The main objective of this study was to identify the status and development opportunities and evaluate the economic viability of investments in large-scale photovoltaic installations in Southeastern Poland. The primary data sources used in the study were empirical materials from all photovoltaic installations implemented with support from the Regional Operational Program of the Lublin Voivodeship (ROP WL) for 2007–2013 (31 projects). The following indices were used to evaluate the economic efficiency of the investments studied: rate of return on investment (ROI), simple payback period (SPP), net present value of investment (NPV), internal rate of return (IRR), discounted payback period (DPBT), and averaged unit cost of electricity generation (LCOE). They were carried out for three scenarios–baseline, conservative, and optimistic–in two variants, for actual capital expenditures considering financial support used and without subsidies. It was determined that the expected lifetime of the studied investments would be 25 years. The sensitivity analysis shows that, regardless of the adopted scenario, investments in solar thermal power with the level of support that took place under the 2007–2013 financial perspective were reasonable long-term investments. In the least favorable scenario (conservative) included in the analysis, the discounted payback period ranged from 8.1 to 22 years. In the optimistic scenario, DPBT values ranged from 5.6 years to more than 15 years. The payback period (both simple and discounted) for investments with the subsidy was, on average, almost twice as fast as for investments without the subsidy, while the average unit cost of electricity generation with the subsidy was about 30% lower than without it.

The material developed focuses on the analysis of energy efficiency trends in Poland, utilising ODEX indicators for the sectors of industry, transport, households and in general, from 2011 to 2021. The objective of the study is to assess the progress made in energy efficiency and to forecast future trends in these sectors. The methods employed are based on statistical modelling of time series, taking into account sector-specific energy consumption dynamics. The following techniques were employed: linear regression, cluster analysis to identify patterns of change, statistical hypothesis testing for energy efficiency and simplified autoregressive models. The results demonstrated significant improvements in energy efficiency in the industrial sector, stability of the ODEX indicator in the transport sector and gradual improvements in households and overall. The prediction indicates an upward trend in the ODEX indicator in the short term, suggesting an increase in energy demand. However, it also predicts a decline in the long term, which may indicate the effectiveness of future energy efficiency strategies and investments. Consequently, the necessity for continued efforts to increase energy efficiency and further research into the factors influencing energy efficiency in different economic sectors is emphasised.

Subject and purpose of work: The aim of this study is to analyse the profitability level of industrial companies in various phases of their lifecycle. Materials and methods: The article uses data from individual annual financial statements of industrial companies in accordance with the classification of the Warsaw Stock Exchange. In order to investigate whether there are essential differences in the level of profitability of companies in various phases of their lifecycle, due to significant deviations from normality, the nonparametric Kruskal-Wallis H test was used. To find out which lifecycle phases differ significantly in terms of the level of analysed profitability ratios, a test of multiple comparisons of medium ranks was used (Post-hoc Dunn’s test). Results: The obtained research results show that a given lifecycle phase significantly differentiates the level of the analysed profitability indices. Conclusions: Based on the conducted research, it was found that the company’s lifecycle phase statistically significantly differentiates the level of the analysed profitability indices. In the early phases of the lifecycle, the level of profitability in the surveyed companies increased gradually reaching maximum and stable values in the phase of maturity or shake-out, after which it decreased in the decline phase. This points to an evolutionary transition of individual companies to the next phase of the lifecycle.

Globalisation, population growth, climate change, and energy-policy shifts have deepened interdependence between agri-food and energy systems, amplifying price volatility. This study examines the determinants of global wheat and corn price dynamics over 2000–2023, emphasising energy markets (oil and biofuels), agronomic and climatic factors, population pressure, and cross-market interdependencies. Using multiple linear regression with backward selection on annual global data from official sources (FAO, USDA, EIA and market series), we quantify the relative contributions of these drivers. The models explain most of the variation in world prices (R² = 0.89 for wheat; 0.92 for corn). Oil prices are a dominant covariate: a 1 USD/barrel increase in Brent is associated with a 1.33 USD/t rise in the wheat price, while a 1 USD/t increase in the corn price raises the wheat price by 0.54 USD/t. Lower biodiesel output per million people is linked to higher wheat prices (+0.67 USD/t), underscoring the role of biofuel supply conditions. We also document an asymmetric yield effect—higher yields correlate positively with wheat prices but negatively with corn—consistent with crop-specific market mechanisms. Although temperature and precipitation were excluded from the regressions due to collinearity, their strong correlations with yields and biofuel activity signal continuing climate risk. The contribution of this study lies in integrating energy, climate, and agricultural market factors within a single empirical framework, offering evidence of their joint role in shaping staple grain prices. These findings add to the literature on food–energy linkages and provide insights for sustainability policies, particularly the design of integrated energy–agriculture strategies and risk-management instruments to enhance resilience in global food systems.

This paper presents research on the dependency between the particular stages of a firm’s life cycle and selected capital structure ratios. The findings are in line with the pecking order theory of capital structure, stating that early stages of a firm’s life cycle should be characterised by the tendency for financing through debt. However, this stands in opposition to both the trade-off theory, and the research conducted on several Polish companies. The enterprises in their stages of introduction and growth were characterised by a substantially lower level of total assets to shareholders' equity ratio in their sources of finance, when compared to those in the shake-out stage. The companies in their growth stage were marked by a significantly higher level in the share of long-term commitments in sources of finance, as compared to the enterprises in their maturity, shake-out and decline stage. Also, the introduction stage showed a significantly higher level in the share of short-term commitments in sources of finance, in comparison with those being in their growth, maturity, and shake-out stage.