A Structural Analysis of Freight Delays in the Indian Railway Network

51 Pages Posted: 13 Dec 2023 Last revised: 22 Jan 2024

See all articles by Himanshu Arha

Himanshu Arha

Indian School of Business (ISB), Hyderabad - Operations Management

Kashish Arora

Indian School of Business; Cornell University

Milind G. Sohoni

Indian School of Business

Raja Gopalakrishnan

Centre for Railway Information Systems

Date Written: January 19, 2024

Abstract

Despite being one of the most cost-effective and sustainable modes for transporting freight, railways globally have been rapidly losing market share in the in-land freight transportation sector. One of the salient reasons for this is the extremely slow speed of freight trains in many parts of the world. For example, in Indian Railways, the world's fourth-largest in size, the average freight train speed is only around 25 kmph and has remained constant for the past few decades. The slow pace of freight trains is because passenger trains, which share the same infrastructure, get prioritized in dispatch by railway traffic managers (also known as section controllers). In this paper, we empirically study freight delays in the Indian railway setting by analyzing how section controllers make freight train stop and hold decisions while managing the movement of freight trains. Subsequently, we propose policies to reduce freight delays and, thus, increase trains' speed through the network. We use detailed high-frequency network congestion data and estimate a structural model to estimate the key parameters underlying the controllers' decisions. The estimated parameters provide empirical evidence for (i) the priority accorded to passenger trains over freight trains, (ii) the push effects in the freight train queue, and (iii) the strategic behavior of section controllers in holding trains at larger stations. Using the estimated model, we conduct a set of counterfactual analyses to address the problem of slow freight train speeds. First, we evaluate the impact of constructing Freight Only Corridors (FOCs), high-capacity corridors reserved for freight transport. We find that the FOCs lead to about a 29% reduction in freight train delays and a 12% improvement in train speeds. Then, we also evaluate non-capacity-investment-based alternatives to FOCs, like (i) threshold-based releases for freight trains dwelling longer than a specified time limit and (ii) freight capacity consolidation by using vertically stacked trains. Interestingly, we find that our non-capacity interventions can provide benefits similar to those of FOCs while being considerably cheaper. Specifically, a 45-minute threshold release policy leads to around 31% reduction in dwell times and 9% increase in speeds. Similarly, vertically consolidating freight capacity by about 25% leads to around a 10% increase in speed, comparable to the improvement achievable with the FOC. Our policy recommendations for improving freight speeds could enhance the overall efficiency of India's transportation infrastructure, benefiting the country's economic and social development.

Keywords: Freight Operations, Indian Railways, Empirical Analysis, Choice Models, Wait times, Structural Estimation

Suggested Citation

Arha, Himanshu and Arora, Kashish and Sohoni, Milind G. and Gopalakrishnan, Raja, A Structural Analysis of Freight Delays in the Indian Railway Network (January 19, 2024). Available at SSRN: https://ssrn.com/abstract=4631346

Himanshu Arha

Indian School of Business (ISB), Hyderabad - Operations Management ( email )

India

Kashish Arora (Contact Author)

Indian School of Business ( email )

Gachibowli
Hyderabad, 500032
India

Cornell University ( email )

Ithaca, NY 14853
United States

Milind G. Sohoni

Indian School of Business ( email )

Hyderabad, Gachibowli 500 032
India

HOME PAGE: http://www.isb.edu/faculty/milind_sohoni

Raja Gopalakrishnan

Centre for Railway Information Systems ( email )

Chanakyapuri
New Delhi, Delhi 110 021
India

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
123
Abstract Views
528
Rank
406,376
PlumX Metrics