@article{34617,
  keywords = {building energy use, EM-STIRPAT model, SEM model, Entropy weight method},
  author = {Changqing Lin and Yafeng Gao and Jinxin Huang and Dachuan Shi and Wei Feng and Qiaoyue Liu and Xiuyuan Du},
  title = {A novel numerical model for investigating macro factors influencing building energy consumption intensity},
  abstract = {<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>},
  year = {2020},
  journal = {Sustainable Production and Consumption},
  volume = {24},
  pages = {308 - 323},
  month = {01/2020},
  issn = {23525509},
  doi = {10.1016/j.spc.2020.07.014},
  language = {eng},
}