Qualitative–Quantitative Warning Modeling of Energy Consumption Processes in Inland Waterway Freight Transport on River Sections for Environmental Management

Elżbieta Szaruga and Elżbieta Załoga
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Elżbieta Szaruga: Department of Transport Management, Institute of Management, University of Szczecin, Cukrowa 8 Street, 71-004 Szczecin, Poland
Elżbieta Załoga: Department of Transport Management, Institute of Management, University of Szczecin, Cukrowa 8 Street, 71-004 Szczecin, Poland

Energies, 2022, vol. 15, issue 13, 1-21

Abstract: The article concerns the assessment of the energy consumption of inland waterway freight transport on river sections in the context of environmental management. The research question was: Does the choice of the route determine the total energy consumption of inland waterway transport and therefore affect the potential of cargo transport of this mode? The article aims to indicate the directions of energy consumption by inland waterway freight transport depending on the route selection, the volume of transport, and the length of the route. The study was carried out on nine sections of the Odra River in Poland during the years 2015–2020. Statistical and econometric techniques were used, i.e., ANOVA, generalized linear models, Eta coefficients, Lasso and Ridge regularization, and X-average control charts (Six Sigma tool). Based on early warning models, river sections were identified that favor the rationalization of energy consumption in terms of the network. The sensitivity of the energy consumption of inland waterway transport to changes in the average distance and in the volume of transport was examined. With the use of Six Sigma tools, the instability of the energy consumption processes of inland waterway transport was identified, paying attention to the source of the mismatch, which was the increase in the average transport distance in the sections, where energy consumption increased due to the operational and navigation conditions of these sections.

Keywords: data science; energy consumption processes; inland waterway transport; Lasso regression; Latent Dirichlet Allocation; warning modeling; Six Sigma (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (12)

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