Search Results (481)

The Solvency II regulatory framework (Directive 2009/138/EC) defines the Solvency Capital Requirement (Solvency Capital Requirement, SCR) using a value-at-risk (VaR) approach, with a confidence level of 99.5% and a one-year time horizon. This structure makes regulatory capital extremely sensitive to the characteristics of the right tail of the loss distribution and, consequently, to the effectiveness of risk transfer mechanisms. This study analyzes the impact of the five main types of reinsurance contracts quota share, surplus, quota–surplus, excess-of-loss (XoL), and stop-loss on the transformation of the net loss distribution and the resulting dynamics of the SCR. The empirical analysis is based on a computational experiment using real data from a ten-year insurance portfolio covering the period 2016–2025. The results show that the use of reinsurance leads to a reduction in the total capital requirement in the range of 18.4–23.4% on an annual basis, with the effect exhibiting an approximately linear relationship with the size of the cession quota. The stratified comparative analysis conducted identifies significant differences in the effectiveness of individual contract structures with regard to the reduction of tail risk. In particular, XoL contracts demonstrate the strongest effect on the extreme quantiles of the loss distribution, with a reduction reaching −52.5% at the 99.5% VaR level and −68.6% at the 99.9% VaR level. In contrast, quota-share contracts result in a practically proportional scaling of risk, characterized by a symmetric reduction of approximately −40% across all confidence levels. The results further show that multi-tiered reinsurance programs combining quota share, excess, catastrophe XoL, and stop-loss components provide the highest degree of capital relief, reaching 48.8%, which indicates the presence of significant nonlinear diversification and complementarity effects among the individual risk transfer mechanisms. A waterfall decomposition is applied to identify the main factors determining the difference between the standard formula and the internal model. The analysis finds that the dominant drivers of the observed capital relief are the effect of precise risk calibration (on average −8.3%) and the effect of diversification (−4.7%). These results underscore the importance of adequately modeling the interdependencies among risk modules and the limitations of standardized regulatory parameterizations. In addition, a “wrong-way risk” stress scenario is developed, involving the simultaneous occurrence of a catastrophic risk and the insolvency of two key reinsurers. Under this scenario, the effectiveness of risk transfer is reduced to −27.3%, and the solvency ratio falls below the minimum capital requirement (12.5%). This result empirically confirms the cautious regulatory stance of the European Insurance and Occupational Pensions Authority regarding the limited recognition of capital reliefs that do not demonstrate resilience under extreme stress conditions. This study provides a quantitatively grounded framework for optimizing reinsurance programs under the Solvency II regime. The main conclusion is that capital efficiency is not a function of a single “optimal” reinsurance contract, but rather results from the strategic combination of various reinsurance mechanisms capable of simultaneously reducing tail risk, improving diversification, and limiting vulnerability to systemic stress events. Full article

The U.S. healthcare delivery infrastructure functions as a complex socio-technical system-of-systems (SoS). In this environment, autonomous, interdependent entities (providers, insurers, and IT networks) must balance local efficiency with system-wide coordination. Existing governance mechanisms frequently fail to prevent operational fragmentation, yet the conditions under which governance pressure generates or inhibits coordination remain poorly understood. This study introduces a three-parameter cost framework. The framework comprises default operational costs, incoherence penalties for structural misalignment, and switching costs associated with modernization. This framework enables the examination of how governance structures shape emergent alignment in healthcare SoS. The three cost components are grounded in the Confluence Interoperability Covenant (CIC), a governance framework that codifies standards for interaction among autonomous healthcare systems and extends it into a computationally tractable form for simulation-based analysis. The contribution lies in jointly operationalizing these three cost components interacting with each other within a healthcare SoS governance framework using agent-based modeling and simulation (ABMS) and examining how their interaction shapes coordination under decentralized, periodic adaptation. Using a stylized exploratory ABMS framework implemented on a network, we analyze how these parameters influence coordination dynamics across a range of simulated governance conditions. The results reveal three emergent patterns. First, higher incoherence costs accelerate the transition from fragmented legacy configurations toward greater alignment. Second, high switching costs can create lock-in dynamics in which inefficient arrangements persist because transition burdens suppress adaptation. Third, the relationship between governance pressure and speed of coordination is non-monotonic: at early review horizons, moderate incoherence costs can produce faster coordination than maximal pressure, whereas stronger pressure eventually produces lower entropy as the simulation progresses. This finding reflects a transient finite-horizon coordination advantage rather than a fixed optimal governance level. This last finding suggests that governance effectiveness is horizon-dependent rather than a simple linear function of regulatory intensity. These findings contribute to a complexity-informed understanding of healthcare governance by showing that alignment in adaptive SoS depends not only on the intensity of interoperability pressure but on its interaction with institutional transition burdens. The model is designed as a mechanism-exploration framework to support future empirically grounded policy analysis and data collection. Full article

We develop a stochastic-control and mean field game framework for catastrophe insurance under stochastic replacement-cost risk. Insurer surplus follows a controlled jump diffusion in which catastrophe losses are scaled by an exogenous mean-reverting replacement-cost factor and attenuated through physical hedging. We establish well-posedness and stability of the controlled state process, derive a stopping-time dynamic programming principle, and characterize the value function as the unique viscosity solution of the associated nonlocal Hamilton–Jacobi–Bellman (HJB) equation. We then formulate strategic interaction among insurers through a coupled nonlocal HJB–Kolmogorov system and establish existence and uniqueness of mean field equilibrium under regularity and monotonicity conditions. The analysis quantifies how elevated replacement costs amplify catastrophe-loss exposure while physical hedging reduces it. Numerical results indicate stronger optimal hedging under high replacement-cost states and weak capitalization and quantify the equilibrium effects of industry-wide vulnerability. Full article

Background: Endotracheal intubation is a painful and stressful procedure for neonates, and premedication is recommended for non-emergent settings. However, there is no consensus on the optimal pharmacological regimen. In recent years, several drugs have emerged as treatment options to improve comfort and safety of neonates undergoing endotracheal intubation. Worldwide, a range of agents are used. Remifentanil is a short-acting opioid with rapid onset and recovery characteristics that may be useful for neonatal intubation. Methods: A structured search of PubMed/MEDLINE, Embase, and Cochrane Library databases (1990–December 2024) identified publications evaluating remifentanil for neonatal intubation. Clinical studies, pharmacokinetic investigations, reviews and guidelines were qualitatively synthesized with an emphasis on dosing, efficacy, safety, dosing, administration technique, and clinical context. Results: The literature search retrieved 45 publications, but only a small subset were randomized clinical studies. Findings generally support feasibility and short-term efficacy, while results vary across studies, particularly for intubation conditions and respiratory adverse events. Chest wall rigidity, apnea, and desaturation appear to be influenced by dose, administration rate, patient characteristics, and co-medication, although the available studies are too small and heterogeneous to define an optimal regimen. Conclusions: Remifentanil can be considered for selected non-emergent neonatal intubation and INSURE procedures when administered by experienced teams under appropriate monitoring conditions. Particular caution is warranted in clinically unstable infants, during LISA procedures where preservation of spontaneous breathing is desirable, and in settings where immediate airway rescue capabilities are unavailable. The study did not demonstrate clear superiority of remifentanil. Current evidence is limited and heterogeneous, and larger comparative studies with standardized dosing, administration, and outcome definitions are needed. Full article

Cultivated land protection is fundamental to sustainable agricultural development, and reducing pesticide use is a key pathway for improving cultivated land quality. While policy-based agricultural insurance plays an important role in ensuring food security, whether it can promote pesticide-use reduction by influencing farmers’ production decisions remains unclear. Using survey data from 521 large-scale rice farmers in Jiangxi Province, China, this study takes the coverage depth of policy-based rice insurance as the core explanatory variable and employs ordinary least squares (OLS) estimation, the instrumental variable (IV) approach, and propensity score matching (PSM) to examine its effect on pesticide expenditure. Furthermore, the mediating roles of green technology adoption and farmland operational scale are explored. Specifically, for every one-unit increase in the coverage depth of policy-based rice insurance, pesticide expenditure decreases by 0.169 units. The results show that (1) greater insurance coverage depth significantly reduces pesticide expenditure among large-scale rice farmers, and this finding remains robust across a series of robustness tests and after addressing endogeneity concerns; (2) policy-based rice insurance promotes pesticide expenditure reduction by encouraging green technology adoption and expanding farmland operational scale; and (3) the pesticide-reduction effect is more pronounced among farmers with larger operational scales and more extensive farming experience. Based on these findings, efforts should be made to dynamically optimize the policy-based rice insurance system, strengthen its risk protection capacity, improve agricultural resource allocation efficiency, enhance its green incentive effects, and implement differentiated insurance support policies with more accurate compensation mechanisms. Full article

Background and Objectives: The optimal timing of orthodontic intervention in children remains debated, particularly during the mixed dentition phase. Despite potential benefits, variability in clinical decision-making persists. This study explored orthodontists’ perceptions, clinical practices, and clinical decision-making regarding the timing of early orthodontic intervention in Saudi Arabia. Materials and Methods: An interpretive qualitative study was conducted using semi-structured interviews with nineteen licensed orthodontists practicing in Saudi Arabia. Participants were purposively sampled to ensure diversity in clinical experiences and practice settings. Interviews were conducted in English and Arabic, using detailed contemporaneous field notes that were subsequently expanded for analysis. Data were analyzed using thematic analysis following Braun and Clarke’s framework, with iterative coding supported by investigator triangulation, reflexive memoing, and participant validation. Data collection continued until thematic saturation was achieved. Results: Four major themes were identified. Early intervention was widely perceived as beneficial, particularly for functional problems, Class III malocclusions, and crossbites. However, decision-making was highly individualized, with many clinicians adopting a selective approach and deferring treatment in mild cases. Variation in clinical reasoning was observed across individual participant accounts, reflecting clinical judgment and contextual influences. Key barriers included limited parental awareness, financial constraints, and delayed referrals. System-level factors, such as variability in insurance coverage, referral pathways, and the lack of structured early screening programs, were identified as important influences on access to timely care. Conclusions: Early orthodontic intervention should be applied selectively, based on clinical indications and patient-specific factors. The context-specific findings highlight the need for appropriately tailored guidance, improved referral systems, structured early screening, and consideration of clinical, practitioner-related, and healthcare system factors to support consistent, patient-centered orthodontic care. Full article

The study addresses the design and development of a unified corporate information system for multimodal transport and logistics companies engaged in maritime and railway transportation. Analysis of the existing literature revealed the absence of a coherent methodological framework for the design of corporate information systems tailored to the specific operational characteristics of multimodal transport and logistics enterprises. To bridge this gap, a design methodology for corporate information system databases is proposed, intended for subsequent deployment in companies operating multimodal supply chains. The development of the unified corporate information system was guided by the principle of “total costs,” which requires that the decision-maker—when selecting transport modes, methods of transportation, carriers, routing, and auxiliary intermediaries (insurer, stevedore, bank, and customs broker)—address the problem as an integrated whole rather than optimizing individual components in isolation. The study encompasses information modeling of the business processes of multimodal transport and logistics companies, construction of an optimal model of the transport process for maritime and railway transportation using integrated computer automated manufacturing definition (IDEF) and structured analysis and design technique (SADT) modeling, and the design of a multilevel unified database structure for the coordination of different transport modes. A decision-making and support system has been developed for managing the operational activities of a multimodal transport and logistics company engaged in maritime and railway transportation. The proposed unified corporate information system enables the replacement of task resolution by local optimization criteria applied separately to each transport mode—such as freight cost and delivery time—with a single global optimization criterion for the multimodal supply chain. Full article

Background/Objectives: In Lebanon, the economic crisis since 2019 has severely strained healthcare infrastructure, yet its impact on cancer treatment adherence remains incompletely characterized. This study assessed factors associated with treatment delay and regimen modification to identify barriers to optimal cancer care among Lebanese patients. Methods: This multicenter, cross-sectional study was conducted in five tertiary hospitals in Beirut, Lebanon, between 13 June 2024, and 27 June 2025. Demographic, clinical and treatment data were collected via a structured questionnaire. Bivariate and multivariable binary logistic regression analyses were performed to identify independent predictors of treatment delay (>2 weeks) and incomplete treatment regimens. Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) are reported. Results: A total of 244 patients were enrolled in the study. The study population was predominantly female (59.0%) and aged ≥60 years (60.2%). Advanced disease was common, with 50.4% of patients presenting with stage IV disease. Financial vulnerability was widespread: 72.6% reported monthly household incomes below USD 1000, 88.1% reported a decline in income due to the economic crisis, and 39.3% relied on unstable income sources. Overall, 52.5% of patients experienced treatment initiation delays, and 9.0% received incomplete or dose-reduced regimens. On multivariable analysis, reliance on unfixed income independently predicted treatment delay (aOR 2.55, 95% CI 1.42–4.59; p = 0.002), lack of health insurance (aOR 1.91, 95% CI 1.08–3.39; p = 0.026) and pre-treatment surgical costs also increased the odds of delay (aOR 9.03, 95% CI 2.57–31.7; p = 0.001). For incomplete treatment, unfixed income remained an independent predictor (aOR 2.09, 95% CI 1.16–5.79; p = 0.015). A lack of insurance (aOR 5.62, 95% CI 1.22–25.9; p = 0.027) and high laboratory costs (>USD 150 per session) were also associated with incomplete regimens (aOR 1.62, 95% CI 1.02–2.57; p = 0.041). Conclusions: In Lebanon’s crisis context, financial instability was a key factor associated with deviations in cancer treatment. These findings highlight the need for strengthened insurance coverage and subsidization of diagnostic and treatment-related costs to ensure timely and continuous oncologic care. Full article

This paper develops a two-period analytical model of trade-in insurance and rebate design in a product upgrade and recovery system with successive product generations. In standard trade-in programs, customers face uncertainty about future rebate eligibility because rebates depend on the condition of the used product at the upgrade stage. We study an optional insurance mechanism through which customers prepay a fixed fee and receive a guaranteed future trade-in rebate. Customers are financially risk-neutral, but insurance may generate a first-period non-monetary psychological benefit: once future rebate eligibility is guaranteed, customers can use the product during the first-period ownership stage with less anxiety about an unexpected failure eliminating their future trade-in opportunity. Under the baseline specification in which this psychological benefit increases with product valuation, trade-in insurance generates valuation-based customer segmentation among insured upgraders, uninsured trade-in customers, product keepers, delayed buyers, and non-buyers. This insured–uninsured single-crossing result extends to general increasing psychological-benefit functions, including concave forms. The model further shows that the insurance price and trade-in rebate should be coordinated because both instruments affect customer upgrade behavior, product sales, rebate obligations, return flows, and recovery value. When product innovation is sufficiently high, customers no longer keep functional used products, and the optimal insurance price and trade-in rebate become independent of innovation and durability. Compared with a standard trade-in program, optional trade-in insurance weakly improves manufacturer profit, while the economic magnitude of the gain depends on market and operational conditions. Full article

Gout is one of the most common inflammatory arthritides worldwide, and its burden is rising in Southeast Asia alongside rapid demographic and socioeconomic transitions. This region, characterized by diverse healthcare systems, cultural practices, and levels of economic development, presents a unique context in which the epidemiology and management of gout are evolving. Despite the availability of effective urate-lowering therapy (ULT) and well-established treat-to-target (T2T) strategies, real-world outcomes remain suboptimal. Barriers to optimal gout care operate at multiple levels. Physician-related factors include clinical inertia and limited awareness of evidence-based recommendations. Patient-related factors include limited understanding of gout and its treatment, compounded by socioeconomic disadvantages. System-level challenges include inequitable access to healthcare services, limited health insurance coverage, and resource-strained health systems. The current evidence base in Southeast Asia remains limited and heterogeneous, raising uncertainty regarding the applicability of global data to local populations. Nevertheless, emerging studies suggest that multidisciplinary, context-oriented approaches can improve gout outcomes. The objective of this review is to explore the evolving epidemiological landscape and barriers to gout management in Southeast Asia. Full article

Background/Objectives: Telehealth (TH) and Telemedicine (TM) can significantly benefit individuals who live far from healthcare institutions and those with limited financial resources by improving access to essential health services. This review explores the attitudes and determinants affecting the use of TH and TM, focusing on the MENA region with insights from the global context. Methods: A narrative review was created using a compilation of scientific articles published between 2020 and 2025 from PubMed and Scopus. Studies were screened to be relevant with the determinants, attitudes or use of TH and TM. Forty one sources met the eligibility criteria and covered evidence from the MENA region with supporting background from global developments. Results: In the MENA region, although high perceived effectiveness is recorded, the use of TH and TM remains below optimal levels. The majority of the studies reviewed suggested that participants have positive attitudes towards TH and TM. Nevertheless, some studies suggest low awareness and limited utilization of available TH and TM services. Determinants affecting TH and TM included pandemic-based, socioeconomic, cultural, financial, health literacy, and infrastructure-based factors, and those relating to physician implementation. Disparities in utilization of these services were evident among individuals with low digital literacy, older individuals and low-income workers. Conclusions: TH and TM are observed to increase the availability and accessibility of preventative and treatment-based health services, especially in regions facing geographic limitations. The findings exhibit the disparities in institution and uptake of these services due to socioeconomic, geographic and cultural aspects. Interventions at the system level, supported by evidence such as multilingual digital platforms, investments in digital infrastructure and coverage in insurance, need to be implemented to ensure equitable utilization of these services in the MENA region. Full article

Background/Objectives: Stroke is the leading cause of death and disability among adults in China. Most survivors experience debilitating symptoms, including limb weakness, pain, fatigue, and depression, which impair quality of life and increase caregiver burden. This study aimed to identify clusters of symptoms and functional status in patients with stroke, their associated factors, and the influence of family burden. Methods: From February 2023 to February 2024, 779 patients with stroke from three Chinese tertiary hospitals completed an electronic questionnaire covering demographics and Patient-Reported Outcomes Measurement Information System measures, including depression, anxiety, pain interference, physical and cognitive function, social participation, and family burden. Using SPSS 26.0 and Mplus 8.0, chi-square tests, analysis of variance, latent class analysis, and multiple logistic regression were performed. Results: Latent class analysis identified three distinct symptom–functional clusters among stroke patients: “low-symptom high-function” (36.4%), “moderate-symptom moderate-function” (54.6%), and “high-symptom low-function” (9.0%). Multinomial logistic regression revealed that age ≥ 60 years (OR = 0.15, p = 0.001), freelancing (OR = 2.75, p = 0.019), unemployment (OR = 2.73, p = 0.018), monthly income ≥ 5000 yuan (OR = 2.56, p = 0.026), no medical insurance (OR = 4.26, p = 0.01), living alone (OR = 2.45, p = 0.031), and family burden (OR = 0.95, p < 0.001) were associated with the “high-symptom low-function class”. Conclusions: Chinese stroke patients exhibit substantial heterogeneity in symptom and functional profiles. To optimize stroke rehabilitation, healthcare professionals should develop targeted management strategies, prioritizing high-risk populations, particularly socio-economically vulnerable and socially isolated patients. Full article

Climate risks and rural labor outflow are jointly challenging the sustainability of farm households in disaster-prone agricultural regions. Agricultural insurance, as an important risk management tool, may influence not only farm income but also farmers’ production and labor decisions. While previous studies on agricultural insurance have primarily focused on staple crops and income stabilization, the effects of labor allocation in facility-based intensive agriculture remain underexplored. This study addresses this gap by examining how participation in agricultural insurance affects farm household labor allocation in the context of greenhouse vegetable production. Using survey data collected from July to August 2025 from 247 greenhouse vegetable farmers in ShouGuang, China’s largest vegetable production base, we employ Probit and Two-Stage Least Squares (2SLS) models to address endogeneity and mediation analysis to explore the underlying mechanisms. The findings show that: (1) Agricultural insurance participation significantly increases the probability of farm households increasing agricultural labor input in the next planting season. (2) Agricultural insurance reduces farmers’ likelihood of exiting agricultural production through increased investment in agricultural technology, but this effect is constrained by the availability of investment capital. (3) The impact of agricultural insurance on labor allocation varies across different farmer groups, and is more pronounced among middle-aged and younger farmers with relatively small farm sizes, lower disaster risk, and higher levels of education. Several insurance-related policy recommendations are proposed to stabilize the agricultural labor force and mitigate rural labor decline—key dimensions of sustainable rural development. Given the single-region focus and sample size, the generalizability of these findings requires further validation in other agricultural contexts. Full article

The main motivation for this study is to develop a predictive framework that provides high accuracy at lower computational and experimental costs, resulting in better decision-making in the chosen application domain. Artificial neural networks (ANNs) are widely used for prediction, classification, and pattern recognition tasks. However, their performance is sensitive to the selection of architectural and learning parameters. Hence, an important research challenge is the effective selection of architectural and learning parameters. Several hybrid GA–PSO approaches have been proposed, but most of the existing studies simultaneously optimize network architecture and trainable parameters or focus on a single application domain. However, there is still a lack of systematic framework that optimizes these components separately and validates its performance on multiple heterogeneous datasets. To fill this gap, this study proposes a novel hybrid optimization algorithm, called GAPSO, which combines the genetic algorithm (GA) and particle swarm optimization (PSO) for efficient tuning of artificial neural network (ANN) parameters. The proposed framework is evaluated on five benchmark datasets, including AirPassengers, Sunspots, Death and Injury, Earthquake, and Insurance. In the proposed approach, PSO is used for determination of optimal network architecture (number of hidden neurons) and GA is used for optimization of connection weights and threshold values. The experimental results demonstrate that for four out of five datasets, the lowest MAPE values were achieved by GAPSO-ANN, and were competitive compared to ANN, GA-ANN, PSO-ANN, LSTM and XGBoost models. Additionally, the Wilcoxon signed-rank test showed statistically significant performance improvements (p = 0.03125). Full article

Global retail e-commerce sales have surged, yet product fit uncertainty remains a significant challenge, leading to rising product return rates. To address consumer concerns about return shipping costs, major Chinese online retail platforms have introduced return shipping insurance (RSI). Retailers can choose between Retailer-RSI (RRSI), which is provided by the retailer, and Customer-RSI (CRSI), which is purchased by consumers. Despite these options, information asymmetry causes insurers to assess return rates with bias—referred to as managerial confidence bias. Consequently, platforms are increasingly partnering with insurers to enhance their RSI offerings. This study develops a game-theoretical model to examine the dynamics between a platform and an insurer, as well as the impact of managerial confidence bias on RSI strategies. Our analysis reveals that the platform–insurer relationship is crucial in determining the optimal RSI strategy. Under an independent insurer, RSI is viable only if the insurer underestimates product return rates (i.e., exhibits overconfidence bias); RRSI is preferred if the bias is sufficiently strong, whereas CRSI is chosen otherwise. In contrast, under a dependent insurer, CRSI is favored by the retailer only when its return handling costs are substantially high; otherwise, RRSI is preferred. Furthermore, RSI consistently increases consumer surplus by reducing return hassle costs while only mildly raising the product price. However, the independent insurer’s bias leads to its own profit loss, resulting in a “loss–win–win–win” scenario across stakeholders. In contrast, the dependent insurer, supported by platform subsidies, can yield a “win–win–win–win” outcome that aligns stakeholder interests and enhances long-term platform benefits. Full article