Seamless air-HSR intermodal solution: Behavioural model-based scheduling of airline timetable and airfare

Ning Huan, Toshiyuki Yamamoto and Enjian Yao

Transportation Research Part A: Policy and Practice, 2023, vol. 176, issue C

Abstract: Empirical experience of air and high-speed rail (HSR) cooperation in Europe and China indicates that seamless intermodal connections are crucial for expanding air-HSR integration services’ market share, particularly in long-haul travel. Given that substantial practical obstacles impede the integrated scheduling of air and HSR systems, adapting oneself to the former competitor is of great practical value but remains largely underexplored. This paper presents a method for improving synchronous operations of air and HSR by unilaterally scheduling airline timetable and airfare, which is an attempt to facilitate air-HSR cooperation to an advanced level of operational integration. Accordingly, a stated preference survey was conducted in the Beijing-Tianjin-Hebei mega-city region to uncover traveller preferences for air-HSR integration services (AHISs) in the airport cluster context based on discrete choice modelling. Using behavioural models as travel demand assignment criteria, an on-demand scheduling model is developed to maximise the total revenue of air transport involved in AHISs. The empirical case investigates AHISs from Beijing to twenty domestic cities via Shijiazhuang Zhengding International Airport. The results show that the optimal scheduling solution decreases air-HSR connection time by a maximum of 41.83% and highlights the necessity of providing efficient shuttle systems, baggage through-check and flexible ticket services to enhance intermodal product appeal. Additionally, incorporating an airfare adjustment mechanism into timetable scheduling is proven supportive of increasing air transport’s revenue up to 16.44% while promoting seamless AHISs, thereby ensuring practical motivation for AHIS upgrades.

Keywords: Air-HSR integration; Intercity travel; Timetable optimisation; Airport cluster; Mega-city region (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.tra.2023.103821

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