Room occupancy rate is a key indicator of star-rated hotel management quality. This paper takes Cobb-Douglas production function as the theoretical framework. Spatial Moran index of autocorrelation, Spatial Lag Model(...Room occupancy rate is a key indicator of star-rated hotel management quality. This paper takes Cobb-Douglas production function as the theoretical framework. Spatial Moran index of autocorrelation, Spatial Lag Model(SLM) and Spatial Error Model(SEM) are used to analyze the star-rated hotels labor productivity of 31 provincial regions in China's Mainland based on the star-rated hotels statistical data of year 2016. The spatial correlation and spatial difference of the star-rated hotels labor productivity is discussed. This paper studies the impact of three factors on spatial characteristics of star-rated hotels labor productivity in China's Mainland. The econometric estimation results show that:(1) Star-rated hotels labor productivity present significant spatial dependence and spatial difference in China's Mainland.(2) The estimation results of Ordinary least Squares(OLS) are reliable.(3) The reliability of the results obtained by the Spatial Error Model(SEM) analysis is the highest, and has a stronger explanatory power to the spatial relationship of star-rated hotels labor productivity in China's Mainland. The average room occupancy rate has more influence on the labor productivity of the provincial star-rated hotels than the impact of capital and labor.展开更多
In this paper, 5 high-rise hotels in Xi'an were selected for research, their energy consumption data from 2015 to 2016 were collected and analyzed, their comprehensive energy consumption per unit area was compared...In this paper, 5 high-rise hotels in Xi'an were selected for research, their energy consumption data from 2015 to 2016 were collected and analyzed, their comprehensive energy consumption per unit area was compared by using the standard coal coefficient, and their energy use characteristics and influencing factors were obtained. The test analyzed various parameters of the indoor environment and evaluated the indoor environmental quality according to the specifications and standards. Starting from the perspective of energy use systems, this paper found energy consumption priorities and problems of these hotels, and proposed feasible energy conservation measures, in a view to providing a reference for energy conservation design of high-rise hotels in Xi'an.展开更多
Recent years have witnessed a rapid development of star-rated hotels in China, especially high- end star-rated hotels. Consequently, there are now approximately12 000 hotels in China. One bottleneck within the industr...Recent years have witnessed a rapid development of star-rated hotels in China, especially high- end star-rated hotels. Consequently, there are now approximately12 000 hotels in China. One bottleneck within the industry is its huge energy consumption and carbon emissions, but the development of a comprehensive energy consumption assessment has lagged. Here, a comprehensive energy consumption and carbon emission model suitable for hospitality is established, using comprehensive data collected for hotels over six years and with reference to general international methods, decomposition analysis methods as recommended by the IPCC, and related standards in China. Our study shows that the maximum comparable unit energy consumption per building area among four- and five-star hotels is 73.26 kg ce m-2 y-l. Through energy-saving reconstruction, the comprehensive energy consumption of five-star hotels has declined by 4.1% in six years and is smaller than the advanced comparable value of 55 kg ce m2 y4. The comparable unit energy consumption per area building of most two- and three-star hotels （53 kg ce m2 y-l） is higher than the reasonable value. There are large numbers of hotels of this type in China and the potential energy savings are huge. Analyzing factors of energy consumption, we found that indirect carbon emissions from electricity usage are the most significant. From an energy consumption structural perspective, Heating, Ventilation and Air Conditioning （HVAC） System accounts for most energy consumption. This research provides a foundation for further examination of energy-savings, emission reduction plans and Monitoring Reporting Verification （MRV） in the hospitality sector.展开更多
高维数据下的均值检验是统计学检验的重要组成部分.在高维情形下,样本协方差矩阵往往是奇异矩阵,传统的均值检验方法因此失效.为解决该问题,对高维数据进行分段,使分得的每一段的维数均小于样本容量,继而运用Hotelling T 2检验依次对每...高维数据下的均值检验是统计学检验的重要组成部分.在高维情形下,样本协方差矩阵往往是奇异矩阵,传统的均值检验方法因此失效.为解决该问题,对高维数据进行分段,使分得的每一段的维数均小于样本容量,继而运用Hotelling T 2检验依次对每一段进行检验,同时给出一种控制犯第一类错误的概率的新方法,使原假设下的检验水平稳定在事先给定的显著性水平左右.经模拟显示,该逐段检验方法比已有方法能更好地控制犯第一类错误的概率.展开更多
基金Sponsored by Humanity and Social Science Youth Foundation of Ministry of Education of China(17YJCZH197)
文摘Room occupancy rate is a key indicator of star-rated hotel management quality. This paper takes Cobb-Douglas production function as the theoretical framework. Spatial Moran index of autocorrelation, Spatial Lag Model(SLM) and Spatial Error Model(SEM) are used to analyze the star-rated hotels labor productivity of 31 provincial regions in China's Mainland based on the star-rated hotels statistical data of year 2016. The spatial correlation and spatial difference of the star-rated hotels labor productivity is discussed. This paper studies the impact of three factors on spatial characteristics of star-rated hotels labor productivity in China's Mainland. The econometric estimation results show that:(1) Star-rated hotels labor productivity present significant spatial dependence and spatial difference in China's Mainland.(2) The estimation results of Ordinary least Squares(OLS) are reliable.(3) The reliability of the results obtained by the Spatial Error Model(SEM) analysis is the highest, and has a stronger explanatory power to the spatial relationship of star-rated hotels labor productivity in China's Mainland. The average room occupancy rate has more influence on the labor productivity of the provincial star-rated hotels than the impact of capital and labor.
文摘In this paper, 5 high-rise hotels in Xi'an were selected for research, their energy consumption data from 2015 to 2016 were collected and analyzed, their comprehensive energy consumption per unit area was compared by using the standard coal coefficient, and their energy use characteristics and influencing factors were obtained. The test analyzed various parameters of the indoor environment and evaluated the indoor environmental quality according to the specifications and standards. Starting from the perspective of energy use systems, this paper found energy consumption priorities and problems of these hotels, and proposed feasible energy conservation measures, in a view to providing a reference for energy conservation design of high-rise hotels in Xi'an.
基金Key Discipline Project of Shanghai Municipal Education Commission(No.J50402)Key Research of Shanghai Institute of Tourism(No.RS2015-B3)
文摘Recent years have witnessed a rapid development of star-rated hotels in China, especially high- end star-rated hotels. Consequently, there are now approximately12 000 hotels in China. One bottleneck within the industry is its huge energy consumption and carbon emissions, but the development of a comprehensive energy consumption assessment has lagged. Here, a comprehensive energy consumption and carbon emission model suitable for hospitality is established, using comprehensive data collected for hotels over six years and with reference to general international methods, decomposition analysis methods as recommended by the IPCC, and related standards in China. Our study shows that the maximum comparable unit energy consumption per building area among four- and five-star hotels is 73.26 kg ce m-2 y-l. Through energy-saving reconstruction, the comprehensive energy consumption of five-star hotels has declined by 4.1% in six years and is smaller than the advanced comparable value of 55 kg ce m2 y4. The comparable unit energy consumption per area building of most two- and three-star hotels （53 kg ce m2 y-l） is higher than the reasonable value. There are large numbers of hotels of this type in China and the potential energy savings are huge. Analyzing factors of energy consumption, we found that indirect carbon emissions from electricity usage are the most significant. From an energy consumption structural perspective, Heating, Ventilation and Air Conditioning （HVAC） System accounts for most energy consumption. This research provides a foundation for further examination of energy-savings, emission reduction plans and Monitoring Reporting Verification （MRV） in the hospitality sector.
文摘高维数据下的均值检验是统计学检验的重要组成部分.在高维情形下,样本协方差矩阵往往是奇异矩阵,传统的均值检验方法因此失效.为解决该问题,对高维数据进行分段,使分得的每一段的维数均小于样本容量,继而运用Hotelling T 2检验依次对每一段进行检验,同时给出一种控制犯第一类错误的概率的新方法,使原假设下的检验水平稳定在事先给定的显著性水平左右.经模拟显示,该逐段检验方法比已有方法能更好地控制犯第一类错误的概率.
