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<p>This study employed the Global Malmquist–Luenberger (GML) index and the non-radial directional distance function (NDDF) to examine the impact of the digital economy on tourism carbon productivity. Spatial econometric models were applied to analyze the temporal evolution and spatial distribution of tourism carbon productivity in China. The results indicated that national tourism carbon productivity increased by 48.0% between 2012 and 2019. Technological progress accounted for approximately 40.8% of this growth and served as the primary driver of improvements in cfarbon resource utilization efficiency. The mean value of the digital economy index was 0.05, suggesting that its overall development level remained relatively low and that substantial growth potential still existed. In the Spatial Durbin Model, the local regression coefficient of the digital economy on carbon productivity was 0.12 (<i>p</i> &lt; 0.01), indicating a significant positive local effect. The spatial spillover coefficient for neighboring regions ranged from 0.091 to 0.132 (<i>p</i> &lt; 0.1). This demonstrated that digitalization improved local carbon efficiency and stimulated green development in surrounding cities. Transportation accessibility and industrial structure exhibited significant positive spatial spillover effects. In contrast, urbanization and environmental regulation showed negative spatial effects on neighboring areas. The coefficient for urbanization was − 0.189 (<i>p</i> &lt; 0.01), reflecting coordination challenges across regions. The Spatial Lag Model further confirmed strong spatial dependence and co-evolution dynamics. The spatial lag coefficient of the digital economy ranged from 0.366 to 0.564 (<i>p</i> &lt; 0.01), indicating substantial interregional interaction effects. These findings provide quantitative evidence and policy implications for promoting the integration of digital transformation and green development in the tourism sector. They also contribute to advancing sustainable tourism and supporting ecological civilization construction.</p>

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The spillover effect of tourism carbon productivity based on the NDDF-GML model under the influence of the digital economy

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  • 出版模式：

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  • 发表日期：

    2026年5月15日

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  • Yanjuan Feng

摘要

This study employed the Global Malmquist–Luenberger (GML) index and the non-radial directional distance function (NDDF) to examine the impact of the digital economy on tourism carbon productivity. Spatial econometric models were applied to analyze the temporal evolution and spatial distribution of tourism carbon productivity in China. The results indicated that national tourism carbon productivity increased by 48.0% between 2012 and 2019. Technological progress accounted for approximately 40.8% of this growth and served as the primary driver of improvements in cfarbon resource utilization efficiency. The mean value of the digital economy index was 0.05, suggesting that its overall development level remained relatively low and that substantial growth potential still existed. In the Spatial Durbin Model, the local regression coefficient of the digital economy on carbon productivity was 0.12 (p < 0.01), indicating a significant positive local effect. The spatial spillover coefficient for neighboring regions ranged from 0.091 to 0.132 (p < 0.1). This demonstrated that digitalization improved local carbon efficiency and stimulated green development in surrounding cities. Transportation accessibility and industrial structure exhibited significant positive spatial spillover effects. In contrast, urbanization and environmental regulation showed negative spatial effects on neighboring areas. The coefficient for urbanization was − 0.189 (p < 0.01), reflecting coordination challenges across regions. The Spatial Lag Model further confirmed strong spatial dependence and co-evolution dynamics. The spatial lag coefficient of the digital economy ranged from 0.366 to 0.564 (p < 0.01), indicating substantial interregional interaction effects. These findings provide quantitative evidence and policy implications for promoting the integration of digital transformation and green development in the tourism sector. They also contribute to advancing sustainable tourism and supporting ecological civilization construction.