Spatial spillover and determinants of tourism efficiency

A low carbon emission perspective

Bibliographic Data

ID21689367
AuthorsHongwei Liu (0000-0001-6471-131X, Anhui University, corresponding author), Chenchen Gao (0000-0002-1631-005X, Anhui University), Henry Tsai (0000-0002-7939-748X, The Hong Kong Polytechnic University, China)
Year2024
Volume30
Issue3
Pages543-566
Publication date2024-05-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueTourism Economics (JOURNAL)
Journal identifiersISSN: 1354-8166 • E-ISSN: 2044-0375
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/13548166231167045
OpenAlexW4362465365
LanguageEN
Citations received12
References cited103

This paper measures tourism carbon efficiency (TCE) in China by incorporating energy consumption and carbon dioxide (CO 2 ) emissions into an efficiency assessment framework, and to further investigate the determinants of TCE by considering the spatial spillover effects. To do this, a bootstrap slacks-based measure (SBM) model was applied to assess the TCE in 30 provincial-level administrative regions of China from 2008 to 2019. Next, the Moran’s index and spatial Durbin model (SDM) were adopted to explore the spatial distribution and determinants of TCE. The results indicate that regional differences affect the level of China’s TCE, as do spatial spillover effects. In addition, technology innovation, urbanization rate, and government support positively affect TCE. In contrast, economic growth negatively affects TCE. Educational attainment, green infrastructure, and government support have a negative spatial spillover effect on TCE. Transportation infrastructure has a negative total effect on TCE

China · Econometrics · Economic growth · Economics · Geography · Greenhouse gas · Microeconomics · Natural resource economics · Spatial dependence · Spatial distribution · Spatial econometrics · Spillover effect · Tourism · Urbanization · Economic and Environmental Valuation · Energy, Environment, Economic Growth · Urban Transport and Accessibility