Techno-Economic Sustainability Potential of Large-Scale Systems: Forecasting Intermodal Freight Transportation Volumes

Author:

Chupin Alexander1ORCID,Morkovkin Dmitry2ORCID,Bolsunovskaya Marina3,Boyko Anna4,Leksashov Alexander3

Affiliation:

1. Institute of Foreign Economic Security and Customs Affairs, Peoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya Street, 117198 Moscow, Russia

2. Institute for the Study of International Economic Relations, Financial University under the Government of the Russian Federation, 125993 Moscow, Russia

3. Graduate School of Intelligent Systems and Supercomputing Technologies, Peter the Great St. Petersburg Polytechnic University (SPbPU), 29 Polytechnicheskaya Street, 195251 St. Petersburg, Russia

4. Industrial Streaming Data Processing Systems Lab, Peter the Great St. Petersburg Polytechnic University (SPbPU), 29 Polytechnicheskaya Street, 195251 St. Petersburg, Russia

Abstract

The sustainability of large economies is one of the most important challenges in today’s world. As the world strives to create a greener and more efficient future, it becomes necessary to accurately analyze and forecast freight volumes. By developing a reliable freight transportation forecasting model, the authors will be able to gain valuable insights into the trends and patterns that determine the development of economic systems. This will enable informed decisions on resource allocation, infrastructure development, and environmental impact mitigation. Such a model takes into account various factors such as market demand, logistical capabilities, fuel consumption, and emissions. Understanding these dynamics allows us to optimize supply chains, reduce waste, minimize our carbon footprint, and, ultimately, create more sustainable economic systems. The ability to accurately forecast freight volumes not only benefits businesses by enabling better planning and cost optimization but also contributes to the overall sustainable development goals of society. It can identify opportunities to shift to more sustainable modes of transportation, such as rail or water, and reduce dependence on carbon-intensive modes, such as road or air. In conclusion, the development and implementation of a robust freight forecasting model is critical to the sustainability of large-scale economic systems. Thus, by utilizing data and making informed decisions based on these forecasts, it is possible to work toward a more sustainable future for future generations.

Funder

Ministry of Science and Higher Education of the Russian Federation

Russian Science Foundation

Publisher

MDPI AG

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