Abstract
AbstractUnderstanding the driving factors of tourism growth provides insights into tourism growth patterns and can inform tourism policymaking. This paper develops a novel data envelopment analysis (DEA)‐based decomposition approach, a combined use of DEA, meta‐frontier theory, and polar decomposition method, for decomposing tourism growth into seven components, that is, technological efficiency, technology gap effect, technological progress, labour input effect, capital input effect, tourism resource endowment effect, and environmental overload effect. Subsequently, an empirical study has been undertaken for Mainland China during the period of 2005–2015. The results reveal that factor inputs contribute more to China's tourism growth than total factor productivity. The gap between the contributions of factor inputs and total productivity to tourism growth has gradually been narrowing over time. Further decomposition shows that the above seven sources of tourism growth show distinct spatial characteristics. Finally, according to the estimation results, this paper formulates targeted strategies to promote sustainable tourism growth in Mainland China.
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 callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
