Spatial characteristics of development efficiency for urban tourism in eastern China: A case study of six coastal urban agglomerations

doi:10.1007/s11442-014-1146-7

Abstract

Abstract:

The traditional data envelopment analysis (DEA), bootstrap-DEA and Malmquist models are employed to measure different tourism efficiencies and their spatial characteristics of 61 cities in six coastal urban agglomerations in eastern China. The following conclusions are drawn. (1) The comprehensive efficiency (CE) of urban tourism using the bootstrap-DEA model is lower than the CE level using the DEA-CRS model, which confirms the significant tendency of the DEA-CRS model to overestimate results. (2) The geometric CE averages of urban tourism in the Yangtze River Delta (YRD) and the Pearl River Delta (PRD) have changed from ineffective to effective since 2000, the averages in the Beijing-Tianjin- Hebei (BTH) and the Shandong Peninsula (SDP) have changed from ineffective to moderately effective since 2000, and those in the Central and Southern Liaoning (CSL) and the West Bank of Taiwan Strait (WBTS) have been ineffective since 2000. (3) The CE values of urban tourism in the PRD, the YRD, the BTH and the SDP have been slightly affected by the pure technical efficiency (PTE), whereas the CE values in the CSL and the WBTS have been slightly affected by the scale efficiency (SE) since 2000. (4) Spatially, the range of geometric averages of the total factor productivity (TFP) for the PRD, the YRD, the BTH, the SDP, the WBTS and the CSL has decreased sequentially, while the one for most cities in six urban agglomerations has exhibited a downward trend since 2000. (5) Collectively, the natural conditions, the economic policies and the tourism capital drive the SE change of urban tourism of the CSL and the WBTS. The tourism enterprises for increasing returns to scale and imitating innovative technology have an effect on the CE change of urban tourism in the BTH and the SDP. The tourism market competition drives the PTE change of urban tourism in the PRD and the YRD. Although the PTE and the SE of urban tourism in six coastal urban agglomerations suffer from uncertain events, the CE maintained overall sound momentum since

Key words: urban tourism, development efficiency, coastal urban agglomerations, eastern China

Rui LI, Qian GUO, Dianting WU, Hongmei YIN, Hua ZHANG, Taoxing ZHU. Spatial characteristics of development efficiency for urban tourism in eastern China: A case study of six coastal urban agglomerations[J].Journal of Geographical Sciences, 2014, 24(6): 1175-1197.

Figures/Tables 10

Table 1

Figure 1

Figure 2

Table 2

Figure 3

Figure 4

Table 3

Figure 5

Table 4

Figure 6

References 31

1	Anderson R I, Fok R, 2000. Hotel industry efficiency: An advanced linear programming examination.American Business Review, 18(1): 40-48.
2	Anderson R I, Lewis D, Parker M E, 1999. Another look at the efficiency of corporate travel management departments.Journal of Travel Research, 37(3): 267-272.
3	Barros C P, 2005. Measuring efficiency in the hotel sector.Annals of Tourism Research, 32(2): 456-477.
4	Barros C P, Matias A, 2006. Assessing the efficiency of travel agencies with a stochastic cost frontier: A Portuguese case study.International Journal of Tourism Research, 8(5): 367-379.
5	Cao Fangdong, Huang Zhenfang, Wu Jianget al., 2012a. The space-time pattern evolution and its driving mechanism of urban tourism development efficiency: A case study of Pan-Yangtze River Delta.Geographical Research, 31(8): 1431-1444. (in Chinese)
6	Cao Fangdong, Huang Zhenfang, Wu Jianget al., 2012b. The relationship between tourism efficiency measure and location accessibility of Chinese national scenic areas.Acta Geographica Sinica, 67(12): 1686-1697. (in Chinese)
7	Caves D W, Christensen L R, Diewert W E, 1982. Multilateral comparisons of output, input and productivity using superlative index numbers.Economic Journal, 92: 73-86.
8	Charnes A, Cooper W W, Rhodes E, 1978. Measuring the efficiency of decision making units.European Journal of Operation Research, 2: 429-444.
9	Fang Chuanglin, Song Jitao, Li Xueqin et al., 2010. The theory and practice of sustainable development of urban agglomerations in China. Beijing: Science Press, 178. (in Chinese)
10	Fang Chuanglin, Yao Shimou, Liu Shenghe et al., 2011. The Development Report of Urban Agglomeration of China in 2010. Beijing: Science Press, 9. (in Chinese)
11	Fare R, Grosskopf S, Lovell C A K, 1994. Production Frontiers. Cambridge: Cambridge University Press, 378.
12	Fare R, Grosskopf S, Norris M, 1997. Productivity growth, technical progress, and efficiency change in industrialized countries: Reply.American Economic Review, 87: 1040-1043.
13	Gregory Mankiw N G, 1977. Principle of Economics. London: Oxford University Press, 79-84.
14	Hall P, 1986. On the number of bootstrap simulations required to construct a confidence interval.Annals of Statistics, 14: 1453-1462.
15	Kniep A, Simar L, Wilson P W, 2003. Asymptotics and consistent bootstraps for DEA estimators in non-parametric frontier models. IAP Technical Report, 0323: 27-29.
16	Lee C K, Han S H, 2002. Estimating the use and preservation values of national parks’ tourism resources using a contingent valuation method. Tourism Management, 23(5): 531-540.
17	Li Xiande, Ning Yuemin, 2012. Review and prospect on urban agglomeration.Scientia Geographica Sinica, 32(3): 282-288. (in Chinese)
18	Liang Mingzhu, Yi Tingting, 2012. An evaluation and analysis of tourism efficiency in different cities and regions of Guangdong Province.Economic Geography, 32(10): 158-164. (in Chinese)
19	Ma Xiaolong, 2008.Evaluation on efficiency and total factors productivity of Chinese primary tourism cities: 1995-2005. Guangzhou: Sun Yat-Sen University. (in Chinese)
20	Ma Xiaolong, Bao Jigang, 2009. Evaluating the using efficiencies of Chinese national parks with DEA.Geographical Research, 28(3): 838-848. (in Chinese)
21	Ma Xiaolong, Bao Jigang, 2010a. Regional difference and spatial patterns of the tourism efficiency in Chinese primary tourism cities.Human Geography, 25(1): 105-110. (in Chinese)
22	Ma Xiaolong, Bao Jigang, 2010b. An evaluation on the efficiency of Chinese primary tourism cities based on the DEA.Resources Science, 32(1): 88-97. (in Chinese)
23	Ma Zhanxin, 2010. The DEA Model and Methods. Beijing: Science Press, 34. (in Chinese)
24	Morey R C, Dittman D A, 1995. Evaluating a hotel GM’s performance: A case study in benchmarking.The Cornell Hotel Restaurant and Administration Quarterly, 36(5): 30-35.
25	Sarkis J, Talluri S, 2004. Performance based clustering for benchmarking of US airports. Transportation Research Part A:Policy and Practice, 38(5): 329-346.
26	Simar L, Wilson P W, 2000. Statistical inference in nonparametric frontier models: The state of the art.Journal of Productivity Analysis, 13(1): 49-78.
27	Tsaur S H, 2000. The operating efficiency of international tourist hotels in Taiwan.Asia Pacific Journal of Tourism Research, 6(1): 29-37.
28	Tsaur S H, Chiang C I, Chang T Y, 1999. Evaluation the operation efficiency of international tourist hotels using the modified DEA model.Asia Pacific Journal of Tourism Research, 14(1): 73-78.
29	Wei Quanling, 2000. Effective methods on evaluating relative efficiency (DEA).Chinese Science Bulletin, 45(17): 1793-1807. (in Chinese)
30	Yu Hu, Lu Lin, Zhu Dongfanget al., 2012. Urban tourism to urban agglomeration tourism: A deepening systematic research.Progress in Geography, 31(8): 1087-1096. (in Chinese)
31	Zeng Chong, Wan Jianping, 2009. Interval estimate for VaR based on bootstrap method.Mathematics in Economics, 26(1): 58-63. (in Chinese)

Evaluation contents	Types	First grade indices	Second grade indices	Index sources
Development efficiency of urban tourism	Input indices	Labour inputs	Number of employees in urban tourism	Barros, Ma Xiaolong, Cao Fnagdong
		Capital inputs	Number of 3A, 4A and 5A scenic spots	Tsaur, Barros, Liang Mingshu, Cao Fangdong
			Number of 3-star, 4-star and 5-star hotels
			Number of international travel agencies
			Number of domestic travel agencies
	Output indices	Efficiency outputs	Total number of tourists	Anderson, Ma Xiaolong, Cao Fnagdong
	Output indices	Efficiency outputs	Total quantity of tourism incomes	Anderson, Ma Xiaolong, Cao Fnagdong

Name	2001CE	2006CE	2011CE	2001PTE	2006PTE	2011PTE	2001SE	2006SE	2011SE
YRD	0.485	0.627	0.743	0.659	0.777	0.878	0.740	0.821	0.879
BTH	0.295	0.463	0.530	0.514	0.646	0.725	0.561	0.722	0.745
PRD	0.478	0.619	0.766	0.657	0.767	0.864	0.737	0.820	0.923
SDP	0.202	0.428	0.606	0.461	0.645	0.750	0.478	0.721	0.848
WBTS	0.188	0.278	0.374	0.350	0.502	0.599	0.457	0.568	0.693
CSL	0.195	0.356	0.484	0.401	0.559	0.655	0.467	0.620	0.752

Name	2001 -2006 PTE	2006 -2011 PTE	2001 -2006 SE	2006 -2011 SE	2001 -2006 TE	2006 -2011 TE	2001 -2006 TP	2006 -2011 TP	2001 -2006 TFP	2006 -2011 TFP
YRD	1.184	1.105	1.078	1.004	1.226	1.277	1.174	1.134	1.441	1.333
BTH	1.158	1.096	1.108	1.059	1.309	1.164	1.104	1.109	1.440	1.313
PRD	1.150	1.138	1.083	1.096	1.274	1.244	1.114	1.157	1.456	1.380
SDP	1.135	1.092	1.105	1.099	1.333	1.238	1.082	1.061	1.327	1.281
WBTS	1.130	1.076	1.151	1.127	1.308	1.081	1.012	1.009	1.306	1.225
CSL	1.114	1.076	1.158	1.121	1.202	1.195	1.001	1.011	1.240	1.204

Influencing factors		Attractions number	Tourists number	Tourism documents number	Tourism input capital	Competitive tourism products number	Star-level tourism enterprises number
PTE		0.458	0.522	0.542	0.855^***	0.905^*	0.876^***
SE		0.853^*	0.916^**	0.836^***	0.692	0.587	0.491
CE	PRD and YRD	0.415	0.493	0.521	0.917^*	0.816^*	0.942^**
	BTH and SDP	0.527	0.618	0.721^***	0.623	0.583	0.893^**
	CSL and WBST	0.819^***	0.922^**	0.932^*	0.482	0.502	0.489

[1]	REN Yufei, FANG Chuangling, LIN Xueqin, SUN Siao, LI Guangdong, FAN Beili. Evaluation of the eco-efficiency of four major urban agglomerations in coastal eastern China [J]. Journal of Geographical Sciences, 2019, 29(8): 1315-1330.
[2]	YU Ling, LIU Jiaming, LI Tao. Important progress and future prospects for studies on urban public recreational space in China [J]. Journal of Geographical Sciences, 2019, 29(11): 1923-1946.
[3]	Gaocong LI, Shu Gao, Yaping WANG, Chunyan LI. Sediment flux from the Zhoushan Archipelago, eastern China [J]. Journal of Geographical Sciences, 2018, 28(4): 387-399.
[4]	Ruili WANG, Guirui YU, Nianpeng HE, Qiufeng WANG, Ning ZHAO, Zhiwei XU. Latitudinal variation of leaf morphological traits from species to communities along a forest transect in eastern China [J]. Journal of Geographical Sciences, 2016, 26(1): 15-26.
[5]	ZHANG Xuezhen, DAI Junhu, GE Quansheng. Variation in vegetation greenness in spring across eastern China during 1982-2006 [J]. Journal of Geographical Sciences, 2013, 23(1): 45-56.
[6]	LI Qian, WEI Fengying, LI Dongliang. Interdecadal variation of East Asian summer monsoon and drought/flood distribution over eastern China in the last 159 years [J]. Journal of Geographical Sciences, 2011, 21(4): 579-593.
[7]	SHENG Wenping, REN Shujie, YU Guirui, FANG Huajun, JIANG Chunming, ZHANG Mi. Patterns and driving factors of WUE and NUE in natural forest ecosystems along the North-South Transect of Eastern China [J]. Journal of Geographical Sciences, 2011, 21(4): 651-665.
[8]	CUI Linli, SHI Jun. Temporal and spatial response of vegetation NDVI to temperature and precipitation in eastern China [J]. Journal of Geographical Sciences, 2010, 20(2): 163-176.
[9]	LIU Ye, WU Shaohong, ZHENG Du, DAI Erfu. Soil indicators for eco-geographic regionalization: A case study in mid-temperate zone of eastern China [J]. Journal of Geographical Sciences, 2009, 19(2): 200-212.
[10]	ZHANG Jia-shen, TAO Shu, CAO Jun. Fluorescence characteristics of water soluble organic carbon in eastern China [J]. Journal of Geographical Sciences, 2001, 11(4): 473-479.