Abstract: This paper features a 1000 simulations of a set of 100 levered companies equity returns in a financial market. The goal was to generate a realistic distribution of company values that follow a Zipf-Mandelbrot power law. The returns should exhibit leverage effects, negative skewness, and feature Black Swan events of correlated down-turns. Realistic positive covariance structures of returns, systematic risk, plus evidence of long-memory properties. The Merton Model and two versions of the Platen Benchmark Asset Pricing Model (BAPM), the original model and the Stochastic Benchmark Process (SBP). The required market attributes were successfuly captured but the models proved to be highly sensitive to the chosen parameters. The BAPM model proved to be more flexible than the Merton Model and the SBP version more readily generated the stipulated financial market characteristics.

Abstract: The article analyzes the role of selected digital services in maintaining the functioning of the Ukrainian state and economy in wartime conditions and assesses their adaptive po-tential for European Union countries in the context of sustainable and resilient develop-ment. The starting point was the concept of institutional and economic resilience, which has grown in importance in the context of global crises, contributing directly to the goals of sustainable development and long-term socio-economic stability. A qualitative and quantitative approach was used, including secondary data analysis, comparative analy-sis, and triangulation of sources. The results of the study showed that platforms such as Diia, Diia.Business, eRobota, and Air Alert played a key role in ensuring the continuity of public services, support for businesses, and crisis communication. The integration of these tools into the public management system enabled Ukraine to maintain basic state func-tions despite the ongoing armed conflict. A comparative analysis with Estonia, Poland, and Denmark confirmed that the Ukrainian model can be a source of inspiration for EU digitalization strategies, particularly in the areas of mobile administrative services and integration with crisis management systems. The article's conclusions emphasize the importance of digitization as a strategic resource that strengthens the resilience and sus-tainability of public institutions and economies in emergency situations.

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This article examines how technological asymmetries—understood as differences in access to advanced digital tools, AI capabilities and IT infrastructure—shape the financial stability and market performance of enterprises of various sizes. The study integrates comparative analyses of 100 industrial joint-stock companies from multiple countries, including technologically advanced large corporations and innovative SMEs, to assess how disparities in digitization and AI implementation influence financial resilience. Using multivariate regression models and index-based financial metrics such as MC, EV, P/E, PEG, P/S, P/B, EV/R and EV/EBITDA, the research identifies relationships between technological advancement, operational efficiency and risk exposure. The findings indicate that companies with higher levels of digitization and AI adoption demonstrate stronger resistance to market disruptions, more effective risk management and more favorable capital structures than SMEs with limited technological resources. However, restricted access to detailed operational data for smaller firms may affect the precision of comparative assessments. The study concludes that investments in digital competences and international cooperation enhance financial stability and support strategic decision-making, while SMEs play an important complementary role by providing outsourcing services that facilitate AI implementation in larger corporations.

Abstract: Circular economy (CE) has become a central policy framework for advancing sustainable urban development; however, evidence regarding the role of micro, small, and medium-sized enterprises (MSMEs) in metropolitan CE transitions remains limited, particularly in arid regions. This study examined how private sector firms and MSMEs engage with CE practices within an arid metropolitan context, adopting a place-based and governance-sensitive analytical lens rooted in urban studies scholarship. Using a structured quantitative survey of 180 firms across key urban–industrial sectors, the study analyzed levels of CE awareness, adoption patterns, perceived barriers, support needs, and future expectations. The findings reveal that MSMEs engage in resource-based and efficiency-oriented circular practices, whereas more systemic models involving supply-chain integration and platform-based solutions remain limited. Moreover, capability-related factors exert a stronger influence on adoption than awareness alone. Importantly, the study demonstrated high latent willingness among MSMEs to invest in circular practices under supportive policy and institutional conditions. The discussion reframed CE transitions as governance-mediated urban development processes, emphasizing metropolitan coordination, institutional capacity-building, and spatial infrastructure. These findings contribute to urban studies and CE research by positioning MSMEs as conditionally willing system-building actors whose engagement is critical for advancing inclusive and place-sensitive circular transitions in arid metropolitan regions.

Abstract: The role of the U.S. dollar in central bank reserves is shrinking significatively world-wide. We identify three main reasons; first, U.S. and European financial sanctions, second, the U.S. inflation tax which reduces the real value of the USD, and third, the consequent dollar depreciation which increases the value of other reserve currencies and gold. We estimate several central banks’ diversification away from dollars, mostly towards gold, from 2015 to 2025. Our results suggest that these three factors explain the de-clining share of the dollar in reserves. As a consequence, the U.S. Treasury forgoes new seigniorage, the “exorbitant privilege” and inflation tax revenue.

Abstract: Distributed projects spanning time zones and cultures strain communication, coordination, and control, demanding project management practices that explicitly govern stakeholder alignment, information flow, and decision cadence. This paper synthesizes evidence on how iterative delivery rituals can be embedded within PM governance—linking standups, sprint reviews, and retrospectives to communication plans, risk registers, change control, and visibility dashboards—to raise predictability in global initiatives. A practical framework maps collaboration tooling (e.g., video, messaging, shared wikis) to specific PM objectives, while outlining mitigations for language barriers, cultural divergence, and trust deficits common to dispersed teams. Reported benefits include clearer requirements, faster feedback cycles, improved knowledge sharing, and higher transparency, counterbalanced by recurring risks such as time-zone friction, uneven tool access, and coordination overheads, with checklists provided for PMOs to operationalize at scale. The contribution equips project planners and delivery leads with actionable playbooks to achieve scope, schedule, and quality targets under high uncertainty—without relying on co-location.

Abstract: Digital technologies such as big data are reshaping resource allocation, raising interest in whether and how Heterogeneous science and technology innovation (STI) policies can help unlock urban carbon lock-in. Using panel data for 286 prefecture-level cities in China from 2009 to 2023, this paper examines the effects of heterogeneous STI policy intensity—classified as supply-side, demand-side, complementary-factor, and institutional-reform policies—on urban carbon unlocking efficiency. We develop a mechanism-based framework and empirically assess (i) the moderating roles of digital infrastructure, science and technology finance, and government green attention, and (ii) spatial spillover effects using spatial econometric models. The results show that all four policy types significantly improve local carbon unlocking efficiency, with institutional-reform policies exhibiting the largest marginal effect. When the four types are included jointly, only supply-side and demand-side policies retain statistically significant direct effects. Heterogeneity analyses indicate that demand-side, complementary-factor, and institutional-reform policies are more effective in low-pollution cities, whereas supply-side and demand-side policies have stronger effects in high energy-consuming cities. Mechanism tests further reveal that digital infrastructure amplifies policy effectiveness by facilitating factor mobility, science and technology finance strengthens policy impacts by easing financial constraints, and government green attention enhances policy effectiveness by improving implementation. Finally, carbon unlocking efficiency displays significant spatial dependence: supply-side and institutional-reform policies generate positive spillovers, while complementary-factor policies exhibit negative spillovers. Overall, the findings provide empirical evidence to inform the design and coordination of heterogeneous STI policy portfolios aimed at improving urban carbon unlocking efficiency.

Abstract: This study seeks to establish how financial leverage mediates the relationship between corporate governance and firm financial performance of 58 carbon-intensive firms listed on the Johannesburg Stock Exchange for a period 2015-2023. The research employed a two-step system generalized method of moments to address endogeneity issues. The study indicates that leverage negatively impacts firm financial performance; but leverage does not mediate the relationship between corporate governance and firm financial performance in carbon-intensive firms. The results of the study also reveal that board remuneration negatively influences firm financial performance, yet board independence shows insignificant impact on firm performance. These results underscore the need for carbon-intensive companies to reassess their remuneration policies to ensure alignment with short-term financial benefits and long-term sustainability initiatives. The findings also suggest that sustainability projects financed predominantly by debts may negatively impact short- firm financial performance, indicating the importance of balanced capital structure during the decarbonisation process.

Abstract: This research examines how rising pressures from global risks, including natural disasters, geopolitical conflicts, cybercrime, and government regulations, affect sustainable supply chains and logistics systems. These pressures are becoming more frequent, intense, and unpredictable. The Global Pressure Supply Chain Index, developed by the Federal Reserve Bank of New York, serves as a proxy for quantifying these pressures and as a comprehensive metric of stress within global supply chains and logistics systems driven by macroeconomic factors. Further investigation is warranted. Quantitative analyses indicate that systemic global risks have a significantly positive effect on these systems. However, additional analyses show that the influence of macroeconomic indicators on these systems remains generally low to moderate. Supplementary statistical tests demonstrate that, among external systemic risks, government trade regulations, cybercrimes, cyberattacks, the transportation index, and political conflicts are significant predictors of pressures on global supply chains and logistics. These factors serve as indicators for forecasting economic fluctuations, which lead to disruptions, delays, and costs in supply chains and logistics systems.

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Purpose: This paper aims to systematically synthesize academic research published between 2020 and 2025 that investigates environmental, social, and governance (ESG) ratings and scores, with a focus on their methodologies, comparative performance, and impact on firm outcomes. Design/methodology/approach: A systematic literature review (SLR) was conducted using the Lens.org scholarly database. A structured title search retrieved 334 open access journal articles published between 2020 and May 2025 containing the terms "ESG Score", "ESG Rating", or "ESG Rater". The PRISMA 2020 protocol guided the selection and screening process. Findings: The literature exhibits growing concern about the divergence among ESG ratings, the methodological opacity of rating providers, and the variable financial implications of ESG scores. Common themes include score disagreements, rating agency biases, and emerging models for standardizing ESG assessments. Originality: This review provides the most up-to-date synthesis of ESG rating literature, focusing exclusively on articles explicitly addressing ESG ratings or scores in their titles. It contributes clarity to the fragmented ESG measurement space by organizing findings around key methodological and evaluative debates.

Abstract: Background: COVID-19 coincided with increased mental health needs in Alberta, Canada, intensifying pre-existing access gaps and service strain. Alberta responded with publicly funded interventions spanning digital care, youth-focused services, and recovery-oriented programs. Objective: To evaluate Alberta’s system-level response to pandemic-related increases in mental health help-seeking/service uptake using a health economics and policy lens. Methods: We extracted empirically reported program delivery outputs from the 2023–2024 Alberta Mental Health and Addiction Annual Report. We used a simulation calibrated to reported trends to examine directional changes in help-seeking (demand), service capacity (supply), and the modeled equilibrium quantity under a zero-copayment design. Results: Empirically reported outputs indicate that delivery met or exceeded planned/funded milestones for CASA Mental Health, VODP, and tele-mental health, while recovery communities reflected phased implementation. In the illustrative simulation, the demand-implied volume increases from 60 to 87 services/month, but delivered volume is capacity-constrained at 78 services/month (implying ~9 services/month unmet demand), while a unit-cost proxy is held constant for visualization (not an observed market price or patient copayment).Conclusion: Alberta’s response illustrates how coordinated, publicly funded capacity expansion and access-oriented policies can support service delivery during system shocks; the model also highlights that if capacity growth lags demand growth, unmet need may persist even under zero copayment.

Abstract: While privacy concerns are traditionally assumed to deter data sharing, this study challenges that consensus within the context of value-aligned green marketing. Drawing on privacy calculus theory and trust-building frameworks, we surveyed 1,136 consumers to investigate the mechanisms driving engagement with AI-driven sustainability initiatives. Following a rigorous attrition analysis to ensure data quality (final N = 482), structural equation modeling reveals a complementary mediation effect: brand trust mediates the relationship between privacy concern and data-sharing willingness (indirect effect = 0.068), yet a significant positive direct effect persists (\beta = .109, p = .010). This finding suggests that privacy-conscious consumers do not exhibit paradoxical behavior but rather exercise privacy self-efficacy—engaging in informed, strategic selectivity where high concern correlates with high competence in managing risks. Furthermore, the study addresses the “Green-AI Paradox”—the tension between AI’s environmental utility and its substantial carbon footprint. We propose a new framework of “Impact Transparency” and introduce the AI Data Usage Efficiency (ADUE) metric for integration into the EU Digital Product Passport. These findings offer a roadmap for marketers and policymakers to foster trust through authentic, outcome-based transparency.

Abstract: This paper focuses on analyzing the dynamic process, strength and orientation of risk spillovers in the Chinese banking system under the exogenous shock scenario of the COVID-19 pandemic. Using the closing prices of 25 chosen banks on a daily basis, it stratifies the data into three periods: before, during, and after the pandemic. The HP-TVP-VAR-DY model is used to model risk heterogeneity and time-varying features in risk transmission processes. A dynamic topological directional graph is further used to track the core risk sources and paths in risk transmission processes. The key findings obtained from this paper are summarized below: (1) The Total Spillover Index for the banking system persisted at a high level following the outbreak of the COVID-19 pandemic, indicating its high sensitivity to abrupt and large-scale events. (2) Bank risk transmission paths are highly heterogeneous and time-varying in nature. Prior to the pandemic, CCBs were prominent in overall risk output; during the pandemic, JSCBs dominated; while in the post-pandemic period, again CCBs dominated overall risk output. In all periods, SOCBs and RCBs were identified as major risk receivables. (3) Concerning the structural change in interbank risk transmission paths, it exhibits phase-dependent features. In the pre-pandemic period, risk spillovers spread from CIB, CMB to ABC. However, in the pandemic period, interbank risk transmission paths became highly decentralized, indicating significant increases in risk outflows and inflows from RCBs and CCBs, respectively. Moreover, CMBC and SZRCB turned out to become key sources for risk radiation, while overall network mechanisms dominated risk absorption effects. However, in the post-pandemic period, interbank risk transmission paths tend to become re-centralized; BOC turned out to become a core source for risk transformation, indicating a revival in risk-output dominance in network topologies.

Abstract: The digital economy, while a pivotal engine for growth, presents a dual challenge in the context of climate goals. Utilizing panel data from 267 Chinese cities covering the period from 2011 to 2022, this study investigates the nonlinear relationship between the digital economy and carbon dioxide emissions, testing its conformity with the Environmental Kuznets Curve (EKC) hypothesis. Moving beyond a static verification, this research introduces a dynamic framework by examining how three exogenous shock variables—green finance, local government fiscal pressure, and climate policy uncertainty—reshape the EKC curve. Specifically, construct an extended EKC model with interaction terms to empirically assess how these exogenous shock variables shift the inflection point horizontally and vertically and alter the curve's slope. Our findings reveal that these factors significantly influence both the timing and peak level of emissions, as well as the efficiency of decarbonization before and after the turning point. This study provides a nuanced understanding of the digital economy's environmental impact, offering policymakers critical insights to navigate the green transition in the digital era.

Abstract: This study examines how banks navigate the dual strategic imperatives of securing market power and optimizing multidimensional operational efficiency—technical, scale, and allocative efficiency—within emerging and transitional banking systems. Focusing on business model diversification and financial stability, the study also accounts for the conditioning roles of governance quality, institutional complexity, credit risk, and digitalization. Using bank-level data from ASEAN and MENA countries, the analysis applies Partial Least Squares Structural Equation Modeling (PLS-SEM) and multi-group analysis to assess direct, mediating, and moderating relationships. The results indicate that diversification and financial stability significantly strengthen market power, while their effects on efficiency are largely negative across efficiency dimensions. Governance quality partially mediates the stability–market power relationship, whereas institutional complexity weakens this linkage. Digital transformation maturity and market digitalization condition the diversification–efficiency nexus, with effects varying across efficiency types and regions. Overall, the findings reveal a strategic trade-off between competitive positioning and operational efficiency, emphasizing the importance of governance structures and digital capabilities in shaping bank performance across heterogeneous institutional contexts.

Abstract: This empirical study examines how FinTech innovation is adopted, scaled, and sustained in a small and highly regulated market, such as Latvia. The triangulated analytical framework is applied in this study, integrating Rogers’ Innovation Diffusion Theory IDT [1], De Meyer’s Innovation Ecosystem framework [2], and the Value Chain Theory [3], [4]. This framework enables the exploration of the interaction between innovation characteristics, ecosystem relationships, and restructuring in the value chain. The data was collected from FinTech leaders, conventional financial institutions (banks), regulators, and associations, and it was analysed thematically. Based on the interviews with stakeholders, the relative advantage of Latvian FinTechs lies in their flexibility, speed, and trialability; however, the adoption barrier is the complexity of regulation and unevenness in infrastructure and institutional readiness. The authors found strong collaboration among the ecosystem's players but limited proactive regulatory engagement. This research provides a replicable model for cross-border or cross-sector analysis to assess the progress of innovation in regulatory and Environmental, Social and Governance ESG integration.

Abstract: Direct-to-consumer (D2C) brands increasingly rely on A/B testing to optimizepaid social advertising, yet common execution errors—inconsistent attribution,underpowered samples, mid-test edits, and metric flexibility—undermine inferentialvalidity.[13] This paper develops a methodological framework for decision-gradeexperimentationonMeta(Facebook)Adsthatbalancesstatisticalrigorwithbusinessguardrails. We synthesize established practices in online experiments[3, 12, 13] andoperationalize them into a prioritized test sequence, integrating power analysis,Sample Ratio Mismatch (SRM) diagnostics,[21, 23] optional CUPED variancereduction,[6] and economic guardrails (e.g., ROAS thresholds, delivery balance,frequency parity).Evidence and scope. All analyses use a synthetic/simulated dataset calibratedto D2C benchmarks; no live-traffic data are analyzed. The simulation demonstratesthe analytical workflow and decision logic without making empirical claims aboutreal-world effectiveness. The contribution is methodological: a reproducibletemplate practitioners can adapt and validate in production.

Abstract: This paper presents a comparative analysis of natural gas and electric power prices using visibility graph methodology, a technique from complex network theory that transforms temporal sequences into network representations. We analyze 1,826 daily observations from the Italian energy market (2019-2023), implementing a three-stage preprocessing pipeline (logarithmic transformation, LOESS detrending, and first differencing) before constructing visibility graphs. Our topological analysis reveals striking differences: gas exhibits substantially higher connectivity (6,202 versus 5,354 edges), heavier-tailed degree distributions (maximum degree 117 versus 54), and dramatically longer-range connections (average temporal distance 26.4 versus 11.0 days). Paradoxically, despite power displaying twice the raw volatility, gas generates more structured long-range correlations due to storage-enabled intertemporal linkages. Both series exhibit small-world properties with high clustering (≈0.76), short path lengths (4.59 and 5.36), and positive assortativity (≈0.17). Correlation analysis reveals moderate contemporaneous return correlation (Pearson r = 0.456) with substantial time variation (range 0.173– 0.696), no lead-lag relationships, and partial synchronization of topological properties. Node-level degree and clustering show positive correlations between markets, while closeness centrality exhibits strong negative correlation (r = −0.719), indicating fundamentally different global network organization. Structural similarity (Jaccard coefficient 0.404) confirms 40% shared visibility connections with 60% commodity-specific structure. These findings demonstrate that physical storability fundamentally shapes temporal correlation structure, with direct implications for risk management, forecasting model selection, and portfolio construction in energy markets.

Abstract: We propose a solver-agnostic framework for analysing convergence in DSGE computation based on a single quadratic \emph{residual of sameness} measured in a fixed, calibrated norm. In the Deterministic Statistical Feedback Law (DSFL) view, an economic model is specified by a frozen defect representation and a declared symmetric positive definite ruler that aggregates equilibrium violations. Once this geometry is fixed, solver behaviour becomes a typed statement about the induced defect dynamics rather than an implementation-dependent notion of error. We show that standard DSGE solvers—time iteration, policy iteration, and Newton or quasi-Newton methods—can be analysed as residual-updating maps whose contraction properties yield explicit convergence envelopes, robust stopping rules under numerical forcing, and comparable rate diagnostics. A Gram-operator construction provides a single solver-agnostic contraction score and exposes non-normal transient amplification that eigenvalue diagnostics alone can miss. Numerical studies for a small New Keynesian model illustrate how the framework enables reproducible and interpretable solver comparisons within a single geometric language.

Abstract: The expansion of internet connectivity and mobile technologies has transformed financial services worldwide, positioning digital banking as a key platform for transactions. In Ethiopia, adoption has accelerated through regulatory reforms and national strategies such as Digital Ethiopia 2025 and the National Financial Inclusion Strategy. Despite these developments, empirical studies remain limited, particularly in urban contexts where usage is rapidly increasing. This study applies the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to examine factors influencing digital banking utilization in Addis Ababa. Using survey data from 405 respondents and Partial Least Squares Structural Equation Modeling (PLS-SEM), the analysis shows that facilitating conditions and price value were the strongest predictors of adoption, followed by performance expectancy and social influence, while effort expectancy was not significant. These findings underscored the importance of infrastructure readiness, affordability, and normative influences in shaping digital banking users. The study contributes to technology adoption literature by contextualizing UTAUT2 within Ethiopia’s financial sector and offers practical insights for policymakers, banks, and technology providers seeking to advance digital financial inclusion.