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<p>Some studies have demonstrated an inverted U-shaped relationship between transportation infrastructure development and tourism growth, suggesting an initial positive impact followed by a subsequent negative effect. In these studies, transportation infrastructure is predominantly treated as an independent variable, and its impact on tourism development is analyzed using various models. However, these studies have failed to adequately account for the significance of industrial synergy and integration. Especially in the context of escalating consumer demands, the growth impetus driven by single-factor scale expansion is approaching exhaustion. Consequently, this paper selects relevant data from 31 regions in China spanning the period from 2008 to 2022. First, it applies the XGBoost machine-learning framework to explore the non-linear relationships within the data. Subsequently, this study employs a panel vector autoregression model with exogenous variables (PVARX) to further validate the dynamic effects of interaction terms. Empirical results demonstrate that the synergy and integration among transportation infrastructure, relevant services, and information technology exert a persistent and stable positive influence on tourism expansion.</p>

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Breaking the inverted U relationship between transportation infrastructure and tourism development provides new evidence for sustainability

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月25日

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  • Ruohan Tang,
  • Yao Sun

摘要

Some studies have demonstrated an inverted U-shaped relationship between transportation infrastructure development and tourism growth, suggesting an initial positive impact followed by a subsequent negative effect. In these studies, transportation infrastructure is predominantly treated as an independent variable, and its impact on tourism development is analyzed using various models. However, these studies have failed to adequately account for the significance of industrial synergy and integration. Especially in the context of escalating consumer demands, the growth impetus driven by single-factor scale expansion is approaching exhaustion. Consequently, this paper selects relevant data from 31 regions in China spanning the period from 2008 to 2022. First, it applies the XGBoost machine-learning framework to explore the non-linear relationships within the data. Subsequently, this study employs a panel vector autoregression model with exogenous variables (PVARX) to further validate the dynamic effects of interaction terms. Empirical results demonstrate that the synergy and integration among transportation infrastructure, relevant services, and information technology exert a persistent and stable positive influence on tourism expansion.