Spatial differences and driving factors of tourism efficiency in border regions

doi:10.3969/j.issn.1004-9479.2020.02.2018454

Abstract

Abstract:

The evaluation of tourism efficiency is of great significance to the improvement and improvement of regional tourism. Based on the demonstration of Yunnan Province, using the data envelopment analysis (DEA) is to analyze the efficiency of tourism, and spatial statistical methods such as spatial autocorrelation and trend surface are used to analyze the spatial correlation and overall trend characteristics of tourism efficiency. The detector model focuses on the driving factors of tourism efficiency. The results show that: 1) The overall level of comprehensive tourism efficiency in Yunnan Province is good, but the gap between cities is relatively large, and the ability of pure technical efficiency to adjust comprehensive efficiency is slightly stronger than scale efficiency. 2) Tourism efficiency presents a spatial agglomeration situation. The overall efficiency is characterized by the spatial characteristics of“the north and south wings are high and the middle is low, and the east and west are smooth transitions”. The high efficiency zone is“convergence in the northwestern Yunnan”; the pure technical efficiency shows a “U” trend in the north and south directions. The gradient in the east-west direction is decreasing; the scale efficiency generally shows the trend characteristics of“the north and south wings are high and the middle is low, and the west is high and the east is low”.3) The number of tourism practitioners, transportation network density and scenic abundance are the main influencing factors of spatial differentiation of tourism efficiency in Yunnan Province. The influence of different factors interaction is higher than the influence of individual effects.

Key words: tourism efficiency, spatial differentiation, influencing factors, DEA model, geographic detector

摘要：

旅游效率评价对区域旅游业提质增效发展具有重要意义。以云南省为实证，采用数据包络分析法(DEA)对其旅游业效率进行分析，运用空间自相关和趋势面等空间统计方法对旅游效率空间关联和整体趋势特征进行剖析，并借助地理探测器模型着重探讨了旅游效率的驱动因子。结果表明：1）云南省旅游综合效率总体水平较好，但州市间差距较大，纯技术效率对综合效率制约能力略强于规模效率;2）旅游效率呈现空间集聚态势，综合效率整体呈“南北两翼高中间低，东西平稳过渡”空间特征，高效区在滇西北“趋同集聚”；纯技术效率在南北方向呈“U”型趋势，东西方向上梯度递减；规模效率总体呈现“南北两翼高中间低，西高东低”趋势特征;3）旅游从业人数、交通网络密度和景区丰度是云南省旅游效率空间分异的主要影响因素，不同因子交互作用时均高于单独作用时的影响力。

关键词: 旅游效率, 空间分异, 驱动因素, DEA模型, 地理探测器

Xiangyang GUO, Xueqing MU, Qingzhong MING. Spatial differences and driving factors of tourism efficiency in border regions[J]. World Regional Studies, 2020, 29(2): 416-427.

郭向阳, 穆学青, 明庆忠. 边疆省域旅游效率空间分异及驱动因素[J]. 世界地理研究, 2020, 29(2): 416-427.

Figures/Tables 8

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指标类型	评价指标	最小值	最大值	均值	标准差
产出系统	旅游总收入/亿元	26.1	723.47	204.76	183.49
产出系统	旅游接待人次/万人	265.31	6911.4	2055.22	1504.49
投入系统	A级景区丰度指数/分	8	96	12.6	6.9
	星级宾馆数量/家	7	195	54	48
	旅行社数量/家	3	124	26.5	28
	旅游固定资产投资/亿元	45	2816	496.2	659.6
	旅游从业人数/人	251	21055	3539.3	4908.7

指标类型	评价指标	最小值	最大值	均值	标准差
产出系统	旅游总收入/亿元	26.1	723.47	204.76	183.49
产出系统	旅游接待人次/万人	265.31	6911.4	2055.22	1504.49
投入系统	A级景区丰度指数/分	8	96	12.6	6.9
	星级宾馆数量/家	7	195	54	48
	旅行社数量/家	3	124	26.5	28
	旅游固定资产投资/亿元	45	2816	496.2	659.6
	旅游从业人数/人	251	21055	3539.3	4908.7

DMU	crste	vrste	scale	规模收益	DMU	crste	vrste	scale	规模收益
昆明	0.845	1.000	0.845	drs	普洱	0.960	0.984	0.976	drs
昭通	1.000	1.000	1.000	-	版纳	1.000	1.000	1.000	-
曲靖	0.471	0.474	0.993	irs	大理	0.548	0.689	0.795	irs
玉溪	0.640	0.898	0.713	drs	德宏	0.938	1.000	0.938	drs
保山	0.523	0.564	0.926	drs	丽江	1.000	1.000	1.000	-
楚雄	0.782	0.811	0.964	drs	怒江	0.895	1.000	0.895	irs
红河	0.610	1.000	0.610	drs	迪庆	1.000	1.000	1.000	-
文山	1.000	1.000	1.000	-	临沧	0.405	0.456	0.887	irs

DMU	crste	vrste	scale	规模收益	DMU	crste	vrste	scale	规模收益
昆明	0.845	1.000	0.845	drs	普洱	0.960	0.984	0.976	drs
昭通	1.000	1.000	1.000	-	版纳	1.000	1.000	1.000	-
曲靖	0.471	0.474	0.993	irs	大理	0.548	0.689	0.795	irs
玉溪	0.640	0.898	0.713	drs	德宏	0.938	1.000	0.938	drs
保山	0.523	0.564	0.926	drs	丽江	1.000	1.000	1.000	-
楚雄	0.782	0.811	0.964	drs	怒江	0.895	1.000	0.895	irs
红河	0.610	1.000	0.610	drs	迪庆	1.000	1.000	1.000	-
文山	1.000	1.000	1.000	-	临沧	0.405	0.456	0.887	irs

旅游效率类型	标准差	均值	变异系数
综合效率	0.219	0.788	0.278
纯技术效率	0.204	0.867	0.235
规模效率	0.116	0.907	0.128