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Modelling new pricing strategies for the Santiago Metro

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  • Bianchi, R.
  • Jara-Di­az, S. R.
  • de D. Ortúzar, J.

Abstract

After twenty years of operation the Santiago Metro decided to start a new strategy of price differences by period in order to decrease congestion in the morning peak and to postpone the acquisition of new equipment. In this paper we report the results of a model specifically designed to test the impact of different price levels on patronage by period. Stated preference (SP) data was collected, focusing on three aspects: change in time of travel, price differences and comfort improvements. A goods-leisure microeconomics framework was adopted to decide on users segmentation and model specification. Two methodological aspects were explored, the non-linear marginal valuation of time displacements and the different known ways to analyse SP rating experiments. In this quest, models were calibrated both with a standard and an optimal probabilistic interpretation of the semantic scale and with the ordinal probit and binary logit models. Comparisons were made and conclusions reached about the more appropriate approach. Finally, the current time-of-day pricing strategy of the Santiago Metro, which commenced operation in February 1994, was simulated using the best models reported in the paper. This was done in order to test their validity against an observed reality.

Suggested Citation

  • Bianchi, R. & Jara-Di­az, S. R. & de D. Ortúzar, J., 1998. "Modelling new pricing strategies for the Santiago Metro," Transport Policy, Elsevier, vol. 5(4), pages 223-232, October.
    • Handle: RePEc:eee:trapol:v:5:y:1998:i:4:p:223-232
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    References listed on IDEAS

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    1. Jara-Díaz, Sergio R. & Farah, Marcelo, 1987. "Transport demand and users' benefits with fixed income: The goods/leisure trade off revisited," Transportation Research Part B: Methodological, Elsevier, vol. 21(2), pages 165-170, April.
    2. Small, Kenneth A, 1992. "Trip Scheduling in Urban Transportation Analysis," American Economic Review, American Economic Association, vol. 82(2), pages 482-486, May.
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    2. José Holguín-Veras & Sergio Jara-Díaz, 2010. "Optimal Two-Part Pricing and Capacity Allocation with Multiple User Classes and Elastic Arrivals at Constrained Transportation Facilities," Networks and Spatial Economics, Springer, vol. 10(4), pages 427-454, December.
    3. 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.
    4. Thorhauge, Mikkel & Swait, Joffre & Cherchi, Elisabetta, 2020. "The habit-driven life: Accounting for inertia in departure time choices for commuting trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 272-289.
    5. Wang, Yu & Wang, Yacan & Ettema, Dick & Mao, Zidan & Charlton, Samuel G. & Zhou, Huiyu, 2020. "Commuter value perceptions in peak avoidance behavior: An empirical study in the Beijing subway system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 70-84.
    6. Joaquín De Cea & J. Enrique Fernández & Valérie Dekock & Alexandra Soto, 2004. "Solving network equilibrium problems on multimodal urban transportation networks with multiple user classes," Transport Reviews, Taylor & Francis Journals, vol. 25(3), pages 293-317, January.

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