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Title: Understanding High-Speed Rail Passengers in China: A Segmentation Approach
Accession Number: 01701409
Record Type: Component
Record URL: Availability: Find a library where document is available Abstract: China has established the world’s largest high-speed rail (HSR) system, which has fundamentally changed the way people travel in the domestic market. As China aims to double its HSR capacity in the next few years, the HSR population will continue to grow, which calls for an in-depth understanding of HSR passengers. While HSR has been of academic interest for many years, existing research has not provided meaningful demographic segmentation in the HSR context. This paper collected empirical data from HSR passengers in Beijing and Shanghai, the largest HSR markets in China, and performed a cluster analysis based collectively on three demographic variables—age, income, and education, which led to the formation of four segments—High-Ed Youths, Mature Travelers, New Starters, and Elite Travelers. Significant differences were found in terms of the passenger demographics and travel experiences across the four segments, to support the validity of the clustering solutions. The multivariate analysis of variance (MANOVA) test further revealed cross-segment differences in terms of passenger evaluation of five HSR variables—reasonableness of price, reliability, food choices, employee service, and likelihood for recommendation, suggesting the possibility of predicting passenger perceptions and behaviors based on their cluster membership. The findings demonstrate that passenger segmentation based on multiple demographic variables can provide deeper insights into the HSR population. For HSR providers in China, an understanding of the characteristics of the four passenger segments can assist them in developing service and communication strategies to cater to the different passenger needs.
Report/Paper Numbers: 19-00826
Language: English
Authors: Pan, Jing YuTruong, DothangPagination: pp 877-888
Publication Date: 2019-4
Serial:
Transportation Research Record: Journal of the Transportation Research Board
Volume: 2673 Media Type: Digital/other
Features: References
(39)
; Tables
(4)
TRT Terms: Geographic Terms: Subject Areas: Planning and Forecasting; Railroads
Files: TRIS, TRB, ATRI
Created Date: Feb 13 2019 10:23AM
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