Transfer Resistance in Long-Distance Rail: Evidence from an On-Board Passenger Survey and Operational Data

Transfer behaviour is a key determinant of the attractiveness of public transport, yet it has been quantified less thoroughly than the elasticities of journey time and fare—particularly in long-distance travel, where the competitiveness of rail determines its potential for modal shift and thus for reducing emissions. This study quantifies transfer resistance in long-distance rail using an on-board survey conducted in 2016 on three major Austrian routes (1009 questionnaires distributed, 903 valid), supplemented by sales data from a long-distance rail operator and an analysis of five tram lines linked into direct, transfer-free through services. Around 53% of respondents travelled without transferring, around 97% transferred no more than twice, and fewer than 2% transferred three times; the decline follows a multiplicative pattern. Among direct travellers, the stated cumulative willingness to accept additional transfers falls from around 44% for one to 4% for two additional transfers; around 51% of all respondents would look for an alternative at two or fewer additional transfers. An additional transfer requires, on average, a journey time saving of around 17% or a fare reduction of around 30%; as journey duration increases, the relative requirement falls from 33% to 10%, while the directly stated absolute requirement rises from around 12 to 37 min. Travel context (journey duration, purpose, frequency, luggage) is associated with transfer behaviour, whereas no association with age, gender or occupation was detectable. Transfers should therefore be modelled as a distinct, non-linear and context-segmented barrier.

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Publication Details

Journal
Sustainability
Published
2026-11-04
DOI
https://doi.org/10.3390/su182111257
Primary Topic
Transportation Planning and Optimization
Type
article
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article

Transfer Resistance in Long-Distance Rail: Evidence from an On-Board Passenger Survey and Operational Data

Bernhard Rüger, Thomas Eigner, Niklas Schnitzer
Sustainability
Transportation Planning and Optimization
article

Transfer Resistance in Long-Distance Rail: Evidence from an On-Board Passenger Survey and Operational Data

Bernhard Rüger, Thomas Eigner, Niklas Schnitzer
article en

Abstract

Transfer behaviour is a key determinant of the attractiveness of public transport, yet it has been quantified less thoroughly than the elasticities of journey time and fare—particularly in long-distance travel, where the competitiveness of rail determines its potential for modal shift and thus for reducing emissions. This study quantifies transfer resistance in long-distance rail using an on-board survey conducted in 2016 on three major Austrian routes (1009 questionnaires distributed, 903 valid), supplemented by sales data from a long-distance rail operator and an analysis of five tram lines linked into direct, transfer-free through services. Around 53% of respondents travelled without transferring, around 97% transferred no more than twice, and fewer than 2% transferred three times; the decline follows a multiplicative pattern. Among direct travellers, the stated cumulative willingness to accept additional transfers falls from around 44% for one to 4% for two additional transfers; around 51% of all respondents would look for an alternative at two or fewer additional transfers. An additional transfer requires, on average, a journey time saving of around 17% or a fare reduction of around 30%; as journey duration increases, the relative requirement falls from 33% to 10%, while the directly stated absolute requirement rises from around 12 to 37 min. Travel context (journey duration, purpose, frequency, luggage) is associated with transfer behaviour, whereas no association with age, gender or occupation was detectable. Transfers should therefore be modelled as a distinct, non-linear and context-segmented barrier.

SustainabilityVol. 18(21)
TU Wien (AT), University of Applied Sciences St Pölten (AT)
Openalex Percentile: Top 13%
Transportation Planning and Optimization
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