基于DEA-Malmquist模型的中国星级饭店经营效率时空演化研究

doi:10.13249/j.cnki.sgs.2017.03.011

摘要/Abstract

摘要：

构建DEA-Malmquist模型,实证分析中国31个省市区星级饭店2004~2014年技术效率的时空演化特征,通过TOBIT模型分析了技术效率的影响因素。结果显示：星级饭店的技术效率逐年提升,东部地区显著高于中西部地区;星级饭店全要素生产率整体有所提升,东部地区高于中西部地区;经济水平、旅游人次、产业结构和区域开放度等因素对星级饭店技术效率提升具有显著正向影响,而旅游收入、人口城镇化、基础设施和信息化则具有负向影响。针对新常态下星级饭店的效率问题,提出要提升饭店发展质量,切实提高技术效率,重视高新技术应用,持续优化饭店发展环境。

关键词: 星级饭店, 技术效率, DEA-Malmquist模型, 时空演化, 影响因素

Abstract:

With the appearing of new industry formats, the star-rated hotels have become an important driving force for the tourism industry development, and there is important practical significance to explore the management efficiency of star-rated hotels for the upgrading and innovation of tourism industry in China. Using panel data of the star-rated hotels of 31 provinces in China in 2004-2014, the article empirically analyzed spatial and temporal evolution characteristics of comprehensive technical efficiency and Malmquist indexes on the star-rated hotels by constructing the DEA-Malmquist model, and analyzed the influencing factors of their technical efficiency through building panel TOBIT regression model. The results showed that: Comprehensive technical efficiency of star-rated hotels increased year by year, but the efficiency value was still relatively low, and the low pure technical efficiency was the main constraints because of the scale efficiency changed little; Technology efficiency in 2013 and 2014 had significantly fallen compared to previous years, but the descent degree of 2014 had become smaller; Comprehensive technical efficiency in Eastern China was significantly higher than that of the Central and Western China, which was mainly because of its higher pure technical efficiency. The Malmquist indexes of star-rated hotels was overall enhancing in 2004-2014, and the technical progress change index was the main driving force to the ascension, though there were also violent annual fluctuations in some period; The Malmquist indexes in 2004-2010 was in a steady growth stage, and that of 2010-2014 was in a volatile fluctuation stage, especially the sharp decline in 2012-2013; Malmquist indexes in Eastern China was higher than that of the Central and Western China, which was mainly because of its significant advantages in technical progress. The technical efficiency of star-rated hotels was affected by many factors in China. The effects of the economic development level, the tourist number, the industry structure and the regional opening degree on the efficiency were significantly positive, while the impacts of the tourism income, the population urbanization, the infrastructure level and the informatization level were significantly negative. Therefore, in order to enhance the technical efficiency level of star-rated hotels, it needs to improve the tourism development quality, and adjust the industrial structure, and pay attention to the soft environment optimization for regional development, and deal with the challenges of informationization and other factors. To the development problems of the technical efficiency of star-rated hotels under the “New Normal Economy”, it needs to focus on improving the hotels’ development quality, effectively improve hotels’ operational efficiency, pay more attention to the advanced technology application, continuously optimize hotels’ development environments and so on.

Key words: star-rated hotels, technical efficiency, DEA-Malmquist model, spatial and temponal evolution, influencing factors

中图分类号:

F590.6

张琰飞. 基于DEA-Malmquist模型的中国星级饭店经营效率时空演化研究[J]. 地理科学, 2017, 37(3): 406-415.

Yanfei Zhang. Spatial and Temporal Evolution of Star-rated Hotels’ Efficiency in China Based on DEA-Malmquist Model[J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(3): 406-415.

图/表 9

表1

图1

图2

图3

表2

图4

图5

表3

表4

星级饭店技术效率TOBIT回归分析结果"

自变量	回归系数	标准误	$z$	$P > z$	95%下的系数置信区间
PGDP	4.22e-06	8.95e-07	4.71	0.000	2.46e-06	5.97e-06
NDT	2.06e-06	1.14e-06	1.8	0.072	-1.81e-07	4.29e-06
DTE	-0.0000519	0.0000139	-3.74	0.000	-0.0000791	-0.0000247
RI	0.0190399	0.0035538	5.36	0.000	0.0120746	0.0260051
UI	-0.0035399	0.0020840	-1.7	0.089	-0.0076246	0.0005447
HWD	-0.0003831	0.0001557	-2.46	0.014	-0.0006882	-0.000078
PTV	-0.0000195	0.0000104	-1.88	0.060	-0.0000398	8.54e-07
DIE	2.21e-06	7.43e-07	2.97	0.003	7.50e-07	3.66e-06
常数项	-0.7759641	0.2717551	-2.86	0.004	-1.308594	-0.2433339
整体方差	0.1116094	0.0168186	6.64	0.000	0.0786456	0.1445731
面板水平方差	0.0987128	0.0040085	24.63	0.000	0.0908563	0.1065693
总方差	0.5610886	0.0784423	-	-	0.406627	0.7066726
对数似然估计值		261.52349		Wald chi²(8)		110.28
				Prob > chi²		0

表4

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类别	指标
投入指标	星级饭店总数（家）
	饭店从业人员数（人）
	星级饭店客房数（间）
	固定资产原值（万元）
产出指标	饭店客房出租率（%）
	星级饭店营业收入（千元）

时段	技术效率变化指数	技术进步指数	纯技术效率变化指数	规模效率变化指数	全要素生产率指数
2004~2005	1.155	0.939	1.122	1.029	1.084
2005~2006	0.977	1.022	0.99	0.987	0.999
2006~2007	0.968	1.023	0.965	1.003	0.991
2007~2008	1.074	0.999	1.076	0.998	1.072
2008~2009	1.023	1.013	1.111	0.92	1.035
2009~2010	1.007	1.769	0.945	1.065	1.782
2010~2011	1.101	0.639	1.071	1.029	0.704
2011~2012	1.051	4.868	1.019	1.031	5.116
2012~2013	0.891	0.316	0.922	0.966	0.281
2013~2014	0.958	0.975	0.968	0.99	0.934
均值	1.018	1.053	1.017	1.001	1.072

模型	变量名称	计算方法	说明	符号
自变量	技术效率	DEA模型计算出的技术效率值		TE
效率影响因素	经济基础	人均GDP（元）	人均GDP反映区域经济水平的可比性强	PGDP
	旅游人次水平	国内旅游人次（万人次）	国内旅游人次占区域旅游人次绝大部分	NDT
	旅游收入水平	国内旅游收入（亿元）	国内旅游收入占区域旅游收入绝大部分	DTE
	产业结构	二、三产业增加值占区域GDP比例（%）	二三产业是产业结构变化的主要标志	RI
	城镇化	人口城镇化率（%）	城镇常住人口比例是城镇化主要标志	UI
	基础设施	等级公路密度（km/万km²）	交通是区域基础设施改善的重要标志	HWD
	信息化	人均邮电业务总量（万元/万人）	邮政、电信、网络等是信息化的重要标志	PTV
	开放程度	人均境内目的地和货源地进出口总额（万元/万人）	进出口反映区域参与国际市场交流的经营能力	DIE