Choosing the Production Function Model for an Optimal Measurement of the Restructuring Efficiency of the Polish Metallurgical Sector in Years 2000–2015

Restructuring of the Coal Mining Industry and the Challenges of Energy Transition in Poland (1990–2020)

The European Union’s climate policy and the energy transition associated with it force individual countries, their economies and their industrial sectors to carry out thorough changes, often of a deep, high-cost and restructuring nature. The aim of the article is to provide a multidimensional assessment of the forms and effects of the restructuring of coal mining companies in Poland in light of the current energy transition process. The research problem is encapsulated within the following two interdependent questions: Has the restructuring process allowed the coal mining industry to achieve sufficient efficiency to sustainably compete in the open market, and to what extent, if at all, have the objectives of restructuring been achieved from the perspective of changes in the energy mix? The research covers all coal mining companies included in the official statistics. It adopts a long-term perspective (1990–2020), dating from the beginning of the systemic transformation in Poland. The research involved the use of multivariate financial analysis methods, including the logit model for predicting the degree of financial threat, as well as taxonomic methods for assessing the dissimilarity of structures and their concentration. The general conclusion of the research is that there has been a lack of consistency (follow-up) between the forms and effects of restructuring in coal mining companies in Poland on the one hand and changes in the composition of the country’s energy mix as a result of the energy transition on the other. In particular, this means that such restructuring, being neither effective nor efficient, has failed to accelerate change in the energy mix.

Resource Intensity vs. Investment in Production Installations—The Case of the Steel Industry in Poland

Resource intensity is a measure of the resources needed for the production, processing and disposal of good or services. Its level decides on the costs the companies have to bear both for production and for environmental protection, which in turn have a crucial importance for their competitiveness. Given these facts, our study analyses the issues of resource intensity in the Polish steel industry in correlation to investments made, and more specifically, to the impact of investments on the consumption of energy media used during steel production. Its key element is the development of econometric models presenting the impact of investments on resource consumption in steel production in Poland. Electricity and coke consumption were analysed according to manufacturing installation. The research was carried out on the basis of statistical data for the period of 2004–2018. The obtained findings confirmed the impact of the increase in investment on the decrease in the resource intensity in steel production in Poland. These facts have implications for both policy makers, as they confirm the thesis on a direct correlation between investments in technology and a reduction in resource intensity (environmental protection), as well as company managers. In the case of the latter, the data show the actions which companies should focus on in their activities.

Risk Assessment and Mitigation Model for Overseas Steel-Plant Project Investment with Analytic Hierarchy Process—Fuzzy Inference System

This paper presents an analytic hierarchy process (AHP)-fuzzy inference system (FIS) model to aid decision-makers in the risk assessment and mitigation of overseas steel-plant projects. Through a thorough literature review, the authors identified 57 risks associated with international steel construction, operation, and transference of new technologies. Pairwise comparisons of all 57 risks by 14 subject-matter experts resulted in a relative weighting. Furthermore, to mitigate human subjectivity, vagueness, and uncertainty, a fuzzy analysis based on the findings of two case studies was performed. From these combined analyses, weighted individual risk soring resulted in the following top five most impactful international steel project risks: procurement of raw materials; design errors and omissions; conditions of raw materials; technology spill prevention plan; investment cost and poor plant availability and performance. Risk mitigation measures are also presented, and risk scores are re-assessed through the AHP-FIS analysis model depicting an overall project risk score reduction. The model presented is a useful tool for industry performing steel project risk assessments. It also provides decision-makers with a better understanding of the criticality of risks that are likely to occur on international steel projects.