Search Results (1,159)

This paper extends the optimal investment control framework by incorporating fractional Brownian motion to capture long-range dependence and memory effects in asset prices. Replacing the standard Brownian component with a fractional Brownian motion governed by the Hurst parameter H with $H\in (1/2,1)$, we employ the Wick–Itô calculus to derive the associated Hamilton–Jacobi–Bellman (HJB) equation. The resulting nonlinear PDE contains a time-dependent diffusion coefficient that reduces to the classical model when $H={\displaystyle \frac{1}{2}}$. We apply a linearized generalized Newton method to construct an iterative sequence for the value function and provide a numerical convergence analysis via the contraction mapping theorem. Using real GOOGL data, we obtain a model-implied mean optimal allocation of ${\overline{\pi }}^{*}=68.35\%$ for $H=0.62$, close to the classical $69.76\%$. A comprehensive sensitivity analysis identifies volatility $\sigma$ and jump intensity $\lambda$ as the dominant drivers of the optimal allocation, with absolute effects of $9.44\%$ and $6.47\%$, respectively, while the Hurst parameter H, the jump threshold $\tau$, and mean return $\alpha$ have smaller effects. The proposed framework provides a dynamic optimal investment ratio ${\pi }^{*}\left(t\right)$ that adjusts to market memory, offering a model-based strategy for portfolio management under both jump and long-memory risks. Empirical validation through backtesting is needed to establish its practical superiority. Full article

Background: Intermittent retail sales create substantial uncertainty for inventory control, particularly across large portfolios of heterogeneous item–location systems. This study develops a scalable GPU-accelerated Fokker–Planck framework for probabilistic inventory modeling and safety-stock optimization. Methods: The framework is evaluated using 30,490 item–store sales series from the M5 dataset. Empirical sales characteristics are mapped to mean-reverting stochastic inventory dynamics, while a conservative finite-volume scheme and normalized formulation enable canonical policy densities to be solved on the GPU and mapped across the portfolio. Results: Numerical verification confirms analytical agreement, probability-mass preservation, grid convergence, and CPU–GPU consistency. More than 70% of the series exhibit intermittent sales characteristics. Across 35 economic scenarios, global and demand-class policies select no incremental safety-stock buffer beyond the baseline target. Item-specific optimization yields a 21.23% mean in-sample model-implied cost reduction under the original objective, whereas the mean locked-test personalization benefit is 2.46%. Conclusions: GPU-accelerated Fokker–Planck modeling provides a numerically stable and scalable framework for portfolio-level probabilistic inventory analysis, although the benefits of item-level personalization depend on the sales process, economic objective, and out-of-sample environment. Full article

Dynamic workforce allocation in project-oriented service environments requires simultaneous consideration of heterogeneous and continuously changing information on employee competencies, availability, workload, expertise, and project requirements. However, allocation decisions frequently remain dependent on fragmented information and managerial judgement, limiting consistency, transparency, and responsiveness. This study develops and empirically evaluates a lightweight multi-criteria decision-support framework for dynamic workforce allocation using an Action Design Research methodology. The framework structures allocation through task characterization, candidate eligibility filtering, and employee ranking based on an Allocation Suitability Score integrating competency matching, availability, normalized workload, and expertise. The weighting configuration was calibrated through four iterative rounds involving ten organizational experts and subsequently examined through sensitivity analysis, demonstrating 100% stability of the top-ranked candidate across 16 weight perturbations and a mean Spearman rank correlation of 0.994. Industrial evaluation was conducted within a project-oriented internal software-development function comprising 102 employees and an organizational portfolio of 284 projects. Quantitative validation used seven purposively selected paired allocation cases evaluated under equivalent conventional and framework-assisted conditions. The framework was associated with an 84.3% reduction in mean allocation time, a 92.9% reduction in workload imbalance, a 12.6% relative increase in resource utilization, a 25.3% increase in allocation consistency, and a 98.0% reduction in manual intervention requirements. These quantitative findings were complemented by favorable managerial assessments of transparency, workforce visibility, responsiveness, and usability. The results provide case-specific empirical evidence that transparent, computationally lightweight multi-criteria decision support can substantially improve workforce-allocation processes while preserving managerial interpretability and implementation flexibility. The proposed framework therefore provides a reproducible foundation for dynamic workforce allocation in project-oriented, knowledge-intensive service environments, while broader generalizability requires longitudinal and cross-organizational validation. Full article

Governments increasingly use processing-time indicators to evaluate development assessment, although comparability across councils is uncertain. This study examines how application composition, determination pathways, recorded workflows and information practices affect council-level comparisons in Greater Sydney, Australia. The analysis links NSW Online Development Assessment Data API metadata to council tracking portal histories across 12 councils between January 2023 and April 2026. It compares application portfolios, processing durations and determination routing, maps events to five stages, and evaluates recording practices. It is found that median processing durations ranged from 53 to 153 days; higher application volumes were not consistently associated with longer processing. Portfolios differed by proposed use, limiting comparisons of aggregate timeframes. Recorded workflows varied, with referrals and internal review representing recurrent coordination pressures rather than a uniform bottleneck. These findings extend research on differentiated policy implementation; common statutory rules do not necessarily produce comparable administrative performance measures. Processing time is a composite governance outcome shaped by case mix, institutional routing, recorded workflows and administrative visibility. Aggregate benchmarks should therefore serve as screening signals. Although numerical findings are context-specific, this analytical argument is relevant to decentralised regulatory systems in which local organisations implement common higher-level rules. Full article

Multi-stage fractured horizontal wells are a critical technique for enhancing the productivity of low-permeability hydrates in the Shenhu Area of the South China Sea, yet their economic feasibility remains unclear. In this study, an improved discounted cash flow model was developed, incorporating economies of scale in drilling and fracturing costs, as well as production efficiency. A systematic multi-factor evaluation was conducted based on field-scale numerical simulation data. The results indicate that all un-fractured scenarios yield negative net present values (NPVs) ranging from −30 to −43 million RMB, confirming their economic infeasibility. Among the fractured scenarios, the optimal combination was identified as a fracture stage spacing of 10 m and a production pressure of 1 MPa, achieving an NPV of 65 million RMB, an internal rate of return of 51.9%, and a payback period of approximately 2 years. Sensitivity analysis reveals that gas price is the most influential factor (sensitivity range: 216 million RMB), followed by horizontal well section length (123 million RMB) and gas–liquid separation efficiency (109 million RMB). In contrast, cost-related parameters—including drilling, fracturing, production system, and operation and maintenance—exhibit low sensitivity, each below approximately 12 million RMB. The recommended technical portfolio for the Shenhu Area comprises a fracture stage spacing of 10 m, a production pressure of 1 MPa, a horizontal well length of 900–1200 m, and a downhole gas–liquid separation efficiency of ≥85%. Viewed from an economic standpoint, these findings provide technically optimized engineering solutions for fractured horizontal well projects in hydrate development. Full article

Green technology supply chains combine rapid demand growth with concentrated production, uneven environmental performance, and exposure to trade disruption. This article links trade network analysis, next-year bilateral trade link prediction, multi-objective portfolio optimization, and disruption stress testing across 14 importing markets and six technology and material groups from 2015 to 2024. The cleaned sample contains 15,186 supplier-year observations and USD 696.1 billion in foreign supplier trade. Concentration rose most clearly in photovoltaic equipment, lithium-ion batteries, and wind equipment. In the chronological 2022–2023 test, gradient boosting achieved ROC AUC 0.911 and a Brier score of 0.119. Logistic regression produced slightly higher AUC, while persistence retained the strongest F1. Event-specific tests show that exits and reactivations are more predictable than rare first observed entries. A historical decision comparison finds only a small and statistically uncertain advantage of calibrated gradient boosting over calibrated logistic regression, while predictive continuity information improves allocation performance relative to a specification without the probability term. Latest-year portfolios remain highly concentrated, with median HHI of 0.632 and a median top-three supplier share of 95.5%. Under balanced priorities, median HHI falls by 53.7%, and sourcing exposure to supplier-country CO₂ intensity of GDP falls by 32.3%. These changes are accompanied by a 5.2% median unit value increase and a 4.8 percentage point decline in predicted next-year link activity. Joint supplier budget scenarios show that individually feasible national diversification plans can compete for the same alternatives. The framework provides a transparent basis for screening sourcing options, identifying cases that require supplier-level verification, and assessing where coordinated investment may be needed. Full article

Cultural tourism research has long recognised that the reasons for taking a trip and the activities undertaken at the destination are not equivalent. This study measures that difference within the same population-based travel microdata and examines its economic relevance. Using 3551 trip records from the March 2026 public-use file of Spain’s Encuesta de Turismo de Residentes (ETR/FAMILITUR), we compare the primary cultural-motive indicator with a non-exclusive measure of reported cultural participation based on cultural visits, performances, and other cultural activities. Among the 3202 trips with an observed activity block, cultural participation accounted for 30.1% of weighted trips, compared with 15.8% identified by cultural primary motive; 56.4% of participating trips had a non-cultural primary motive (respondent-cluster bootstrap 95% confidence interval (CI): 52.2–60.8%). Exploratory multiple correspondence analysis (MCA) and weighted latent class analysis (LCA) identify heterogeneous activity portfolios; a culture-excluded LCA also shows large between-class differences in externally measured cultural participation. In adjusted models, reported cultural participation remains associated with approximately 13.0% higher total trip expenditure (95% CI: 5.8–20.7%), but its association with expenditure per night is smaller and non-significant. Model-selection criteria favour participation over motive, although the incremental R² and respondent-grouped prediction gains are small. No independent association with global satisfaction is detected. The findings support a bounded measurement contribution: primary motive and reported participation capture different aspects of cultural tourism and should be reported separately. Full article

Urban public buildings offer large rooftop PV potential, yet cross-building comparison is often hindered by heterogeneous sizes, operating conditions, and incomplete monitoring. This study develops and applies a standardized indicator framework to benchmark rooftop PV impacts across 12 municipal food markets in Madrid, Spain, using harmonized geometric, energy, PV-system, economic, and environmental metrics. Annual PV impact is screened through changes in purchased electricity derived from pre- and post-installation bills, using 12-month windows where available, while PV generation is represented by the expected production reported in project documentation. The framework includes energy intensity (kWh/m²·year), relative electricity reduction, the reduction-to-expected-production ratio, investment cost per installed capacity, and levelized cost of energy. Descriptive statistics and an LCOE sensitivity analysis are included using discount rates of 3–7%, OPEX values of 1–2% of gross CAPEX, a 25-year system lifetime, and an optional annual degradation rate of 0.5%. The portfolio comprises approximately 735 kW of installed PV, with an aggregated billing-based electricity reduction of approximately 0.994 GWh/year compared with 1.192 GWh/year of expected PV production. The median consumption reduction is approximately 40%, and the reduction-to-expected-production ratio ranges from 0.38 to 2.42. This dispersion confirms that the ratio is a screening and data-consistency indicator rather than a PV performance ratio or a causal estimate of PV generation. The framework supports transparent portfolio screening, cross-building benchmarking, identification of anomalous cases, prioritization of detailed audits, and definition of monitoring requirements for municipal PV programs. Full article

Process-based arts interventions—engaging participants in active embodied creation rather than analysis of completed works—produce more substantive cognitive, emotional, and behavioural change than product-based methods, yet present a significant accessibility challenge: non-artists asked to engage in such practices often respond with resistance, discomfort, and self-doubt, particularly in higher education where embodied learning differs from assumptions about legitimate study formats. This article introduces ARTFUL—a six-stage framework informed by neuroscience research on physiological readiness for learning, cognitive scaffolding, and embodied cognition—which addresses this barrier through progressive pairing of cognitive understanding with embodied experience. The framework was developed iteratively in an exploratory qualitative case study format: earlier course editions employed a three-stage format and the resistance observed motivated the extension of the format. Qualitative data from 24 management students (pre-programme surveys, post-programme semi-structured interviews, creative diaries and reflective portfolios) were analysed thematically. Three self-reported domains of cognitive change emerged: enhanced attention and concentration, increased openness to novelty, and reduced cognitive rigidity. Students moved from initially dismissing embodied methods as inappropriate for higher education to actively integrating them into professional and academic contexts. These findings suggest that systematic scaffolding may support a self-reported shift from initial resistance towards perceived cognitive flexibility, offering a transferable approach for designing accessible process-based arts interventions for non-artist learners. Full article

Stock market volatility forecasting is important for risk management, portfolio allocation, and investment decision-making. This study provides a bibliometric and methodological review of stock market volatility measurement and forecasting research published between 2016 and 2025. A model-neutral search of the Web of Science Core Collection, conducted on 18 August 2026, identified 440 records. Following title, abstract, full-text, and document-type screening, 177 eligible journal articles were retained. To assess search-term sensitivity, a supplementary search conducted on 4 September 2026 using alternative volatility terminology identified 33 additional eligible studies, yielding a final corpus of 210 studies. Bibliometrix/Biblioshiny and structured methodological classification were used to examine the field. Econometric approaches remained dominant (168 studies; 80.0%), followed by Machine Learning (25; 11.9%), Deep Learning (8; 3.8%), and Hybrid approaches (9; 4.3%). The evidence reveals substantial methodological diversification beyond conventional GARCH models and increasing use of realized and implied volatility, high-frequency information, sentiment, macroeconomic variables, and uncertainty indicators. No methodological family demonstrates universal forecasting superiority, as performance depends on markets, horizons, information sets, benchmarks, and evaluation criteria. Overall, the literature reflects methodological diversification, information enrichment, and selective integration rather than replacement of econometric models by artificial intelligence. Although the review is limited to the Web of Science Core Collection, the sensitivity analysis demonstrates the importance of alternative terminology in identifying relevant studies. Full article

Quantum algorithms for trading span computational tasks with different input models and standards of evidence. This structured critical review describes its search scope, selection criteria and limitations, and distinguishes reported findings from author assessments. Amplitude estimation estimates bounded expectations to additive error $ϵ$ with $O\left({ϵ}^{-1}\right)$ oracle queries rather than the $O\left({ϵ}^{-2}\right)$ samples of plain classical Monte Carlo at fixed confidence. This query advantage does not establish an end-to-end runtime advantage: state preparation, arithmetic, error correction and classical competitors must also be costed. Published resource estimates for benchmark exotics require thousands of logical qubits and demanding logical operation rates. An illustrative sensitivity analysis shows how the crossover depends on classical throughput, oracle depth and the comparison window; its numbers are scenarios, not calibrated hardware forecasts. Portfolio and trading-trajectory formulations have device demonstrations, but a 250-instance benchmark of discretized minimum-variance allocation finds classical mixed-integer programming and a tailored heuristic superior on the tested formulation. Specific low-rank quantum machine learning algorithms have been dequantized under analogous sampling-access assumptions. Separately, a controlled study of quantum kernels for Chinese equity returns finds no significant advantage and demonstrates sensitivity to evaluation design; this does not settle other learning tasks. Entanglement-assisted coordination offers advantages in specified nonlocal games without computational-complexity assumptions, while its financial implementation and economics remain open. We distinguish computational performance from economic value and identify input/output costs, structured algorithms, reproducible benchmarking and explicit financial evaluation as priorities. Full article

Financial markets exhibit complex nonlinear dynamics driven by interactions between firm-specific characteristics and macroeconomic conditions, requiring robust mathematical models capable of capturing structural changes and temporal heterogeneity. This study proposes an explainable machine learning framework that combines regime-switching analysis and predictive modeling to investigate the long-term resilience of firms listed in the BIST 100 Index. Structural breaks in monthly return and volatility series are first detected using the Pruned Exact Linear Time (PELT) algorithm, enabling the classification of firm trajectories into resilient and fragile market regimes. A Regime Persistence Score is then introduced to quantify the proportion of time each firm remains in the resilient state. This score serves as the response variable in a Random Forest model that evaluates the influence of firm-specific financial indicators and macroeconomic variables, including exchange rates, producer price inflation, and commercial loan interest rates. In addition, a forward-looking classification model estimates the probability that firms will transition into a fragile regime within the subsequent six months. The proposed framework achieves an AUC of 0.706 and demonstrates stable predictive performance under alternative regime definitions, penalty parameters, cost functions, and cross-validation strategies. Explainability analysis derived from Shapley Additive Explanations (SHAP) data shows book-to-market ratio and sensitivities to inflation and interest rate changes as the most important components of enduring resilience. The proposed methodology provides an interpretable mathematical framework for regime detection, nonlinear time-series modeling, and decision support in sustainable financial systems, offering practical value for risk assessment and resilience-oriented portfolio management. Full article

Standardized urban indicators are essential for assessing smart and sustainable cities, yet their application in developing countries remains limited. This study addresses the critical gap regarding the availability of ISO 3712x standard indicators among local governments in Brazil—a nation marked by territorial and socioeconomic heterogeneity. Urban indicators based on open government data across all 5570 Brazilian municipalities were analyzed in this study using the ISO 37120, 37122, 37123, and 37125 standards. A synthetic smart and sustainable cities index was drawn up, supported by Factor Analysis and Principal Component Analysis (PCA). Considering the Local Indicator of Spatial Association (LISA), clustering patterns of municipal sustainability and smartness performance were identified: LISA analysis identified pronounced spatial clusters, with high-performance municipalities concentrated in the Southeast and South-Central regions, while low-performance clusters spread across the North and Northeast of Brazil. Despite the diversity of characteristics among Brazilian cities, 22 of the 302 ISO 3712x indicators (7.3%) could be collected with complete national data for all 5570 Brazilian municipalities; data for 59 indicators were available from open sources, though with gaps. Since the ISO 3712x standards offer a voluntary portfolio of indicators rather than a mandatory set, partial data coverage does not make the framework inapplicable; rather, they delimit the scope of the synthetic index presented here and highlight where open-data infrastructure must be strengthened. Municipal smartness and sustainability result from the multidimensional integration of technological innovation, human capital, social protection, and responsible environmental management. Despite the availability of ISO indicators, observations based on the authors’ institutional experience as members of ABNT/CEE-268—Brazilian mirror committee of ISO/TC 268—“Sustainable cities and communities”—reveal that local governments face challenges in systematically integrating them into strategic planning, presenting a significant opportunity for capacity building and evidence-based governance. In addition to the innovative aspect of this research—which involves using ISO-standardized indicators and collecting numerical data from official open data sources—this article presents a comprehensive index calculation for sustainable and smart cities based on these indicators, followed by the identification of its spatial clusters. Full article

Workplace wellbeing is a multidimensional construct shaped by psychological, physical, and organisational determinants. In higher education, human resource and governance policies influence these determinants, yet policy portfolios are often compliance-oriented rather than explicitly wellbeing-focused. Despite increasing global attention to workplace wellbeing, there remains limited empirical analysis of how institutional policy environments conceptualise and operationalise wellbeing, particularly in African higher education contexts. This study critically analysed workplace-related policies at a tertiary academic institution in Johannesburg to assess how wellbeing is conceptualised and operationalised, and to identify gaps relevant to academic employees. A qualitative single-case document study design was employed, guided by the Walt and Gilson Policy Triangle Framework (content, context, actors, processes) and complemented by a wellbeing classification lens. Policies were purposively selected based on predefined inclusion criteria relating to working conditions, inclusion, health and safety, development, and employment governance. Deductive framework analysis was followed by inductive thematic synthesis. Workplace wellbeing was not explicitly defined within the policy portfolio and was inconsistently operationalised. Most policies functioned through indirect pathways and emphasised legal compliance, governance, and procedural oversight. Five cross-cutting themes were identified, including compliance-driven policy architecture, uneven workload governance, and bounded disability inclusion. Key gaps included limited integration of psychosocial risk, insufficient support for chronic illness and non-visible disability, and lack of monitoring of wellbeing outcomes. Institutional policies provide important safeguards but do not operate as an integrated workplace wellbeing framework. Strengthening conceptual clarity, aligning policies with contemporary evidence, and embedding measurable wellbeing indicators may improve employee wellbeing and institutional sustainability. As a single-institution document analysis, the findings reflect formalities of policies rather than implementation and may therefore have limited transferability to other higher education sections. Nevertheless, the study provides a thourough framework for examining how institutional policies shape workplace wellbeing and offers a foundation for future comparative policy analyses. Full article

This study examines the dynamic transmission of geopolitical risk across Brent crude oil, gold, the U.S. Dollar Index, and the Thai stock market using a Bayesian time-varying coefficient vector autoregressive (TVC-VAR) framework. Using monthly data from January 1990 to December 2025, the analysis combines time-varying impulse responses, generalized forecast error variance decomposition, dynamic connectedness measures, and network analysis. The results show substantial time variation in spillover intensity and direction. On average, Brent crude oil is the strongest net transmitter, gold has a smaller positive net position, and the U.S. Dollar Index and the Thai stock market are net receivers. Episode-specific point estimates indicate changes in transmitter-receiver roles and bilateral channels, but bootstrap sensitivity analysis shows that several apparent role changes are not statistically distinguishable once uncertainty is considered. The evidence therefore supports a dynamic, reconfigurable connectedness structure while cautioning against causal, safe-haven, or portfolio-performance interpretations that are not directly tested in this study. The findings are relevant to financial-risk monitoring and macro-financial surveillance under changing geopolitical conditions. Full article