Aim: This paper proposes a novel paradigm of Artificial Intelligence (AI) grounded in the epistemological process of converting tacit knowledge into explicit knowledge. Drawing on the foundational philosophies of science, particularly the works of Popper, Kuhn, Lakatos, and Gospodarek, the study conceptualizes AI not merely as a computational tool but as a systemic method for epistemic transformation. The paradigm is structured as a Lakatosian Research Programme, with a clearly defined hard core asserting that AI enables the symbolic representation of internalized, experiential knowledge. Surrounding this core is a protective belt of auxiliary hypotheses derived from general systems theory, cybernetics, machine learning, and symbolic processing. The programme's heuristics guide theoretical and technological advancements while preserving its epistemological foundation. By formalizing the tacit-to-explicit knowledge conversion, this paradigm repositions AI as a critical instrument for knowledge creation, management, and application in digital and socio-technical systems. This allows one to build measures and values of generative and language models, which is important from an economic point of view. This research tries to clarify the framework of use AI models for converting tacit knowledge inside a learning data of neural network systems to explicit information requested by the asking. It is important for economic evaluation of AI systems where accuracy considered utility as a criterion. Design / Research methods: Research programme in Lakatos’ sense and multidisciplinary heuristic related to the theory of systems. Conclusions / findings: Artificial Intelligence should be understood not only as a technological artefact but as a systemic method for transforming tacit knowledge into explicit knowledge. The proposed AI paradigm adheres to the structure of a Kuhnian paradigm and a Lakatosian research programme. Its hard core is defined by the thesis that AI operationalizes the conversion of experiential, intuitive, or unconscious knowledge into symbolic, formalized, and actionable representations. Lakatosian protective belt as a dynamic epistemic layer. This AI paradigm offers a progressive problem-shift capacity by enabling novel ways of organizing, analyzing, and applying knowledge in digital and socio-technical environments. It also provides a coherent framework for developing AI systems that are more aligned with human cognitive and organizational processes. Originality / value of the article: This paper introduces: new concepts of usefulness of AI systems, new definition of AI systems based on conversion of the knowledge, original conversion paradigm and research program in Lakatos sense. It is original conceptional heuristic based on philosophy of science in relation to economic usefulness of view AI systems. JEL: C67, C18.
Aim: To enable longitudinal linkage in online panel surveys without collecting direct identifiers and while aligning with modern data-protection requirements Design / Research methods: The article proposes a client-side protocol where participants create a reproducible secret from a self-chosen pseudonym and an ordered image sequence. The browser normalizes and cryptographically hashes these inputs to derive a short alphanumeric core code, adds a modulus-97 checksum for strict local validation, and the backend stores only a salted hash scoped to a specific study (form-family) context. Conclusions / findings: This paper introduces a client-side protocol for generating anonymous yet linkable participant identifiers in web-based surveys by deriving a reproducible code from a user-chosen pseudonym and image sequence entirely in the browser, and by storing only a form-family–salted hash on the server for longitudinal linkage within a study. The design incorporates a checksum for strict client-side validation and is intended to reduce spurious identifiers caused by typographical errors; empirical validation of matching performance, usability, and security properties is left for future work. Originality / value of the article: The work refines SGIC-style respondent-generated linkage by combining graphical secrets with browser-based cryptographic processing, checksum-based client-side validation, and form-family salting-yielding a concrete, implementable algorithm that improves privacy-respecting longitudinal linkage. JEL: C81, C83.
Aim: The purpose of this study is to look into how investor sentiment affected the profit spreads of three significant oil and gas companies from 2014 to 2024: PB PLC, Exxon Mobil, and Chevron. The study investigates the relationship between investor sentiment and market performance, especially during times of global upheaval like the COVID-19 pandemic and the crisis in Russia and Ukraine. Design / Research methods: The study evaluates the correlation between daily profit spreads and weekly investor sentiment indices using a Mixed Data Sampling (MIDAS) regression framework. Analysis is done on data from January 2014 to May 2024. To assess the MIDAS model’s performance and explanatory power, the results are contrasted with those of conventional linear regressions. Conclusions / findings: The findings show a complicated and firm-specific relationship between profit spreads and investor sentiment. However, there are mixed positive and negative MIDAS regression coefficients for lagged sentiment. Because of its strong mean reversion and emphasis on long-term projects, Chevron exhibits little sensitivity. Although the direction and interpretation are still unclear, Exxon Mobil exhibits some notable sentiment effects. The oil and gas industry’s long-term orientation is reflected in PB PLC’s inconsistent sentiment effects. In general, it seems that investor sentiment has little effect on daily stock prices, but it might have a more subtle effect on profit spreads. Originality / value of the article: By integrating high-frequency sentiment data into asset pricing models, this paper adds to the expanding body of research on behavioural finance. In a turbulent decade characterised by pandemics and war, it employs the MIDAS approach in a novel way to evaluate the sentiment-profitability relationships among three multinational oil companies JEL: C32, C58, G11, G12, G14, Q40.
Aim: Reclamation is a complex and costly process that involves technical and biological activities aimed at restoring degraded areas for specific future uses. The effectiveness of reclamation depends on the chosen direction, which influences whether the land can immediately serve its intended function or requires further development. Beyond environmental benefits, reclamation and development efforts support economic growth, job creation, and improved quality of life, while also contributing to the preservation of cultural heritage and sustainable development. The article presents the results of literature review focusing on answering the following questions: how is cultural heritage linked to the issues of the regeneration of degraded areas and how do different forms of regeneration use cultural heritage to counteract the effects of degradation of given areas? Design / Research methods: A secondary study was conducted focusing on reviewing existing research materials, concentrated on summarizing the obtained data. Conclusions / findings: The concepts of reclamation, rehabilitation, restoration, revitalization, recultivation, and revegetation were explained. The research part focused on four approaches to heritage in the context of revitalization: cultural heritage in areas after natural disasters; cultural heritage in areas damaged by human intervention; preparations for intervention in the event of natural disasters and disasters resulting from human intervention; and cultural heritage as a means/tool facilitating the regeneration of given areas. Originality / value of the article: Materials devoted to the subject of heritage are related to four different aspects. Two of them are associated with the preservation of heritage in degraded areas, the third is related to the group of remedial and preventive actions, and only a small part is devoted to heritage as a tool and its role in revitalization processes. JEL: Q01, Q56, Z10.
Aim: To examine the impact of online trading and technological innovations on stock market efficiency, with a focus on the GameStop case as an illustrative example. Research methods: Conceptual and qualitative analysis drawing on the GameStop event, regulatory comparisons between the US and Europe, and a review of literature on electronic trading platforms, financial information dissemination, and social media–driven investor coordination. Findings: Online trading platforms, Web 2.0, and social media have transformed investor behaviour and market dynamics. The GameStop case revealed how coordinated retail investors can challenge traditional market mechanisms and the efficient market hypothesis. The “gamification” of trading apps encourages speculative behaviour and raises concerns about investor risk awareness. Regulatory approaches to short selling differ between the US and Europe, highlighting the need for balanced, internationally coordinated frameworks. Strengthened financial education and updated regulation are essential to mitigate risks while retaining the benefits of technological advances. JEL: G14, G18, G23, O33
Aim: This article explores the evolving role of social investments and regionalism as contemporary phases in the development of social policy, with a focus on Poland. The research aims to examine how shifting economic, demographic, and technological conditions — including labor market volatility, environmental constraints, and educational inadequacies — create the need for a transformation of traditional welfare models into more adaptive, regionally-sensitive, and investment-oriented strategies. Design / Research methods: This is a conceptual and analytical study based on critical review and synthesis of historical developments, institutional changes, and policy strategies in European and Polish social policy. Conclusions / findings: The paper identifies social investments — particularly in education — as a key instrument for improving societal adaptability to modern challenges. It emphasizes the growing importance of regional differentiation in social policy, highlighting the need for decentralized and flexible approaches. In Poland, this transformation remains limited due to institutional inertia and centralization, despite evidence of local readiness and emerging initiatives. Originality / value of the article: The article offers a novel integration of social investment theory with regionalism, showing their potential synergy for modernizing welfare policy. It is particularly valuable for policymakers, educators, and scholars interested in sustainable and inclusive development, as well as for practitioners designing regionally responsive social programs. Implications of the research: The findings suggest that enhancing local autonomy and investing in adaptive education systems can significantly strengthen social cohesion and labor market inclusion. They offer a policy framework for rethinking how central and regional authorities share responsibility for social development. JEL: I38, H75, R58, I24, J24.
Aim: In teaching and science, texts are translated from different languages. In this context, the present study investigates the potential distortions and systemic risks that arise when a source text on energy transition and sustainability is translated multiple times across different languages and by different agents, including professional translators and AI-based translation models. The research aims to analyze how these translations impact meaning, tone, and factual integrity, particularly in the context of complex topics like energy transition and related systemic risks. By comparing multiple versions of a text across English, Polish, and German, the study assesses the implications of translation-mediated communication in sustainability discourse. Design / Methodology: First, an English source text was created, summarizing two scientific articles on the urgent need for energy transition and related system risk of such a transition. This text was translated into Polish by AI (text A) and by two professional translators (text B and C). The analysis of complexity (using Jasnopis) showed that the Polish texts were more complex (7/7, 7/7 and 6/7) for respectively texts A, B and C, than the English original text (O, 5/7). Text C was selected for translation into German by AI and by two professional translators. For comparison, the English source text was translated into German. The complexity of these translations was compared to the source text and the Polish versions. Afterwards, linguistic and semantic comparisons were carried out, evaluating shifts in meaning using cosine similarity (TF-IDF) and Levenshtein distance (edit distance). Furthermore, changes in emphasis, severity, and emotional tone across translations were analyzed. Findings: This study shows that multi-stage translations in sustainability communication introduce significant distortions, affecting meaning, tone, and emphasis. AI translations tend to neutralize urgency and emotional intensity, while human translations introduce biases, either amplifying or softening risk perceptions. Additionally, differences in sentence complexity and terminology shift the focus of sustainability discourse. These findings highlight the risks of translation-mediated miscommunication in critical topics like energy transition and systemic risks. Research limitations: The article presents a case study based on a small sample of translations. The results should be the basis for a more detailed research, comparing a larger group of AI translation and professional translations due to translator’s bias, language-specific issues and the complexity of sustainability related notions. Originality / Value: This research contributes to the sustainability communication discourse by focusing on the risks of multi-stage translations, where small wording changes can lead to significant distortions in meaning of notions and key-concepts, where miscommunication can impede decision-making and stakeholder involvement. Keywords: translation accuracy, sustainability communication, multi-stage translation, systemic risks in translation, AI vs. human translation, computational linguistics, language education. JEL: Q54, Z13, O33, C63.
Aim: This study examines recent green finance developments to evaluate how institutional, economic, and policy factors affect renewable energy investments globally. It employs a comparative approach to identify key success drivers and barriers influencing the effectiveness of green finance in promoting renewable energy across different national contexts. Research Methods: The study systematically examines green finance impacts on renewable energy investments through a literature review, thematic analysis, and case studies. It reviews peer-reviewed articles (2015–2025). Prioritizing qualitative research, it analyzes policies, institutional frameworks, and outcomes. Comparing successful cases (e.g., Singapore, China) with failures (e.g., Middle East & Central Asia, Latin America) provides key insights. Findings: The findings depict a varied global scenario for green finance. Successes like Singapore’s Green Bond Grant Scheme and China’s Green Finance Pilot Zones showcase how strong regulations and blended financing boost renewable energy. In contrast, challenges in Africa (weak policies), Southeast Asia (high costs), and Latin America (political instability) emphasize the importance of tailored strategies to overcome structural obstacles. Originality: This study provides a unique comparative analysis of regional green finance initiatives, examining successes and failures. Unlike previous research, it identifies key factors and barriers, offering practical recommendations for policymakers. Addressing region-specific challenges enhances understanding of global green finance and supports sustainable development. Implications: The study underscores the necessity of strong regulations, blended finance, and regional collaboration for green finance success. Addressing weak governance, financing gaps, and political instability is crucial to scaling renewable energy investments and achieving sustainability goals globally. Limitations: Limited quantitative analysis; future research should explore hybrid financing models. Keywords: Green finance, renewable energy investments, sustainable development, Climate Finance. JEL: G23, Q01, Q42, Q56.
Aim: This study investigates foreign exchange market dynamics by forecasting and analyzing the Value-at-Risk (VaR) for the Nigerian Naira against BRICS currencies utilizing daily data from January 1, 2010 to December 31, 2024. Design/Research methods: The five BRICS currencies (BRL, RUB, INR, CNY, and ZAR), were analyzed to explore the impact of foreign exchange market dynamics on the Nigerian Naira against BRICS currencies. The value-at-risk methodology was implemented plus the Monte Carlo simulation. The calculated VaR95% quantifies potential losses, emphasizing the importance of managing downside currency exchange risks in a volatile financial market at both the 95% and 99% confidence thresholds. The robustness of the Monte-Carlo simulation (MCS) and historical simulation (H-S) results validates the conditional variances and the corresponding value-at-risk estimates for the Naira exchange rate in relation to each currency of the BRICS derived from the variance-covariance model. GJR-GARCH model reveals critical insights into the valuation and volatility risk associated with the Naira exchange rate against BRICS currencies. Findings: The valuation of the Naira/Real rate has significant vulnerabilities to changes in oil prices, external debt, and changes in money supply; the results show that the Naira/Rubble exchange rate had significant and negative responsiveness to changes in output growth, crude oil prices and external debt levels; valuation of the Naira/Rupee exchange rate is significantly responsive to the vulnerability of trade balance, external reserves, foreign debt, monetary policy rate, and crude oil prices; valuation of the Naira/Yuan exchange rate has significant vulnerabilities to changes in oil prices, output growth, external debt, and CBN policy rate; valuation of the Naira/Rand has significant vulnerabilities to changes in external reserves, financial healthiness and external debt levels. Originality / value of the article: The study findings are robust explanation of asymmetric risk identified by VaR with policy advice for the CBN to strategically rebalance its exposure to BRICS currencies by using risk-weighted analysis instead of just trading volumes. Also, the study contributed to prediction of possible losses associated with unfavorable Naira currency fluctuations when trading particularly with the BRICS, and so emphasized the necessity for the adoption of VaR-based stress testing to national foreign exchange reserves and financial institutions. Conclusion: Given the asymmetric risk, the CBN should intentionally rebalance its exposure to BRICS currencies by using risk-weighted analysis instead of just trading volumes. For example, the CBN ought to look at establishing more local currency settlement agreements with the BRICS countries. This could reduce exposure to the volatility of the US dollar and dependence on it. Keywords: Variance-Covariance methodology, Monte-Carlo Simulation (MCS), Historical-Simulation (H-S), BRICS currencies, VaR, Naira Exchange Rate JEL: B23, D25, C17.
Aim: This study investigates the digital gap in enterprises (particularly SMEs) and introduces the Digital Gap Benchmarking Model as a solution to bridge this gap and enhance their digital transformation processes. Design / Research methods: The research employs a narrative literature review of studies on enterprise competitiveness within digitalization contexts with predefined inclusion criteria. In addition, based on the concept of the digital gap for SMEs, the authors proposed original concept of a Digital Gap Benchmarking Model as a tool for optimizing the digitalization process in SMEs. Conclusions/findings: The study identifies the digital gap along three key dimensions: digital potential, digitalization strategy, and position in the digitalization process. Additionally, benchmarking was identified as a key tool to assess and monitor digital transformation progress, helping SMEs close the digital gap and enabling to pinpoint weaknesses and strategically enhance their digital maturity. Originality/value of the article: While many studies have examined the importance and impact of digital transformation, few have focused on how to assess and bridge the digital gap. This study addresses this gap by identifying the digital gap and proposing the Digital Gap Benchmarking Model as a tool to support SMEs in closing this gap. JEL: L20, L21, M15, M21
Abstract: Aim: This paper introduces Sokrates Forms, an innovative survey instrument with advanced functionalities that enhance data accuracy, respondent engagement, and compliance with data protection regulations. The primary objective is to develop and implement a dynamic, secure, and customizable survey tool that supports both cross-sectional and longitudinal studies while offering a feedback mechanism to participants. Design / Research methods: The study presents the architecture, methodology, and implementation of Sokrates Forms, highlighting its modular and scalable design. The tool integrates adaptive survey paths, rigorous data validation protocols, and a personalized feedback system, which not only improves response quality but also fosters user engagement. Anonymization features ensure compliance with data protection standards, allowing surveys to be conducted either anonymously or through login-based participation for repeated studies. A case study on assessing organizational vulnerabilities in the context of system risk management demonstrates the tool’s application in real-world research scenarios. JEL: C81, D63, D81, D84
Abstract: Aim: This study honors the pioneering work by André Dorsman on energy finance, especially on oil prices and company performance. The objective is to investigate the relationship between the global oil price and the profitability of Dutch companies. Design / Research methods: In our research, a model is formed which evaluates the relationship between a global oil price index and the profitability of Dutch public companies. Publicly available data from 143 Dutch listed firms during the period 2010 till 2023 has been used to conduct this research. Besides the independent variable (the oil price) and the dependent variables (return on assets and return on equity), a firm’s leverage, market capitalization and degree of internationalization are used as control variables in the conceptual model. The model is evaluated via multiple panel regression analyses. Conclusions / findings: We reveal a positive relationship between the oil price and the return on assets as well as the return on equity. However, this relationship is dependent upon the presence of oil and energy related companies in the sample. When oil and energy related companies are removed from the sample, no relationship is found between the global oil price and profitability. The control variable market capitalization is found to be significant and positively related to return on equity and return on assets. Contrary, the control variable leverage is found to be negatively related to return on assets. The variable for degree of internationalization of Dutch firms is insignificant for all the regression models, indicating that there is no linear relationship between the degree of internationalization and profitability. Originality / value of the article: The study confirms a complicated relationship between oil prices and company profitability. JEL: G10, L95
Aim: Research on supply chain disruptions is most commonly conducted on the inter-organizational level of analysis. Although personal relationships in business-to-business relationships are generally considered important, the role of personal relationships during supply chain disruptions has been neglected in extant literature. Our study aims to fill this void by focusing on the role of personal relationships from the buyer perspective. Design / Research methods: An embedded case study was conducted at manufacturer ASML on the role of personal relationships during seven supply chain disruptions. ASML is the world’s leading supplier of machines for the semiconductor industry. The unit of analysis is a supply chain disruption due to a delay or interruption in supply caused by the supplier or a sub-supplier. A total of seven sub-cases were examined. Conclusions / findings: We found that personal relationships facilitate communication, the building of trust, flexibility, mutual understanding and anticipating behaviors. The results indicate that personal relationships indeed can play an important role in advancing supplier performance and addressing supply chain disruptions. Originality / value of the article: The lack of research into the role of personal relationships in handling supply chain disruptions is a notable omission and points to a gap in the current body of knowledge. This study contributes to current understandings and knowledge by being one of the first studies to specifically investigate the role of personal relationships in a context of supply chain disruptions. Implications of the research (if applicable): The results of this study have important implications for practice. The recommendation for management is to make employees aware and train them to invest in personal relationships which lays the foundation for successful collaboration also on the inter firm level. Trust and communication can be reinforced by regular face-to-face meetings, team-building activities with counterparts and communication training for better personal skills. Regular communication and maintaining relationships in stable times can help to increase supply chain resilience. Limitations of the research: A limitation of this research is its focus on describing the role of personal relationships during different supply chain disruptions within a single focus organization. Another limitation of our study is the focus on supply chain disruptions that were successfully resolved. Further research could address these issues. JEL: L63, M5
Aim: This study aims to investigate the root causes of the MS Estonia and Doña Paz maritime disasters and to derive interdisciplinary lessons that can enhance the safety and reliability of maritime operations. Design/Research methods: The study takes a case study approach and adopts Labib & Read’s (2013) framework for learning from failures. This study addresses the following questions: a) What technical factors contributed to the MS Estonia and Doña Paz maritime disasters? b) What human and organizational factors played a role in these maritime disasters? c) How do the reliability and vulnerability of individual components influence the overall safety and failure risk of MS Estonia and Doña Paz? To answer these questions, Fault Tree Analysis (FTA) and Reliability Block Diagram (RBD) techniques are employed. These methods are used to identify a range of technical, organizational, and human factors that contributed to these accidents and to assess the reliability and vulnerability of individual components affecting the safety and failure risk of the vessels. Conclusions/findings: The analysis revealed that multiple factors, including technical failures, human errors, and organizational shortcomings, contributed to the disasters. The study found that the emergency response and search and rescue systems were particularly vulnerable, where a failure in any component could lead to system-wide failure. Based on these findings, evidence-based recommendations were proposed to enhance safety management practices, regulations, and oversight in the maritime industry. Originality/value of the article: This study underscores the importance of a systemic approach to learning from failures. It highlights the necessity of addressing technical, human, and organizational factors in maritime safety and provides a framework for future research and improvements in safety management practices. The findings offer valuable insights for maritime organizations aiming to enhance their safety protocols and prevent future disasters. JEL: L92, D81, O33, C63, M48
