Estimation of demand models for long-distance international travel – Key determinants for Swedes’ travel abroad

Abstract

Although long-distance international travel contributes significantly to global emissions from the transport sector, disaggregated travel demand forecasting models on long-distance international travel are scarce. Large infrastructure investments such as high-speed rail may have a profound impact on long-distance international travel demand and thus need to be evaluated using such models. In this study, a disaggregated travel demand forecasting model is estimated using Swedish national travel survey data from 2011-2016 along with detailed supply data from European road, train, and ferry networks and a World-wide air network, aiming at forecasting Swedes’ long-distance travel abroad. Mode choice, destination choice and trip generation are modelled by traditional Nested Logit models and Multinomial Logit models. The model is segmented by purpose (private or business) and for private trips also by number of nights away. The model estimation results reveal effects of individual socio-economic attributes, level-of-service attributes, and destination characteristics. Marginal effect estimates of level-of-service attributes for train suggest that infrastructure investments in high-speed rail network may have a profound effect on demand for long-distance international travel, especially for business trips.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 4 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.