Search Results (128)

Background: Hypertension commonly complicates Type 2 diabetes mellitus (T2DM), contributing significantly to increased morbidity and mortality. This study determined the prevalence and factors associated with hypertension among people with T2DM at a tertiary health facility in Northern Uganda. Methods: A hospital-based cross-sectional study was conducted from 18 July to 24 October 2024. Participants with confirmed T2DM were selected through systematic random sampling at Lira Regional Referral Hospital (LRRH) in Lira City, Uganda. Data were collected using a structured questionnaire adapted from the WHO STEPS (2022) tool. Patient charts and registers were used to verify information. Data were analyzed using STATA version 16. Multivariable logistic regression was performed, and p-values < 0.05 were considered statistically significant. Results: A total of 340 participants were enrolled in the study; the median age was 55 years; 244 (71.8%) were female; and nearly half of the participants (163, 47.9%) had attained primary education. Overall, 67.1% (228/340) of the participants with T2DM had hypertension. Factors independently associated with higher odds of hypertension were as follows: age 61+ years (aOR = 5.55, 95% CI: 1.34–23.1, p = 0.018), being overweight (aOR = 3.77, 95%CI: 1.05–13.57, p = 0.042), T2DM duration of more than five years (aOR = 2.51, 95% CI: 1.41–4.67, p = 0.002), and being widowed (aOR = 8.04, 95% CI: 1.87–34.61, p = 0.005). Earning UGX 50,001–100,000 per month (aOR = 0.35, 95% CI: 0.13–0.93, p = 0.037) was associated with 65% lower odds of having hypertension. Conclusions: Two-thirds of patients with T2DM had hypertension, and factors such as older age, being overweight, a longer T2DM duration, and marital status significantly increased hypertension risk; meanwhile, moderate-income status offered a protective effect. The high burden of hypertension among patients with T2DM demonstrates the necessity for targeted public health interventions such as comprehensive lifestyle modification programs, routine screening for hypertension, early detection, and its management among patients with T2DM through enhanced healthcare access. These interventions should focus on integrated care approaches that monitor and manage T2DM alongside hypertension. Full article

The Golden Triangle circuit (Delhi–Agra–Jaipur) is India’s most iconic tourism product, yet it faces mounting pressure from overtourism, environmental degradation, and economic leakage to non-regional operators. We argue that strategic management of visitor satisfaction can play a key role in transforming this high-volume circuit into a sustainable destination that delivers long-term economic growth. Drawing on expectancy disconfirmation theory (EDT), SERVQUAL (service quality), perceived value theory, social exchange theory (SET), destination competitiveness models, and systematic classification of destination attributes, this study evaluates destination attributes and visitor satisfaction. This study assesses the importance of visitor satisfaction with the Golden Triangle and proposes a comprehensive framework for its measurement and application with destination-specific attributes. It uses a qualitative methodology that incorporates an extensive review of information available through various sources and triangulates findings with autoethnography. It identifies key attributes driving tourist satisfaction in the Golden Triangle and assesses the overall current state of the circuit. Furthermore, it identifies major challenges (harassment, congestion, and leakage) and proposes actionable improvements through smart technology, community-based tourism, and real-time feedback. A comprehensive evaluation of visitor satisfaction with various destination attributes of the Golden Triangle reveals that it performs well, as the outcome shows high overall satisfaction. This study also highlights that overall visitor satisfaction is an indirect economic lever that impacts local economic activity by creating jobs and earning foreign currency. The Golden Triangle can possibly serve as a replicable model for other heritage circuits in the Global South with similar characteristics. Full article

In construction project management, the execution phase relies on deterministic scheduling methods that cannot represent activity-level uncertainty or support quantitative corrective-action testing before physical commitment. This study presents a conceptual framework and proof-of-concept application that addresses this gap by integrating Building Information Modeling (BIM) with the COSMOS Simulator—a construction-specific discrete-event engine benchmarked against industry simulators in prior work. The framework formalizes a semi-automated pipeline from Autodesk Revit through Dynamo BIM to COSMOS via a governed parameter store, converting BIM-derived quantity takeoffs into stochastic simulation inputs. This study makes two contributions: The first is the development of a governed BIM-to-simulation data pipeline in which an identifier-keyed data contract and in-flow validation establish an auditable chain of custody from design element to simulation input. The second is an advancement toward addressing a limitation the engine’s own validation studies identify—execution-phase site–data integration—through a control loop that couples Earned Value Analysis in a 4D BIM environment (Synchro) with iterative COSMOS-based scenario testing, enabling managers to evaluate corrective actions quantitatively before site implementation. Feasibility is demonstrated on an illustrative reinforced concrete building schedule, in which a schedule-performance shortfall triggers the loop and stochastic forecasting exposes an upper-tail completion risk hidden by the deterministic estimate. By establishing a governed pathway from BIM to the previously BIM-isolated COSMOS engine, this work provides a basis from which field-based evaluation of BIM-integrated stochastic project control can proceed. Full article

This study investigates the possibilities for recently listed Romanian Information and Communications Technology (ICT) firms to select optimal sets of financial strategies under adverse macroeconomic conditions, with high and persistent inflation, high volatility, high cost of financing and liquidity constraints that influence investment decisions and financial resilience. Using a stochastic investment model with the Tobin’s Q factor in a dynamic framework equipped with a generalized Wiener process, this study offers an intuitive approach for simultaneously assessing corporate market value under financial constraints and formulating optimal decisions based on liquidity management. In this research, the numerical simulations in Python for a set of 16 scenarios resulting from combining technological and macroeconomic variables were performed, with a series of parameters held constant. The results highlight the decisive role of financial restrictions and macroeconomic volatility in shaping the investment behavior, as well as the importance of adjusting the timing of investments together with liquidity mechanisms capable of improving financial resilience. The main contribution of this study is the simplicity with which one can assess the impact of the risk-free rate and volatility on the main parameters of the set of strategies (earnings dynamics, liquidity risk, cost of capital, liquidation value, opportunity cost associated with holding cash) and to assess the integrated perspective on financial resilience. This procedure is simple and scalable and can also represent a practical tool to support management and investment decisions in volatile and turbulent conditions. Full article

With the increasing adoption of the Engineering, Procurement, and Construction (EPC) contracts in government-funded and large-scale infrastructure projects, bill-of-quantities bidding based on preliminary design has emerged as a new procurement approach. Although this approach improves early-stage investment control, it also imposes higher requirements on contractors’ cost-management capabilities. Based on whole-process cost-control theory, this study develops a design-driven full-process cost-control framework for EPC projects using a reclaimed water plant project in northwest China as a case study. The model comprises three layers: a design-driven decision-making layer, a whole-process cost-control layer, and a collaborative management support layer. It covers the key stages of bidding, design, procurement, construction, and final settlement, and integrates design, cost, and procurement management with Building Information Modeling (BIM) and dynamic monitoring based on Earned Value Management (EVM). The case results show that the model can effectively identify and control cost risks, promote the integration of design optimization and cost control, and improve cost management performance. The final settlement price was 0.93% below the contractual settlement ceiling and about 6.6% below the initial investment estimate. This study provides both theoretical support and practical guidance for enhancing full-process cost control in EPC projects under preliminary-design bill-of-quantities bidding. Full article

The concept of virtual water is currently one of the most important issues in water resource management, especially in a context marked by structural water scarcity. Beyond the analysis of virtual water flows, which has been widely studied in the literature, this study aims to better understand the relationship between virtual water exports and economic growth. This paper analyzes the dynamic relationship between Morocco’s economic growth and agricultural virtual water exports to the European Union over the period of 1986–2023. An ARDL model was used based on annual data to test cointegration and estimate short- and long-term effects, controlling for gross fixed capital formation and agricultural value added. The bounds test confirms the existence of a stable long-term relationship between the variables. The results suggest that export specialization may be associated with foreign earnings and agricultural activity while also coinciding with greater pressure on resources and potential adaptation costs, especially for blue water resources. However, estimates indicate that in the long term, investment is positively and significantly associated with growth, while virtual water exports are associated with a negative effect on GDP, suggesting that export gains may be offset by increasing water constraints and sectoral trade-offs, and that agricultural value added mainly influences short-term dynamics. The results highlight the importance of integrating water footprint and virtual water trade concepts, as well as climate constraints, into agricultural and trade strategy planning while strengthening policies on water efficiency, innovation, and governance. Full article

This study explores the informativeness of forward-looking disclosures in managers’ speeches in U.S. quarterly earnings conference calls, focusing on time-frame specificity—whether statements provide precise temporal horizons. Using a keyword search, forward-looking statements (FLSs) in managers’ speeches in U.S. quarterly earnings conference calls are classified into those with and without specific time frames, and tests of their determinants, market responses, and implications for firms’ future performance are conducted. First, uncertainty is positively associated only with FLSs without time frames, likely because managers find it more difficult to specify time frames under uncertainty or are less willing to be held accountable. Second, investors respond more quickly to FLSs with time frames and more slowly to those without, while analysts use both types to improve forecasts; however, FLSs without time frames increase forecast dispersion, whereas those with time frames reduce it, suggesting greater information processing difficulty. Third, larger changes in future earnings and discretionary accruals are associated with more FLSs without time frames, while capital investment increases only with more FLSs with time frames. Collectively, these findings indicate that time-frame specificity conveys differential informational value. Full article

The objective of this paper is to offer a mathematical formulation of economic value added (EVA) that incorporates distance-to-default (DD) and thus a default-free capital structure. The latter is extended via the weighted average cost of capital (WACC) to introduce a default-free EVA. The data include the nonfinancial firms listed in the DJIA30 and NASDAQ100 covering the period 1992Q2–2023Q3. The results of standard specification tests and the GMM estimator show that (a) DD causes an increase in WACC and thus, EVA decreases; (b) the interest coverage ratio can be used effectively to compensate for default risk, thus adjusting the default-free EVA positively; (c) both EVA and default-free EVA can effectively be managed via common determinants, namely, net working capital ratio, total liabilities to EBITDA, sales growth rate, debt–equity ratio, and earnings per share; (d) the positive impact of the inflation rate on both EVA and default-free EVA justifies the use of default-free EVA as a metric for equity risk premium; and (e) the robustness of the results via stochastic geometric Brownian motion shows that the determinants of default-free EVA are stable. This paper contributes to related studies by incorporating credit risk via the DD into default-free EVA. Full article

The article examines the persistent stability of the weighted average cost of capital (WACC) disclosed by German DAX40 companies despite substantial declines in risk-free interest rates between 2004 and 2021. While theory suggests that WACC should reflect lower risk-free interest rates and decline as well with falling government bond yields, empirical evidence reveals minimal adjustment in reported WACC figures. Disclosed WACC of DAX40 companies remains between 7% and 8% as the yield of the ten-year German government bond fell from 4.1% to −0.2%. This study employs quantitative analyses to investigate whether systematic increases in risk exposure can explain this phenomenon. Using capital market data spanning from 2000 to 2023, we analyze five risk dimensions: systematic risk (beta factors), overall market volatility, risk aversion (lambda factors), earnings risk, and financial structure risk. Bootstrap analyses reveal a 41.5% reduction in beta factor variance, while volatility analyses demonstrate declining market risk exposure. The market price of risk analysis does not reveal definite findings. Earnings risk measures indicate improved financial stability, and debt ratios show modest declines. These findings suggest that observable risk parameters cannot explain persistent WACC levels, indicating a disconnect between theoretical WACC calculations and practitioner applications in investment project decision-making following value-based management principles. Full article

Construction projects generate large volumes of schedule and cost data throughout their lifecycle, requiring systematic integration for effective performance control. Despite the increasing adoption of BIM and Earned Value Management System (EVMS), existing studies have not sufficiently validated an interoperable IFC-centered framework that systematically links Work Breakdown Structure (WBS), cost data, and performance indicators within a single openBIM environment. To address these issues, a BIM-based EVM application system was developed using the Industry Foundation Classes (IFC) standard for efficient process–cost integrated management. Therefore, this study develops and validates an IFC-based openBIM Earned Value Management System (EVMS) to enable structured schedule–cost integration and performance monitoring within a unified data model. In this study, domestic and international methods of process–cost integrated management and current EVMS applications were investigated, and a BIM-based EVMS analysis process was established. The proposed system was then applied to two reinforced concrete construction project case studies to analyze EVMS results. The proposed framework integrates classification-based IFC object data, quantity extraction, and rule-based schedule–cost linkage to generate BCWS, BCWP, and ACWP indicators for performance evaluation. The system was implemented and empirically validated through a reinforced concrete construction project case study. Validation demonstrated the system’s ability to identify a significant cost overrun of 23,090,381 KRW and project a final budget excess of 92,447,283 KRW, demonstrating the practical feasibility of IFC-centered process–cost integration and its capability to provide early warning signals for schedule and cost deviations. The findings provide empirical evidence that an openBIM-based single-model structure can enhance interoperability, reduce manual reconciliation between WBS and cost breakdown structures, and support data-consistent EVMS analysis in heterogeneous software environments. Full article

Ensuring product integrity across Malaysia’s East Malaysian states (Sabah and Sarawak) requires a cold chain that is resilient to tropical heat, long multimodal routes, intermittent power, and dispersed rural populations. This paper proposes a sustainability-first architecture for vaccine and blood component logistics that combines World Health Organization and the United Nations International Children’s Emergency Fund Effective Vaccine Management (EVM 2.0) criteria with energy-aware transport planning, solar-hybrid edge refrigeration, phase-change materials, and digital temperature monitoring compliant with ISO 23412 for temperature-controlled delivery services. In this study, a mixed-methods methodology was employed, including (1) route and mode optimization under temperature risk and carbon intensity constraints; (2) equipment right-sizing using duty-cycle energy models and IEC 60068 environmental tests as design baselines; (3) governance with real-time earned value management (EVM) and key performance indicators (KPIs); and (4) scenario analysis for riverine, road, air, and drone last-mile segments relevant to remote East Malaysian communities. Results from realistic logistic scenarios indicate a 45–65% reduction in dose-weighted temperature-excursion minutes, 28–41% reduction in CO₂e per successful dose delivered, and 35–52% reduction in product loss compared with status quo planning. For blood components, solar-hybrid storage and mixed-mode routing reduced breach risk by 37% while maintaining red cells (2–6 °C), platelets (20–24 °C, continuous agitation surrogate), and fresh frozen plasma (≤−18 °C) requirements aligned with WHO guidance and Malaysia’s national transfusion policies. We provide a reference architecture, implementation bill of materials, and an EVM-aligned KPI dashboard to guide scale-up. Full article

The Earnings Response Coefficient (ERC) has emerged as a pivotal topic in academic literature and financial practice, elucidating the critical relationship between corporate earnings information and market response, which directly impacts corporate performance evaluation and investment decision-making. This study aims to identify the most frequently researched topics in the Earnings Response Coefficient domain, explore the basic concepts and theoretical frameworks underlying ERC research, and propose potential future research directions in the field, all within finance and investment management. This research employs bibliometric analysis to use data from Google Scholar and Scopus, accessed through Publish or Perish (PoP), to evaluate the literature’s performance, explore related topics, and identify research trends, thereby deepening the understanding of ERC studies. The findings reveal that income smoothing and intellectual capital disclosure have a significant impact but low connectedness, indicating a need for deeper exploration to heighten their relevance in ERC studies. Research on corporate social responsibility exhibits a high degree of interconnectedness and substantial impact. Underexplored topics such as economic uncertainty and analysts’ influence require greater attention to understand their contributions fully. This study identifies publication trends and citation networks related to ERC, provides insights into researcher collaborations, and offers guidance for academics, practitioners, and policymakers to enrich their understanding, develop more effective earnings management strategies, and design regulations that bolster market transparency and efficiency in the realm of finance and investment management. This research is particularly beneficial for practitioners, as it helps evaluate more effective earnings management strategies and understand the market’s response to earnings information, ultimately enhancing firm value. For policymakers, this study provides a framework for designing regulations and policies that support financial information transparency and market efficiency to enhance economic stability and investor confidence. Full article

Nowadays, the European economy faces significant global challenges that threaten the continuity of economic growth, especially in the German manufacturing sector, which is under strain from financial turmoil, resulting in numerous layoffs and firm closures. In this respect, FinTech significantly contributes to addressing these issues by providing data-driven analytical tools that improve the assessment and monitoring of firms’ financial position. However, in the literature, we have not found any paper that uses machine learning (ML) algorithms to assess the financial distress of German manufacturing firms, highlighting methodological and sectoral gaps that need to be bridged. Therefore, this study aims to develop an econometric and ML-based financial distress scoring model for German manufacturing firms by estimating contemporaneous Altman Z-scores that provide better insights into the financial distress determinants, enabling better financial management. The econometric findings revealed that the regression model has an adjusted R-squared value of 86%, confirming that the selected firm-specific and macroeconomic factors play a substantial role in explaining financial distress. The findings recommend that German manufacturing businesses retain more earnings rather than distributing them as dividends, while reducing their debt in capital structures to enhance financial stability. Moreover, the ML results found that Gradient Boosting and Random Forest have the highest accuracy scores among the ML methods, suggesting that these models provide strong capability for assessing financial distress and supporting more effective financial risk management, allowing firms to effectively respond to the threats of a dynamic environment and thereby better support the growth of the German and European economies. Full article

There is substantial empirical heterogeneity in the literature on the intersection between ESG performance and financial outcomes. To address this fragmentation, we foreground ESG integrity, the alignment between sustainability claims and high-quality financial reporting, as the mechanism through which ESG is translated into value. Using Scopus and Web of Science, the study identifies and screens 205 peer-reviewed articles published until October 2025 that jointly address ESG, earnings management, and financial performance. Using VOSviewer and Bibliometrix, we map the conceptual and intellectual structure and synthesize the evidence via interdisciplinary integration. We identify four primary intellectual pillars that govern the ESG–financial performance relationship: national institutions, governance architectures, disclosure quality, and earnings quality. The results suggest a “conditional chain” where ESG tends to be associated with sustained financial value when anchored in rigorous internal governance and high-quality reporting. Conversely, in weak institutional settings, ESG often serves as a “masking” mechanism for managerial opportunism and earnings management. The study reveals a significant shift in the literature from broad corporate social responsibility narratives toward material ESG metrics, gender diversity, and the “Twin Transition” (green and digital). This paper moves beyond traditional descriptive reviews by introducing a conceptual framework to mitigate “construct conflation” between governance and ESG. It provides a critical roadmap for future research, emphasizing the need for causal identification and granular measurement of real versus accrual-based earnings management. Full article

This study examines the impact of tax avoidance practices on investment efficiency in Egypt, with particular emphasis on the moderating role of earnings management by exploring whether these tactics reflect managerial opportunism or serve as a mechanism to ease financial constraints. We employ panel data regression to analyze a sample of 58 non-financial firms listed on the Egyptian Exchange (EGX) over the period 2017–2024, yielding 464 firm-year observations. Data are collected from official corporate websites, EGX, and Egypt for Information Dissemination (EGID). Grounded in agency theory, signaling theory, and pecking order theory, this study reveals how conflicts of interest and information asymmetry between managers and stakeholders lead to managerial opportunism. The findings show that tax avoidance undermines the investment efficiency in the Egyptian market. Earnings manipulation further intensified this effect due to the financial statements’ opacity. A closer examination reveals that earnings management exacerbates overinvestment by masking managerial decisions. Conversely, for financially constrained firms with a tendency to underinvest, tax avoidance and earnings management may contribute to improved efficiency by generating internal liquidity and alleviating external financing constraints. These results provide valuable insights for regulators, highlighting that policy should be directed against managerial opportunism and improving transparency, instead of focusing solely on curbing tax avoidance. From an investor perspective, they should closely monitor and understand the tax-planning strategies to ensure they enhance the firm’s value. Full article