Analysis of the Transfer Time and Influencing Factors of Air-Rail Integration Passengers: A Case Study of Shijiazhuang Zhengding International Airport

Fan Jiang (), Lichao Wang and Shiyu Huang
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Fan Jiang: School of Transportation, Southeast University, Nanjing 211189, China
Lichao Wang: School of Transportation, Southeast University, Nanjing 211189, China
Shiyu Huang: School of Transportation, Southeast University, Nanjing 211189, China

Sustainability, 2022, vol. 14, issue 23, 1-14

Abstract: As China’s high-speed rail and civil aviation gradually move from a competitive relationship to a cooperative relationship, air-rail integration services (ARISs) have begun to be promoted, and an increasing number of passengers are choosing the combined travel mode of high-speed rail and aviation. As two long-distance transportation modes are involved, transfer time also affects transfer service satisfaction, and the factors affecting the transfer time of ARIS need to be further clarified. In this study, a stated preference (SP) survey on the transfer reservation time of ARIS passengers was conducted, the perception accuracy of the transfer reservation time was analyzed, and the influencing factors of the transfer reservation time in each link were analyzed by using a multivariate ordered logistic regression model. The results show that the average transfer time of air-rail combined transportation passengers is 102 to 128 min; more than half of passengers’ reservation time is reasonable; and passengers’ genders, educations, occupations, incomes, travel modes, costs, and distances have different degrees of impact on the transfer reservation time. This study holds a certain guiding significance for improving the service quality of air-rail intermodal transportation and improving transfer efficiency and provides a theoretical basis for personalized and customized services for air-rail intermodal passengers.

Keywords: air-rail integration services (ARIS); intermodal passenger; reservation travel time; influencing factors; multinomial ordered logistic regression (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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