Determinants of air-rail integration service of Shijiazhuang airport, China: analysis of historical data and stated preferences

In order to explore the determinants of air-rail integration service in China, this paper employed a comparative analysis based on historical data and stated preferences. According to the results of a partial least-squares regression model and a binary logit model, the numbers of destination cities and flights are the most important factor influencing the use of the ARIS at Shijiazhuang Zhengding International Airport. The impact of other factors is small. Consequently, policymakers have to find rational target markets to promote air-rail integration service at regional airports to attract passengers from overloaded hub airports. Although the impact of other determinants is rather small, considering the large number of passengers at hub airports, a small increase in the market share of air-rail integration service implies considerable increment in the number of air-rail integration service passengers.

[1]  A. Zhang,et al.  Air-rail revenue sharing in a multi-airport system: Effects on traffic and social welfare , 2019, Transportation Research Part B: Methodological.

[2]  Yonglei Jiang,et al.  Hinterland patterns of China Railway (CR) express in China under the Belt and Road Initiative: A preliminary analysis , 2018, Transportation Research Part E: Logistics and Transportation Review.

[3]  A. Avenali,et al.  Strategic formation and welfare effects of airline-high speed rail agreements , 2018, Transportation Research Part B: Methodological.

[4]  Changmin Jiang,et al.  Determinants of partnership levels in air-rail cooperation , 2018, Journal of Air Transport Management.

[5]  Anming Zhang,et al.  Air and high-speed rail transport integration on profits and welfare: Effects of air-rail connecting time , 2017 .

[6]  T. D’Alfonso,et al.  Air-rail cooperation: Partnership level, market structure and welfare implications , 2017 .

[7]  Qiang Wang,et al.  Impact of high-speed rail on China’s Big Three airlines , 2017 .

[8]  Yu Zhang,et al.  Air Transport versus High-Speed Rail: An Overview and Research Agenda , 2017 .

[9]  Yu Zhang,et al.  Finding -Hub Median Locations: An Empirical Study on Problems and Solution Techniques , 2017 .

[10]  Zhi-Chun Li,et al.  Forecasting passenger travel demand for air and high-speed rail integration service: A case study of Beijing-Guangzhou corridor, China , 2016 .

[11]  Mikio Takebayashi,et al.  Multiple hub network and high-speed railway: Connectivity, gateway, and airport leakage , 2015 .

[12]  John M. Rose,et al.  Applied Choice Analysis , 2015 .

[13]  Juan R. Trapero,et al.  Measuring the substitution effects between High Speed Rail and air transport in Spain , 2015 .

[14]  Juan Carlos Martín,et al.  Integration of HSR and air transport: Understanding passengers’ preferences , 2014 .

[15]  Changmin Jiang,et al.  Effects of high-speed rail and airline cooperation under hub airport capacity constraint , 2014 .

[16]  Moshe Givoni,et al.  Competition, Integration, Substitution: Myths and Realities Concerning the Relationship between High-Speed Rail and Air Transport in Europe , 2013 .

[17]  Thibaut Lavril,et al.  Measuring the willingness-to-pay of air-rail intermodal passengers , 2013 .

[18]  Massimiliano Zanin,et al.  Environmental Benefits of Air–Rail Intermodality: the Example of Madrid Barajas , 2012 .

[19]  Paul Chiambaretto,et al.  Air–rail intermodal agreements: Balancing the competition and environmental effects , 2012 .

[20]  M. Pilar Socorro,et al.  The effects of airline and high speed train integration , 2013 .

[21]  Frédéric Dobruszkes,et al.  High-speed rail and air transport competition in Western Europe: A supply-oriented perspective , 2011 .

[22]  Milan Janic Assessing some social and environmental effects of transforming an airport into a real multimodal transport node , 2011 .

[23]  Werner Rothengatter Competition between airlines and high-speed rail , 2010 .

[24]  Concepción Román,et al.  Analyzing Competition between the High Speed Train and Alternative Modes. The Case of the Madrid-Zaragoza-Barcelona Corridor , 2010 .

[25]  John M. Rose,et al.  Combining RP and SP data: biases in using the nested logit ‘trick’: contrasts with flexible mixed logit incorporating panel and scale effects , 2008 .

[26]  Reinhard Clever,et al.  Interaction of Air and High-Speed Rail in Japan , 2008 .

[27]  Concepción Román,et al.  Competition of high-speed train with air transport: The case of Madrid–Barcelona , 2007 .

[28]  Makoto Okumura,et al.  Air-Rail Inter-modal Network Design under Hub Capacity Constraint , 2007 .

[29]  David Banister,et al.  Airline and railway integration , 2006 .

[30]  Juan de Dios Ortúzar,et al.  Analysing Demand for Suburban Trips: A Mixed RP/SP Model with Latent Variables and Interaction Effects , 2006 .

[31]  J. Polak,et al.  MIXED LOGIT MODELLING OF AIRPORT CHOICE IN MULTI-AIRPORT REGIONS , 2005 .

[32]  Milan Janic,et al.  High-speed rail and air passenger transport: A comparison of the operational environmental performance , 2003 .

[33]  Michel Bierlaire,et al.  BIOGEME: a free package for the estimation of discrete choice models , 2003 .

[34]  John Stubbs,et al.  The integration of rail and air transport in Britain , 1998 .

[35]  T. Dijkstra Some comments on maximum likelihood and partial least squares methods , 1983 .