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Effects Of Temporally Differential Fares On Taipei Metro Riders’ Mode And Time-Of-Day Choices

Author

Listed:
  • Lawrence Lan
  • Hsiang-Yi Lee
  • Chieh-Hua Wen

Abstract

Introducing temporally differential fares to shift a portion of peak-hour demand to offpeak hours shows promise in mitigating the overcrowded Taipei Metro system during peak hours. This study looked to elucidate how Taipei Metro riders would change their times of travel or use of other travel modes, should peak-hour surcharge or off-peak discount fare schemes be introduced. Multinomial logit and nested logit models were employed to depict the riders’ stated behavior, in terms of arrival times and mode choices, within the context of a scenario involving tested differential fare levels. Results showed that introducing temporally differential fares would prompt a portion of peak-hour Metro riders to shift to off-peak periods, or even to choose the use of other modes. The Metro riders were sensitive to the tested differential fare levels, especially the peakhour surcharge. The afternoon riders were more sensitive to proposed fare changes than the morning riders. To implement the temporally differential fares successfully within the Metro system, it is suggested that peak hours be carefully designated and that peak-hour riders be clearly distinguished from off-peak riders.

Suggested Citation

  • Lawrence Lan & Hsiang-Yi Lee & Chieh-Hua Wen, 2010. "Effects Of Temporally Differential Fares On Taipei Metro Riders’ Mode And Time-Of-Day Choices," Articles, International Journal of Transport Economics, vol. 37(1).
    • Handle: RePEc:jte:journl:2010:1:37:5
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    Cited by:

    1. Adnan, Muhammad & Nahmias Biran, Bat-hen & Baburajan, Vishnu & Basak, Kakali & Ben-Akiva, Moshe, 2020. "Examining impacts of time-based pricing strategies in public transportation: A study of Singapore," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 127-141.
    2. Antonín Pavlíček & František Sudzina, 2020. "Intergroup Comparison of Personalities in the Preferred Pricing of Public Transport in Rush Hours: Data Revisited," Sustainability, MDPI, vol. 12(12), pages 1-9, June.
    3. Yang, Hai & Tang, Yili, 2018. "Managing rail transit peak-hour congestion with a fare-reward scheme," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 122-136.

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