By utilizing the panel data of 26 cities in the Yangtze River Delta urban agglomeration of China from 2000 to 2018, this study constructs a panel threshold model to examine the nonlinear relationship between Tourism E...By utilizing the panel data of 26 cities in the Yangtze River Delta urban agglomeration of China from 2000 to 2018, this study constructs a panel threshold model to examine the nonlinear relationship between Tourism Environmental Carrying Capacity(TECC) and Tourism Industry Agglomeration(TIA). TECC is evaluated based on the Driver-Pressure-State-Impact-Response(DPSIR) model, and TIA is estimated by the location quotient index.The analysis reveals that TIA and TECC both show growth trends and significant regional differences among the 26cities, but the latter fluctuates at certain stages. Moreover, TIA has a significant double threshold effect on TECC,which shows that the positive impact of TIA is enhanced initially but then weakens afterwards. Theoretically, this study contributes to enriching the current literature on TECC from the perspective of TIA. Practically, it could help local governments effectively arrange agglomerations to promote the sustainable development of the tourism industry in China.展开更多
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 agglomera...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.展开更多
基金The National Social Science Fund Project of China (21BGL02119BGL138)+1 种基金The Macro Decision-making Projects on Culture and Tourism of China Tourism Academy (2021HGJCG04)The Natural Science Planning Project in Shandong Province (ZR202102200015)。
文摘By utilizing the panel data of 26 cities in the Yangtze River Delta urban agglomeration of China from 2000 to 2018, this study constructs a panel threshold model to examine the nonlinear relationship between Tourism Environmental Carrying Capacity(TECC) and Tourism Industry Agglomeration(TIA). TECC is evaluated based on the Driver-Pressure-State-Impact-Response(DPSIR) model, and TIA is estimated by the location quotient index.The analysis reveals that TIA and TECC both show growth trends and significant regional differences among the 26cities, but the latter fluctuates at certain stages. Moreover, TIA has a significant double threshold effect on TECC,which shows that the positive impact of TIA is enhanced initially but then weakens afterwards. Theoretically, this study contributes to enriching the current literature on TECC from the perspective of TIA. Practically, it could help local governments effectively arrange agglomerations to promote the sustainable development of the tourism industry in China.
基金National Natural Science Foundation of China,No.41401158No.41140007No.41261035
文摘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.