Behavioral finance has grown exponentially beyond classical biases into crises, digital assets, and sustainable investing, resulting in a fragmented literature that is difficult to synthesize into a narrative. This work presents a systematic bibliometric mapping of the intellectual, social and conceptual structures of the field. Based on 3,110 Q1 and Q2 articles indexed in Scopus between 2015 and 2025, we combine performance indicators with network analyses, using VOSviewer and the Bibliometrix R package. The analysis shows that there are six thematic groups: behavioral biases and decision-making, financial markets and crises, corporate governance and firm performance, digital finance and social commerce, technology and forecasting, and demographics and psychology. The international co-authorship is 76.17%, with intense collaboration in Asia, Europe, and North America. Although classical theories continue to hold a structurally central position, the field demonstrates a clear convergence with ESG investing, cryptocurrency markets, and financial behavior during the pandemic. The results reveal methodological monocultures and low cross-cluster connectivity, providing a data-driven basis for setting future research agenda priorities.
Generative Artificial Intelligence (GenAI) is reshaping labour markets and creating new challenges for higher education. This study develops an analytical framework for assessing the occupational exposure associated with university study programmes. The framework maps university qualifications to occupational profiles and applies the ILO Global Occupational Exposure Index to estimate the occupational exposure of future graduates. A database was developed by integrating information from the Romanian National Qualifications Register (RNCIS), official data on enrolment capacity, COR, ISCO-08 and occupational exposure data from the ILO Global Occupational Exposure Index. The database covers 263 Business and Economics Bachelor’s programmes and 27,690 potential graduates from Romanian public universities. The findings show that 66.9% of potential graduates are associated with occupations characterised by high exposure to Generative AI, while no study programmes are linked to occupations classified as Not Exposed, Minimal Exposure or Gradient 1. The study provides the first systematic assessment of occupational exposure associated with university study programmes through the analysis of Business and Economics Bachelor’s programmes in Romanian public universities. The proposed framework is transparent, replicable and can be applied to other ISCED fields and national higher education systems.
This paper provides a bibliometric analysis of resilience in the public finance field, covering the period from 2008 to February 2026. Using a sample of 656 papers collected from Scopus database, and following the PRISMA reporting protocol, the study employs Bibliometrix package and VOSviewer as analytical and processing tools to produce a science map of the literature. The analysis examines publication trends, leading authors, institutions, and countries, as well as the thematic evolution over time. Results reveal three distinct phases of development. The first phase (2008-2019) was primarily focused on the theoretical conceptualization of the concept, with the financial vulnerability and the regional urban economic resilience. The second phase (2019-2022) was dominated by research on the COVID-19 shock and its effects on public finance resilience, alongside the emergence of governance as a central theme. The third and recent phase (2023-2026) notes the emergence of new themes, including digital finance, risk management, and artificial intelligence, reflecting a broader and more interdisciplinary analysis of public finance resilience. The study identifies key research gaps, including the geographical concentration of contributions and collaborations, the absence of anticipatory analysis and preventive dimensions of resilience, and the limited cross-country comparative work between highly and low-resilience contexts.
The continuous transformation of higher education, shaped by internationalization, digitalization, labor market dynamics, and increasing institutional competitiveness, has intensified the need for strategic adaptation within universities. The purpose of this study is to identify the dominant strategic priorities for the development of Romanian universities based on the recommendations formulated by specialists from the national higher education system between 2014 and 2025. The research focuses on two main questions: which strategic themes were considered the most relevant over time and how these priorities varied across the main development regions of Romania. A text mining approach was applied using Orange Data Mining on a final corpus of 944 validated responses, while topic modeling was performed through the Negative Matrix Factorization algorithm to identify the dominant thematic structures. The analysis was further supported by temporal and territorial comparisons of the extracted themes. The results revealed ten major strategic topics, among which internationalization, interdisciplinary projects, partnerships between universities, teaching quality, and academic staff development emerged as the most prominent directions. Important variations were also identified across years and development regions, reflecting the influence of institutional and socio-economic contexts on university development priorities. The findings provide useful implications for university managers and decision-makers by supporting the design of development strategies adapted to both institutional needs and regional specificities.
Sustainable finance has become a central mechanism for aligning financial systems with sustainable development objectives by integrating environmental, social, and governance (ESG) considerations into financial decision-making. Despite its growing importance, the literature remains fragmented, with diverse conceptualizations, frameworks, and classifications that hinder the development of a coherent understanding of the field. This study addresses this gap by conducting a systematic literature review to identify, synthesize, and analyze the key dimensions of sustainable finance and their interrelationships. Following the PRISMA 2020 guidelines, the review examines academic publications indexed in Web of Science, Scopus, and Google Scholar between 2000 and 2026. The analysis focuses on how sustainable finance has been conceptualized across different scholarly traditions and investigates the evolution of its principal dimensions. The findings reveal that sustainable finance can be understood as a multidimensional construct comprising six interconnected dimensions: environmental, social, governance, economic and financial sustainability, institutional and regulatory, and strategic and innovation dimensions. These dimensions collectively contribute to sustainable development, financial performance, risk mitigation, and long-term value creation. The study advances the literature by proposing an integrated conceptual framework that synthesizes the multidimensional nature of sustainable finance and identifies emerging themes and future research directions. The findings provide valuable insights for researchers, practitioners, and policymakers seeking to advance sustainable finance theory and practice.
This study investigates the conceptual evolution of the gender–performance relationship: specifically, how the two constructs have been examined within the business and economics literature, how performance is measured when the impact of board gender diversity is assessed, which factors shape this relationship, and which research gaps remain. Addressing these questions provides a broad understanding of the field’s intellectual structure and thematic development. The study adopts a bibliometric approach, employing co-citation analysis and bibliographic coupling to map this development, combined with a systematic literature review to ensure a comprehensive interpretation of the findings. The analysis reveals two important shifts. First, the relationship between board gender diversity and organisational performance has moved from an assumption of linear effects toward mechanism-based explanations: performance is shown to be mediated by the specific governance role that female directors occupy (monitoring versus advisory, independent versus executive) rather than by board presence alone. Second, the conceptualisation of performance has expanded beyond financial indicators to include environmental, social, and governance outcomes, reflecting a multidimensional understanding of organisational value. The review identifies the drivers of board gender diversity, as opposed to its consequences, as a significant and persistent gap in the literature.
This study investigates financing preferences in microenterprises, focusing on the use of internal and external sources of capital and behavioral determinants in financial decision-making. Microenterprises constitute a fundamental component of modern economies; however, their capital structure remains underrepresented in the empirical literature, which predominantly concentrates on larger firms. Addressing this gap, the paper analyzes financing behavior of microenterprise owners within the context of constrained access to external capital. The results indicate a clear predominance of internal financing, primarily retained earnings and owners’ personal savings, used to support operations and smaller investment activities. External financing is employed more selectively and is generally associated with projects requiring higher capital expenditures. This pattern suggests a hierarchical approach to financing consistent with the pecking order theory and reflects constraints faced by microenterprises. The findings also demonstrate that behavioral factors, particularly attitudes toward indebtedness, play a significant role in financing decisions. Lower debt aversion is associated with a higher propensity to use external funding, whereas financial knowledge does not exhibit a statistically significant effect. The study contributes to the literature by integrating structural and behavioral perspectives and provides implications for policymakers and financial institutions seeking to improve access to finance for microenterprises.
Buy now, pay later (BNPL) represents an emerging form of deferred payment that enables consumers to divide purchases into interest-free installments, gaining rapid adoption alongside the expansion of e-commerce and marketing targeted at younger, lower-creditworthiness consumers. While BNPL improves accessibility and user experience, limited regulatory oversight and soft credit check raise concerns about over-indebtedness and potential risks to financial stability. This study analyzes the global BNPL market by constructing a comprehensive provider-level database (N = 149). Firm characteristics are examined alongside service-specific features. Descriptive statistics, as well as Mann-Whitney and Kruskal-Wallis tests, are used to assess differences across providers using revenue rank as a proxy for revenue performance. Findings indicate that BNPL providers are concentrated in Europe and North America but operate worldwide, with most firms remaining small and early-stage. Services predominantly target online commerce, conduct soft credit check, and rely largely on internal funding and merchant fees. The results further suggest that revenue performance is associated with the firm size and fee structures. The sustainability of BNPL firms depends on balancing growth, profitability, and effective credit risk management, while their long-term viability will be influenced by evolving regulatory frameworks and the adoption of responsible business practices.
This research explores the intersection of three domains: marketing sustainability (as a professional competency), journalism education and international capacity building. The study investigates the mechanisms through which a transformative, student-centered curriculum reform can dismantle traditional rote-learning barriers and foster a sense of global responsibility, framing sustainability as a strategic professional tool rather than just academic content. This study utilizes an instrumental case study design, focusing on a single, cross-border initiative: the Sustainable Development Goals in Journalism Reporting project, involving academic partners from Spain, Romania, Luxembourg, China, Cambodia, and Malaysia. This paper addresses two main research questions: How do interdisciplinary co-creation processes in journalism curricula work to promote the 2030 Agenda? How can this case serve as a blueprint for marketing sustainability in higher education, both in theory and in actual practice?
This study targets female owners of micro, small and medium-sized enterprises (MSMEs) who use digital payments, with a core focus on examining the effects of two digital-payment-related independent variables perceived ease of use and perceived usefulness on three categories of outcome variables: MSMEs satisfaction, intention to use digital payments, and MSMEs performance. This study adopts a quantitative correlational research design. Through convenience sampling, a type of non-probability sampling, 354 valid samples were collected. Partial least squares structural equation modeling (PLS-SEM) analysis was conducted using SmartPLS 3. The results indicate that all hypotheses were accepted. Perceived Ease of Use significantly influences Perceived Usefulness, MSMEs Satisfaction, and Intention to Use Digital Payment. Additionally, Perceived Usefulness significantly influences MSMEs Satisfaction and Intention to Use Digital Payment. The findings also indicate that MSMEs Satisfaction and Intention to Use Digital Payment significantly influence MSMEs Performance. These results confirm that the ease and usefulness of digital payments enhance satisfaction and usage intent, which ultimately contribute to improved performance among female MSMEs owners.
The objectives of this study were (i) to examine the influence of public expenditure on sports services and goods on private consumption and (ii) to assess whether the prevalence of sedentary behaviour could be predicted by public expenditure in sports, taking into account educational level, and sex differences in European countries. Data from 27 European countries were used; one additional country was included for objective (i) (n=29) and three for objective (ii) (n=30). A Pearson bivariate correlation and a distributed lag model were used to examine the relationship between public expenditure and private consumption, with GDP per capita included as a control variable. Additionally, multiple linear regression models were applied to predict sedentary behaviour based on GDP, educational level, and sex. Results showed a strong positive correlation between public expenditure and private consumption (r=0.846–0.922, p<0.001). The lagged model, including public expenditure over five years and GDP per capita, explained more than 75% of the variance in private sports consumption. GDP per capita predicted sedentary behaviour in over 44.3% of cases across medium, high, and total education groups. Public expenditure was also a significant predictor in selected subgroups, particularly in the total education group and among women.
This study examines the effect of Environmental, Social, and Governance (ESG) performance on firm value and the moderating role of leverage in non-financial firms in the ASEAN region. The study employs secondary data obtained from Bloomberg ESG Data Services and firms’ annual reports, comprising 820 firm-year observations from ASEAN-5 countries during the period 2018-2022. Panel data regression analysis is employed to test the direct effect of ESG on firm value and the moderating effect of leverage. Firm value is measured using Tobin’s Q and price-to-book value (PBV), and robustness tests are conducted with lagged ESG variables and alternative firm-value proxies. The results indicate that ESG has a positive and statistically significant effect on firm value, suggesting that stronger ESG performance enhances market valuation and investor confidence in ASEAN firms. Furthermore, leverage weakens the positive effect of ESG on firm value, suggesting that high debt levels reduce ESG’s ability to enhance market valuation. These findings suggest that the ESG-firm value relationship is conditional and influenced by firms’ financial structure and risk profile. This study contributes to the literature by integrating ESG and capital structure perspectives within the context of emerging ASEAN markets.
This paper examines the relationship between earnings management and wage subsidies allocated to Croatian hotels during the COVID-19 pandemic. Quarterly financial data available on the Zagreb Stock Exchange and subsidies data provided by the Croatian Employment Office were used to estimate the coefficients of random-effects panel models. The level of earnings management in financial statements was estimated by the modified Jones model. The results show that companies with a higher share of subsidies in total assets have a higher propensity to reduce their magnitude of earnings management. In the context of signed accruals, this finding holds only for companies that managed earnings upwards, while the relationship was not statistically significant regarding their counterparts that managed earnings downwards. Considering all the results, it may be concluded that the earnings management behaviour of hotels indicates their tendency of avoiding unnecessary public scrutiny in times of a crisis. Research also has practical implications for the institutions that regulate the allocation of subsidies and other stakeholders of subsidy recipients.
Are you an Enthusiast, an Optimist, or a Skeptic regarding AI adoption? The question is not merely rhetorical: as artificial intelligence reshapes labor markets at an accelerating pace, workers’ orientations toward AI-driven change vary substantially across attitudinal, institutional, and individual dimensions, and these differences have direct consequences for who seeks upskilling, who benefits from it, and who is left behind. This study develops a three-profile AI readiness framework and investigates which factors predict the intention to pursue AI tools training. Drawing on original survey data collected from 357 respondents in the South-East Development Region of Romania, it has been applied K-Means cluster analysis to identify three distinct workforce profiles: Optimists, characterized by positive AI attitudes and strong organizational preparedness; Skeptics, combining negative attitudes with near-absent institutional support; and Enthusiasts, whose high AI impact perception coexists with only moderate organizational readiness. Chi-square analyses reveal that AI literacy is the only competency priority that differs significantly across profiles, following an inverted gradient, the workers most exposed to displacement risk are least likely to prioritize it, a pattern we term the AI readiness inversion. Binary logistic regression further shows that training intention is predicted by personal preparedness and positive AI attitudes, but not by organizational readiness. These findings challenge the dominant policy assumption that institutional investment in digitalization automatically generates upskilling demand and point instead to attitudinal barriers as the primary constraint on training uptake. The three-profile framework offers a practical tool for designing differentiated upskilling interventions calibrated to the heterogeneous readiness configurations found within any given workforce or region.
Carbon taxation is increasingly recognized as a market-based instrument for internalizing emissions externalities and influencing firms’ strategic behavior. In the context of Vietnam’s net-zero commitment and evolving carbon-pricing agenda, understanding how carbon taxation relates to enterprise strategy has become increasingly important, although existing evidence remains fragmented. This study provides a bibliometric synthesis of the global literature on carbon taxation with an explicit focus on enterprise-level strategy. Based on 152 publications indexed in the Web of Science Core Collection from 2010 to 2025, with a total of 4,150 citations, the study applies performance analysis and science-mapping techniques using VOSviewer and the bibliometrix package in RStudio. The results show a marked increase in publication output after 2020, suggesting that this is a rapidly expanding yet still relatively young research field. Six dominant thematic streams emerge: carbon tax governance and instrument interactions; firm-level strategic responses; low-carbon supply-chain decisions; innovation and competitiveness under tax pressure; system- and technology-oriented modeling; and performance-oriented strategic adaptation in regulatory contexts. Based on these patterns, the study discusses implications for Vietnam’s research and policy agenda, emphasizing policy coordination, sequencing, revenue recycling, and enterprise-level adjustments in production, investment, and supply-chain management. Overall, the study offers a structured knowledge base for future research and policy design in emerging economies.
This study examines the association between corporate governance mechanisms and firm performance using a panel of 754 Indian listed non-financial firms over the period 2000–2020. Specifically, we analyze how board size, board independence, CEO duality, board committee intensity, gender diversity, and business group affiliation are associated with firm performance across different points of the performance distribution. The analysis employs multiple estimation approaches, including firm fixed-effects panel regression, instrumental-variable estimation, and panel quantile regression methods following Powell (2020, 2022). The findings reveal substantial heterogeneity in governance–performance relationships across quantiles. Board independence and the number of board committees show positive associations with firm value, particularly among higher-performing firms. Board size exhibits heterogeneous associations across the performance distribution, with positive associations among lower-performing firms but negative associations at higher performance levels. CEO duality is associated with lower firm performance. Gender diversity shows mixed associations across performance levels, with post-reform interactions suggesting that changes following the Companies Act 2013 were largely compliance-driven. Overall, the results highlight the distributional nature of governance–performance relationships and underscore the role of institutional reforms in shaping governance outcomes in emerging markets.
The Environmental Kuznets Curve (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 multidisciplinary nature of EKC research integrates environmental economics, energy studies, sustainability science and econometrics methodology, focusing on the relations between economic development and environmental degradation. At the same time, 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. This study investigates the long-run and short-run relationships between economic growth, energy consumption, and carbon dioxide (CO₂) emissions in Romania over the period 1990–2023 by employing the Autoregressive Distributed Lag (ARDL) approach. The empirical findings reveal a stable long-run relationship in which energy consumption is the main driver of CO₂ emissions, while no robust evidence is found to support either the conventional or the N-shaped Environmental Kuznets Curve (EKC) hypothesis.
Drawing on effectuation theory, this study examines how resource-constrained entrepreneurs in emerging markets reconcile the analytical capabilities of Generative Artificial Intelligence (GenAI) with relationship-based effectual decision-making under high uncertainty. It aims to resolve the tension between algorithmic efficiency and human-centric logic in non-Western contexts. Adopting an abductive multiple case study design, we conducted in-depth semi-structured interviews with twelve Moroccan entrepreneurs (N=12) engaged in international expansion across three distinct sectors: agri-business, traditional crafts, and sports technology. Data analysis followed a hierarchical coding process to identify cross-case patterns of integration and resistance. Findings reveal a Decision-Type Integration Hierarchy (DTIH) where entrepreneurs delegate analytical tasks to AI to operationalize affordable loss while strictly retaining human control over trust-intensive decisions. We document Crisis Reversion (CR), a novel phenomenon where entrepreneurs abandon algorithmic tools during supply chain shocks, reverting to human effectual networks. Furthermore, cultural authenticity acts as a strict boundary condition limiting AI adoption in high-touch sectors. This research extends effectuation theory by demonstrating how GenAI functions as a mechanism for Cognitive Expansion rather than substitution. It contributes a preliminary framework for AI-Enabled Effectuation challenging linear adoption models by highlighting the temporal fragility of AI reliance during crises.
This study provides a comprehensive econometric assessment of Qatar’s economic diversification trajectory following the 2022 FIFA World Cup, employing dynamic factor models and structural break analysis to evaluate sectoral transformation and resilience. Using quarterly data from 2017–2024, we test three formally derived hypotheses concerning structural breaks in economic composition, sectoral resilience to external shocks, and the effectiveness of diversification policies. Our findings reveal a statistically significant structural break in Q4 2022, with non-hydrocarbon sector growth accelerating while exhibiting lower volatility relative to hydrocarbon sectors, consistent with the hypothesis of a sustained legacy effect rather than a purely transitory construction boom. Tourism, financial services, and logistics demonstrate the strongest resilience to external shocks, while construction exhibits persistent fiscal-cycle vulnerability. The estimated diversification elasticity suggests moderate but incomplete progress toward reducing oil-revenue dependence. Policy simulations indicate that current trajectories may approach, yet require acceleration to comfortably achieve, Qatar National Vision 2030 targets. Findings contribute to the broader literature on mega-event legacies and structural transformation in resource-rich economies.
This study examines the impact of sample size on the independent and identically distributed (i.i.d.) assumption in financial time series and its subsequent effect on risk-return estimations. Focusing on Latin American and US stock market indices from August 2007 to December 2024, using 4,477 daily log-returns, our methodology employs moment estimations, i.i.d. tests (Ljung-Box and Augmented Dickey-Fuller), and a modified Capital Asset Pricing Model (CAPM) and Download CAPM across four rolling windows (60, 250, 500, and 1,000 days). Our findings show that financial returns consistently exhibit heavy tails and negative skewness, challenging the assumption of normality. Statistical properties and i.i.d. violations vary significantly with sample size, with tests becoming more stringent for larger samples. CAPM alpha and beta coefficients are also sample size dependent, revealing distinct risk-return profiles: the S&P 500 exhibits higher systematic risk (Beta > 1) with performance explained by the model (alpha approximate to 0), while Latin American markets are more defensive (Beta < 1) with more dispersed alphas, indicating greater influence from local factors. These results show the importance of considering sample size for robust financial modeling and informed investment decision-making, particularly in emerging markets, highlighting that no single model is universally applicable to all stock markets.
