Energy consumption of a hotel can be a hot topic in
smart city; it is difficult to evaluate the contribution of impact factors
to energy consumption of a hotel. Therefore, grasping the key impact
factors has great effect on the energy saving management of a hotel.
Based on the SPIRTPAT model, we establish the identity with the
impact factors of occupancy rate, unit area of revenue, temperature
factor, unit revenue of energy consumption. In this paper, we use the
LMDI (Logarithmic Mean Divisia Index) to decompose the impact
factors of energy consumption of hotel from Jan. to Dec. in 2001. The
results indicate that the occupancy rate and unit area of revenue are the
main factors that can increase unit area of energy consumption, and the
unit revenue of energy consumption is the main factor to restrain the
growth of unit area of energy consumption. When the energy
consumption of hotel can appear abnormal, the hotel manager can
carry out energy saving management and control according to the
contribution value of impact factors.
 World Bank. Growth and CO2 Emissions: How Does India Compare to
Other Countries? (R). India: Relationship between Growth and CO2
 Yuhui Ou, Yifang Liu, Jiangyi Man, The decomposition of energy
consumption in our country based on LMDI method (J). Economic
management, 2007, 29(7): 91-95.
 Fumin Liao, Research on industrial energy consumption decomposition
based on LMDI method (J). Search, 2008, (8): 23-25.
 Liaoqing Wei, Dequn Zhou. Empirical analysis of the influence factors of
energy consumption in Jiangsu Province based on LMDI method (J).
Price monthly, 2009, (2): 51-54.
 Junsong Tu, Canchi He. Energy consumption, economic growth and the
change of CO2 emissions in China-Analysis Based on LMDI method (J).
Resources and environment in the Yangtze River Basin, 2010, 19(1):
 Yuan Tu, Benyong Wei, Xiuqi Fang etc. Implicit carbon decomposition
of China's international trade based on LMDI method (J). Population,
resources and environment in China, 2011, 21(2): 141-146.
 Lu Jiang, Research on virtual water trade of China based on input output
analysis (D). South China University of Technology, 2012.
 Ying Han, Ping Ma, Lu Liu. A new method of impact factors of energy
consumption intensity (J). Quantitative economic technology and
economic research, 2010(4): 137-147.
 F. Q. Zhang, B. W. Ang, Methodological issues in cross-country/ region
decomposition of energy and environment indicators. Energy Economics
2001, 23(2), 179-190.
 B. W. Ang, Decomposition analysis for policymaking in energy: which is
the preferred method? Energy Policy 2004, 32(9), 1131-1139.
 B. W. Ang, Na Liu, Handling zero values in the logarithmic mean Divisia
index decomposition approach (J). Energy Policy, 2007, 35(1), 238-246.
 T. Dietz, E. A. Rosa, Rethinking the environmental impacts of
population, affluence and technology (J). Human Ecology Review,