This study developed system dynamic modeling (SDM) based on the International Classification of Functioning, Disability and Health (ICF) framework to simulate and identify key leverage points for enhancing social participation among older adults with noncommunicable diseases (NCDs), aiming to offer a robust theoretical foundation for designing effective interventions. Utilizing a system dynamics modeling, we simulated intervention strategies to augment social participation among older NCDs patients. Initial insights from in-depth interviews with 31 older individuals informed the construction of a causal loop diagram, elucidating the multifactorial relationships and feedback mechanisms among pertinent variables. Data from 500 patients were analyzed using correlation analysis, an independent weighting approach, and multiple regression to identify key variables, determine their equation coefficients, and construct a stock flow diagram for the model. The model then simulated social participation trends over 16 months under varying intervention intensities. The results showed significant improvements in mobility function, functional ability, pain management, and social support, resulting in increases of 54.9%, 32.4%, 28.7%, and 25.0%, respectively, at a 10% intervention level. When intervention intensity was escalated to 20%, the impact became even more pronounced, with mobility function leading the way at a 127.5% increase, followed by pain management (63.6%) and functional ability (62.8%), and social support (48.7%). Self-care and emotional functions showed minimal improvement in social participation, with increases of less than 3% and 5%, respectively. Improving social participation in older NCDs adults requires understanding complex system dynamics. This study highlights mobility function, functional ability, pain management, and social support as key leverage points, stressing the need for targeted interventions based on individual assessments.

This study aims to develop a system dynamics model to predict healthcare waste generation and associated costs, focusing on hazardous healthcare waste. Systems dynamics approach is utilized to analyze the complex dynamics of healthcare waste management. Data collection involves precise waste categorization across 46 departments of Jordan University Hospital, facilitating the development of a comprehensive model. The developed model accurately predicts future hazardous healthcare waste output and estimates disposal costs, considering various waste types and operational limitations. Sensitivity analysis demonstrates the model's stability, with consistent predictions across different parameter values and forecast accuracy within 5% for most waste categories. The study further evaluates two disposal scenarios for formalin chemical waste: outsourcing to external treatment providers versus internal treatment using a hospital-installed system. Scenario 2, internal treatment, could reduce chemical waste disposal costs by approximately 80%, corresponding to about a 6.45% reduction in total hazardous waste disposal costs (medical + chemical combined) in the forecast year 2031. Scenario 1, removing the hospital’s internal disposal machine and relying solely on external services, results in significantly higher long-term waste management costs. Over the next decade, the model predicts patient admissions to increase from 699,925 in 2021 to 797,434 in 2031, driving medical waste from 164,982 kg to 187,967 kg and chemical waste from 2,371.5 kg to 2,701.89 kg. Long-term projections indicate waste management expenses could rise by 167% by 2041, 268% by 2051, and exceed 500% by 2071 if current practices continue. Integrating system dynamics modeling into healthcare waste management offers a comprehensive approach, considering environmental, epidemiological, and economic dimensions. This provides a versatile tool for optimizing resource allocation, reducing expenses, and enhancing patient and healthcare staff safety, particularly during crises like the COVID-19 pandemic. This study contributes to the field by developing a novel system dynamics model that independently predicts chemical waste and provides distinct forecasts for each department. It also estimates costs for hazardous waste disposal in hospitals and assesses alternative scenarios, offering insights into waste creation and management strategies. This study does not investigate the causes of excessive waste generation in specific departments. Future research could explore this aspect and further integrate recycling practices into the model and hospital waste management systems.

Assessing vineyard sustainability through a Water-Energy-Food-Ecosystems Nexus indicator using System Dynamics Modelling

Advancing palm oil sustainability to address the climate crisis: Leveraging theory of change and system dynamics model at the jurisdictional level

Sustainable-circular water resources management in the mining industry using system dynamics modeling

System dynamics modeling and copula-based risk evaluation of the water–energy–carbon nexus

Simulation study on the urban-rural integration circulatory mechanism system in China: Based on system dynamics model and multi-objective genetic algorithm

A system dynamics model of community-based health insurance system in Bangladesh

Development and validation of a system dynamics model for geothermal energy networks

ABSTRACT The urgent need to combat climate change and reduce greenhouse gas emissions underscores the importance of transitioning to renewable energy as a sustainable alternative to fossil‐fuel‐based electricity. This study evaluates a novel financing mechanism for renewable electricity in Iran that leverages profits from the petrochemical industry and carbon tax revenues to support a feed‐in tariff (FIT) model. By reallocating natural gas from inefficient fossil‐fuel power generation to high‐value petrochemical production, the approach enhances economic value, reduces CO₂ emissions, and promotes renewable energy deployment. Iran plans to expand its petrochemical production from 91.5 million tons in 2022 to 183 million tons by 2033, which will drive a 166% increase in demand for fuel and feedstock. Given these resource constraints, integrating renewable electricity into the grid is critical for sustaining industrial growth. System dynamics modeling indicates that carbon tax revenues could reach between $3.8 billion and $37.7 billion by 2033. Meanwhile, the profitability of the petrochemical sector shows wide variability depending on product prices, with a 326% spread between optimistic and pessimistic scenarios. The resulting FIT ranges from 6.24 to 20.29 cents per kilowatt‐hour, with higher carbon taxes being particularly beneficial under low‐price scenarios. This study presents a sustainable, market‐aligned strategy for renewable energy financing that can enhance economic resilience and environmental performance in fossil‐rich nations.

Purpose This paper tries to give a unique standpoint on establishing a system dynamic (SD) model that addresses the real-time problems associated with green human resource management (GHRM) practices and increased environmental performance (IEP). Design/methodology/approach Based on the ability-motivation-opportunity (AMO) theory perspectives, the study applied the system dynamics (SD) method to draw a generic causal loop diagram (CLD) Model to understand the complex and dynamic behavior between GHRM and IEP. Further, the Model structure is validated using quantitative data from 555 executive-level employees of manufacturing industries in India. Findings The study find twelve important loops (ten reinforcing and two balancing) in the Model. Loops R1-10 show reinforcing behavior in the system. However, B1-B2 represents the balancing behavior. The study tries to analyze different loop behaviors in the Model and provide a solution to the problem associated with GHRM and IEP achievement. Practical implications The study contributes to the literature on GHRM and IEP by identifying essential variables that impact the dynamic relationships. Further, the paper attempts to develop a robust model for the stakeholders. Furthermore, the proposed Model will provide guidelines to stakeholders with dynamic questions on how to embrace environmental performance within GHRM practices. Originality/value The paper's findings have presented an exclusive worth to the GHRM and IEP literature as it employs SD methods to understand the complexity and dynamism in the relationships. There is significantly less research on GHRM where the SD approach is applied, particularly in a developing country setting like India.

Abstract Magnetorheological elastomers (MREs) exemplify field-responsive smart materials where tunable damping emerges from magnetic-field-dependent interfacial slippage between carbonyl iron particles (CIP) and multi-walled carbon nanotubes (MWCNT). While critical for adaptive vibration control in reconfigurable robotics and aerospace actuators, current designs correlate component fractions with quasi-static properties-neglecting frequency-dependent interfacial recovery kinetics that govern real-time adaptability in dynamic environments. So, in this research, a fixture-MRE damper-workpiece dynamic model considering contact effect is constructed with generalized Lagrange equation to study the impact of CIP volume fraction and MWCNT mass fraction to the MRE damper’s dynamic character. To exhaustively exploit the model's capabilities, the specific form of the magnetic flux density at any point is derived with Biot-Savart-Laplace theorem and Laplace equation in spherical coordinate. And the transfer function of this system in multi-degree of freedoms with damping effect is carried out. The damping coefficient in this model is identified by tension-compression test. The contributions of both CIP and MWCNT fractions to this dynamic model have been studied; both positively increase the transfer function's peak gains. The dynamic model’s accuracy is verified by comparing the natural frequency with the one collected by the experiment platform constructed in this paper, whose percentage relative errors for natural frequency below 5% in 61 of 64 CIP-based tests and under 6% in 60 of 64 MWCNT cases. All these results indicate the high accuracy of the model constructed in this research, which could be the significantly robust foundation for future real-time magnetic-tuning of damping behavior and 3D-printed graded MREs-advancing SMS’s mission of self-adapting composites in intelligent systems.

The sustainability of ecotourism is the primary concern for the tourism industry. However, sustainability of ecotourism is unresolved issue, in terms of deep analytical for integrated simulation, material-energy flow, and the trends of the process generating constricting ecological and economical positive–negative impacts. In this study, a system dynamic model is developed based on the community's socio-cultural and economic factors, biodiversity, and tourism parameters for sustainable ecotourism of Tasik Kenyir were collected and evaluated. Data on wildlife was extracted from the management authorities. The analysis revealed that the variance portrayed in socio-cultural and economic aspects among the communities is influenced by ecotourism development, and positive contribution of conservation activities, local support for conservation and ecotourism, and upon the distribution of wildlife around Tasik Kenyir. This study contributes towards comprehending the natural resource of the community–ecotourism inter-relationship, besides bridging the knowledge gap that impedes the initiatives taken for biodiversity conservation.

Background: Jute, recognized as the ‘golden fiber’ of Bangladesh, produces a substantial amount of stick left over (waste), a byproduct of the fiber. Usually, unused jute sticks (JS) are thrown away or burned, since they are treated as landfill or unusable waste. Noteworthy research gaps exist in the farming process, infrastructure, [supply chains], unfavorable policies, government interference, and insufficient farmers’ knowledge of the export market. This research examines the potential of jute stick charcoal (JSC) as a sustainable and value-added product within the circular economy framework. Methods: This study employs a system dynamics (SD) modeling approach to examine how various factors, including agricultural output, supply chain process efficiency, trade flows, and relevant variables, influence JSC supply chain performance. Considering technologies, logistics, and policy variables, this study constructed a simulation model with three scenarios: current, worst-case, and improved, using Vensim DSS to identify system behavior under changing conditions. Results: The simulation indicates that optimizing idle jute resources, enhancing supply chain processes, and expanding markets can increase economic returns, reduce waste, and create more rural jobs, particularly for women. Conclusions: Enhanced coordination, technologies, and logistics can reduce carbon emissions, benefit farmers, support rural industries, and contribute to SDGs 8, 12, and 13.

As a vital component of urban transportation systems, subways play a crucial role in the development of a city. However, opportunistic behaviors by subway construction contractors frequently occur, adversely affecting project objectives. This study employs literature review methods to identify six key dimensions that influence the governance of opportunistic behaviors by subway project contractors, thereby constructing a theoretical model of governance factors. Based on this theoretical framework, hypothesis testing and questionnaire design were conducted. Structural Equation Modeling (SEM) path analysis identified construction process management as the direct cause influencing the governance of opportunistic behavior by subway project contractors, exerting a direct effect on such governance. Meanwhile, industry standardization, external oversight mechanisms, project governance quality, contractor credit evaluation, and internal organizational controls within the construction firm were identified as indirect governance factors. A system dynamics model was employed for dynamic simulation analysis of the governance system, revealing the dynamic evolution of opportunistic behavior governance levels under various influencing factors. Scenario simulations identified the pathway, industry standardization → internal controls within the construction organization → project governance quality → construction process management → opportunistic behavior governance, as yielding the lowest frequency of opportunistic behavior occurrence and optimal governance levels. The findings provide a governance basis for addressing the frequent occurrence of opportunistic behavior in subway construction projects.

Abstract This paper introduces a system dynamics (SD) model for analyzing public sector cost growth, where costs are tied to indices. The SD model isolates the effects of automatic indexation, providing probabilistic projections of expenditure growth. It enables testing of alternative indexation strategies and cost‐reduction measures. Findings show how automatic indexation can accelerate spending during inflation spikes, emphasizing the need for risk‐ and uncertainty‐aware fiscal analysis. Using the Finnish welfare system as an illustrative case, the model output is examined in terms of its value for economic policy planning, providing insights for academics and policymakers.

Thailand is a major palm oil producer that serves domestic and international markets. With an increased demand, the need for polymer materials used in palm oil bottle production rises. To achieve efficient production processes and minimize the effects of dynamic changes in the market, effective inventory management is required to ensure smooth production with the lowest total inventory cost. This study utilizes a system dynamic (SD) modeling approach to examine the interrelationships of parameters affecting the total inventory cost of polymer material used in palm oil bottle production. The SD model considers parameters: order quantity, discount price, ordering cost, holding cost, warehouse cost, transportation cost, and product cost. The simulation results indicate that the product cost takes over 95% of the total inventory cost. Taking the biggest discount price with the largest order quantity provides the lowest inventory cost in the long term. The warehouse cost ranks second. By fully utilizing the warehouse space, the total inventory cost is reduced. The sensitivity analysis is performed to confirm the model’s validity and suggest strategies to minimize the total inventory cost in the long term. The results suggest that the companies negotiate with the suppliers to match the best order quantities with suitable prices. The selected order quantities should fully utilize the warehouse space to reduce the total inventory cost in the long term.

A robust organizational culture plays a vital role in upholding nuclear safety and security by shaping individual decision making. Recognizing this significance, international initiatives have focused on fostering nuclear safety and security culture within nuclear facilities. To assess these cultural aspects, various methodologies, including surveys, interviews, document reviews, and observations, have been applied. Nevertheless, the inherent complexity and evolving nature of organizational culture pose challenges in identifying improvement areas and examining policy impacts. This study presents a system dynamics (SD) model to assess nuclear security culture in nuclear facilities that accounts for these cultural dynamics. The proposed SD model is comprised of a causal loop diagram that illustrates feedback loops, such as a policy-work environment, workload-stress, and learning mechanisms, as well as a stock flow diagram that quantifies the dynamic interplay of these elements through stock and flow processes. To empirically validate the hypothesized relationships within the model, survey data from 846 nuclear power plant workers and 10 physical protection experts in the Republic of Korea, collected in 2015, were analyzed. The statistical analysis demonstrated the need for two distinct SD models, one for security personnel and another for nonsecurity personnel, based on the proportion of time allocated to security duties relative to total working hours. To assess the validity of the key model inputs, a comparative analysis using survey data from 2014 and 2015 was conducted. A sensitivity analysis that examined the effects of policy interventions to improve nuclear security culture was conducted using a baseline scenario with no carryover of security knowledge across years. The findings indicated that for nonsecurity personnel, the most effective strategy was to increase security knowledge by shortening the training cycle and enhancing its quality. For security personnel, strategies that focused on enhancing the policy level and increasing the frequency of regulatory actions were the most impactful. The developed SD model provides a quantitative tool to capture dynamic system behaviors, thereby facilitating the analysis of cultural interrelationships and informing more effective policy implementation.

Software supply chains have emerged as a critical battleground in cyberspace security, with their compromise posing direct threats to critical infrastructure and information systems. The inherent multi-level structures and complex interdependencies among supply chain entities have introduced novel challenges in network and information security. This study investigates the contagion mechanisms of information security risks in software supply chains, aiming to identify key factors influencing risk propagation and evaluate effective defense strategies under multi-layer network conditions. We employ system dynamics (SD) modeling to construct a risk contagion framework for software supply chains, incorporating multi-layer network structures. Dynamic simulations are conducted to analyze risk transmission patterns under different attack and defense scenarios. The simulation results show that the risk transmission rate of software supply chain information security is influenced by the attack path. As compared to random attacks, selective attacks result in a faster risk transmission. In terms of defense strategy, increasing information security investment and improving the level of software quality are more effective for defense against random attacks. In terms of governance measures, increasing technological progress is more effective as compared to reducing the vulnerability rate. The results show that the marginal benefits of the technological progress rate show a decreasing trend. The study quantitatively validates the cascading effects of security risks in multi-layer supply chain networks and provides actionable insights and establishes a system dynamics foundation for predictive risk assessment in complex software supply chain ecosystems.

ABSTRACT Decarbonising its extensive, fossil-fuel-reliant maritime sector is crucial for Indonesia, which seeks to balance economic growth with its role in global climate change mitigation. This study uses a detailed System Dynamics (SD) model to evaluate the long-term effectiveness of diverse decarbonisation strategies by assessing their impact on economic and environmental dimensions within the Indonesian marine sector. We compared three policy pathways: continuing current practices (Business as Usual), a gross tonnage (GT) ship policy, and a carbon emission regulation framework utilising tokens. Findings identify the Carbon Token approach as the most promising for long-term sustainability, projecting an over 92% emission cut by 2045 alongside significant financial gains. GT-based policies offer short-term economic boosts but risk environmental compromise. We recommend integrated, sustainable policies to guide Indonesia towards an economically sound, ecologically responsible, low-carbon maritime future. A green shipping transition is possible and beneficial.