Spatio-temporal pattern and influencing factors of border tourism efficiency in China

In recent years,tourism has emerged as a significant driver of economic development in China’s border regions.The study utilizes various methods,such as the super-efficiency SBM model,spatial variability,cold and hot spot analysis,and Geo-Detector approach,to measure and describe the spatial and temporal evolution patterns of land border tourism efficiency and its influencing factors.The findings reveal that the Dai autonomous prefecture of Xishuangbanna has the highest border tourism efficiency of 1.6207,while Ngari prefecture has the lowest tourism efficiency with a value of only 0.0365 at the prefecture level during the period 2010-2019.The southwest and northwest regions of China are high-and low-level agglomeration areas respectively,indicating varying levels of border tourism development.Additionally,the study identifies an upward trend in China’s border tourism efficiency from 2010-2019.The southwest region emerges as a hotspot and the most active region,while the northwest and northeast regions are considered cold spots with ample room for improvement.Furthermore,the density of transportation facilities,national vulnerability,cultural proximity,the number of border ports,and market opportunity are crucial factors influencing the spatial and temporal pattern of border tourism efficiency in China.

Is the Infuence of Chinese Local Government Act on Tourism Efficiency Positive?

In China,local governments play a very important role in the development of the tourism industry.Local governments appear to have a positive effect on the development of tourism because of the fact that the tourism industry output has improved for more than a decade.Many researchers have studied the relationship between government and tourism development.However,the existing studies were limited to qualtative discussion and there is still no relatively scientific quantitative analysis which can prove whether the impact is positive or not.Therefore,the purpose of this paper is to verify whether the impacts of Chinese local government act on the tourism industry are positive or negative from the perspective of efliciency.To achieve this aim,this paper binned a quantitative model of local govermment act,data envelopment analysis and spatial statistics together in a creative way,measured tourism industry eficiency with and without the influence of local government act and compared the changes in results and their spatial patterms and spatial interactions.On the basis of these analyses,the author found that positive impacts as a result of the local govermment act on eficiency in the tourism industy do exist.

Beyond skyline and borders: Unraveling the evolution and drivers of tourism green development efficiency in the Beijing-Tianjin-Hebei urban agglomeration, China

Green development is a critical component of sustainable tourism, which prioritizes a comprehensive, ecologically-friendly, and people-oriented approach to development. This study presents a case study of the Beijing–Tianjin–Hebei(BTH) urban agglomeration from 2001 to 2021 to analyze the spatio-temporal evolution characteristics and influencing factors of tourism green development efficiency(TGDE). The study defines the concept of tourism green development and constructs an evaluation system, which is used to explore the internal differences and spatial patterns of TGDE within the urban agglomeration. The methodological approach includes the SBM–Undesirable model, kernel density estimation, Markov chain, and spatial gravity model. The findings indicate that the TGDE in the BTH urban agglomeration is generally favorable, displaying a temporal phase of “rising–declining–rising.” However, the study observes lower TGDE in tourism node cities compared to tourism regional center cities and tourism core hub cities. The non-equilibrium degree of each region indicates significant spatio-temporal evolution patterns and internal differences among the three regions, with a spatially decreasing distribution of “core hub-regional center-node city.” The TGDE in the urban agglomeration experienced an evolutionary trend of “first decreasing and then increasing” with apparent endogenous evolution characteristics. The linkage pattern of green development efficiency in the tourism industry between cities is relatively stable. Furthermore,neighboring cities generally exhibit a higher spatial connectivity strength of green development efficiency in the tourism industry compared to non-neighboring cities. Economic development level, industrial structure, and science and education level are identified as key factors that affect TGDE. However, the study finds that the factors influencing TGDE in tourism core hub cities, tourism regional center cities, and tourism node cities differ somewhat. Economic development level, industrial structure, science and education level, openness, and government regulation impact TGDE in tourism core hub cities and tourism regional center cities, while economic development level, industrial structure, and tourism resource endowment are the primary factors affecting TGDE in tourism node cities. The study provides policymakers and tourism practitioners with valuable insights into enhancing the green development of the tourism industry in the BTH urban agglomeration and other similar regions.Corresponding policy recommendations based on the results are proposed to improve the TGDE of the tourism industry in these regions, promote sustainable tourism development,improve the quality of life of local residents, and protect the ecological environment.

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

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-TianjinHebei（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.