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Abstract: The main problem this research addresses is the EU energy policy, which focuses on a critical analysis of strategic energy management in all process phases. Particular emphasis is placed on strategic control, which is a key phase of the management process. Strategic control includes evaluating the effectiveness of implementing planned measures and making decisions about necessary adjustments or changes. The purpose of the study is to assess how well EU energy management strategies are aligned with policy objectives, in particular, to ensure energy security, sustainability and economic competitiveness, and at the same time to identify areas where improvements are needed to address current challenges. Energy management in the European Union is a crucial aspect of its energy policy, which focuses on ensuring energy security, sustainability and efficiency. Since the middle of the 20th century, organisations' increasing energy intensity has emphasized the need for a comprehensive and flexible approach. Energy management involves controlling the entire life cycle of energy - from extraction, conversion and distribution to consumption and waste disposal - in a complex environment shaped by various external factors. These challenges become even more pronounced in regions that experience frequent environmental, economic or geopolitical changes. Designing a universal model for global energy management is difficult because of the different conditions, regulations, and energy needs worldwide. Adaptable and adaptive strategies are essential to respond to supply and demand fluctuations, integrate renewable energy sources, manage geopolitical risks and achieve sustainability goals. Therefore, energy management must evolve to respond to a dynamic global environment. The EU prioritizes energy security but lacks a unified approach, which creates challenges in defining and measuring energy security. The absence of standardized criteria makes it difficult to strategically evaluate policies and make decisions, which could have long-term consequences for both energy and national security. Initially, energy security was focused on stable supply for economic growth, but global changes – such as rising demand, geopolitical tensions and environmental concerns – have made it more complex. The recent years have underscored significant vulnerabilities in global energy security and the sustainability of energy systems, particularly in Europe. The dual crises of the COVID-19 pandemic and the conflict in Ukraine have highlighted the urgency of addressing these challenges, pushing the European Union to accelerate its efforts toward more sustainable and secure energy practices. In response, the EU has diversified energy sources and strengthened energy security to reduce its dependence on politically unstable suppliers. Given the complexity of the geopolitical situation, disrupted supply chains and the EU's clear official commitment to decarbonisation by 2050, the above should be viewed from different angles. EU energy policy (short-term and long-term) is conditioned by the action of many factors, which differ in type, intensity of action and effect (positive or negative) - but the need to analyse existing and define new methodologies for evaluating the effectiveness of EU energy policy is evident. The doctoral dissertation examines the above and suggests improvements.
Keywords: Energy management, sustainable management, energy security, aggregate index, composite indicator
Published in DKUM: 10.04.2025; Views: 0; Downloads: 15
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Abstract: The main objective of this paper is to analyze model settings of the International Energy Security Risk Index developed by the U.S. Chamber of Commerce. The study was performed using stepwise regression, principal component analysis, and Promax oblique rotation. The conclusion of the regression analysis shows that Crude Oil Price and Global Coal Reserves are sufficient to explain 90% of the variance of the Index. However, if a model that explains 100% of the variance of the Index is chosen and other variables are added, Global Coal Reserves loses importance due to the presence of other parameters in which it is contained. Regardless of the chosen model of analysis, it is evident that there is room for revising the Index and removing variables that do not contribute to its precision. The research showed that the main disadvantage of the variables that make up the Index rests with the fact that the variables are of different degrees of generality, that is, one parameter is contained in other parameters (unclear which other). The research covers data for 25 countries over a 26-year period, with the first year of the research being 1980 and the last 2016 (the latest available report).
Keywords: international energy security risk index, analysis, stepwise regression, principal component analysis, Promax oblique rotation
Published in DKUM: 04.02.2025; Views: 0; Downloads: 16
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Abstract: In the heavy industry, the value of cargo transported by rail is very high. Due to high value, poor security and volume of rail transport, the theft cases are often. The main problem of securing rail transport is predicting the location of a high probability of risk. Because of this,the aim of the presented research was to predict the highest probability of rail cargo theft for areas. It is important to prevent theft cases by better securing the railway lines. To solve that problem the authors' model was developed. The model uses information about past transport cases for the learning process of Artificial Neural Networks (ANN) and Machine Learning (ML).The ANN predicted the probability for 94.7% of the cases of theft and the Machine Learning identified 100% of the cases. This method can be used to develop a support system for securing the rail infrastructure.
Keywords: rail transport security, supply chain disruption, drones, security support systems, cargo theft, predicting, logistics, artificial neural network, drone monitoring, machine learning
Published in DKUM: 28.01.2025; Views: 0; Downloads: 4
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Abstract: Today, sharing knowledge requires taking into account many aspects. Variable environmental conditions, the people factor, and the security of resources are just a few that should be considered for a noticeable improvement in the functioning of the company. Supporting this course of action requires the identification of all barriers that may exist in the enterprise. Only the owner and senior management by establishing system and organizational changes can influence this element of the business. The aim of the article is to indicate the problems in this respect that block the proper functioning of the company in the field of information and knowledge exchange. The survey was conducted with the help of a questionnaire among 189 respondents. The industry has significantly decreased in the last few decades, currently there are 307 companies operating in Poland. Conclusions from the conducted research were collected on the basis of a questionnaire survey. The further stage of the research will be to compare the collected results with the results from Western European countries.
Keywords: knowledge sharing, knowledge management, information security, knowledge exchange, business organization, Poland
Published in DKUM: 22.10.2024; Views: 0; Downloads: 7
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Abstract: Auditing, as a form of control (for example over financial management or compliance), has traditionally relied on manual processes that are time-consuming, labor-intensive and prone to human error. With the advent of robotic process automation (RPA), there has been a paradigm shift from manual to automated processes in audit processes as well. Automation dates back to the 1990s, which led to the creation of robotic process automation (RPA) tools. Today we are approaching or we are in the fourth industrial revolution, the era of universal automation. RPA refers to the use of software robots (or "bots") to automate repetitive rule-based activities previously performed by humans. As companies try to keep up with rapid technological improvements, incorporating RPA into audit processes provides a number of benefits that can radically change auditing. RPA has emerged as a transformative technology in auditing, changing established approaches with its ability to improve productivity, accuracy and compliance. One of the most significant benefits of RPA in auditing is its ability to increase efficiency. Traditional audit procedures can sometimes be time-consuming and labor-intensive, as auditors must manually collect and evaluate data from multiple sources. RPA accelerates these activities by automating common tasks such as data entry, coordination and report generation. For example, an RPA robot can be trained to collect financial data from multiple sources (eg from multiple companies) and verify its accuracy using established criteria. This not only reduces the time required to perform audits, but also eliminates the possibility of human error. In addition to efficiency, there is another key advantage: accuracy. RPA enables auditors to take proactive measures to reduce risk, thereby protecting the financial integrity and reputation of the organization. By automating mundane and repetitive activities, RPA allows auditors to focus on more strategic activities that deliver value to the business. Auditors (in the broadest sense) can spend more time evaluating data models, finding areas for improvement, and making strategic suggestions to management. The aim of this bachelor's degree thesis is to explore and demonstrate the application of RPA in audit procedures, highlighting its benefits such as increased productivity, improved quality of rapid processing of large databases, improved risk management, and cost savings. The thesis also discusses the challenges and considerations related to the implementation of RPA in audit practices. The history of RPA is detailed, revealing its use by different industries and their goals. The thesis defines all types of RPA tools and their advantages and weaknesses. It also distinguishes between artificial intelligence (AI) and RPA, as it can confuse the activities of RPA tools with AI.
Keywords: robotic process automation, RPA, monitoring, analytics, security, productivity, auditing, audit process.
Published in DKUM: 09.09.2024; Views: 25; Downloads: 36
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