Skip to main content
Top
Published in: Innovative Infrastructure Solutions 6/2022

01-12-2022 | Technical Paper

Examining the Effect of COVID-19 on rail freight volume and revenue using the ARIMA forecasting model and assessing the resilience of Indian railways during the pandemic

Authors: Aditya Saxena, Ankit Kumar Yadav

Published in: Innovative Infrastructure Solutions | Issue 6/2022

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

India implemented a nationwide lockdown on 22 March 2020 to prevent Coronavirus (COVID-19) from spreading throughout the nation. Only the most critical services were running during this period. As a result of the pandemic, several organizations, including the travel industry, put a moratorium in place. This included the Indian Railways. In spite of the lockdown, the freight services were operational and carrying out essential duties, but the volume of freight and revenue generated was adversely affected. Railways contribute around 1% to the overall GDP of India and a significant part of India's economy is freight transport by rail. This necessitates an analysis of rail freight volume and corresponding revenue loss due to COVID-19. The present study is an attempt to estimate these losses. Based on the monthly historical data the present study employed the ARIMA forecasting model to develop a scenario and measure freight volume without COVID-19. Under the first scenario, month-wise actual historical freight volumes were considered for the period from April 2012 to November 2021. On the other hand, in the second scenario, the monthly historical data from April 2012 to March 2020 and from October 2020 to November 2021 were used as-is, while from April 2020 to September 2020, ARIMA modelling was used to forecast freight volume without the effect of COVID-19, since the first lockdown occurred in the latter days of March 2020. Further, in order to predict revenue loss, we developed a linear regression model based on the temporal data (April 2012–November 2021) for freight volume and revenue generated by Indian Railways. Based on the ARIMA modelling, the total loss of freight volume and revenue was estimated at 149.08 million tonnes and INR \(16712.68\) crores, respectively. Furthermore, the present study also discusses the resilience shown by the Indian railways during the outbreak of COVID-19.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
29.
go back to reference Autoridad Nacional del Servicio Civil (2021) Monthy Data: Indian Railwys. Indian Railwys Autoridad Nacional del Servicio Civil (2021) Monthy Data: Indian Railwys. Indian Railwys
36.
go back to reference Williams BM, Durvasula PK, Brown DE (1998) Urban freeway traffic flow prediction application of seasonal autoregressive integrated. Transp Res Rec 1644(98):132–141CrossRef Williams BM, Durvasula PK, Brown DE (1998) Urban freeway traffic flow prediction application of seasonal autoregressive integrated. Transp Res Rec 1644(98):132–141CrossRef
41.
go back to reference Suwardo MN, Kamaruddin I (2009) Arima models for bus travel time prediction. J Inst Eng 71(2):49 Suwardo MN, Kamaruddin I (2009) Arima models for bus travel time prediction. J Inst Eng 71(2):49
Metadata
Title
Examining the Effect of COVID-19 on rail freight volume and revenue using the ARIMA forecasting model and assessing the resilience of Indian railways during the pandemic
Authors
Aditya Saxena
Ankit Kumar Yadav
Publication date
01-12-2022
Publisher
Springer International Publishing
Published in
Innovative Infrastructure Solutions / Issue 6/2022
Print ISSN: 2364-4176
Electronic ISSN: 2364-4184
DOI
https://doi.org/10.1007/s41062-022-00929-2

Other articles of this Issue 6/2022

Innovative Infrastructure Solutions 6/2022 Go to the issue