This article concerns the identification of inefficient airports and the exploration of spatial autocorrelation for programming sustainable development. The first research question was: do domestic airports cooperate by shifting passenger service and traffic to the geographically closest airport to respect the idea of sustainable development (in view of the rationalization of energy consumption)? The second question was: do they excessively compete for passengers and the carriers serving them? The aim was to identify ineffective units (taking into account energy consumption, airplane traffic, and passenger movement) and to evaluate the spatial autocorrelation between national airports, which shows whether airports cooperate or compete with each other. The study was conducted on 12 airports. An innovative extension of the data envelopment analysis method using methods in the field of spatial econometrics (including two-dimensional Moran I statistics and local LISA statistics) and artificial intelligence was applied. It was verified that ineffective airports have a non-rationalized structure of inputs to outputs. Based on the map-graph of connections, airports have been identified to which part of airplane traffic service can be transferred. Based on Moran statistics and local LISA statistics, it was confirmed that airports compete with each other. There was a strong polarization of efficient airports.

Confidence in intermodal transport has not yet been defined. There are many different approaches to the concept of trust. However, the authors have integrated them with the paradigm shift in light of the challenges of sustainability. The objective of this article is to indicate the directions and criteria for that indicate the implementation of the paradigm shift, relative to the idea of sustainable transport. The auxiliary objective is to predict which countries in a given year will have the TRUST status, i.e., implement the paradigm shift, and which ones will not implement it (DISTRESS). The study used taxonometric techniques and built a model using General Discriminant Analysis. On these bases, the utility function was approximated, including the directions of implementation of the paradigm shift, depending on the scale of the environmental load of transport. Over the course of this research, an original and innovative econometric model was constructed, pointing to three variables which have the greatest impact on trust. Thanks to the cognitive value of the model, it is possible to identify individuals who deserve trust (i.e., it will implement the paradigm shift) with 93% probability. In the future, it is worth expanding the research by programing models for each country.

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.

This paper presents the synchronisation of economic cycles of GDP and crude oil and oil products cargo volumes in major Polish seaports. On the one hand, this issue fits into the concept of sustainable development including decoupling; on the other hand, the synchronisation may be an early warning tool. Crude oil and oil products cargo volumes are a specific barometer that predicts the next economic cycle, especially as they are primary sources of energy production. The research study applies a number of TRAMO/SEATS methods, the Hodrick–Prescott filter, spectral analysis, correlation and cross-correlation function. Noteworthy is the modern approach of using synchronisation of economic cycles as a tool, which was described in the paper. According to the study results, the cyclical components of the cargo traffic and GDP were affected by the leakage of other short-term cycles. However, based on the cross-correlation, it was proved that changes in crude oil and oil products cargo volumes preceded changes in GDP by 1–3 quarters, which may be valuable information for decision-makers and economic development planners.

The article concerns the verification of links between the energy intensity of public urban transport, regional economic development and urbanisation in the light of sustainable development challenges and club convergence processes. Three research questions were formulated in the article: (1) Does the regional economic development of voivodeships affect the energy intensity of public urban transport? (2) Does urbanisation shape energy consumption patterns in public urban transport (and are there agglomeration effects)? (3) Does the level of urbanisation of voivodeships depend on their regional level? The study covered 16 subregions of Poland from 2010 to 2020. A spatial dynamic exploration of the relationships between energy intensity patterns of public urban transport and the phenomenon of urbanisation and regional economic development was carried out. Panel models of vector autoregression and panel causality testing were used. The influence of the economic development of regions and the level of urbanisation on energy intensity patterns of public urban transport was confirmed. The link between economic development and the process of urbanisation was identified. An additional effect was noticed (novelty knowledge), i.e., there is a delayed club convergence between voivodeships in the area of energy intensity of public urban transport, regional economic development and urbanisation (polyconvergence).