Search Results (607)

Infrastructure projects of significant scale face persistent challenges in data coordination, scheduling, and cost control. Although individual digital tools are widely adopted in the construction sector, empirical evidence on their coherent systemic integration within a unified management cycle remains limited. This explanatory case study addresses that gap by examining ^{Section 3} of the Sibiu–Făgăraș Motorway (17.61 km, 27 structures) in Romania—an ongoing TEN-T project. Evidence was collected during the active construction phase (January 2022–December 2024) from Common Data Environment (CDE) logs, BIM/BrIM model outputs, drone photogrammetry datasets, schedule and payment records, and Business Intelligence (BI) dashboards. The study demonstrates how six digital applications—CDE, model-based fabrication (LOD 400), 3D coordination, 4D/5D simulation, reality capture, and BI dashboards—were operationalized as a closed-loop Plan–Do–Check–Act (PDCA) cycle, functioning as a human-in-the-loop digital twin for project Please check if this address is duplicate with aff .1 or not. If so, please merged them into one and revise the author’s associated number and ensure that each number in numerical order. delivery. Illustrative operational indicators observed during implementation include an estimated 20% reduction in coordination-related RFIs, a 15% reduction in steel fabrication material waste, a reduction in payment validation cycle time from 15 days to approximately 2 days, and a 40% improvement in cash flow stability through data-driven activity re-sequencing. These findings suggest that systemic digital integration, rather than isolated tool adoption, supports more proactive and sustainability-aligned infrastructure project control. Full article

Stationary energy storage (SES) is increasingly needed to integrate variable renewable generation and improve consumer self-consumption, but technology choices involve associated trade-offs between cost, efficiency, and life-cycle impacts. This study evaluates the role of second-life lithium-ion (Li-ion) batteries repurposed from electric vehicles for stationary applications, compared to lead-acid (Pb-acid) batteries and power-to-hydrogen-to-power (PtH₂P) systems. We develop an optimization-based sizing and dispatch framework using measured PV–load profiles and hourly market electricity prices, and evaluate performance per 1 MWh delivered to the load over a 10-year life cycle. Economic performance is quantified through discounted cash flows equal to levelized cost of storage (LCOS), while environmental performance is assessed through life-cycle metrics with explicit representation of recycling and second-life credits. In addition to global warming potential (GWP), the analysis considers additional resource and impact metrics, as well as key operational efficiency metrics, including bidirectional consumption efficiency, autonomy, and share of self-consumption/export of photovoltaic systems. Scenario and sensitivity analyses examine the impact of policy and financial parameters, in particular feed-in tariff remuneration and discount rate, on the comparative ranking of technologies. The results highlight how circular economy pathways, especially second-life distribution for Li-ion batteries and high end-of-life recovery for lead-acid batteries, have a significant impact on the life-cycle burden for delivered energy, while market-driven conditions for dispatching and export activities shape economic outcomes. Overall, the proposed workflow provides a transparent, circularity-aware basis for selecting stationary storage technologies associated with photovoltaic systems, under realistic operational constraints. Full article

New approaches to improve organisational performance in firms are evolving in this data-driven age. However, there is lack of studies in examining the relationship between revenue, net profit, cash flow per share, and earnings per share. The energy sector remains under-researched regarding the multi-dimensional drivers of profitability. Existing research shows inconclusive evidence with studies predominantly examining revenue—performance relationship limiting to a single factor and not guiding potential investors regarding future earnings per share in the energy industry. This paper aims to bridge the gap in literature by proposing a data-driven approach to analyse the relationships between revenue, net profit, cash flow per share, and earnings per share. We examine these relationships by conducting an empirical analysis using secondary data derived from published annual reports of the energy firms listed on the Australian Securities Exchange (ASX). Our empirical study uses Pearson correlations and regression techniques to test the hypotheses on the relationships between revenue, net profit, cash flow per share, and earnings per share. Also, we use market capitalisation as a control variable and predictor of earnings per share in the energy industry. The data analysis results in four findings: (i) revenue positively influences earnings per share because higher revenue expands the firm’s earnings capacity within the financial performance, (ii) net profit has a strong positive effect on earnings per share, consistent with profitability theory and the direct derivation of EPS from net income, (iii) cash flow per share influences earnings per share because liquidity supports operational stability, investment decisions, and earnings sustainability (e.g., heavy capital expenditure contexts), and (iv) the combined effects of revenue, net profit, and cash flow per share provide a stronger and more holistic prediction of earnings per share than any single variable, consistent with multidimensional organisational performance theory (a more holistic valuation model than looking at single factors). In addition, the results indicate that market capitalisation (control variable) has both strong prediction of earnings per share and strong association with earnings per share. The results of this study can offer practitioners and investors in Australia and other countries for a better understanding of the relationships between revenue, net profit, cash flow per share, and earnings per share from energy companies. The data will help investors to make good investment data-driven decisions in the energy industry or other industries. It also motivates researchers to conduct similar studies in different contexts. We further provide recommendations, including a closed-loop Artificial Intelligence (AI) data-driven approach integrated into energy accounting and operational processes to enhance profitability. This approach operationalises the revenue and earnings-per-share (EPS) strategies identified in our empirical analysis, offering practical value for industry practitioners and guiding future research in this direction. Full article

The European Union’s Carbon Border Adjustment Mechanism (CBAM), the world’s first system to impose tariffs on the carbon emissions of imported products, commenced its transition period in October 2023 and is scheduled for full implementation in January 2026. This mechanism exerts a profound impact on the global trade landscape and corporate environmental management practices. Taking the CSI All Share Index constituent companies as a research sample, this paper empirically evaluates the impact of the CBAM transition period on the environmental scores of Chinese export enterprises utilizing the Propensity Score Matching Difference-in-Differences (PSM-DID) method. The results indicate that the CBAM transition period significantly inhibits the short-term environmental performance of regulated enterprises. Mechanism analysis reveals that increased financing constraints serve as a core mediating channel, wherein escalated compliance costs and compressed cash flows crowd out resources for low-carbon investments. Furthermore, heterogeneity analysis demonstrates that the negative impact is more pronounced among state-owned enterprises, firms with lower audit quality, and firms with a higher proportion of female executives. Accordingly, the study recommends establishing targeted green transition financing mechanisms, accelerating domestic carbon market reforms, and strengthening international technical harmonization to build corporate resilience against global climate governance shocks and promote sustainable growth. Full article

This paper derives a closed-form expression for the expected discounted value of aggregate cash flows when arrival times follow a Poisson process but both the time horizon and the number of arrivals are finite. The result provides a tractable analytical formula for the expected discounted sum under simultaneous constraints on time and arrival counts. We show that the expression converges to the well-known infinite-horizon and infinite-arrival results as limiting cases. Numerical illustrations demonstrate the behavior of the formula under different parameter values. The result can be interpreted as the valuation of a discounted compound Poisson process with finite constraints and may be useful in stochastic modeling and risk-analysis applications. The proposed formula provides a simple analytical tool for evaluating discounted losses or revenues in finite risk portfolios. Full article

The contemporary green transformation of the economy is a strategic imperative for businesses, especially small and medium-sized enterprises (SMEs) operating in the energy market, forcing the integration of sustainable practices in decision-making processes, including investment efficiency assessment. Classic financial tools, such as the internal rate of return (IRR) and net present value (NPV), commonly used in the SME sector, do not always adequately account for environmental, regulatory, and social risks associated with green transformation, as—particularly in the case of IRR—they rely on the assumption of stable cash flows and do not incorporate regulatory uncertainty, environmental externalities, or ESG-related risks into discounting parameters. The aim of the study was to determine the impact of nominal and real discount rates, adjusted for a synthetic measure of green transformation, on investment decisions. The research methodology combines advanced multi-criteria decision-making techniques, specifically TOPSIS and CRITIC, with sustainable finance concepts, offering an innovative approach to investment decision-making in the SME sector. The study shows that integrating environmental factors, when treated as a risk component, increases the cost of capital and reduces the net present value, while maintaining the profitability of the analysed projects. Incorporating green components into the discount rate enhances valuation appropriateness and improves investment risk management, particularly under macroeconomic uncertainty. The main contribution of the study lies in linking a synthetic green transformation indicator with dynamic discount rate adjustment within a multicriteria framework, extending existing ESG-adjusted valuation models by enabling a more structured and data-driven incorporation of environmental transition risk. Full article

This paper presents a comprehensive life-cycle analysis of distribution transformers, based on realized measurements of the increased power losses as a result of their long-term service under real-world conditions. The study is based on aggregated measured data from extensive fleets of oil-immersed distribution transformers characterized by diverse designs, manufacturing vintages, and service lives. The evolution of no-load losses and short-circuit losses is analyzed as a function of operational duration, structural characteristics, and the specific technologies employed for windings and magnetic core construction. Statistical models describing the variation in these losses are presented, highlighting the limitations of the static assumptions commonly utilized in power distribution network planning. On this basis, an approximation of the time evolution of the transformer’s total power and energy losses is proposed as appropriate for implementation in a life-cycle analysis model. Furthermore, the impacts of thermal loading and abnormal operating conditions—such as unbalanced loads, frequent short circuits, and repeated overheating of the transformer oil—are analyzed as drivers of accelerated transformer aging. These effects are integrated into a unified life-cycle framework, enabling the quantitative assessment of loss variations and their associated operational expenditures (OPEX). A numerical example is provided to evaluate the cost-effectiveness of “repair vs. replacement” scenarios, utilizing a discounted cash flow analysis that incorporates a carbon component. The findings establish a methodological foundation for a broader assessment of technical condition and energy performance, identifying the optimal intervention point for repair or replacement to support decision-making for Distribution System Operators (DSOs) amidst increasing requirements for efficiency and decarbonization. Full article

This study explores how board characteristics impact corporate cash flow risk in an emerging market setting. While previous research has examined firm risk, crash risk, and earnings quality, there is limited evidence on cash flow risk and its governance factors, especially in developing economies. To fill this gap, this study differentiates between volatility-based and distortion-based measures of cash flow risk and assesses how board attributes influence these aspects. Using a balanced panel of 327 non-financial firms listed in Vietnam from 2013 to 2023, cash flow risk is measured by the rolling five-year volatility of operating cash flows and short-term distortions shown in earnings–cash flow mismatches. To address endogeneity and dynamic persistence, the analysis uses the system generalized method of moments estimator, along with fixed-effects and feasible generalized least squares models for robustness. The findings suggest that board independence, gender diversity, and financial expertise are linked to lower cash flow risk, highlighting the importance of effective monitoring. Conversely, board meeting frequency is positively linked to risk, suggesting that boards tend to increase meeting frequency as a reactive response to heightened uncertainty. Board size and CEO duality do not show consistent effects. Focusing on Vietnam’s institutional context, this study provides evidence that governance mechanisms influence different dimensions of cash flow risk through separate channels, offering valuable insights for enhancing board effectiveness in emerging markets. Full article

This paper develops and applies a techno-economic optimization framework for sizing photovoltaic (PV) and battery energy storage systems (BESSs) in grid-connected energy communities. An in-house developed modeling platform featuring custom MATLAB (R2025a) code implements a mixed-integer linear programming (MILP) model that minimizes differential net present value (NPV) over a 25-year lifetime, integrating capital expenditures, operating cash flows, and carbon taxation. The formulation captures temperature-dependent PV efficiency, battery round-trip efficiency, and time-varying electricity prices, and is validated on a real campus energy community with hourly demand, irradiance, and tariff data. Two design scenarios are examined: the optimal unconstrained case and a budget-constrained configuration (CAPEX ≤ 2.0 M€). Results show the unconstrained system installs 3.19 MW_p PV and 12.3 MWh storage, achieving 78.9% self-sufficiency and a 78.9% emissions reduction. The constrained case installs 0.99 MW_p and 1.68 MWh, achieves 32.0% self-sufficiency, and delivers a 4.46 M€ NPV with payback in 3.9 years. Under current costs and tariffs, PV-dominated configurations provide the highest value, with limited battery benefit except under generous budgets or higher carbon prices. A dedicated CAPEX sensitivity analysis explores PV and battery cost variability and its impact on optimal sizing and economic outcomes. The core methodological contribution is a master-planning formulation that solves design decision variables and optimal dispatch concurrently within a single MILP. The flexible platform enables future reassessment as technology, tariff, and policy landscapes evolve. Full article

Vanadium (V) is a strategically important metal commonly recovered from titaniferous magnetite ores. Its principal application is in steel production, where it enhances mechanical properties, while smaller quantities are utilized in chemical processing, catalysis, and emerging energy storage technologies. It is expected that the demand for vanadium in the steel industry will increase by a compound annual growth rate of approximately 2.7% by 2029, and demand in energy storage will increase by an additional 6%. The growing demand for V has triggered global concerns regarding the supply risks of this critical metal. Industrial recovery of vanadium from magnetite deposits is carried out either through dedicated primary vanadium extraction routes or integrated processes that co-produce vanadium alongside steel. The latter accounted for approximately 73% of global vanadium output in 2021. These co-production operations generate significant volumes of by-product slag, often referred to as titaniferous slag, which can still contain notable concentrations of vanadium. In this study, a modified primary vanadium extraction route is proposed to recover V from such slag, using material containing approximately 0.9% V₂O₅ sourced from the former Evraz Highveld Steel and Vanadium Corporation in South Africa as a representative case. The work focuses on assessing the economic feasibility of the proposed process through a Discounted Cash Flow (DCF) analysis. Key financial metrics including net present value (NPV), internal rate of return (IRR), and payback period were calculated to evaluate viability and to identify process stages requiring further optimization. Full article

Capital structure decisions are among the most critical financial choices for firms, as they directly influence them. There is an ongoing debate among researchers regarding the optimal capital structure, motivating this study to examine the impact of various factors on firms’ capital structure, while also considering the COVID-19 pandemic as an influential external factor. This study investigates the financial behavior of 147 non-financial firms listed on the Egyptian Stock Exchange over the period of 2011–2022, using firm year observations. Firms were classified into 14 sectors, excluding banking and non-banking financial services, due to their unique regulatory environments. Data were collected from multiple reliable sources, including financial statements, corporate reports, and EGX databases. Advanced econometric techniques, including the Panel Generalized Method of Moments (GMM), the Arellano–Bond test, and Johansen cointegration analysis, were employed to address endogeneity and explore long-run relationships. The results show that leverage is persistent over time, is positively associated with firm size, tangible assets, and growth opportunities, and is negatively related to profitability, cash flow, and liquidity. The COVID-19 pandemic had a small but significant positive effect, and sectoral differences were also observed. The findings provide robust insights into corporate financing behavior in emerging markets, highlighting the interplay between firm characteristics, external shocks, and financing decisions. Full article

Community pharmacies in the United States (US) face an increasingly unsustainable future due to declining third-party reimbursement (remuneration) and ongoing cash flow challenges following the elimination of retroactive direct and indirect remuneration (DIR) fees. These pressures have contributed to widespread pharmacy closures, the emergence of pharmacy deserts, and reduced access to care for millions of patients. Despite these challenges, community pharmacy remains the most common employment setting for pharmacy school graduates in the US. However, currently required community pharmacy Advanced Pharmacy Practice Experience (APPE) student rotations may offer limited exposure to business, management, and entrepreneurial activities, potentially leaving students underprepared for practice in this setting. US colleges and schools of pharmacy are uniquely positioned to address this gap by partnering with their community pharmacy APPE rotation sites to intentionally integrate business- and practice-focused knowledge, skills, and attitudes (KSAs) into the APPE. Equipping students with these KSAs may enhance early career readiness while also supporting the financial sustainability of US community pharmacies through the development of innovative, revenue-generating services. These efforts further align with the 2025 Accreditation Council for Pharmacy Education (ACPE) Standards and may help advance the profession. Future research should examine optimal community pharmacy APPE structures, models, and assessment strategies to maximize student preparedness and long-term community pharmacy sustainability. Full article

In this study, we propose a structured valuation framework for non-fungible tokens (NFTs), a distinct class of digital assets whose pricing mechanisms remain insufficiently understood. Based on previous empirical studies and illustrative case analyses of three major NFT collections, we synthesize insights from non-cash-flow asset theory, market microstructure, and behavioral finance to construct a four-layer valuation framework consisting of the Asset, Market, Technology, and Ecosystem layers. We identify three NFT-specific mechanisms—verified digital scarcity, pseudonymous signaling, and on-chain herding—that modify or extend traditional valuation paradigms. Empirical evidence from the literature suggests that rarity-driven asset features and social-influence dynamics are dominant price determinants, while wash trading, fragmented liquidity, and platform incentive structures generate persistent distortions in price discovery. Case analyses of CryptoPunks, Bored Ape Yacht Club, and Pudgy Penguins demonstrate how differing risk exposures across the four layers translate into distinct valuation trajectories. With this framework, we obtain a basis for improved risk assessment, regulatory oversight, and business model design in NFT markets. Full article

Rapid urbanisation in arid regions has increased reliance on energy-intensive desalinated water, intensifying environmental and financial pressures on the built environment. Although non-potable water (NPW) reuse is promoted within regional water strategies, empirical validation of decentralised systems at asset scale remains limited. This study applies a greenhouse gas (GHG) intensity metric (kgCO₂e/m³) to multi-year operational data from a large healthcare facility in Abu Dhabi. The analysis integrates calibrated water balance records, onsite pumping energy (Scope 2), embedded desalination emissions (Scope 3), and a 20-year discounted cash flow framework. Three configurations are evaluated: a fully desalinated baseline, the observed mixed-supply system, and an optimised NPW configuration. The baseline exhibits an emission intensity of 19.53 kgCO₂e/m³. The observed configuration reduces desalinated supply but achieves only marginal decarbonisation (0.40 kgCO₂e/m³) due to continued dependence on desalinated make-up water. The optimised configuration reduces outdoor water demand by 36.7% and achieves 10.94 kgCO₂e/m³ net decarbonisation while improving life-cycle cost (LCC) performance. The results show that GHG intensity is primarily driven by water source substitution and system configuration rather than volumetric reuse alone, providing asset-level evidence for evaluating decentralised NPW systems in arid-climate buildings. Full article

Exchange rate volatility creates uncertainty for firms in open economies, especially in emerging markets with structural vulnerability and shallow financial markets. This work examines the impact of exchange rate volatility on the cash-flow performance of non-financial firms in the Middle East and North Africa (MENA) region of 292 firms across 11 countries from 2014 to 2023. Heteroskedasticity, serial correlation and cross-sectional dependence were estimated using fixed effects, random effects and robustness estimation using Driscoll–Kraay standard errors and Feasible Generalized Least Squares (FGLS). Exchange rate volatility has no statistically significant impact on corporate cash flows across all specifications, confirming the existence of an exchange rate exposure puzzle in emerging markets. Firm size always appears to be the strongest and most robust predictor of liquidity performance. The macroeconomic growth effect is weaker and context dependent: It is insignificant with baseline panel estimations, is negative with Driscoll–Kraay corrections and is marginally positive with FGLS structural controls. Profitability and inflation are virtually nonexistent. These insights inform both financial risk management and policy actions aimed at enhancing corporate stability and supporting sustainable development in emerging markets. Full article