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March 26, 2026Public Transport0 citationsOpen Access

The price of proximity: analysing distance-based fare structures in liberalised Greek coastal shipping

ISIoannis Sitzimis

Key Points

  • This article aims to determine whether passenger fares in Greek coastal shipping are influenced by distance after market liberalisation.
  • Examined 52 non-PSO routes in Greek coastal shipping.
  • Measured association between lowest economy-class passenger fare and distance.
  • Compared 11 curve families to derive a fare benchmark.
  • Estimated fare variations using a no-intercept power function.
  • Distance explains 99.3% of fare variation for high-speed services and 99.6% for conventional ships.
  • Fares increase with distance but less than proportionally, indicated by elasticity below unity.
  • Average model-implied benchmark fare per nm is €0.72 for high-speed and €0.33 for conventional ships.

Abstract

This article examines whether passenger fares in Greek coastal shipping remain distance-driven after market liberalisation. Using a harmonised 2025 cross-section of 52 non-PSO routes (i.e. routes not operated under Public Service Obligation—PSO—contracts), we measure the association between the lowest economy-class passenger fare and distance, compare 11 curve families, and derive a route-level fare benchmark. A no-intercept power function emerges as the empirically preferred specification. For high-speed services (S), distance explains 99.3% of fare variation; for conventional ships (CS), 99.6%. In both cases the estimated elasticity is below unity, so fares rise with distance but less than proportionally, implying a declining €/nm profile. Market concentration, measured via route-level Herfindahl–Hirschman indices (HHI) based on frequencies and capacities, places almost all lines in the “highly concentrated” range, with many effective monopolies. The average model-implied benchmark fare per nm is €0.72 for S and €0.33 for CS. The benchmark is a descriptive statistical construct that summarises the observed distance–fare pattern in a concentrated market. It is not a regulatory target and should be interpreted alongside information on costs, service quality and demand.

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Cite This Study

Ioannis Sitzimis (2026) studied this question.

synapsesocial.com/papers/69c4cd5afdc3bde4489198achttps://doi.org/10.1007/s12469-026-00422-4
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