energy consumption are also presented.</p>