Abstract

For the healthy development of regional tourism systems, performance evaluation is vital for regulators so that they can determine the source of inefficiency to enhance systems’ competitiveness through a series of systematic policy plans. Past research has recognized the importance of network collaboration in the tourism sector but has focused mainly on the separate stages of performance (e.g., hotels), with limited discussion on how sectoral interactions can be distilled into collaborative models. Consequently, this paper intends to construct a more comprehensive performance evaluation framework for the Chinese regional tourism system that not only focuses on network interactions and dynamic features among stages but also considers spatial dependency to enhance the accuracy of performance evaluation. Using the panel data of 30 provincial-administrative regions on China’s tourism industry from 2012 to 2016, the operating performance of each regional tourism system and its tourist stages are measured by the SBM-DNDEA model. Furthermore, the spatial effect of regional tourism system operational performance and its influencing factors are investigated via the Tobit spatial Durbin model. The results showed that the operational performance of the Chinese regional tourism system was still relatively low, with the attraction stage performing the best, and there were significant differences among the four economic zones. The strength of traffic convenience had a significant positive effect on the operational performance of the local tourism system, but fiscal expenditure on environmental management also had a negative spillover effect on the surrounding region. The urbanization level had not only a significant positive effect on local areas but also a positive spillover effect on adjacent areas. Interregional development may also affect the performance of attractions, highlighting the importance of systematic integration and allocation of resources for tourism development.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call