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We are honored to announce the 33rd edition of the International Economic Conference of Sibiu (IECS), one of the most prominent academic and professional events in the field of economics and related disciplines.
The conference continues its long-standing tradition of fostering dialogue and collaboration among researchers, academics, and practitioners from around the globe. Participants are invited to present original research, case studies, and policy-focused papers that contribute to addressing contemporary economic challenges and opportunities.
Organized by
in partnership with
Chairs: Diana VASIU & Adrian MOROȘAN
This study investigates the role of corporate human capital investments in aligning financial and environmental performance in carbon-intensive industries. Grounded in established theoretical frameworks, it posits that firms can concurrently enhance carbon efficiency and financial outcomes through human capital investments. A novel human capital investment index is developed using the entropy weighting method, integrating the multidimensional nature of human capital inputs – training, compensation, satisfaction, and sustainability-linked incentives – across a global sample of 874 firms in 15 carbon-intensive industries over the 2019–2023 period. Employing a multi-method empirical framework – including two-stage least squares (2SLS), autoregressive distributed lag (ARDL) models, mediation analysis, and panel threshold regression – the analysis reveals a statistically significant, non-linear relationship between human capital investments and carbon-adjusted profitability. Specifically, human capital investments exhibit a positive long-run marginal effect on firm-level financial performance per unit of CO₂ emissions. However, the relationship is characterized by threshold effects, where returns diminish beyond certain levels of investment intensity. Mediation analysis reveals that the resources rate of return partially mediates this relationship, though not uniformly – suggesting that human capital influences carbon-adjusted performance both directly and via efficiency-enhancing mechanisms. This study contributes to the sustainability finance literature by introducing an entropy-weighted index that captures the firm-level complexity of human capital investments, empirically validating the mediating role of resources efficiency and identifying non-linear dynamics in the impact of human capital on carbon-adjusted performance. These insights offer actionable implications for firms operating in emission-intensive sectors seeking to navigate decarbonization pathways while preserving financial viability.
This study investigates the validity of the Efficient Market Hypothesis (EMH) in contemporary financial markets by examining short-term return dynamics across six international equity indices over the period 2015–2025. The analysis aims to assess whether stock returns exhibit serial dependence and whether deviations from the random walk hypothesis persist in modern market conditions characterized by high liquidity, algorithmic trading, and major structural shocks such as the COVID-19 pandemic.
To achieve this objective, the study employs three complementary econometric methods: the Autocorrelation Function (ACF), the Ljung–Box test, and the Variance Ratio test. These methods are used to identify linear autocorrelation, joint serial dependence across multiple lags, and deviations from variance scaling consistent with a random walk process.
The empirical results provide consistent evidence of short-term dependencies across most markets analyzed. While the ACF indicates generally weak autocorrelation at individual lags, the Ljung–Box test reveals statistically significant serial dependence in several indices, particularly Brazil and the United States. Furthermore, the Variance Ratio test strongly rejects the random walk hypothesis across all markets, indicating systematic mean-reverting behavior at short horizons.
These findings suggest that financial markets are not fully efficient in the strict sense of the EMH, particularly over short time intervals. However, the degree of inefficiency varies across markets, with Japan and Poland exhibiting comparatively weaker evidence of dependence. The results also highlight that market efficiency may be sensitive to structural conditions and crisis periods.
Overall, the study contributes to the literature by providing an updated empirical assessment of market efficiency using recent data that includes the COVID-19 period. It offers evidence that short-term predictability persists in modern markets, while also emphasizing the importance of structural breaks and market-specific characteristics in shaping return dynamics.
Chairs: Sorin TERCHILĂ & Nancy PANȚA
Abstract:
In times of financial constraints, people tend to change their consumer behavior in such ways that this adds even more complexity to the planning process of the companies that try to constantly adapt to those changes from their working environment. In these circumstances, for a cultural organization like a museum it's even more important to develop resilient marketing strategies to make sure that they can maximize the added value offered to the customers while at the same time keeping their costs at a reasonable amount.
But not even the best strategy in the world can cope with the situation when people simply decide to cut the visits to the museums, so that's why it is very important for a museum to adopt A strategy that will prevent from the beginning the people to simply cut the visits.
In this context, this paper explores how perceived household budget pressure influences consumers’ willingness to minimize the museum visits and examines what marketing strategies could help cultural organizations to remain attractive during financial constraints.
The study assumes that even if museums bring social and educational value, they can still be very vulnerable when people reprioritize spendings as a measure to rebalance the living costs. The research adopts a quantitative approach based on a questionnaire designed to measure perceived economic pressure, spending-cut priorities and museum visit behavior under budget constraints to establish who are the consumers categories that are most likely to reduce or cut visits, and the appropriate strategies that the museums must build in order to preserve demand, such as price-related incentives, better communication, family-oriented offers, free-entry days, and enhanced visitor experience.
The relevant contribution of this paper is that is bringing a clear understanding of consumer behavior toward cultural organizations in times of financial pressure and provides important marketing strategies that contribute to increase the marketing resilience by identifying the best measures that may help museums remain relevant and accessible when household budgets tighten and prevent the “by default cut of the visits” in some consumers.
Keywords: Consumer behavior, financial constraints, museums, cultural organizations, marketing strategies, marketing resilience, budget pressure, visiting intention
This study explores AI integration maturity and task-level AI usage in workplace settings across industries and organization sizes. Rather than treating adoption as a simple yes/no measure, it studies how frequently professionals use AI, which tasks are supported, the typical depth of assistance (from suggestions to automation), and how governance and readiness mechanisms (official AI policies, training provision, approved tool lists, and confidential-data rules) relate to adoption and perceived impact. A quantitative, cross-sectional survey design was employed to capture self-reported practices and organizational context in a cross-industry sample. Data were collected via an anonymous online questionnaire administered via Microsoft Forms and open for approximately one month (20 January 2026 – 19 February 2026). Convenience sampling through online distribution channels yielded an international respondent pool, with the largest shares from the United States (20.37%, n=44), Romania (17.13%, n=37), and the United Kingdom (14.81%, n=32). After data screening and quality controls (including removal of AI-user responses with completion times under 2 minutes 30 seconds, exclusion of non-valid country entries, and manual review of straight-lined or internally inconsistent cases), the final dataset included 216 valid respondents, of whom 161 reported using AI tools for work in the past three months. Descriptive statistics were used to characterize adoption and task-level patterns. Chi-square tests examined associations between categorical variables (industry, company size, policy presence, training, approved tools, confidential-data rules), and Spearman correlations assessed relationships among ordinal variables (usage frequency, assistance depth, time saved, perceived productivity/efficiency impact). Results indicate high overall AI adoption (74.5%), with significant variation across industries and company sizes. Adoption was positively associated with the presence of an official AI policy and with training provision. AI policy was strongly linked to operational governance mechanisms such as approved tool lists and clearer confidential data rules, suggesting that organizational structures support more mature integration. Task-level findings show that AI is most frequently used for search/summarization and writing/communication, while customer interaction and meetings show lower assistance. Across tasks, AI use is predominantly augmentation-oriented (suggestions and drafting), with fully automated steps rare. More frequent AI use correlates with greater self-reported time savings and more favourable perceptions of productivity, work quality, and organizational efficiency. Reported barriers are dominated by confidentiality, trust/accuracy, and compliance concerns, underscoring the importance of governance and risk management for responsible AI integration.
The car-sharing sector is undergoing a rapid global evolution which shows a movement away from traditional vehicle ownership toward integrated "Mobility as a Service" ecosystems. The transformation in Romania received a major boost when Uber and other major platforms launched their services in 2015. The Romanian market has established different ride-hailing services but research on how companies manage their innovation process remains insufficient.
The research investigates how ride-hailing companies in Romania manage their innovation processes which has become essential for the transforming shared transportation industry. The process of innovation management requires organizations to implement their innovation activities through established process frameworks that encompass all phases of development from initial concepts to final product launch. The ride-hailing sector develops new business models while expanding service offerings through both small feature updates and complete transport solution deployments. The successful innovation process implementation requires organizations to establish partnerships with multiple external parties who contribute to the process. The process requires different groups which include customers and drivers to participate in the development of transportation solutions. The analysis of innovation processes enables researchers to assess how platforms develop their technology while meeting market needs and following regulatory requirements which enables their long-term success and their effects on city transportation systems. The digital platforms use their understanding of complex innovation processes to develop effective strategic frameworks for their business growth. The study aims to show how ride-hailing companies use innovation to gain competitive advantages which improve user experiences and shape future urban transportation systems. Organizations can expand their understanding through process comparison which enables them to develop customized processes that match their specific business requirements.
Sustainability has evolved from a peripheral concern into a central pillar of economic and organizational strategy, requiring a redefinition of leadership and value creation in complex, globalized markets. This paper explores how simulated environments can enhance the development of sustainable leadership competencies, bridging the gap between theoretical frameworks and real-world decision-making.
Grounded in the 8P Model of Sustainable Business Growth (Bradford, 2026), which integrates Purpose, Principles, Partnerships, and Propositions as drivers of sustainable outcomes (Profits, Planet, People, and Prosperity), this study adopts an experiential learning approach to examine how future leaders internalize and apply sustainability principles. The research is based on the implementation of the Sustainability World Cup, an international, simulation-based competition involving participants from over 25 countries across higher education and professional contexts.
Methodologically, the study combines qualitative and quantitative data collected over two years, including participant feedback, performance metrics, and reflective assessments. The simulation environment places participants in dynamic market scenarios where they must make strategic decisions under uncertainty, balancing economic performance with environmental and social impact. This allows for the observation of behavioral and cognitive shifts in leadership approaches.
Preliminary results indicate significant improvements in participants’ ability to manage trade-offs between profitability and sustainability, with 87% reporting a deeper understanding of strategic decision-making in complex systems. Furthermore, participants demonstrated enhanced collaborative capabilities, adaptability, and ethical reasoning, reflecting a transition towards more holistic, systems-oriented leadership. From an economic perspective, the findings highlight the importance of integrating sustainability into growth strategies not as a constraint, but as a driver of long-term competitive advantage and innovation.
The paper contributes to the literature by positioning simulated environments as a scalable and effective tool for sustainability education, while also reinforcing the relevance of integrated frameworks such as the 8P Model in aligning business growth with broader societal and environmental goals. It argues that sustainable leadership development requires not only knowledge acquisition but also immersive, practice-based experiences that reflect the interconnected nature of modern economic systems.
Introduction: Cardiovascular diseases remain a leading cause of mortality worldwide, which makes early risk identification a major clinical and public health priority. Reliable risk estimation depends not only on the selected model, but also on the quality and consistency of the underlying data.
Purpose: The purpose of this paper is to examine the needed ETL procedures for preparation the Framingham cardiovascular dataset for subsequent statistical analysis and risk assessment.
Methods: The study is based on a publicly available cardiovascular dataset containing demographic, anthropometric, biochemical, and behavioural variables. Considering the available fields, the Framingham Risk Score was selected as the most suitable reference model for further analysis. The ETL workflow consists of identifying and treating missing values, standardising measurement units, reconstructing incomplete variables from related fields, deriving additional indicators, and converting categorical variables into numerical formats suitable for analysis. In addition to data preparation, the study outlines a set of acceptable preliminary analyses, including distributional checks, screening for potential outliers, correlation analysis, and tests of association between selected categorical risk factors and estimated cardiovascular risk.
Practical implications: The initial exploratory analyses suggest that the transformed data behave in a clinically plausible way and that the main variables are suitable for subsequent statistical use. Early results also suggest that the prepared dataset captures expected patterns between established cardiovascular risk factors and estimated risk levels, while remaining appropriate for further modeling and validation.
Findings: The study supports the view that ETL is not merely a technical preprocessing step, but a methodological prerequisite for valid secondary analysis of clinical data. The proposed workflow demonstrates how careful transformation and validation can improve the usability of real-world health data and define which analytical procedures are appropriate at the preliminary stage. The resulting dataset is intended to serve as a foundation for future predictive modeling, comparative evaluation of risk estimation approaches, and possible adaptation of the workflow to other clinical datasets.
The relevance of this study is driven by the rapid growth of smart technologies, as well as the worsening situation with environmental problems, the energy crisis and economic disruptions, which affect not only individual enterprises and countries, but the global economy as a whole. Under these circumstances, a legitimate question arises: can smart technologies become a real tool for addressing these challenges, or are they themselves becoming part of the problem?
The purpose of this study is to identify the specific features of the impact of smart technologies — most of which are based on artificial intelligence and related devices — on the potential for implementing the 3E system at the micro and macro levels. The 3E concept — Environment, Energy, Economy — is considered here not as an abstract theoretical construct, but as a practical tool for assessing the sustainability of development at the level of an enterprise, industry and national economy. To achieve this goal, the following tasks were addressed: global trends in the development of smart technologies were analysed; the interrelationships within the 3E system were established taking into account the influence of modern technologies; and the risks and opportunities of this interaction were identified.
The research methods include comparative analysis, synthesis of conceptual aspects of the 3E system and the characteristics of smart technologies, as well as empirical research incorporating forecasting trends in the development of this relationship. The application of this set of methods made it possible to examine the phenomenon under study from both theoretical and practical perspectives.
The results show that smart technologies act as a real driver of the 3E concept — accelerating environmental monitoring, improving energy efficiency and creating new points of economic growth. Intelligent management systems, IoT devices and big data platforms are already changing the way enterprises approach resource consumption and waste management. However, the same driver produces reverse effects: high energy consumption of data centres, growing volumes of electronic waste and deepening digital inequality between countries and economic sectors. This confirms that modern technologies, on the one hand, represent enormous opportunities for economic growth, environmental and energy optimization, while at the same time creating even greater challenges in these three areas. Thus, such multifaceted development requires a balanced approach both at the level of individual enterprises and at the level of national and international policy.
Abstract: This study examines the relationship between artificial intelligence (AI) adoption in multinational companies and workforce restructuring, with a focus on the effects on household financial distress and perceived welfare strain in Western Romania. The research is set against recent layoffs in Arad and Timiș counties and explores whether AI-driven restructuring creates measurable vulnerability for displaced employees and broader economic pressure in the regional labour market. The study uses a quantitative, cross-sectional survey design. Data were collected through Google Forms over one week in January 2026 from 541 current and former employees of multinational companies in Arad and Timiș counties who had either been laid off or felt at risk of job loss. Respondents evaluated 16 statements on a 5-point Likert scale across four areas: AI adoption and workforce substitution, difficulty of reemployment, household financial distress, and perceived welfare and regional economic strain. Descriptive statistics were analysed using SPSS. The results show consistently high mean scores across all areas, with an overall average of approximately 4.41 out of 5. Respondents largely agree that AI is used to justify or support workforce reductions, that finding new employment after layoffs is difficult, and that job loss leads to significant financial strain, including difficulty covering basic expenses and repaying loans. Many report reliance on unemployment benefits and perceive AI-related layoffs as harmful to the local economy. At the same time, most respondents do not believe AI can fully match the judgment and quality of skilled human work. The findings suggest that AI-driven restructuring creates a chain of effects that extends from firm-level decisions to household financial stress and increased pressure on public welfare systems, with clear implications for regional labour policy and social protection.
This study investigates the relationship between data analytics adoption and organisational performance, with a particular focus on the moderating role of industry-level gender composition. Prior research suggests that analytics rarely has a direct impact on business performance, but instead, it creates the appropriate conditions that lead to value realisation. Considering this, this paper examines how these conditions are shaped by the characteristics of the workforce and organisational context. The analysis is based on Dynamic Capability Theory and the Resource-based View and conceptualises analytics as an organisational capability and gender composition as an attribute which influences the decision-making processes within an organisation. For testing the relationship between the constructs, a panel data approach using sector-level data across multiple European countries over an extended period of time is employed. Analytics adoption is proxied by the implementation of enterprise systems and the use of data analytics and artificial intelligence to capture the extent to which organisations develop data integration capabilities. Organisational performance is measured through financial and operational indicators, and gender composition through the proportion of female representation within sectors and leadership roles. The model also includes control variables such as industry size and human capital, and it accounts for the fact that analytics impact is not immediate; therefore, lagged independent variables are added to mitigate reverse causality concerns. The findings mirror the results of previous research demonstrating that analytics' impact on organisational performance is conditioned by intermediate organisational mechanisms. Moreover, the findings contribute to a comprehensive understanding of the relationship between analytics and performance by integrating demographic and organisational factors into capability-based explanations. This study highlights the importance of fostering an inclusive and diverse organisational environment.
Keywords: data analytics, data-driven decision-making, organisational performance, gender parity
Recent advances in artificial intelligence (AI), particularly the rapid expansion of generative AI technologies, have intensified debates regarding their implications for labour markets and skill demand. Within the European Union (EU), increasing AI adoption is expected to reshape employment structures, particularly in knowledge-intensive sectors such as Information and Communication Technology (ICT). This study investigates whether the growing diffusion of AI technologies is associated with changes in labour demand for ICT specialists across EU member states.
The empirical analysis is based on quarterly panel data covering multiple EU countries, combining indicators of ICT labour demand derived from online job advertisement statistics with measures of AI adoption based on enterprise-level data. A panel data regression framework (PanelOLS) with country and time fixed effects is employed to estimate the relationship between AI adoption and ICT labour demand. The model incorporates lagged variables to capture delayed effects of AI adoption, as well as macroeconomic control variables, including unemployment and inflation rates, to account for broader labour market conditions.
The results indicate a modest relationship between AI adoption and ICT labour demand, with relatively low explanatory power, suggesting that AI adoption and macroeconomic controls explain only a limited share of the observed variation in ICT job demand. The estimated effects remain moderate in magnitude, highlighting that the relationship between AI diffusion and ICT employment demand is complex and influenced by multiple structural factors.
Overall, the findings suggest that AI adoption is associated with measurable but heterogeneous changes in ICT labour demand across EU countries. The results emphasize the importance of technological readiness and national labour market characteristics in shaping employment responses to emerging technologies. This study contributes to the literature by providing cross-country panel evidence on AI-related labour market dynamics and offers insights relevant for policymakers concerned with digital skills development, workforce adaptation, and long-term labour market resilience.
Aims. This paper aims to examine how narratives about artificial intelligence (AI), automation, and workforce transformation have been constructed, framed, and contested across European specialized press between 2022 and 2025. Specifically, the study seeks to identify the dominant discursive framings of AI-driven change in operations-intensive sectors, to trace their evolution over time, and to map the geographic variation in how different European media and institutional contexts have approached these issues. The broader objective is to contribute to a more grounded understanding of the discursive mechanisms through which technology-related narratives shape managerial decisions, worker expectations, and policy responses.
Methodology. The methodology draws on Critical Discourse Analysis (CDA), applied to a purposively constructed corpus of over 50 sources. These include institutional reports from Eurofound, the International Labour Organization (ILO), the OECD, and the European Parliament Research Service, as well as major economic and business publications from Germany, France, Italy, the United Kingdom, and pan-European outlets. Sources were selected to ensure both thematic relevance to AI and workforce issues in operations management and broad geographic representation. The analytical framework focuses on identifying recurring narrative frames, lexical patterns, and rhetorical strategies used to position AI either as a disruptive threat or as an enabling force for operational efficiency.
Preliminary results. Preliminary results reveal two dominant and competing framings across the corpus: displacement (AI as job eliminator) and augmentation (AI as productivity enhancer and human-work complement). A clear temporal shift is observed: coverage in 2022–2023 was predominantly alarmist, foregrounding fears of technological unemployment and the erosion of human roles. By 2024–2025, augmentation-centred narratives had gained significant traction, reflecting both empirical evidence from early AI deployments and a broader policy turn toward human-centric technology governance. Geographically, Northern European sources emphasize collective bargaining and institutional adaptation, while Southern European outlets focus more on adoption gaps and regulatory uncertainty. These findings have direct implications for operations management practice and align with the emerging frameworks of the EU AI Act and Industry 5.0.
The growing imperative for enterprises to align digital growth with Environmental, Social, and Governance (ESG) commitments has placed sustainable digital transformation at the forefront of both academic and policy agendas. Within this context, Design Thinking (DT) - with its human-centered, iterative approach to innovation - has emerged as a promising methodology for embedding sustainability into digital platforms and enterprise practices. However, the literature at this intersection remains fragmented across innovation management, information systems, and environmental economics, lacking a coherent synthesis of dominant themes and research gaps. This study addresses that need through a systematic bibliometric analysis of the literature connecting DT, sustainable digital transformation, and ESG performance.
Peer-reviewed publications indexed in Scopus and Web of Science are retrieved using a structured keyword search combining terms such as "design thinking", "digital transformation", "sustainability", "ESG", "Green ICT", and "sustainable innovation", covering the period 2000–2025. Analyses are conducted using VOSviewer and the Bibliometrix package in R, encompassing performance analysis of publication trends, leading journals, and contributing countries; keyword co-occurrence mapping to identify thematic clusters; co-citation analysis to reveal the intellectual structure of the field; and thematic evolution analysis to trace shifts in research priorities.
Preliminary results indicate a sharp acceleration in publication output after 2018, coinciding with the mainstreaming of EU sustainability frameworks including the European Green Deal and mandatory ESG reporting directives. Keyword mapping is expected to reveal dominant clusters around human-centered innovation, ESG governance and Green ICT practices, and sustainable digital platform design. Critically, the empirical study of DT's measurable contribution to enterprise ESG outcomes remains underrepresented - directly motivating a research agenda integrating cybernetic modeling with DT methodology.
This study offers a consolidated overview of an emerging interdisciplinary field, a replicable methodology for literature mapping, and a forward-looking research agenda - positioning DT as a mediating mechanism between digital intensity and ESG-aligned sustainability practices - with implications for researchers, practitioners, and EU digital transition policymakers.
This paper explores the Romanian Orthodox Church (ROC) as a social economy actor, positioned at the intersection between traditional philanthropy and emerging forms of social enterprise. Building on recent reports that document the ROC’s extensive social‑philanthropic investments and its nationwide network of social and medical institutions, the study asks to what extent these activities can be conceptualised within the framework of social economy and social entrepreneurship. Using a qualitative research design that combines document analysis (church reports, policy documents, secondary statistics) with one illustrative case study, the paper maps key organisational forms (parishes, monasteries, faith‑based NGOs) and examines their governance, funding patterns and community embeddedness. The analysis, drawing on evidence from the Filantropia Federation (2020–2024), highlights both the continuity with older Orthodox traditions of charity and mutual aid and the recent shifts towards project‑based, professionalized social service provision. The paper argues that the ROC offers a revealing example of how religious institutions can contribute to social cohesion and local development through hybrid, value‑driven models of social economy.
The accelerated integration of generative artificial intelligence (GenAI) into accounting practice is reshaping professional roles, task structures and required competencies. Automation of routine procedures has shifted the emphasis of accounting work toward analytical reasoning, ethical judgment and the supervision of AI‑generated outputs. However, many accounting programmes continue to rely on traditional, rule‑based teaching methods that offer limited opportunities for experiential learning and decision‑making in realistic professional contexts.
The aim of this paper is to explore how GenAI‑powered simulations can be employed in accounting education to support experiential learning, ethical reasoning and the development of higher‑order professional skills. Rather than focusing on technical automation, the study examines the pedagogical potential of GenAI to create dynamic, interactive learning scenarios that mirror contemporary accounting challenges, such as financial analysis under uncertainty, ethical dilemmas in reporting, fraud detection, and audit planning.
The paper adopts a qualitative, conceptually driven methodology based on three elements. First, a structured review of recent academic literature on experiential learning, simulation‑based education and GenAI applications in business and accounting education is conducted. Second, common accounting decision contexts are identified and structured as simulation‑based learning scenarios generated or mediated by GenAI systems. Third, a comparative pedagogical analysis of selected GenAI platforms used for adaptive tutoring, role‑playing and scenario generation is undertaken, focusing on criteria relevant to higher education, such as feedback quality, scalability, accessibility and alignment with accounting learning objectives.
The preliminary results indicate that GenAI‑powered simulations offer significant pedagogical advantages over traditional case‑based approaches. They enable continuous interaction, personalised feedback and the exploration of multiple decision pathways, thereby strengthening reflective learning and professional judgment. The analysis further suggests that GenAI‑mediated role‑play is particularly effective in addressing ethical reasoning and professional scepticism, competencies that are frequently identified as underdeveloped in accounting graduates. Additionally, the use of adaptive AI tools allows instructors to shift their focus from content delivery toward learning design and guided reflection.
The paper contributes to current debates on digital transformation in economic and business education by demonstrating how generative AI can be leveraged as a pedagogical resource rather than a threat to academic integrity. It offers practical insights for accounting educators seeking innovative, experience‑based teaching approaches that respond to the evolving demands of the profession, without relying on quantitative data analysis or primary empirical testing.
In recent years, artificial intelligence (AI) has rapidly advanced across multiple domains, reshaping how individuals learn, work, and make decisions. While AI systems increasingly outperform humans in rule-based and pattern-recognition tasks, human intelligence remains diverse and multifaceted, resisting standardization. This raises critical questions about how “intelligence” is defined and understood in the context of machines. Despite its transformative potential, AI adoption is uneven across regions, disciplines, and user groups. Moreover, significant risks accompany its use, including misinformation, hallucinated content, data privacy concerns, and the potential manipulation of user behavior. These challenges highlight the urgent need for AI literacy as a fundamental competence in higher education.
AI literacy can be defined as the ability to understand, use, and critically evaluate AI systems. It encompasses conceptual knowledge of how AI works, awareness of its limitations, critical assessment of outputs, and ethical, responsible use. At the European level, the AI Act (EU Regulation 2024/2689) establishes a comprehensive risk-based framework, reinforcing the need for informed and responsible engagement with AI technologies.
This paper proposes a three-level educational model for integrating AI literacy into higher education: (1) foundational AI literacy for all students, (2) applied AI competencies tailored to specific disciplines, and (3) advanced specialization in AI and ethics. Such an approach supports critical thinking, reduces technological dependency, and prepares graduates for an AI-driven labor market. Ultimately, embedding AI literacy into university curricula is essential for fostering responsible innovation and ensuring that future professionals can navigate the opportunities and risks of AI effectively.
Chairs: Cristina POPA & Emanuel MEȘTERU
The analysis of the poverty level in Romania involves numerous aspects, from poverty of material means, to the lack of employment opportunities on a labor market characterized by an imbalance in supply (of jobs). In this context, the level of education could constitute the defining component for increasing the chances of reducing poverty, under the conditions of a functional economy, in which imbalances are reabsorbed in the short term, as a result of the mutations that occurred on the goods and services market, with consequences in terms of employment. Thus, the poverty level is accentuated, on the one hand, in the absence of specific behaviors, necessary for employment in conditions of economic efficiency, and, on the other hand, in the absence of the adoption by the population of sustainable consumption models, correlated with available income, susceptible to growth. In our vision, poverty becomes a societal variable determined by endogenous and exogenous factors. The propensity for unsustainable consumption, an effect of behavioral decisions, determines the poverty indicator of people whose precarious state occurred, not accidentally, based on irrational choices. Poverty induced by deprivations (material, non-material), is a variable resulting from political decisions that induce a state of precariousness through the lack of effectiveness of social services. Our work establishes an order relationship between societal factors that could reduce the impact of poverty by adopting sustainable consumption models, based on education, rationality in relation to choice, including at the level of the political act. By considering poverty as a societal variable, the means of alleviating poverty are rooted, from our perspective, in stimulating social policies to generate the effects that were assigned to them for their achievement, within the framework of government strategies. Thus, we consider poverty as an effect of the lack of effectiveness of the instruments with which government strategies operate or have operated within the Romanian economy. In essence, the paper structures the causes of poverty in Romania and identifies different ways of approaching social policies to reduce the deprivations generated by unsustainable societal models.
This research aims to create a strictly quantitative mapping of the global scientific landscape regarding SMEs placed in the context of innovation and regulatory frameworks. Compared to traditional literature reviews, this paper does not focus on the qualitative content of the research, but on the metadata of the targeted field of study. Specifically, the study aims to identify information such as: which are the countries with the greatest contribution in this field; what is the chronological evolution of the researched field; key institutions as well as other relevant data regarding global production on this topic. Thus, the research methodology will consist of performing a bibliometric analysis, using data extracted from the Web of Science platform. While their interpretation will be carried out in the VOSviewer program and will include interactive and relevant visualizations for future works in the field. In principle, the cartography pursued through the interpretation program will have two dimensions: a geographical one as the main dimension, and a temporal one as a secondary dimension. In line with this, preliminary data analysis revealed a clear concentration of research in specific global nodes, such as the United States of America, which also maintained collaborative links with countries around the world, both from Europe and from other parts. In terms of temporal evolution, preliminary results have also shown a significant increase in studies in this field over time; which means that the study of the impact of innovations in the SME area is becoming increasingly popular. A fact which aligns with the general directions in the economic area. However, the interest in innovation is not new, with its strong presence being indicated since the period between 2015 and 2020. Moreover, it remains important to note that the study was not without limitations, and the main barrier encountered was the relatively low number of works identified in the Web of Science platform.
The practical implementation of the principles of sustainable development has created several fundamental challenges. One of the most deeply debated topics in the academic environment is the direct relationship between economic growth and energy consumption, as economic development leads to a significant increase in energy consumption, which leads to increased carbon dioxide emissions (CO₂).
In this context, the analysis of interdependencies contributed to the development and consolidation of the key concepts in the economic literature, such as: 3E indicator, the energy nexus–GDP–CO₂, Environmental Kuznets Curve (EKC), energy intensity, carbon intensity, dissociating effect, energy transition, climate policies, etc. The interest in these subjects is amplified by the demanding regulatory framework in the area of environmental protection, well-known at the European Union level, as well as the need to align the Republic of Moldova's policies with EU community standards and practices.
This article aims to analyse the Energy Nexus–Economy–Medium (3E) in the context of the Republic of Moldova, by applying the identity of Kaya, an analytical tool that permits the breakdown of total CO₂ emissions into four determinants: population, GDP per capita, energy intensity and carbon intensity.
This research aims, first of all, to identify the core theories integrated in the 3E indicator, considered a relevant strategic framework for the analysis and promotion of sustainable development. Secondly, the study aims to explore the correlations between economic development, energy consumption and CO₂ emissions in the Republic of Moldova, as well as to conduct a comparative analysis with the member states of the European Union. The empirical analysis covers the period of 2000–2024 and is based on the Kaya identity, which facilitates a rigorous quantitative approach to the determinants of CO₂ emissions and allows highlighting the relative contribution of each factor in their dynamics.
This paper gives an overview of determining the degree of separation between the economic development level in the Republic of Moldova and environmental impact, facilitating the development of feasible recommendations for public policies to align with the objectives set by the European Union.
The research study is performed within the bilateral complex project RO–MD (2025–2027), „Valuing artificial intelligence for sustainable growth: a multidimensional analysis of the 3E system and political implications”, code PN-IV-PCB-RO-MD-2024-0343.
The concept of secular stagnation has re-emerged as a central framework for understanding the prolonged weakness in economic growth observed in advanced economies since the 2008 global financial crisis. Originally introduced during the Great Depression and later revitalized in contemporary macroeconomic debates, secular stagnation describes a persistent and structural slowdown in growth with no clear prospect of reversal. This paper aims to examine whether such a phenomenon characterizes the trajectory of major European economies and to assess its depth relative to the United States.
The study focuses on four key European economies—United Kingdom, Germany, France, and Italy—and investigates whether they exhibit a more severe and persistent form of stagnation compared to the US. The central hypothesis is that European economies have entered a deeper and more entrenched stagnation regime, driven by structural factors such as demographic aging, debt overhang, and weak productivity growth. These dynamics are argued to have contributed to the emergence of a “new normal” defined by chronically low growth rates in the post-2008 period.
Methodologically, the paper employs a longitudinal, data-driven analysis of economic growth rates spanning from the 1960s to the present. By examining long-run GDP growth trends, the analysis identifies deviations from historical patterns and evaluates whether the post-2008 slowdown constitutes a structural break rather than a cyclical downturn. This empirical strategy reduces reliance on subjective interpretation and allows for a clearer distinction between short-run business cycle fluctuations and long-term structural transformations. In addition, the study engages with the relevant literature on secular stagnation to contextualize the findings within broader theoretical and empirical debates.
Preliminary results indicate that European economies have experienced a more pronounced and persistent decline in growth compared to the United States. The evidence suggests that the slowdown is not consistent with a typical business cycle recovery characterized by temporary weakness, but rather reflects a long-run structural deterioration in growth dynamics. The findings support the interpretation of secular stagnation as a durable condition rooted in diminishing returns to traditional growth drivers and systemic economic constraints.
Overall, the paper contributes to the growing body of evidence that secular stagnation may represent a lasting feature of modern advanced economies. In the European context, it may also signal the need for profound structural adjustments, as the “new normal” of low growth becomes an increasingly dominant and potentially irreversible reality.
This paper examines the applicability of machine learning techniques to spatial data modeling and the identification of urban patterns using a limited set of demographic and geographic indicators. Drawing on sector-level data for Bucharest obtained from the National Institute of Statistics of Romania, the analysis incorporates variables such as surface area, total population, population density, and distance to the city center. The latter is computed as the Euclidean distance between sector centroids and a predefined central reference point, ensuring a consistent spatial measure across all observations. The dataset is processed through a standardized and reproducible analytical workflow that includes data preprocessing steps such as feature normalization to ensure comparability across variables with different scales. Clustering is performed using the k-means algorithm, with the optimal number of clusters determined through the elbow method, allowing for an informed balance between model simplicity and explanatory power. To further support interpretation and visualization, principal component analysis (PCA) is applied, reducing dimensionality while preserving the most relevant variance in the data. The findings reveal three distinct spatial groupings that correspond to peripheral, intermediate, and central urban structures. Sector 1 emerges as a clearly differentiated cluster, characterized by a relatively large surface area, low population density, and greater distance from the city center. In contrast, Sectors 2, 4, and 5 exhibit more compact spatial configurations and are more centrally located, reflecting higher levels of urban concentration. Sectors 3 and 6 display intermediate profiles, combining moderate spatial extent with balanced demographic characteristics. The silhouette score of 0.266 indicates moderate cluster separation, which is consistent with the limited size and dimensionality of the dataset. Despite these constraints, the results highlight the potential of relatively simple machine learning approaches to support exploratory spatial analysis. Overall, the study demonstrates that interpretable and reproducible workflows can generate meaningful insights into urban spatial structure and provide a solid foundation for the development of more advanced modeling approaches in future research.
This paper investigates the ongoing reconfiguration of STEAM (Science, Technology, Engineering, Arts and Mathematics) curricula in the Business and Administration study programs by examining how different stakeholder groups conceptualize competence formation and its relevance to contemporary occupational structures. Positioned within the framework of the Skills4Future program (ERASMUS-EDU-2022-CBHE-STRAND-2 -101081787), the study seeks to clarify the extent to which current educational practices respond to shifting labor market demands shaped by digitalization, technological acceleration, and the transition toward sustainable economies.
The research adopts a mixed-methods design that integrates qualitative evidence from stakeholder consultations with quantitative data collected through structured survey instruments applied across multiple institutional contexts. Emphasis is placed on identifying key competence domains such as interdisciplinary thinking, digital fluency, creativity, and socio-emotional skills and evaluating both their perceived importance and their effective incorporation into curricular structures.
Analytically, the study employs comparative techniques alongside econometric estimation methods to explore the relationship between curriculum design features and perceived employability outcomes. The approach allows for the identification of systemic gaps between educational outputs and occupational expectations, as well as the factors that facilitate or constrain curriculum responsiveness.
The findings indicate that competence relevance is increasingly shaped by processes of inter- and transdisciplinary hybridization, rather than by narrowly specialized knowledge structures. At the same time, the empirical results highlight the presence of a persistent structural mismatch between educational outputs and labor market requirements, largely explained by the limited degree of institutionalized stakeholder integration in curriculum design processes.
The analysis further suggests that strengthening mechanisms of curriculum co-creation and enhancing forms of collaborative governance between educational institutions and socio-economic actors represent critical determinants for improving the systemic adaptability and occupational relevance of STEAM programs.
Keywords: STEAM education, competence formation, employability, stakeholder perspectives, curriculum transformation, Skills4Future
JEL Classification: I25, J24, O33, M1
Chairs: Ioana NEGRU & Lia BALTADOR
The title of the book aims at the normative layer of Economics, specifically focusing on the area of environmental policies; uninterrupted, however, by a generous theoretical register drawn from various economic, social and political doctrinal directions. It is, par excellence, a heterodox and pluralistic study. Within this context, a clearly defined dilemma emerges, demanding urgent resolution. Despite pursuing the same ultimate goal – better and better living through technological progress while preserving the biosphere – the ideas that configuring the architecture of this dilemma appear irreconcilable. In other words, reconciling scholars influenced by Georgescu-Roegen with those following Solow, Nordhaus, or Friedman, or aligning followers of Hartwick’s neoclassical approach with those of Daly, Costanza, Dasgupta, or Acemoglu proves challenging. On this register, the book aims to outline a distinct message: the time of purely theoretical, scholarly contemplation is over, and a normative activation is necessary to resolve this dilemma It argues that the traditional principle of profit as the sole entrepreneurial objective, rooted in individualism and self-interest, increasingly fades in the face of rising ethical and societal demands. Finally, ecological economics is insistently called to the fore with its specific and environmentally and socially friendly offer, with the potential to become classicized in an attempt to reshape the traditional epistema of the construction of wealth. With such a generous structure, the book can be of wide interest, targeting pupils, students, doctoral students, researchers, teachers, influencers, social or environmental activists, politicians or, simply, citizens interested in the fate of what is happening on planet Earth.
This chapter examines how economies can be provisioned sustainably in the face of ecological constraints while maintaining full employment and price stability. It argues that the prevailing macroeconomic frameworks misdiagnose both the nature of inflation and the constraints facing currency-issuing governments, leading to policy responses that rely on unemployment, suppressed demand, and underinvestment in social and environmental priorities. Drawing on insights from Modern Monetary Theory (MMT), the chapter reframes sustainability as a problem of real resource allocation and institutional design rather than financial affordability. Against this backdrop, it advances the Job Guarantee as a principal component of an alternative macroeconomic policy framework, one that replaces unemployment with a buffer stock of employed labour, anchors nominal values more effectively, and supports ecological transition without sacrificing social inclusion.
The chapter considers the implications for how inflation is understood and managed. In an ecologically constrained economy, inflation is unlikely to arise primarily from excess aggregate demand. Instead, it is more likely to emerge from disruptions to energy supply, food systems, housing availability, or other resource-intensive sectors. Recent inflationary episodes associated with energy price shocks, climate-related disruptions, and housing shortages illustrate this dynamic. In such contexts, inflation reflects underlying real resource constraints rather than an economy-wide excess of spending.
A Job Guarantee constitutes a central pillar of an alternative counter-inflation framework to the current approach which relies on monetary policy, a blunt tool which is inappropriate for the task for which it has been employed. By offering a fixed-wage job to all who are willing and able to work, the state establishes a nominal benchmark for labour in its own unit of account. The stabilising properties of this approach derive from its buffer stock dynamics. During downturns, workers transition into Job Guarantee employment rather than unemployment, protecting both incomes and skills, and limiting output losses. As private demand recovers, employers can recruit from the Job Guarantee pool by offering higher wages or better conditions. The size of the buffer stock therefore expands and contracts automatically over the business cycle, without the need for discretionary intervention.
We argue that environmental sustainability and full employment need not be treated as competing objectives. Addressing ecological limits requires a more granular approach to macroeconomic management than is currently the case, one capable of distinguishing between activities that must contract and those that must expand. A Job Guarantee contributes to this task by providing a standing mechanism for employment, stabilisation, and reallocation during this structural transition.
In a recent contribution to environmental policy, Thomas Pogge recommends an Ecological Impact Fund (EIF). The fund could, he suggests, play a pivotal role in enabling greater diffusion of green technology in less developed regions. A defining feature of the EIF is that innovators retain patents on new technologies but must price at unit cost. Compensation for foregone monopoly rents comes from contributing governments and is paid for evidenced carbon reduction. A seeming strength of Pogge’s idea is its realism. The fund intends to sustain innovation while improving diffusion through the use of financial incentives, thereby appealing to the rational self-interest of the corporate sector. In this chapter, however, I query the sufficiency of financial incentives as a means to attract innovators to the scheme. I argue instead for a commitment-based model of agency and draw out the implications for a revised EIF.
This paper provides a critical examination of Social Ecological Economics (SEE) as articulated by Clive Spash, tracing its emergence as a dissident movement within ecological economics. The primary aims are threefold: (1) analyse Spash's three-pronged critique of mainstream ecological economics, namely methodological pluralism, fragmentation, and mainstream takeover; (2) articulate the foundational principles and proposed agenda of SEE as a radical alternative; (3) critically evaluate the practical viability of SEE's prescriptions, identifying key barriers to its adoption by policymakers and the general public.
The paper argues that while Spash's diagnosis of ecological economics's failings is accurate, the SEE framework suffers from weaknesses that must be addressed before it can achieve meaningful influence. Specifically, the paper identifies three core challenges: an excessively broad scope that undermines focused action, reliance on socialist ideological frameworks with poor historical track records and insufficient concrete proposals for navigating a post-growth transition.
The paper adopts a qualitative, critical review methodology grounded in documentary analysis. It engages with the corpus of Clive Spash's publications spanning four decades, alongside foundational texts in ecological economics, critical responses, and empirical studies of the field's evolution. The analysis proceeds through three sequential stages: (1) reconstructing Spash's critique of ecological economics using his own typology of failures, (2) synthesising the agenda of SEE from his scattered programmatic statements and (3) subjecting this agenda to critique that evaluates its coherence, feasibility, and historical precedents.
The analysis yields several findings. First, Spash's critique is substantively robust: ecological economics's indiscriminate methodological pluralism indeed enabled neoclassical formalism to dominate, its fragmentation into three incompatible camps prevents unified action, and mainstream economists strategically captured key institutions. Second, SEE offers a distinctive political economy approach centred on Kapp's theory of social costs, Georgescu-Roegen's thermodynamic limits and critical realism. However, preliminary assessment reveals that SEE's goals (revolutionise economics, solve social inequities, transcend fossil fuels, and redesign resource allocation) likely exceeds its practical capacity. The proposed distributive schemes of administrative price-setting or in-kind provisioning do not appear feasible for scaling at the level of the global economy. Finally, the paper finds that SEE lacks a credible transition strategy for post-growth adaptation, particularly regarding the sudden phasing out of fossil fuels or Global South development needs. These findings suggest that while SEE provides valuable diagnostic tools, its prescriptive framework requires substantial refinement before it can serve as a counterpoint to neoclassical orthodoxy.
The paper examines the role of these key concepts in studying green policies aimed at achieving a more sustainable pattern of development. Contemporary capitalism has achieved a significant increase of well-being through a sophisticated division of labour and a systematic substitution of energy for labour. However, this progress has come at the cost of disregarding waste and environmental degradation. Many consider humanity to be in a lock-in situation regarding the transition to an ecological-friendly economy.
Lock-in is an ideal-typical figure pointing to an inefficient behaviour due to habituation and costs of transition to a better solution (Goldstein et al. 2023). This concept is based on a rationalistic interpretation of the actor-structure relationship, leading to inadequate solutions such as nudging.
Institutionalism, starting from the idea of «ceremonial values», has proposed the principle of «ceremonial encapsulation» to highlight unfit institutions that deprive a community of higher levels of instrumental efficiency (Bush, 1989). However, this approach also assumes the existence of some superior technology.
The paper explores the relationship between individual agency and structural change in socio-technical systems starting from the notion of environmental awareness and technical encapsulation. It emphasizes the change of values needed to induce a systemic change of capitalism.
Abstract
Introduction: The distributional effects of environmental taxes are widely debated in fiscal policy and governance. Although essential for sustainability, these taxes may be regressive, disproportionately affecting low-income households. This study examines their impact on income inequality across the 27 EU member states over the period 2013–2023, with a particular focus on whether governance quality mediates this relationship and can mitigate their regressive effects.
Methods: The study uses a quantitative approach based on Eurostat and World Bank data, carried out in three stages: KNN clustering to group EU countries, multiple regression to test the direct effect of environmental taxes on inequality, and mediation analysis to assess institutional transmission channels. Inequality is measured using the Palma ratio, while environmental tax revenue, governance effectiveness (GE), and regulatory quality (RQ) serve as key variables. Unemployment and social protection expenditure are included as control variables to ensure robustness.
Results: The cluster analysis reveals substantial heterogeneity among EU member states in institutional and distributional terms. The regression results show no statistically significant direct effect of environmental taxation on income inequality, indicating the need to consider indirect transmission channels. In this respect, the mediation analysis identifies contrasting effects: governance effectiveness (GE) exerts a positive indirect influence, while regulatory quality (RQ) has an opposing effect, resulting in a significant net indirect impact. Finally, control variables confirm that social protection reduces inequality, whereas unemployment increases it, highlighting important redistributive dynamics within the EU fiscal context
Discussion: These results show that the impact of environmental taxes is nonlinear and depends on institutional quality. Strong governance can mitigate regressive effects through efficient revenue use and compensation mechanisms, while weak governance may increase inequality. Overall, the findings highlight cross-country heterogeneity in the EU and suggest that uniform green fiscal policies are inadequate, as institutions shape whether environmental taxes support sustainability or deepen inequality.
Conclusions: The study shows that while environmental taxes are necessary, their fairness depends on the regulatory capacity of public institutions. Targeted revenue recycling, such as lowering labour taxes or funding social transfers, is essential to offset regressive effects. Strengthening institutional quality and social safety nets is, therefore, key to ensuring that environmental taxes do not increase income inequality.
Keywords: Environmental taxation, Income inequality, Governance quality, Mediation analysis
JEL classification: D63, H23, Q58
Acknowledgement: This work was supported by a grant, PNRR, CF 193/28.11.2022, Funding Contract no. 760078/23.05.2023
Abstract: The growing frequency of geopolitical disruptions and energy crises has reshaped the global economic landscape, reinforcing sustainability as a strategic imperative for resilient development. This study is based on a comparative empirical analysis of the ESG pillars ((Environmental, Social, and Governance) and macroeconomic performance, focusing on the 27 EU member states and five benchmark Asian countries (China, Japan, South Korea, India, and Singapore), over the period 2000–2025. The research aims to capture the impact of economic, social, and governance factors through proxy indicators on economic performance, measured by economic growth as a percentage of GDP and the attraction of foreign direct investment. The main results indicate a long-term positive correlation between environmental indicators and government effectiveness on economic performance and investment attraction, with sustainability no longer being an optional condition but a mandatory one. In contrast, results for the Asian region are mixed, indicating a transition from a volume-based economy to one based on value added and the consistent attraction of foreign capital. The study acknowledges the limitations arising from the use of single proxy indicators for ESG factors. However, robustness tests confirm the model’s stability alongside technical estimates, with a view to validating the results and observing differences in the integration of sustainability across the European Union and Asia. The study contributes to the literature by bridging the gap between sustainability performance and macroeconomic outcomes across continents, offering empirical insights into how ESG integration can strengthen competitiveness and long-term economic stability. Its novel comparative framework highlights sustainability as an essential precondition for structural development and global investment positioning.
Key words: ESG, foreign direct investment, economic performance, European Union, Asia
JEL classification: Q56, F21, 047, F15, O53
Chairs: Diana VASIU & Ioana SBÂRCEA
The aim of this study is to compare the organizational structures of the cooperative banking sector in Denmark, Finland, and Poland, as well as their role and importance in the banking systems of these countries. The research covered the changes and current organizational structure of the sector, the number of branches, their share in the banking sector, and the scope of their operations. Basic parameters describing the financial situation of these institutions were also analyzed. Attention was drawn to similarities and differences in the functioning of cooperative banks in these countries, which also have historical roots.
This study analyzes the cooperative banking sectors in the following countries: Denmark, Finland, and Poland, which are members of the European Association of Cooperative Banks (EACB). The selection criterion was based on the availability of detailed data on cooperative banks published by the EACB, with a temporal and spatial perspective. The analysis period covered the years 2014-2024. The empirical basis for the issues addressed in this study is a review of the relevant literature and a comparative analysis of the cooperative banking sector in these countries.
The findings from the study indicate differences in the organizational structure of the cooperative banking sector in Denmark, Finland, and Poland. Danish cooperative financial institutions do not form a single, distinct organizational structure, as is the case in Poland and Finland. The Polish cooperative banking sector, on the other hand, is more similar to the Finnish one, but less centralized and the scope of protection is significantly narrower. The consolidated nature of cooperative banks' operations in Finland ensures their operational stability, as evidenced by the low bankruptcy rate of entities associated with the OP Financial Group.
The financial situation of cooperative banks in Denmark and Finland is better than in Poland, which influences the role and importance these institutions play in the banking sector. This is evidenced by the increasing number of members and clients of cooperative banks in Finland and Denmark. Against this background, Polish cooperative institutions fare modestly. Their activities and activity are not as visible or significant. The share of Danish and Finnish cooperative banking institutions in the banking sector, measured by asset size and loan market share, is significantly higher than in Poland. Moreover, the disparities concern not only the size of assets but also their equity, which determines the potential of these institutions in the financial market and their potential for further development. On the other hand, the growth rate of assets and net profit in recent years has been higher in Poland than in Denmark and Finland.
Realized volatility forecasting remains one of the most active research frontiers in financial econometrics, as volatility governs option pricing, risk-parity allocation, Value-at-Risk estimation, and macroprudential stress testing. Classical linear models, especially the Heterogeneous Autoregressive Realized Volatility (HAR-RV) model, remain notoriously difficult to beat at short horizons, yet they cannot capture the nonlinear, regime-dependent dynamics that dominate volatility behavior during market stress. Pure deep-learning approaches, by contrast, typically overfit and fail to exploit the strong linear persistence of volatility. This paper addresses that tension by proposing a disciplined residual-learning hybrid in which a compact Long Short-Term Memory (LSTM) network learns nonlinear corrections to a HAR-RV baseline, incorporating ARIMA log-volatility forecasts as an additional input, complemented by SHAP interpretability. The aim is to test whether nonlinear deep-learning corrections can systematically improve a well-specified linear benchmark in both a developed and an emerging equity market, and to identify economically meaningful drivers behind the improvement.
The empirical analysis uses daily data for the S&P 500 (^GSPC) and the CEE Fund (NYSE: CEE), a U.S.-listed proxy for Central and Eastern European equities, from January 2019 to December 2024. The dependent variable is the natural logarithm of one-step-ahead realized volatility, measured over a five-day rolling window. Features include three HAR horizons (daily, weekly, monthly), high-low range, log volume, negative semivariance, absolute returns, and an expanding-window ARIMA forecast. The pipeline is strictly out-of-sample: HAR-RV is fit by OLS on log horizons; ARIMA(p,d,q) is selected via AIC; and a shrunken LSTM (32 units, L2 regularization, gradient clipping, 22-day lookback) is trained to predict HAR residuals. The hybrid forecast is reconstructed as HAR plus LSTM-residual and exponentiated, benchmarked against standalone HAR-RV, ARIMA, GARCH(1,1), and pure LSTM models. Evaluation uses MAE, RMSE, R², QLIKE, and HMSE.
Preliminary results show the hybrid achieves R²=0.738 on the S&P 500 and R²=0.825 on CEE. On the highly efficient S&P 500, the hybrid matches HAR-RV and ARIMA on symmetric metrics while delivering the lowest HMSE (0.087), indicating superior proportional accuracy during volatility spikes. On the less efficient CEE market, the hybrid is the outright best model on R² and RMSE, with DM p=0.175 versus HAR-RV. Against pure LSTM, the hybrid wins decisively on both markets (DM p<0.001). SHAP reveals a strong recency bias (lags t-1 to t-4) and a distinct cross-market contrast: beyond core volatility persistence, intraday high-low range is the strongest residual driver on the S&P 500, while recent daily shocks (daily RV and absolute returns) drive CEE forecast adjustments, reflecting fundamental differences in market efficiency.
The aim of this study is to compare the organizational structures of the cooperative banking sector in Denmark, Finland, and Poland, as well as their role and importance in the banking systems of these countries. The research covered the changes and current organizational structure of the sector, the number of branches, their share in the banking sector, and the scope of their operations. Basic parameters describing the financial situation of these institutions were also analyzed. Attention was drawn to similarities and differences in the functioning of cooperative banks in these countries, which also have historical roots.
This study analyzes the cooperative banking sectors in the following countries: Denmark, Finland, and Poland, which are members of the European Association of Cooperative Banks (EACB). The selection criterion was based on the availability of detailed data on cooperative banks published by the EACB, with a temporal and spatial perspective. The analysis period covered the years 2014-2024. The empirical basis for the issues addressed in this study is a review of the relevant literature and a comparative analysis of the cooperative banking sector in these countries.
The findings from the study indicate differences in the organizational structure of the cooperative banking sector in Denmark, Finland, and Poland. Danish cooperative financial institutions do not form a single, distinct organizational structure, as is the case in Poland and Finland. The Polish cooperative banking sector, on the other hand, is more similar to the Finnish one, but less centralized and the scope of protection is significantly narrower. The consolidated nature of cooperative banks' operations in Finland ensures their operational stability, as evidenced by the low bankruptcy rate of entities associated with the OP Financial Group.
The financial situation of cooperative banks in Denmark and Finland is better than in Poland, which influences the role and importance these institutions play in the banking sector. This is evidenced by the increasing number of members and clients of cooperative banks in Finland and Denmark. Against this background, Polish cooperative institutions fare modestly. Their activities and activity are not as visible or significant. The share of Danish and Finnish cooperative banking institutions in the banking sector, measured by asset size and loan market share, is significantly higher than in Poland. Moreover, the disparities concern not only the size of assets but also their equity, which determines the potential of these institutions in the financial market and their potential for further development. On the other hand, the growth rate of assets and net profit in recent years has been higher in Poland than in Denmark and Finland.
This paper examines the dynamic interactions between green bonds and major traditional financial markets using a multivariate vector autoregressive (VAR) framework. The key questions are whether green bond returns are mainly driven by conventional fixed income and macro financial factors, and whether green bonds act only as shock receivers or also as transmitters within the global system.
The analysis uses daily logarithmic returns over January 2019–December 2025 for six assets: the iShares Global Green Bond ETF (BGRN), Brent crude oil futures (OIL), the US dollar index (DXY), the S&P 500 index (SPX), the iShares 7–10 Year Treasury Bond ETF (IEF) and the iShares Global Clean Energy ETF (ICLN). Standard unit root and cointegration tests justify estimating a VAR model on returns, with lag length selected by information criteria. An economically motivated Cholesky ordering places global macro factors first (oil, dollar), followed by equities, Treasuries, clean energy and, finally, green bonds.
The empirical strategy combines Granger causality tests, impulse response functions with bootstrap confidence intervals and forecast error variance decomposition. This allows us to identify directions of causality, quantify the transmission of shocks and assess the relative contribution of each market to green bond volatility.
Results show that green bonds are strongly anchored in the conventional fixed income segment. Shocks to US Treasuries explain the bulk of BGRN’s forecast error variance at medium horizons, while the US dollar contributes a stable additional share, underlining the importance of global rate and currency conditions. In contrast, shocks from oil and clean energy equities have a smaller but non negligible impact, suggesting that the energy transition channel is present but secondary to the interest rate channel.
At the same time, green bonds are not purely passive. Granger tests and impulse responses indicate that innovations in BGRN can influence oil prices, US equity returns and, to a lesser extent, Treasuries, especially during the COVID 19 shock and the subsequent interest rate hiking cycle. Overall, the findings portray green bonds as primarily fixed income instruments that have nonetheless become an active node in the global financial network. This has implications for portfolio construction—limited diversification versus Treasuries but potential benefits against equity and energy risk—and for policymakers, who should monitor green bond markets as part of financial stability surveillance.
Behavioral finance has shaped recent years of research by shedding light on how financial decisions are influenced by investors’ cognitive and emotional biases. Our paper offers an integrative approach to recent literature, combining bibliometric and systematic perspectives to capture the dynamics of research and the emerging evolution of the field. The bibliometric component highlights an accelerated growth in academic interest in the study of investor behavior, supporting thematic polarization and the crystallization of author collaboration clusters. This section traces the trajectory of behavioral finance over the past five decades, outlining the key research areas. The core of this paper lies in the systematic analysis of the literature. This section consists of two pillars. The first proposes an analysis of antecedents, decisions, and outcomes, while the second focuses on the financial theories addressed, the geographical context, and the methods used to quantify market emotions. The methodology of this paper combines the PRISMA structure with a descriptive analysis and uses the ADO-TCM and PICO qualitative analysis frameworks, which encapsulate the most relevant contributions to behavioral finance research. The study’s findings reveal the persistence of recurring behavioral patterns. Risk perception, herd behavior, disposition bias, and investor overconfidence are prevalent in the behavioral landscape of the capital market. Educational level, gender, wealth status, and investment experience round out an individual’s behavioral profile. Prospect theory leads the American and Indian fronts as central research hubs. Methodological diversity, dominated by statistical and factor modeling, extends beyond investment decisions through the application of robo-advisor consulting. The interdisciplinary trend observed in the interpretation of psychological concepts, neuroscience, and experimental finance converges toward a comprehensive understanding of financial behavior. In the context of an irrational market, our analysis underlines a series of tensions and gaps in the existing literature, along with conceptual fragmentation, reliance on controlled experimental settings, and the fragility of existing predictive models. In this way, this research focuses on reconfiguring the approach to behavioral finance, oriented toward adapting behavioral theory to the dynamics of financial innovation and high-impact anomalies.
The integrity and informational value of financial reporting are fundamental to the proper functioning of capital markets, as they shape the extent to which firm-level signals are embedded in equity prices. This paper examines how the qualitative characteristics of financial disclosures influence the degree of stock price co-movement, proxied by return synchronicity, within the context of the Bucharest Stock Exchange. The empirical investigation relies on a panel dataset comprising 334 listed entities over the period 2008 - 2023 and applies econometric modeling to evaluate the association between reporting quality proxies and the informational structure of stock returns. The results reveal that market-wide factors account for approximately 19% of the variation in individual stock returns, indicating a predominance of idiosyncratic information in price formation. The empirical analysis indicates that accrual-based earnings management does not constitute a statistically significant determinant of stock return synchronicity. In contrast, the persistence of reported earnings demonstrates a positive and moderately robust association, suggesting that smoother and more predictable financial performance may lead to a marginal increase in return co-movement, likely due to enhanced market anticipation of firm prospects. Regarding firm-specific controls, both profitability and company scale display a negative and statistically significant linkage with stock return synchronicity, implying that larger and more efficient firms tend to convey more firm-specific information to investors. Conversely, no significant effects are identified for audit quality, industry, or financial leverage. By providing evidence from an emerging European market, this study enriches the literature on the informational role of financial reporting and its implications for price formation mechanisms. The findings offer insights for market participants and regulatory authorities interested in strengthening transparency and improving the informational efficiency of capital markets.
The increasing digitalisation of financial services has changed the way banks compete, intermediate funds, and transmit monetary and financial shocks across countries. In this context, the role of FinTech in shaping the integration of banking markets has become an important research question, especially for the European Union, where financial integration remains uneven across member states. This paper aims to examine the relationship between FinTech development and the degree of banking market integration in the EU, using country-level banking interest rate data and a factor-based measure of integration.
The empirical analysis will focus on the 27 EU member states over a period determined by data availability, expected to cover approximately the last fifteen years. Banking integration will be measured using monthly MFI Interest Rate Statistics, with separate attention given to deposit rates and lending rates. The main methodological approach relies on Principal Component Analysis applied in a rolling-window framework. The degree of integration is proxied by the share of variance explained by the first principal component, interpreted as the strength of the common factor driving banking interest rates across countries. A higher contribution of the first principal component indicates stronger co-movement and, therefore, a higher degree of banking market integration. Alternative transformations of the data, including standardised interest rate levels, interest rate spreads, and monthly changes in basis points, may be used as robustness checks.
The second stage of the analysis investigates whether FinTech development helps explain differences in banking integration across EU countries. For this purpose, the paper will construct a panel dataset combining the integration measure with annual FinTech indicators, such as internet banking usage, card payments, e-money transactions, digital payment intensity, or other comparable indicators of financial digitalisation. The econometric framework will rely on panel data models with country and time fixed effects, while alternative specifications may account for cross-sectional dependence, heterogeneous slopes, and potential endogeneity. Macroeconomic, financial, and banking-sector controls—such as GDP per capita, inflation, unemployment, private credit, banking concentration, non-performing loans, or sovereign risk—will be considered depending on data availability and model parsimony.
In the context of strengthening financial governance and aligning with European standards, the integration of human rights into the budget process becomes an essential direction for increasing the efficiency and equity of public finances. The concept of human rights-based budgeting is gaining increased relevance in emerging economies, including the Republic of Moldova, where challenges persist related to the efficient allocation of resources and ensuring equitable access to basic public services.
The purpose of the research is to assess the role of human rights-based budgeting as a tool for increasing public finance performance, with a focus on its applicability in the Republic of Moldova. The specific objectives are: (i) theoretical substantiation of the concept; (ii) analysis of the structure of public expenditures from the perspective of fundamental rights; (iii) identification of the relationship between budget allocations and relevant social indicators; (iv) formulation of directions for improving the budgetary framework.
The research uses a mixed approach, combining conceptual analysis with empirical analysis. The applied component is based on the analysis of statistical and budgetary data for the Republic of Moldova (public spending on health, education and social protection), correlated with social indicators (poverty rate, access to services, inclusion indicators). The methods used include comparative analysis, structural analysis and descriptive interpretation of data.
The research starts from the following hypotheses: (H1) directing public spending towards areas that reflect fundamental rights contributes to improving social performance; (H2) in the Republic of Moldova there is a gap between budget allocations and social results achieved; (H3) the explicit integration of human rights principles into program budgeting can increase the efficiency of the use of public resources.
Preliminary results highlight that, although the share of social spending is relatively significant, its efficiency remains limited, reflected in the persistence of social vulnerabilities. The analysis highlights the need for a better correlation between budget allocations and results achieved, as well as the introduction of rights-based performance indicators.
The originality of the research lies in integrating the human rights perspective into the assessment of public finance performance and in proposing an analytical framework applicable to emerging economies, adapted to the specifics of the Republic of Moldova.
The results of the study can contribute to improving the decision-making process in the field of public finances, providing support for the development of fairer and more efficient budgetary policies, aligned with sustainable development objectives and European standards.
This paper examines whether the predictability of WTI crude oil futures returns is a regime dependent feature of the market. Building on the theory of storage and risk premium explanations of commodity returns, we test whether a simple model using basis changes and realized volatility can deliver economically meaningful out of sample forecasts and whether its performance is concentrated in high volatility states.
The theoretical framework combines two channels. Changes in the spot–futures basis proxy shifts in inventories, scarcity and convenience yield, which should translate into subsequent futures returns. Realized volatility captures periods of heightened uncertainty and risk aversion, when pricing relations become tighter and risk premia more pronounced. These arguments imply that basis and volatility should be especially informative in turbulent markets, generating regime dependent predictability.
Empirically, we construct a monthly data set for WTI front month futures and spot prices over 1985–2024, resulting in 471 observations after cleaning and transformations. Futures returns are computed from front month settlement prices, while the predictors are the first difference of the spot–futures basis and 12 month realized volatility. The baseline model is a linear OLS regression with robust standard errors, estimated in a recursive expanding window scheme to mimic real time forecasting and avoid look ahead bias. Volatility regimes are defined exogenously by terciles of realized volatility.
Preliminary results show that, relative to a historical mean benchmark, the two variable model attains an out of sample R2R2 of about 40%, with a substantial reduction in mean squared forecast error and statistically significant Clark–West test statistics. This forecasting power is strongly regime dependent: in low volatility states, out of sample R2R2 is modest, while in high volatility regimes it exceeds 50%. These findings suggest that WTI futures returns are only weakly predictable in tranquil markets but become strongly predictable when volatility is elevated, highlighting the central role of regime dependent dynamics in crude oil futures pricing.
Chairs: Mircea FUCIU & Radu ȘERBAN
Romanian migration represents one of the most extensive and persistent demographic phenomena in Eastern Europe, evolving from isolated movements during the communist period into a complex process shaped by political, economic, and social transformations. This article provides a comparative analysis of three major waves of permanent migration of Romanian citizens to Western countries such as Germany, France, Italy, and Spain, corresponding to the periods 1990–1993, 2007–2010, and 2021–2024. Although the existing literature addresses these stages in a fragmented manner, an integrated evaluation of the determining factors and the long term dynamics of the phenomenon is still lacking.
The study employs a quantitative methodology based on the analysis of official statistical series, complemented by contextualized interpretations of economic and institutional developments in Romania and in the destination countries. The results highlight distinct characteristics for each wave: the first post communist wave is marked by the departure of ethnic minorities and migration driven by instability and poverty; the second wave, associated with Romania’s accession to the European Union, reflects the liberalization of mobility and the intensification of economic migration; the third and most recent wave indicates a diversification of motivations, the consolidation of circular migration, and the emergence of return trends influenced by labor market changes and the post pandemic context.
The comparative analysis offers insight into how Romanian migration aligns with the logic of sustainable development and European economic and social interconnectivity, contributing to a deeper understanding of the relationship between population mobility, structural transformations, and the reintegration prospects of migrants.
The concept of organizational culture is in continuous evolution, both theoretically and practically, through the development of research and analysis tools used today by organizations to enhance their performance.
Local business associations are important stakeholders with the capacity to bring together experts and expertise in attracting foreign investment, stimulating a dynamic business ecosystem, and representing international networks. This study starts from the premise that business associations are built upon the elements of a central organizational culture, which includes aspects such as visual identity, language elements, internal structure, and strategic directions. However, it also assumes that the imprint of the local culture is the one that ultimately shapes their distinct identity. This study aims to explore the unique elements that define the specific characteristics of organizational culture at the local level. The study wants to highlight employees’ perceptions regarding multiculturalism, leadership, and the role of stakeholders in shaping this distinct identity.
Romanian migration after 1990 has evolved into a structural process with profound effects on the labor market, economic development, and demographic balances, far beyond the scope of a conjunctural phenomenon. This paper analyzes the evolution of external mobility among Romanian citizens through the lens of internal socio economic transformations and regulatory changes at the European level, focusing on the periods in which migration flows intensified. The study examines how mobility liberalization, persistent wage differentials, industrial restructuring, and institutional changes have shaped migration decisions, as well as how these flows have reshaped regional development within Romania.
The methodology combines the analysis of official statistical series with comparative interpretations of economic, demographic, and legislative developments. The results highlight three major directions: the consolidation of economic migration as an adaptation strategy during the post communist transition; the transformation of the Romanian diaspora into a transnational community characterized by circular mobility patterns; and the emergence of new forms of migration, including skills based mobility and flexible temporary migration, influenced by post pandemic changes and the digitalization of the labor market.
A central element of the analysis is the regional economic impact, manifested through the deepening of territorial disparities between regions experiencing massive losses of active population and those with more stable economic dynamics; the reduction of local labor supply in rural and mono industrial areas; the increasing dependence of certain regions on remittances; as well as the emergence of positive effects such as return driven investments, migrant led entrepreneurial initiatives, and skill transfers. The study shows that migration simultaneously contributes to the vulnerability of some regions and the revitalization of others, shaping a profoundly asymmetric internal economic landscape.
By integrating these perspectives, the paper provides a comprehensive understanding of how Romanian mobility fits into the broader European labor market dynamics and highlights the long term challenges and opportunities for regional development and the reintegration of human capital from the diaspora.
In the cities of today, place branding has evolved from a communication tool aimed at attracting tourists and investment into a strategic governance mechanism that integrates territorial identity, public policy, and sustainable development. However, most approaches to “sustainable” place branding remain grounded in output-based frameworks, such as triple bottom line indicators, and tend to overlook the relational infrastructures that connect actors, resources, and narratives over time. This paper introduces the concept of relational sustainability in place branding. It compares two types of institutional intermediaries that contribute to it: a film office and a major international theatre festival.
Grounded in participatory place branding, territorial sustainability and Service-Dominant Logic, relational sustainability is defined as a territory’s capacity to generate shared value through transparent, equitable and trust-based interactions among stakeholders. Empirically, the paper adopts a comparative case study design. The first case is Malaga Film Office (Spain), an intermediary between local government and the audiovisual industry that implements a Sustainable Production Seal and eco-friendly filming guidelines, aligning creative economy growth with environmental objectives and the city brand “Malaga, la ciudad redonda”. The second case is the Sibiu International Theatre Festival (Romania) and the related Sibiu Culture Factory, where the municipality has strategically used culture and the reuse of industrial spaces as drivers of urban regeneration, tourism development, and international city branding, following the 2007 European Capital of Culture and integrating culture as a core pillar of the Integrated Urban Development Strategy 2021-2030.
Methodologically, the study adopts a mixed-methods approach, combining documentary analysis, secondary quantitative data, and qualitative insights. The documentary analysis includes strategic plans, sustainability protocols, and EU-funded project reports, enabling an understanding of policy frameworks and institutional priorities. This is complemented by secondary quantitative evidence on economic and tourism-related impacts, providing contextual indicators of territorial performance.
The paper aims to make the following contributions:
- it advances sustainable place branding theory by shifting attention from isolated outputs (e.g. green projects, visitor numbers) to relational capabilities such as participation, transparency, coordination and fair distribution of benefits.
- it proposes an initial typology of intermediary organisations in sustainable place branding, showing convergences and differences between film offices and cultural festivals as governance nodes.
Keywords: Place branding; relational sustainability; film offices; cultural festivals; urban regeneration; creative industries; territorial governance; sustainable development.
Abstract
Household purchasing power represents a key indicator of population welfare and economic stability. In the post-pandemic period, Romania has faced significant macroeconomic challenges, characterised by rising inflation and a sharp increase in interest rates following restrictive monetary policy measures adopted by the National Bank of Romania. Although necessary to curb inflationary pressures, higher interest rates have increased borrowing costs for households, particularly those holding mortgage and consumer loans, thereby affecting disposable income and living standards.
This paper aims to analyse the impact of rising interest rates on the purchasing power of Romanian households, with a particular focus on credit-consuming households. The research is based on a quantitative methodological approach, combining the analysis of secondary data from official statistical sources with a questionnaire-based empirical study conducted among Romanian households. The collected data were processed using statistical analysis methods implemented in SPSS.
The results indicate that rising interest rates have significantly reduced households’ capacity to save and constrained their ability to cover current expenditures, especially among households with multiple active loans. Although nominal income levels have increased in recent years, these gains have not fully compensated for the negative effects of inflation and higher borrowing costs. The findings underline the need for coherent monetary and fiscal policies aimed at protecting household purchasing power and ensuring long-term financial stability.
Keywords: interest rate, household purchasing power, credit, inflation, living standards, Romania
Chairs: Claudia OGREAN & Monica ȚICHINDELEAN
Abstract
This paper examines the main coordinates of educational management in the context of the institutional transformations affecting pre-university education in Giurgiu County, Romania.
The study is based on qualitative documentary analysis of the current Romanian legal framework, OECD and UNESCO policy documents, county statistical publications and public managerial documents issued by the Giurgiu County School Inspectorate.
The analysis shows that educational management in Giurgiu County is currently structured around five interrelated coordinates: regulatory alignment, pedagogical leadership, participatory governance, territorial adaptation and evidence-informed organisational resilience.
The county context is relevant because official data indicate a predominantly rural profile and a school network that requires differentiated managerial responses.
The paper concludes that effective school leadership depends not only on compliance with reform, but also on the capacity to translate new regulations into coherent institutional practice, collaborative decision-making and context-sensitive school improvement.
Keywords: educational management; school leadership; institutional transformation; governance; Giurgiu County
J.E.L. classification: I21, I28, M10
Abstract. The concept of innovation, linked to the idea of economic singularity, is becoming increasingly relevant in the context of the rapid transformations driven by digitalization, artificial intelligence, and globalization. This article aims to analyze how economic singularity—defined as the point at which technological progress produces exponential and irreversible changes in economic structures—influences contemporary and future business models. The study explores the interdependence between innovation and competitive advantage, highlighting the role of emerging technologies in redefining value, productivity, and market relationships. Recently, numerous publications and political strategies have emerged at European and global level regarding the need for economic innovation based on advanced technologies and disruptive innovations, such as artificial intelligence, big data, and fintech. All these technologies bring with them various benefits, such as increased labor productivity, replacement of heavy and repetitive work, etc. At the same time, various questions arise in society, at the state level, in academic circles, situations in which the level of innovation can get out of control.
Research objective: How the convergence of advanced technologies (AI, blockchain, automation, etc.) can lead to a fundamental change in the structure of economies and financial markets. What will the global economy look like in the near and distant future, given that disruptive technologies could reach a point of economic "singularity" where changes become impossible to anticipate?
Methodologically, the research combines a theoretical analysis of the literature with an examination of current trends in the business environment, including automation, platformization, and the data-driven economy.The research methods used are qualitative analysis, observation and trend analysis, synthesis, and simulation. Studying economic effects using concepts from physics.
The research results will show how innovations in technology and the global economy can lead to a point of singularity, where rapid changes are so significant that they become difficult to predict. Expected results include: transformation of business models; increased automation and artificial intelligence; emerging economic and financial systems; social and economic challenges. The results suggest that organizations that adopt innovative strategies focused on flexibility, adaptability, and the integration of disruptive technologies are significantly more likely to thrive in an economic environment characterized by uncertainty and rapid change. At the same time, the risks associated with economic singularity—such as labor market polarization and the concentration of economic power—are discussed.
Key words: economic singularity, technological innovations, artificial intelligence, labor market
Classification JEL O33
In an era defined by permacrisis, global brands face the dual challenge of maintaining market relevance while supporting consumers through periods of intense psychological and economic stress. This research investigates the role of Generative Artificial Intelligence(GenAI) as a transformative tool for marketing resilience, focusing on its capacity to stabilize consumer-brand relationships during disruptions. While traditional crisis marketing often relies on static, broad-reach messaging, this paper argues that GenAI enables a shielding effect through hyper-personalized, real-time communication that addresses individual consumer vulnerabilities. The study is grounded in Social Cognitive Theory (SCT), specifically utilizing the framework of triadic reciprocal determinism. By analyzing the interplay between the crisis environment (external stressors), personal cognitive factors (consumer anxiety and self-efficacy), and behavioral outcomes (consumption patterns), the article defines how GenAI shifts the consumer’s internal locus of control. The paper argues that GenAI does not merely automate content, rather it modifies the consumer’s cognitive environment by providing tailored information that enhances self-efficacy – the belief in one’s ability to navigate financial or social instability. The methodology integrates a systematic review of emerging AI marketing literature with applied case studies of brands that leverage algorithmic agility during recent market shocks. These real-world examples demonstrate how AI-driven personalization mitigates algorithm aversion and restores consumer trust by providing transparent, utility-focused guidance rather than generic promotional content. A central contribution of this paper is the proposal of the AI Resilience Model (ARM). This strategic framework provides practitioners with a roadmap to identify low self-efficacy consumer segments using predictive analytics. The model then dictates the deployment of supportive, AI-generated content designed to foster adaptive coping mechanisms. By bridging the gap between fundamental psychological theory and applied AI technology, this research contributes to the Marketing and Consumer Behavior field by illustrating how technology can humanize brand responses in inhumane times. Ultimately, the GenAI Shield is presented as a socio-cognitive buffer. It suggests that marketing resilience in the age of AI is not defined by corporate survival alone, but by the brand’s ability to use intelligent systems to restore consumer agency and maintain the delicate equilibrium between well-being and commercial sustainability in volatile markets.
The evolution of Corporate Social Responsibility (CSR) represents a central trajectory in the redefinition of the role of business in contemporary economic systems. Beginning in the second half of the twentieth century, CSR ushered in a shift away from an exclusively profit-oriented vision, promoting the integration of social, ethical, and environmental considerations into corporate decision-making processes. In its initial phase, however, CSR was configured as a set of predominantly voluntary and discretionary practices, often limited to reputational or philanthropic initiatives, with limited capacity to structurally impact corporate strategies. Starting from these premises, this paper aims to answer the following research question: what was the transformation path of CSR from a voluntary practice to a strategic lever capable of guiding governance and long-term value creation?
The turning point in managerial terms was represented by R. Edward Freeman's stakeholder theory, which redefines the firm as a system of relationships between multiple stakeholders. From this perspective, management is called upon to balance and integrate the expectations of heterogeneous stakeholders, transcending the exclusive focus of shareholders and orienting corporate action toward the creation of shared value. The theoretical contributions of Carroll and Elkington fit into this evolutionary path, providing a systematization of corporate responsibilities and introducing an integrated view of performance across economic, social, and environmental dimensions. The paper continues its analysis of the evolution of CSR with an illustration of ESG (Environmental, Social, Governance) criteria, which translate the stakeholder approach into measurement systems, performance indicators, and reporting tools, promoting the integration of sustainability into decision-making processes and governance models.
The final section of the paper presents hybrid business models, in which stakeholder orientation is incorporated into the organizational structure and management logic. These models represent the outcome of the path proposed in the paper and introduce an innovative managerial approach capable of combining economic objectives and social impact within a long-term corporate strategy.
Technostress, defined as the psychological strain arising from the need to adapt to rapidly evolving information and communication technologies (ICTs), has emerged as a critical challenge in remote work contexts. Rooted in job demands–resources theory, technostress reflects negative effects on individuals’ attitudes, behaviors, cognition, and overall psychological well-being, particularly among teleworkers who rely heavily on digital tools for communication, coordination, and task completion. As remote and hybrid work arrangements continue to expand, understanding the implications of technostress for both employees and organizations has become increasingly important. This study examines technostress and its associations with work-related outcomes and demographic factors in a sample of 207 remote workers.
All constructs demonstrated acceptable to strong internal consistency (technostress α = .696; perceived productivity α = .911; flexibility α = .829), supporting the reliability of the measures used. Correlational analyses revealed that technostress was moderately and negatively associated with productivity (r = –.382, p < .001), indicating that higher technostress is linked to lower perceived efficiency, focus, and output when working remotely. A smaller but statistically significant negative relationship was also found between technostress and flexibility (r = –.163, p = .019), suggesting that greater autonomy, scheduling control, and the ability to manage work around personal needs may help reduce technostress.
Gender comparisons indicated minimal differences overall, although women reported slightly higher productivity; importantly, no significant gender differences were observed for technostress levels. A Spearman’s rho analysis further identified small but significant demographic patterns: technostress was positively associated with age cohort (ρ = .139, p = .046), indicating higher levels among older participants, and negatively associated with residence (ρ = –.183, p = .008). Age and residence were also modestly related (ρ = –.162, p = .020), suggesting some variation in living contexts across age groups.
Overall, the findings highlight technostress as a meaningful factor influencing remote work experiences, with modest but noteworthy demographic variation. These results underscore the importance of organizational strategies aimed at reducing technostress, such as improving digital support, training, and workload management, to enhance employee well-being, maintain performance, and support sustainable remote work practices across diverse populations.
The impact of banking digitalisation on retail and corporate client acquisition in Romania
Extended Abstract
This paper examines banking digitalisation in Romania from the perspective of financial institutions’ capacity to attract new clients — both individuals (retail) and legal entities (corporate) through digital channels. The study is motivated by the accelerated structural transformation of the Romanian banking system, particularly after 2020, when the COVID-19 pandemic compressed four to five years of digital progress into a very short timeframe. IRES/ARB (2024) data confirm that 57% of the adult population now conducts transactions via internet or mobile banking, compared to 30% in 2020, marking the threshold of mass digital adoption.
The research is structured around three objectives: assessing the effective digitalisation level of six major institutions (BCR, Banca Transilvania, Raiffeisen Bank, BRD, ING Bank and Revolut) through measurable indicators; identifying the critical success factors in digital client acquisition beyond the mere existence of mobile applications (UX/UI quality, onboarding simplicity, processing speed, perceived security); and analysing the fundamental behavioural differences between retail and corporate segments, with emphasis on the digitalisation gap recorded among SMEs.
Methodologically, the study adopts a descriptive-analytical approach combining a systematic literature review (2011–2025) with critical examination of institutional reports (BNR, EIB, IRES/ARB) and conceptual modelling of causal mechanisms linking digitalisation, user experience and banking performance.
Preliminary results indicate that digitalisation significantly enhances client acquisition, but its impact differs across segments. Retail clients are primarily driven by convenience, speed and ease of use, while corporate clients focus on operational efficiency, integration with internal processes and regulatory compliance. The findings also reveal a persistent digital gap among SMEs, which represents both a structural limitation and a potential growth opportunity for banks.
A fundamental behavioural asymmetry is confirmed: individuals adopt digital banking for convenience and speed, while legal entities prioritise operational efficiency and regulatory compliance integration. A persistent gap among SMEs where 72.1% record very low digital intensity represents both a vulnerability and an unexploited market opportunity. The study proposes an integrated framework for analysing banking digitalisation as a strategic vector of institutional growth.
Keywords: banking digitalisation, digital onboarding, open banking, customer acquisition, banking performance, SMEs.
This research aims to analyze the structural impact of market deregulation on consumer behavior, specifically focusing on the "paradox of fulfillment". The paper explores how the elimination of scarcity—traditionally a core driver of economic value—alters the psychological and social utility of goods. By examining contemporary economic models that prioritize immediate satisfaction, the study seeks to identify the threshold at which absolute desire fulfillment ceases to drive growth and begins to erode social cohesion. This analysis is critical in understanding the shift from traditional commodity-based markets to experience-driven economies where value is increasingly subjective and tied to psychological gratification. The study employs a mixed-methods approach. First, a comparative analysis of longitudinal macroeconomic data from OECD countries is used to correlate high consumption indices with social stability indicators. Second, the paper utilizes a game-theory framework to simulate market environments where traditional scarcity is artificially removed. This allows for a formal evaluation of "utility exhaustion" and its consequences on labor productivity and long-term capital investment. The research also integrates behavioral economic theories to assess how labeling and social categorization (as proxies for non-monetary costs) function as alternative regulatory mechanisms. By incorporating these multidimensional variables, the methodology ensures a comprehensive view of how non-financial incentives influence modern decision-making processes. Initial findings suggest that when economic systems move toward the absolute fulfillment of consumer desires without calibrated scarcity, there is a measurable decline in marginal utility that transcends individual products, affecting overall market engagement. Preliminary data indicates that social labeling (reputation-based systems) often emerges spontaneously to replace traditional price signals in high-fulfillment environments. The research concludes that sustainable economic stability requires a dual framework: one that manages material abundance while accounting for the social costs of absolute desire satisfaction. This proposed framework suggests that future economic policies must integrate psychological constraints to maintain functional market dynamics and long-term societal equilibrium in an era of unprecedented accessibility.
The enforced collection of tax receivables represents the final stage of tax administration, through which the state forcibly recovers owed amounts (taxes, duties, contributions) if they have not been paid voluntarily. The procedure is primarily regulated by Law no. 207/2015 on the Tax Procedure Code.
The tax authority may use the following methods, successively or simultaneously:
• Garnishment (Attachment of Assets): Blocking bank accounts or withholding amounts owed to the debtor by third parties (e.g., employer, clients).
• Enforced Execution of Movable Property: Seizure and sale of objects, inventory, or vehicles owned by the debtor.
• Enforced Execution of Immovable Property: Seizure and auctioning of land or buildings.
Enforced collection begins with the service of a summons. If the debt is not settled within 15 days of the summons notification, or if the tax authority is not notified regarding the intent to initiate a mediation procedure, the enforcement measures continue. The summons is accompanied by a copy of the enforceable title issued by the enforcement body.
In order to carry out the mediation procedure, the debtor shall notify the tax authority of their intention within 15 days of receiving the summons. The notification must be accompanied by documents and information supporting their economic and financial situation.
Any seizable amounts representing income and cash availability in local or foreign currency, securities, or other intangible movable assets, held by and/or owed to the debtor by third parties—or which they will owe/hold in the future based on existing legal relationships—are subject to enforced collection through garnishment.
Any movable assets of the debtor are subject to enforced execution, with the exceptions provided by law. The enforced execution of movable assets is carried out through their seizure and recovery (liquidation), even if they are held by a third party. The seizure is established through an official minute (proces-verbal).
If the tax debt is not settled within 15 days from the date the seizure minute is concluded, the seized assets shall be liquidated without further formalities, except for situations where, according to the law, the seizure was lifted or the enforced collection was suspended.
The competent enforcement body proceeds with the recovery of the seized assets through:
a) agreement of the parties;
b) sale of movable assets through consignment;
c) direct sale;
d) sale by auction, including by electronic means;
e) other methods permitted by law, including the recovery of assets through auction houses, real estate agencies, or brokerage firms, as applicable.
Decentralized finance (DeFi) is increasingly discussed as a successor to traditional financial intermediation, yet its significance for investment capital depends on whether protocol-based mechanisms can deliver durable improvements in settlement, governance, and market integrity rather than episodic gains driven by speculative cycles. This article evaluates DeFi as an alternative financial architecture for capital formation and investment intermediation by integrating classic theories of transaction costs and agency with contemporary evidence and policy assessments. It argues that DeFi is best understood as a modular system that can replicate core functions—trading, secured lending, collateral management, and cash-like settlement—through smart contracts and blockchain-based recordkeeping, while simultaneously introducing distinctive risks tied to code vulnerabilities, oracle dependence, transaction ordering (MEV), and governance capture. The analysis synthesizes how automated market makers and liquidity pools reshape price formation; how overcollateralized lending and algorithmic liquidation alter leverage dynamics; and how stablecoins and tokenized treasuries function as the on-chain “cash leg” and bridge to regulated markets. Drawing on international policy frameworks, the article further contends that DeFi’s integration with mainstream investment capital will likely proceed through hybrid arrangements—regulated stable settlement assets, qualified custody, compliant interfaces, and permissioned liquidity venues—rather than through wholesale displacement of existing institutions. The conclusion is conditional: DeFi can become a meaningful layer of future investment infrastructure where it demonstrably reduces post-trade frictions and enables programmable settlement, but its capacity to host fiduciary-grade capital at scale will be bounded by progress in security engineering, market design for execution fairness, and legally enforceable governance arrangements.
This research provides a comprehensive analysis of the information architecture governing public sector transparency in Romania, with a primary focus on budgetary reporting and fiscal accountability. In the context of increasing European demands for financial discipline, the study maps the complex circulation of data between critical operational systems, specifically Forexebug and PatrimVen, and their corresponding public reporting platforms. The central objective is to track the lifecycle of financial information, from its initial registration in the accounting records of public entities to its final disclosure as budget execution reports, ensuring alignment with EU Directive 85/2011 on requirements for budgetary frameworks.
The methodology employs Data Flow Mapping techniques to evaluate the processes of collecting, validating, and aggregating accounting data. This approach identifies systemic "information gaps" and failures in budgetary reporting caused by a lack of interoperability between Ministry of Finance systems and national open data portals. The analysis highlights that while the introduction of Forexebug has enhanced cross-validation with Treasury data, the reporting landscape remains hampered by "hybrid" practices where electronic submissions often still rely on manual data preparation and non-digital validation steps. Furthermore, the study evaluates the limitations of cash-basis accounting in assessing true financial performance, arguing for the necessity of fully transitioning toward an accrual-based accounting framework to bridge the existing information asymmetry between public institutions and citizens.
The research introduces an original Matrix of Digital Transparency Maturity to assess public institutions based on their degree of internal system integration and the resulting quality of financial disclosure. Preliminary results reveal significant fragmentation: institutions with integrated digital architectures provide granular, real-time data on budget implementation, whereas those reliant on manual processes struggle with accuracy, timeliness, and cross-system consistency. The findings demonstrate a direct correlation between the degree of automation in accounting flows and the quality of published budgetary indicators.
The paper proposes a standardized information flow based on a unified financial reporting protocol to ensure real and automatic convergence between local accounting data and mandatory statistical reporting in accordance with ESA 2010 standards. By integrating EU-wide open data directives and digital governance strategies, this framework offers a strategic roadmap to enhance administrative efficiency, reduce human error, and cultivate deeper public trust through fiscal data that is not only accessible but also consistent and actionable for all stakeholders.
Abstract
The agricultural sector in Central and Eastern Europe (CEE), with a particular focus on Romania, is characterized by a structural paradox: high agricultural potential coupled with a limited capacity to generate value added along the production chain. Although transitioning towards high-performance agribusiness requires significant capital infusions, access to traditional bank lending remains restrictive for many agricultural firms. Digital financial solutions and non-traditional funding instruments (Agri-FinTech) offer viable alternatives, yet their large-scale adoption is heavily contingent on the human factor.
This paper evaluates the capacity of regional agricultural firms to assimilate financial innovation by analyzing the intersection between generated value added and human capital profiles. The research explores how labor market characteristics and the decision-making profile of agricultural management-viewed through the lenses of qualification, corporate governance, and openness to innovation-act as key determinants or barriers to the utilization of digital financial services.
Taking a microeconomic approach, the study demonstrates that the successful implementation of non-traditional finance does not depend exclusively on the availability of technological infrastructure, but rather on the degree of organizational sophistication. This work addresses a major gap in the current literature by shifting the focus from macro-technological barriers to micro-structural ones. The findings highlight the critical need to align support policies and FinTech products with the educational, demographic, and operational realities of decision-makers in Eastern European agriculture.
Public sector transparency bears a significant importance in the underlying processes that foster advancing democratic governance, building trust in public systems and institutions, all while mitigating negative phenomena such as corruption and misinformation. Current developments reveal a straining concern for core themes surrounding public trust and comprehension of public systems, while unveiling the effects of imperfections in their intrinsic principles.
Transparency is a core pillar of public governance soundness, part of its backbone, alongside accountability, rule of law, integrity, efficiency, effectiveness, digital capacity, participation or stakeholder engagement, responsiveness, inclusiveness and social equity, sustainable outcomes and effective control. De facto, transparency is a multifaceted and ambiguous concept, which conveys the level of visibility of governmental processes, decisions and finances coupled with the extent to which the before mentioned aspects are made accessible and coherent to the general public. OECD views transparency and openness as foundational values of governance. In order to concretize the concept of transparency, an array of indicators are employed: budget disclosure, access-to-information compliance, open data availability, procurement disclosure and financial reporting quality.
The present paper aims at providing a viable assessment framework of public sector transparency and subsequently connecting it to topical implications and effects regarding corruption and democratic participation. By consequence, the proposed methodology introduces a composite multi-criteria assessment index, designed for the empirical operationalization of public sector transparency by aggregating sub-indexes across complementary analyzed dimensions. Furthermore, the advanced index normalizes the data and facilitates future comparative studies. The index is then applied on the available data for Romanian municipalities, contextualized and contrasted against the current state of the scientific literature on the topic.
The study confirms the initial expectations in that the general baseline of transparency has improved in Romanian public institutions, specifically considering formal regulatory alignment juxtaposed with enhancements in digital disclosure protocols. Ultimately, the resulting findings suggest the need for building a culture of transparency which surpasses mere formal compliance, unveiling challenges in implementing open government initiatives. Moreover, there is a great opportunity and value for instrumenting strong accountability mechanisms, through genuine and independent avenues for holding public actors accountable. Finally, we emphasize the need for improved analytical accuracy, highlighting areas that require theory development and empirical research, from which we stress the need for citizen engagement data, thorough quantitative impact assessments and longitudinal analysis of reforms.
The study explores the evolution of the research on the Environment Kuznets Curve (EKC) through a exhaustive bibliometric analysis, using SCOPUS platform, aiming to map its theoretical foundations, empirical contributions and emerging research directions. The EKC hypothesis, originally introduced by Grossman and Krueger in 1991, proposes an inverted U-shaped relationship between economic growth and environmental degradation, suggesting that environmental pressure tend to worse in early stages of development before gradually improving as income level rise. The bibliometric analysis was performed on a Scopus database, the query generating a number of 634 articles, covering the last 25 years of academic research. The bibliometric network visualization reveals the main thematic clusters, keyword co-occurrence and dominant trends in specialized literature, illustrating at the same time the multidisciplinary nature of EKC research, a field that integrates environmental economics, energy studies, sustainability science and econometrics methodology. Frequent associations with keywords such as” economic growth”,” carbon emissions”,” energy consumption” and renewable energy” indicate that the EKC literature mainly focuses on the relations between economic development and environmental degradation. At the same time, the study demonstrates that EKC research has emerged as a globally interconnected scientific field, supported by academic contributions from both developed and emerging economies. This reflects the worldwide relevance of the issue of harmonizing economic growth with the imperatives of ecological sustainability and highlights the increasingly important role of international partnerships in advancing environmental economics research. Although the field is highly developed, several important research gapes within the EKC literature were reveal. One major research gap concerns the limited integration of social dimensions into EKC studies, related keywords appearing relatively peripheral and weakly connected, compared to dominant environmental and economic terms. Another gape relates to technological transformation and digitalization, as future research could investigate how artificial intelligence, smart cities and green innovation influence the EKC relationship and environmental sustainability. Furthermore, EKC research remains heavily carbon-centered and could be improved with future research that pays increased attention to biodiversity loss, ecosystem service, circular economy and climate resilience. Regarding methodologically, there is a concentration around traditional econometric methods, such as panel data analysis and regressions. Thus, future studies may take into consideration emerging techniques such as machine learning, spatial econometrics and dynamic simulations. Regional diversity should also be considerate, as most of the studies are related to China, BRICS and emerging economies, neglected small island and low-income countries.
The transition toward sustainable and digitally enhanced higher education ecosystems has become a critical priority in the context of global environmental and technological challenges. The GREENVERSITY project addresses this need by promoting the development of green competencies and digital laboratories as innovative infrastructures that foster both sustainability and entrepreneurial thinking within universities. At its core, the project emphasizes the concept of “human infrastructure” as a driver of innovation, highlighting the role of competencies, and organizational culture in enabling green transitions. By integrating digital technologies with sustainability principles, GREENVERSITY supports the creation of laboratories that are not only environmentally responsible, but also resilient and adaptive to complex global systems. A key aspect of this approach is the shift from linear problem-solving to systemic thinking, particularly in digital laboratory environments where automated processes interact dynamically within broader networks .
From an entrepreneurship and innovation perspective, the project encourages the development of new business models and educational practices that align with green economy objectives. It promotes collaboration between academia, industry, and policymakers, facilitating knowledge transfer and the co-creation of innovative solutions. Furthermore, GREENVERSITY contributes to the development of entrepreneurial competencies among students and researchers, equipping them to address sustainability challenges through innovative ventures and research initiatives.
The findings presented in this paper demonstrate that the integration of green and digital strategies in higher education can generate significant value, both in terms of environmental impact and innovation capacity. By positioning universities as key actors in the transition toward sustainable economies, the GREENVERSITY project exemplifies how entrepreneurship and innovation can drive systemic change. The paper concludes by outlining the implications for policy and practice, emphasizing the need for scalable models that can be replicated across diverse educational contexts.
Nowadays, the hotel industry is undergoing a significant transformation, in which disruptive technologies, such as Artificial Intelligence, Virtual Assistants, Chatbots or Blockchain, contribute significantly to redefining the guest experience and the operational models of hotel groups. By adopting various artificial intelligence applications, such as automated guest communications, in-room smart technology, sentiment analysis and guest review processing, and personalized booking experiences, global hotel chains are reaching new levels of operational efficiency and customer engagement. This shift goes beyond basic automation, improving decision-making and resource management, and marking a new era in which technology and human creativity work together to create innovative solutions and a competitive edge. In this context, the present paper aims to highlight how artificial intelligence acts as a driver of innovation in global hotel chains and transforms the industry through new solutions. The study results reflect a significant shift in strategic priorities: beyond the 34% of hotel chains that have implemented AI assistants, the industry is clearly moving toward proactive agents, as 40% are planning their adoption. Despite the continued dominance of traditional tools such as chatbots and revenue management systems (40–42%), the focus is expanding to areas like guest engagement and analytics, with 48–50% planning adoption.
Overall, the findings demonstrate that global hotel chains are successfully replacing basic automated tasks with innovative, autonomous technologies, highlighting their growing application in business areas such as staff training and performance monitoring, marketing and communication, customer service, guest experience and personalization, energy management and sustainability efforts, and fraud prevention and cybersecurity.
As digital technologies restructure labor markets, business models, and the conditions of economic participation, digital literacy has shifted from a marginal competency concern to a central research priority in business and management (B&M) literature. Yet the construct remains conceptually fluid, continuously redefined in response to technological change and lacking clear analytical boundaries despite rapid growth in the literature. This study maps the conceptual development of digital literacy in B&M research, identifying dominant thematic configurations in its conceptual framing and emerging directions shaping its organizational relevance.
The empirical basis is a bibliometric co-occurrence analysis of author keywords from 385 publications indexed in the Web of Science B&M category (2010–2025). Using VOSviewer, a network of 87 keywords was generated and grouped into six thematic clusters. The analysis integrates average publication year overlay visualization and normalized citation impact indicators to identify temporally differentiated patterns of thematic concentration and influence; for analytical clarity, the six clusters were interpreted as five broader thematic configurations.
Read through this temporal lens, the field exhibits a cumulative expansion in both the meaning and organizational role attributed to digital literacy: (1) An early configuration frames digital literacy primarily as a skills deficit associated with the digital divide, internet access, and public administration capacity. (2) A subsequent organizational capability configuration consolidates around technology adoption, digital transformation, innovation, leadership, and HRM, positioning digital literacy as a strategic capability supporting organizational continuity and competitiveness (particularly during Covid-19). (3) An industrial transformation configuration connects the construct to automation, Industry 4.0, and entrepreneurship, highlighting workforce readiness for structural economic change. (4) A socio-economic inclusion configuration embeds digital literacy within financial inclusion, fintech, and women’s entrepreneurship, reframing it as a condition for economic participation and market access. (5) The most recent configuration centers on AI literacy, where generative AI, ChatGPT, and digital leadership cluster around higher education and organizational contexts, signaling an emerging emphasis on managerial capability in AI-enabled environments.
While clarifying the emergence of AI literacy as an emerging conceptual frontier, the analysis identifies a central unresolved tension: whether AI literacy represents a sub-dimension of digital literacy, its contemporary expression, or a successor construct. Future research should focus on managerial competencies for AI adoption and governance, and on the organizational conditions that enable digital/AI literacy to translate into performance outcomes.
The present paper aims to assess the efficiency with which European Union Member States transform the adoption of artificial intelligence at the enterprise level, under ESG constraints, into sustainable economic, social and institutional outcomes. In the current context, characterized by the acceleration of digital transformation processes, artificial intelligence is widely recognized as a key driver of economic competitiveness. However, its contribution to sustainable performance is not uniform, as it is conditioned by structural and institutional factors specific to each economy.
From a methodological perspective, the research employs the Data Envelopment Analysis (DEA) method, applying a basic radial model, output-oriented and characterized by variable returns to scale. The analysis focuses on the 27 European Union Member States, considered as comparable decision-making units, and is based on data for the year 2024, given their availability at the time of the analysis. The set of variables is designed to capture both the digital dimension and sustainability-related constraints. Accordingly, the input variables include the level of artificial intelligence adoption in enterprises, greenhouse gas emissions and energy intensity, while the output variables reflect sustainable performance through the share of renewable energy in final energy consumption, the employment rate and a composite governance indicator, constructed as the average of control of corruption, government effectiveness and rule of law.
The results highlight significant differences across the analyzed countries in terms of the efficiency of transforming inputs into sustainable outputs. A total of 16 countries are positioned on the efficiency frontier, while the remaining economies exhibit varying degrees of inefficiency. Nevertheless, the relative proximity of efficiency scores to unity suggests that most inefficiencies are moderate and could be reduced through improved policy coordination and more effective use of available resources.
Furthermore, the findings indicate that a higher level of artificial intelligence adoption in the business sector does not automatically translate into superior sustainable performance. Efficiency is significantly influenced by the quality of the institutional environment and the ability of economies to integrate digital technologies within coherent development strategies. In this respect, the results underline the importance of complementarity between digitalization and governance, suggesting that the benefits of digital transformation are maximized in the presence of effective institutions and well-articulated public policies.
Given the aforementioned aspects, the study emphasizes that digital transformation, particularly through the adoption of artificial intelligence at the enterprise level, can contribute to sustainable performance only if supported by an adequate institutional framework and strategic policy integration.
In the last ten years, marketing research has shifted in response to artificial intelligence, advanced data analytics, and the growth of digital platforms. One key change is the rise of AI-driven personalization. What started as a helpful tool is now central to shaping customer experiences. With machine learning, deep learning, and natural language processing, companies can send tailored messages, make recommendations, and create consistent interactions across channels. Still, these advances raise ongoing concerns about data privacy and how transparent algorithms are.
Alongside these changes, marketing’s creative side has also evolved. Generative AI now helps create advertising content and sometimes even replaces traditional creative methods. These new tools offer more options but also spark debates about authenticity, ethics, and keeping consumer trust. Meanwhile, there is growing interest in how emotions influence consumer behavior. With affective computing, companies can read emotional cues from faces, voices, and text, but concerns about accuracy, bias, and cultural differences still matter.
As digital spaces keep growing, influencer marketing and public opinion analysis have changed as well. AI tools help track how information spreads and improve engagement, making micro- and nano-influencers more important for brands. At the same time, AI now plays a key role in marketing decisions, from forecasting and pricing to demand estimates and resource planning. This shift affects how companies measure performance and plan their strategies.
These changes have brought more attention to ethics and governance, such as algorithmic bias, consumer choice, and fair access. These issues are especially important as AI becomes part of customer relationship management and journey analysis, where real-time data allows for more flexible and ongoing interactions. Recent studies also look at how the field is developing, using bibliometric and scientometric methods to map its structure and growth.
In this context, the present paper aims to provide a structured overview of these major research directions, based on a review of studies published after 2014, while also identifying relevant avenues for future investigation over the next three to five years.
The restaurant industry has historically resisted wholesale automation — not for lack of technological capacity, but because hospitality, as a commercial practice, has been understood to require irreducibly human interaction. That assumption is now under sustained pressure. Chatbots have emerged as the leading AI application in food service, with roughly six in ten restaurant operators reporting daily use for customer-facing functions including ordering, reservations, and service issue resolution — a penetration rate that, only three years ago, would have seemed implausible for an industry structured around face-to-face encounter. This paper examines the theoretical and operational implications of large-scale chatbot deployment in chain restaurants and coffee franchises. Rather than treating this as a straightforward efficiency gain, we argue that conversational AI introduces a fundamental tension within the service encounter itself: while restaurants report benefits such as higher check averages from more consistent AI-driven upselling, consumer research suggests that roughly a quarter of customers would be less likely to revisit a chain following a negative AI interaction a fragility that standard labor-substitution models do not capture. Drawing on service quality theory (SERVQUAL), labor process theory, and emerging frameworks in human-machine interaction, the paper maps three axes of transformation: the displacement of affective labor, the datafication of the service encounter, and the reconfiguration of employee roles from service providers to AI supervisors. Empirical cases — including McDonald's AI-integrated drive-thru rollout and Taco Bell's voice-ordering experiment, subsequently reconsidered after high-profile failures — illustrate that the transition is neither linear nor inevitable, but contingent on brand architecture, customer demographic, and the specific tasks delegated to conversational agents. The paper contributes a conceptual framework for analyzing chatbot integration not as technological diffusion but as a restructuring of the hospitality labor contract — with implications for workforce policy, service design, and the long-term identity of the restaurant as a social institution.
The accelerated expansion of artificial intelligence across the tourism and hospitality sector has reignited the debate on how digital technologies translate into sustained competitive advantage. Although AI investments have grown substantially among European tourism organizations from hotel chains and online travel agencies to destination management organizations empirical evidence suggests that adoption alone does not automatically generate superior performance. Increasing attention is therefore directed towards the organizational behaviour mechanisms that mediate the relationship between AI deployment and competitive outcomes, including leadership commitment, employee engagement, organizational learning, and change readiness. This paper aims to investigate how EU-based tourism organizations transform AI investments into sustained competitive advantage, and to identify the organizational behaviour mechanisms that activate this transformation. Methodologically, the study employs a comparative case study design based exclusively on secondary data sources, drawing on Statista industry datasets, European Travel Commission reports, UNWTO statistics, OECD Tourism Statistics, Eurostat, and the European Commission's Digital Economy and Society Index. Preliminary findings indicate that competitive advantage materializes predominantly in organizations where AI is embedded in customer experience routines, dynamic pricing, and service personalization, supported by a culture of experimentation and continuous learning. The paper offers an empirical foundation for a subsequent full-length article exploring the behavioural drivers of digital competitiveness in European tourism.
Tourism scholarship has long operated under the normative horizon of sustainability — a framework that, however well-intentioned, encodes a fundamentally defensive logic: reduce harm, minimize footprint, sustain the status quo. This paper argues that such a logic is structurally insufficient. Not because sustainability has failed as a policy aspiration, but because it was never designed to address the deeper question of what tourism could actively restore in ecological and social systems already in deficit.
The regenerative turn, emerging at the intersection of ecological economics, systems thinking, and place-based development theory, reframes the relationship between tourism and its host environments. Where sustainability asks "how little damage can we do?", regeneration asks "what conditions of vitality can tourism help co-create?" The distinction is not merely rhetorical — it implies a fundamentally different ontology of the destination, reconceived not as a resource to be managed but as a living system capable of renewal.
This paper pursues a conceptual-theoretical approach, drawing on paradigm theory (Kuhn) and recent work in regenerative development (Mang & Reed; Wahl) to map the structural contours of this shift within tourism studies. We identify three axes along which the transition from sustainability to regeneration can be theorized: from mitigation to contribution, from carrying capacity to systemic health, and from stakeholder management to community agency. Each axis surfaces a set of unresolved tensions in current tourism governance frameworks.
The paper further examines why regenerative tourism resists straightforward operationalization — partly because regeneration is inherently place-specific and defies universal indicators, partly because it demands a reconfiguration of the value chains that currently structure the industry. These are not obstacles to be overcome by better measurement tools; they point to epistemological commitments that mainstream tourism research has yet to fully confront.
By positioning regenerative tourism as a paradigmatic — rather than merely practical — departure from sustainability discourse, this paper contributes to the growing theoretical literature seeking to articulate what a genuinely post-extractive tourism might look like.
The business environment of the 2020s no longer follows the familiar pattern of alternating between crisis and stability. For many entrepreneurs, uncertainty has become a constant reality shaping everyday decisions. Geopolitical shifts, rapid technological change, economic pressures, and evolving consumer behavior are challenging traditional management approaches. In this context, communication is no longer just a supporting function, but a core resource for adaptation and continuity. This paper explores how entrepreneurial leaders’ communication contributes to organizational resilience, drawing on empirical research conducted among SMEs operating in volatile environments. The study is based on semi-structured interviews with entrepreneurs, allowing for an in-depth understanding of their real experiences and communication practices. Through these conversations, the research examines how consistent, transparent, and context-sensitive communication influences team cohesion, stakeholder relationships, and the ability of organizations to navigate disruption. The findings suggest that organizations where communication is consciously embedded in daily routines are better equipped to deal with uncertainty. Rather than avoiding or downplaying challenges, leaders who communicate openly create an environment where issues are acknowledged and addressed constructively. In this sense, strategic communication becomes more than a reactive tool used in times of crisis; it functions as an ongoing mechanism that supports organizational stability and direction. Building on these insights, the paper proposes a conceptual framework centered on three key dimensions of entrepreneurial communication: transparency, consistency, and narrative coherence. These dimensions are linked to measurable indicators of organizational resilience, including employee trust, decision-making capacity, and the stability of stakeholder relationships. The study offers practical implications for entrepreneurs, as well as relevant insights for educators and policymakers, in a context where adaptation is no longer optional, but an ongoing necessity.
The rapid expansion of cross-border e-commerce has renewed academic interest in how cultural values shape online purchasing decisions. The cultural dimensions framework developed by Geert Hofstede remains one of the most widely employed perspectives for explaining cross-cultural variation in consumer behavior; however, the literature has become increasingly fragmented across methodologies and regional contexts. Against this background, the present paper aims to map the intellectual structure and thematic evolution of research linking Hofstede's cultural dimensions to online consumer behavior, with particular emphasis on individualism–collectivism, uncertainty avoidance, and power distance, the three dimensions most frequently mobilized in e-commerce studies.
The methodology relies on a bibliometric analysis of publications indexed in Web of Science for the period 2010–2025. After applying inclusion criteria related to topical relevance and document type, the resulting dataset was processed in VOSviewer to perform co-authorship, co-citation, bibliographic coupling, and keyword co-occurrence analyses. Performance indicators (publication output, citation impact, leading journals and authors) are complemented by science mapping techniques designed to reveal thematic clusters and their dynamics over time.
Preliminary findings indicate a steady acceleration of publication output after 2015, a significant concentration of contributions originating from Asian and North American institutions, as well as the emergence of distinct research clusters centered on trust formation, perceived risk, mobile commerce adoption, and social commerce. The individualism–collectivism dimension dominates as an explanatory variable, while uncertainty avoidance gains increasing relevance in studies addressing consumer trust and payment behavior. The paper concludes by outlining underexplored research directions and key gaps in the literature, including the interaction between cultural dimensions and emerging technologies such as AI-driven personalization and live-streaming commerce.