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

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 2000.

The Spatial Differentiation of the Suitability of Ice-Snow Tourist Destinations Based on a Comprehensive Evaluation Model in China

“…As shown in Figure 3a, among the 32 provinces, autonomous regions and municipalities in China, the regions in which the density of coastal scenic areas is greater than the number of inland scenic areas are Jiangsu Province, Zhejiang Province, Henan Province, and Guangdong Province; tourism is highly developed in these areas [25]. In particular, the 5A-level scenic areas for ice-snow tourism and the resources that influence ice-snow tourism are distributed in Heihe City, Harbin City, Mudanjiang City, and Mohe County in Heilongjiang Province, Changchun City and Jilin City in Jilin Province, Lijiang City in Yunnan Province, Altay County in the Xinjiang Autonomous Region, and Hulun Buir in Inner Mongolia.…”

“…Summarizing the information above reveals that Northeast China has formed an entirely integrated industry circle for ice-snow tourism and the region is the national leader in the development of multiple scenic areas involving ice and snow; its ice-snow tourism industry has a broad scope and significant influence, and its suitability according to the development status index for ice-snow tourism is the highest. The Beijing-Tianjin-Hebei, Inner Mongolia, Gansu, Ningxia, and Qinghai regions are comparatively unsuitable due to the lack of core scenic areas featuring snow and ice [24][25][26]. As shown in Figure 3b, traffic accessibility has significant influence on the selection of ice-snow tourism destinations [29].…”

Extracting Network Patterns of Tourist Flows in an Urban Agglomeration Through Digital Footprints: The Case of Greater Bay Area

“…Urban agglomerations are highly developed spatial forms of integrated cities, and are the spatial carrier of regional economic and industrial development [1]. Tourism, as an important driving factor for economic growth in cities, is an external manifestation of the integrated development process of urban agglomerations [2,3]. Evaluating tourism development in urban agglomerations not only provides an important reference for the spatial restructuring of industry, but also has important significance for promoting industrial collaboration and resource exchange within and outside the urban agglomeration, thereby contributing to building an international trade platform [4].…”

Identification and Geographic Distribution of Accommodation and Catering Centers

“…Conventional opinions about the industry distribution rely highly on expert knowledge (and/or experiences) and on analyses based on administrative district-scale economic census data [3,11]. However, the lack of accurate spatial details of industry agglomeration patterns leads to insufficient knowledge for decision-makers and managers [8,12].…”