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How far will we travel? A global distance pattern of international travel from both demand and supply perspectives

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  • Ya-Yen Sun

    (The University of Queensland, Australia)

  • Pei-Chun Lin

    (National Cheng Kung University)

Abstract

The travel distance of international journeys critically determines our reliance on different transportation modes and the associated carbon intensity. This study quantified the influence of macrolevel determinants to the inbound and outbound average distance per visitor from a panel data of 152 countries using spatial econometric analysis. Results confirmed that national development and transport capacity assisted the spatial expansion of outbound travel, while tourism competitiveness, geographic attributes, and institutional arrangements regarding people’s mobility facilitate inbound visits from distant source markets. A high level of heterogeneity was found across five continents where the distance friction effect through geographic barrier, transport accessibility, and the freedom of people’s movement exhibited a different level of influences. To manage the spatial expansion of international travels for a sustainable transport future, a strong geopolitical integration system across countries within the region and adjustments to the aviation capacity to disfavor long-haul flights have been proposed.

Suggested Citation

  • Ya-Yen Sun & Pei-Chun Lin, 2019. "How far will we travel? A global distance pattern of international travel from both demand and supply perspectives," Tourism Economics, , vol. 25(8), pages 1200-1223, December.
    • Handle: RePEc:sae:toueco:v:25:y:2019:i:8:p:1200-1223
    DOI: 10.1177/1354816618825216
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    2. Chiambaretto, Paul, 2021. "Air passengers’ willingness to pay for ancillary services on long-haul flights," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    3. Rosselló-Nadal, Jaume & Santana-Gallego, María, 2024. "Toward a smaller world. The distance puzzle and international border for tourism," Journal of Transport Geography, Elsevier, vol. 115(C).
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    5. Eugenio-Martin, Juan L. & Cazorla-Artiles, José M., 2020. "The shares method for revealing latent tourism demand," Annals of Tourism Research, Elsevier, vol. 84(C).
    6. Maximilian Weigert & Alexander Bauer & Johanna Gernert & Marion Karl & Asmik Nalmpatian & Helmut Küchenhoff & Jürgen Schmude, 2022. "Semiparametric APC analysis of destination choice patterns: Using generalized additive models to quantify the impact of age, period, and cohort on travel distances," Tourism Economics, , vol. 28(5), pages 1377-1400, August.
    7. Hongjiu Tang, 2020. "Regional Patterns and Hierarchical Tendencies: Analysis of the Network Connectivity of 63 Service-Oriented Tourist Cities in China," Sustainability, MDPI, vol. 12(16), pages 1-22, August.
    8. Jaume Rosselló Nadal & María Santana Gallego, 2022. "Gravity models for tourism demand modeling: Empirical review and outlook," Journal of Economic Surveys, Wiley Blackwell, vol. 36(5), pages 1358-1409, December.

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