Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/27824
Title: A dynamic pricing strategy model for Indian Railways
Authors: Singh, Kartikeya
Dhake, Pushkaraj
Narayanaswami, Sundaravalli
Keywords: Dynamic Networks;Microeconomics;Rail Vehicles;Queueing Theory;Taxation Policy;Transportation Economics
Issue Date: 23-Nov-2023
Publisher: Springer Nature
Abstract: The Indian Railways has adopted a dynamic pricing mechanism for its premium trains like Shatabdi, Rajdhani, and Duronto. This led to an increase in its revenue but also a fall in passenger traffic. In this paper, we have analyzed the existing dynamic pricing model. A major flaw in the existing system is that the present system is only a fare hike system rather than a dynamic pricing system as there is no provision for a decrease in prices when the demand is low. Considering this, we have developed a new model that incorporates both inter-temporal pricing and demand-based pricing to come up with the dynamic fares along with the provision of having a downside in case of low demand. We developed a route selection criteria based on the key parameters identified by us where dynamic pricing would yield good results. The model was then tested on these routes using real-time data to determine the feasibility of the dynamic pricing system.
Description: The Indian Railways has adopted a dynamic pricing mechanism for its premium trains like Shatabdi, Rajdhani, and Duronto. This led to an increase in its revenue but also a fall in passenger traffic. In this paper, we have analyzed the existing dynamic pricing model. A major flaw in the existing system is that the present system is only a fare hike system rather than a dynamic pricing system as there is no provision for a decrease in prices when the demand is low. Considering this, we have developed a new model that incorporates both inter-temporal pricing and demand-based pricing to come up with the dynamic fares along with the provision of having a downside in case of low demand. We developed a route selection criteria based on the key parameters identified by us where dynamic pricing would yield good results. The model was then tested on these routes using real-time data to determine the feasibility of the dynamic pricing system.
URI: http://hdl.handle.net/11718/27824
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