Search Results (60)

To achieve regional sustainable development, the low-carbon transformation of agriculture is essential, as it serves both as a significant carbon source and as a potential carbon sink. This study calculated the agricultural carbon emissions in Liaocheng from 2010 to 2022 by analyzing processes including crop cultivation, animal husbandry, and agricultural input. Additionally, a simulation model of the water–energy–food–carbon nexus (WEFC-Nexus) for Liaocheng’s agricultural production process was developed. Using Vensim PLE 10.0.0 software, this study constructed a WEFC-Nexus model encompassing four major subsystems: economic development, agricultural production, agricultural inputs, and water use. The model explored four policy scenarios: business-as-usual scenario (S1), ideal agricultural development (S2), strengthening agricultural investment (S3), and reducing agricultural input costs (S4). It also forecast the trends in carbon emissions and primary sector GDP under these different scenarios from 2023 to 2030. The conclusions were as follows: (1) Total agricultural carbon emissions exhibited a three-phase trajectory, namely, “rapid growth (2010–2014)–sharp decline (2015–2020)–gradual rebound (2021–2022)”, with sectoral contributions ranked as livestock farming (50%) > agricultural inputs (27%) > crop cultivation (23%). (2) The carbon emissions per unit of primary sector GDP (CEAG) for S2, S3, and S4 decreased by 8.86%, 5.79%, and 7.72%, respectively, compared to S1. The relationship between the carbon emissions under the four scenarios is S3 > S1 > S2 > S4. The relationship between the four scenarios in the primary sector GDP is S3 > S2 > S4 > S1. S2 can both control carbon emissions and achieve growth in primary industry output. Policy recommendations emphasize reducing chemical fertilizer use, optimizing livestock management, enhancing agricultural technology efficiency, and adjusting agricultural structures to balance economic development with environmental sustainability. Full article

The objective of this paper is to examine the game-theoretic relationship between local governments and coal mining enterprises with regard to the issue of coal mine intelligent construction. Firstly, this paper employs prospect theory to construct the value perception function and the decision weight function, which are then used to optimize the parameters of the traditional income matrix. The equilibrium point is then analyzed for stability under different conditions. Subsequently, Vensim PLE and MATLAB simulation software are employed to substantiate the impact of spillover penalties and associated parameters on the value perception equilibrium of the two parties. The results of the simulation demonstrate that, in addition to the initial strategy selected, the spillover penalty exerts a considerable inhibitory effect on the process of enterprise intelligence construction. Secondly, from the perspective of value perception, the lower the costs to enterprises of carrying out intelligent construction in terms of labor and mental effort, the more enterprises are inclined to engage in this construction. The higher the costs to enterprises of complying with strict government regulation, and the lower the costs to enterprises of deregulation, the more the government can govern by non-interference. Finally, the behavioral trends of local government departments are also correlated with additional revenue they receive from firms and the factor of fines linked to government performance. Full article

Incentive policies for prefabricated buildings (PBIP) can effectively promote the development of prefabricated buildings (PB) and improve the sustainability of the construction industry, attracting increasing attention from academia and industry. The government has issued many PBIPs (including land policy, plot ratio reward policy, fund policy, financial support policy, preferential tax policy, research and development support policy, and construction process management policy) but the implementation effect of PBIP remains to be clarified, especially regarding the research gap from a dynamic perspective. This study proposes an analytical framework of policy implementation effect based on the chain of “policy text content–policy impact path–policy implementation effect”, aiming to analyze the implementation stage and effect of PBIPs using the system theory analysis method. Combining the main factors affecting the PBIP impact system, a quantitative model containing 50 variables is established based on the system dynamics (SD) model. Finally, using Shenyang, one of China’s first PB pilot cities, as an example, the system simulation and sensitivity analysis of main parameters are carried out in Vensim software. The research results indicate that PBIP in Shenyang has not been fully utilized and targeted improvements and strengthened implementation of PBIP are needed. In the simulation of individual policies, the implementation effect of fund policy is the best, and the impact of research and development support policy on carbon reduction is the most significant. The promotional effect of the policy combination on PB development is more prominent. Using the policy combination reasonably is necessary to leverage the incentive effect fully. Simulation and sensitivity analysis results provide valuable insights for government departments to enhance the implementation effectiveness of the existing PBIP. This study responds to the global trend of promoting sustainable building development. It proposes a new framework for systematically analyzing the implementation effects of PBIPs, filling the research gap in policy evaluation from a dynamic perspective. Its methods and findings are not only applicable to the Chinese context but also provide valuable experience for other countries to develop and optimize PBIPs. Full article

This study aims to evaluate various waste-to-energy conversion scenarios in terms of their potential to reduce greenhouse gas (GHG) emissions and improve sustainability based on economic and environmental outcomes. To achieve this, a comprehensive waste management model was developed using the system dynamics approach in the Vensim software to predict waste generation and composition and compare pyrolysis, incineration, gasification, and sanitary landfill scenarios with the baseline scenario over 25 years (2025–2050). The analysis of different waste management scenarios highlights the superior performance of pyrolysis in terms of energy recovery, economic profit, GHG emissions reduction, environmental outcomes, and long-term sustainability. Results show that the pyrolysis scenario generates the highest electricity, with a cumulative net electricity output of 10,469 GWh. Although pyrolysis has GHG emissions due to energy consumption and direct process emissions, it results in the largest net reduction in GHG emissions, primarily due to avoided emissions from increased electricity generation, leading to a 346% reduction compared to the baseline scenario. Furthermore, the pyrolysis scenario demonstrates the highest economic profit at 354 million USD and the highest sustainability index (SI) at 499 million USD. The cumulative SI from 2025 to 2050 shows a 503% increase compared to the business-as-usual scenario, highlighting its superior sustainability performance. This study highlights the importance of strategic waste-to-energy planning in reducing GHG emissions and promoting sustainability. It also offers valuable insights for policymakers and researchers, supporting the development of sustainable waste management strategies and effective efforts for climate change mitigation. Full article

Based on the perspective of an innovation ecosystem, the system dynamics research method is used to construct a technological innovation ecosystem model of autonomous vehicles in China. Vensim PLE software was used for simulation to obtain the development trend of technological innovation from 2015 to 2030 and to explore the impact of various elements inside the system on the overall system. This research finds that the dynamic mechanism of China’s autonomous vehicle technology innovation ecosystem mainly includes the innovation resource supply subsystem, the technology innovation diffusion subsystem, and the incentive and guarantee subsystem. Each subsystem interacts to jointly promote continuous innovation and iterative upgrading of technology. Education investment, infrastructure construction, innovation platform construction, and other factors all have a positive impact on the technological innovation level of autonomous vehicles, and the effect of multiple parameter changes is far more significant than that of single factor changes. The number of research and development patents, level of technological innovation, actual adopters of technological innovation, and benefits of technological innovation are all showing a good growth trend in the future. Accordingly, it is concluded that there should be optimization of scientific research investment strategies, acceleration of infrastructure layout, and expansion of application scenarios. These insights provide a theoretical basis and practical guidance for promoting the high-quality development of autonomous vehicle technology in China. Full article

With the rapid growth of global energy demand, the fossil fuel-dominated electric power industry has led to serious environmental problems. Tradable green certificates (TGC) and carbon emission trading (CET) have become key mechanisms for promoting sustainable development of the electricity market by serving as market-oriented policy tools. To deeply analyze the impact of TGC and CET on the sustainable development of China’s electricity market and provide a scientific basis for policymakers. This study uses system dynamics (SD) methods to construct a policy synergy analysis framework for TGC and CET. It explores the impact mechanism of dual policy incentives on the sustainable development of the electricity market. Firstly, the current application status of TGC and CET in China was reviewed. Based on the literature analysis, identify key factors that affect the sustainable development of the electricity market. Then, by deconstructing the interaction between TGC policy and CET policy, an SD model was established that includes multidimensional feedback such as policy, technology, funding, and market, and the dynamic functional relationships in the SD model were quantified. Finally, Vensim PLE software 7.3.2 was used to simulate the evolution of sustainable development in the electricity market under different policy scenarios. The research results indicate that (1) the adjustment of the TGC quota ratio can change the supply and demand mechanism to form a price leverage effect, effectively stimulate the growth of renewable energy generation capacity, and accelerate the low-carbon transformation of power enterprises; and (2) the CET market changes the cost structure of power generation through carbon price signals. When the carbon emission cap target tightens, CET prices quickly rise, leading to a significant trend of carbon reduction in the electricity market; (3) the application of policy combinations can significantly promote the sustainable development of the electricity market, but the unreasonable setting of policy parameters can trigger market risks. Therefore, policy design should focus on flexibility and implement appropriate policy combinations at different stages of electricity market development to promote green transformation while ensuring smooth market operation. This study innovatively reveals the synergistic effect of TGC and CET in the sustainable development of the electricity market from a systems theory perspective. The research results provide a scientific basis for decision-makers to formulate policy adjustment plans and have essential reference value for achieving the dual goals of energy structure transformation and electricity market stability. Full article

The advantages of green roofs and solar panels are numerous, but in dry periods, green roofs can place urban water resources under pressure, and the efficiency of solar panels can be affected negatively by high temperatures. In this context, our analysis investigated the advantages of bio-solar green roofs and evaluated the impact of green roofs on solar panel electricity production and solar panels on green roof water consumption. The assessment was conducted through simulation in a selected case study located in Cosenza, a city with a Mediterranean climate, with solar panels covering 10% to 60% of the green roof. Analyses were performed on the power outputs of four kinds of photovoltaic panels: polycrystalline, monocrystalline, bifacial, and Passivated Emitter and Rear Contact (PERC). The energy production and shade frequencies were simulated using PVGIS 5.3 and PVSOL 2024 R3. The impact of photovoltaic (PV) shade on the water consumption of green roofs was evaluated by image processing of a developed code in MATLAB R2024b. Moreover, water–energy interconnections in bio-solar green roof systems were assessed using the developed dynamic model in Vensim PLE 10.2.1. The results revealed that the water consumption by the green roof was reduced by 30.8% with a bio-solar coverage area of 60%. However, the electricity production by the PV panel was enhanced by about 4% with bio-solar green roofs and was at its maximum at a coverage rate of 50%. This investigation demonstrates the benefits of bio-solar green roofs, which can generate more electricity and require less irrigation. Full article

Prefabricated building construction is a crucial approach to achieving “green” building goals, yet it differs significantly from traditional cast-in-place construction methods. Due to complex cross-operations, high mechanization requirements, insufficient worker experience, and inadequate safety measures, prefabricated construction faces greater safety management challenges than traditional methods. This study identifies 17 key indicators influencing unsafe behaviors among prefabricated building construction workers across four dimensions: physical environment, individual factors, team factors, and safety management. A combined weighting method, integrating the entropy weight method and the coefficient of variation method, was employed to determine the weight of each factor. Based on the weight analysis results, a system dynamics intervention model for unsafe behaviors of prefabricated building construction workers was developed and simulated using the Vensim platform. The results indicate that, among single intervention measures, improving individual comprehensive skills has the most significant effect, reducing unsafe behaviors by 37.78%, though this still falls short of the desired target. In contrast, combined interventions yield superior outcomes, with reductions of 68.87% for individual factor interventions, 59.93% for safety management interventions, 46.32% for team factor interventions, and 20.71% for physical environment interventions. These findings highlight the significant advantages of combined interventions. Based on the study results and the characteristics of prefabricated construction, this paper proposes specific intervention strategies, emphasizing the importance of training and institutional development to systematically enhance workers’ safety behaviors. Full article

Previous studies have focused on the fact that government policies are the key factors in promoting the development of intelligent construction in construction enterprises. However, how to select different forms of policy support and quantify the intensity of policy support, as well as the impact on the behavioral strategies of construction enterprises and the government, still needs in-depth exploration. This paper constructs an evolutionary game model between construction companies and the government, using the system dynamics simulation software Vensim to analyze the model under three different government policy support scenarios. The study explores how varying levels of policy support and key factors influence the strategic choices of the game participants, providing valuable insights for promoting the development of intelligent construction. The key findings are as follows: (1) The willingness to adopt intelligent construction is heavily dependent on policy incentives. The incentive effect of the three single policies is much lower than that of the combined policies, and only high-intensity special fund support (more than 8 CNY/m²) significantly promotes widespread adoption. Among combinations of policies, tax incentives coupled with special funds prove most effective. (2) The government’s decision to actively promote intelligent construction hinges on a cost–benefit analysis. Under medium to high levels of special fund support, medium to low levels of service support are more beneficial for reaching a stable state of intelligent construction implementation. (3) Reducing the incremental costs of intelligent construction transformation is the primary key factor in promoting construction. The findings contribute to a deeper understanding of how both the government and construction companies can adjust their strategies in response to policy changes, ultimately leading to more effective policy implementation and strategic decision-making. Full article

This paper aims to assess the impact of the New Energy Vehicle (NEV) mandate policy on the passenger vehicle market in China, with a focus on its effectiveness in promoting NEV adoption. In response to global climate goals and energy security concerns, China has implemented various NEV policies, including the phase-out of direct subsidies and the introduction of the NEV mandate policy (dual-credits policy). This policy, which combines NEV credits and Corporate Average Fuel Consumption (CAFC) credits, aims not only to promote NEV adoption but also to support industrial policy objectives by helping the auto industry leapfrog traditional internal combustion engines and become globally competitive. In this study, a System Dynamics (SD) model was developed using Vensim software (10.2.2) to simulate interactions between automakers, government policies, and consumer behaviors. The results show that the NEV mandate policy significantly boosts NEV sales, with projections indicating that NEV sales will reach 15 million units by 2030, accounting for 55% of the passenger vehicle market. Additionally, the study finds that tightening NEV credits standards and increasing the NEV credit proportion requirements can further enhance market growth, with stricter measures post-2023 being crucial to achieving a 50% market share. In contrast, under a scenario where the dual-credits policy ends in 2024, the NEV market share would still grow but would fall short of the 50% target by 2030. The findings suggest that stronger policy measures will be essential to maintain long-term market momentum. Full article

Grasping the effective carrying capacity of airport hub subway stations in real-time serves as the foundation for enhancing the safety assurance capability of the hub. Starting from the perspectives of multiple subsystems, including people, stations, and trains, and combining passenger flow, system structure, and multiple attributes of trains, a system dynamics (SD) model for passenger travel in airport hub subway stations is established. The model is simulated using Vensim PLE 5.9d to analyze the effective carrying capacity of the transfer system under the existing configuration and layout of transfer facilities and equipment in the hub. The model features a modular architecture and interface, enabling quick and easy model establishment, and adapts to various configurations and operational characteristics of airport hub subway stations in a user-friendly manner. Multiple sensitivity simulation analysis experiments are designed to analyze changes in passenger flow density from multiple perspectives. This method can calculate the effective carrying capacity of airport hub subway stations, providing a scientific basis for planning, construction, and operational management. The effectiveness of the model is verified by analyzing the Pudong International Airport terminal subway station. Full article

As a clean energy source, shale gas plays a crucial role in mitigating the supply–demand imbalance of natural gas and in facilitating the transition to a low-carbon economy. This study employs a system dynamics model to forecast future production trends in shale gas in China, analyze its implications for the natural gas supply–demand structure, and explore pathways for sustainable development. Firstly, by integrating the characteristics of China’s shale gas resources, market dynamics, and policy frameworks, the key factors influencing production are identified, and their interrelationships are systematically analyzed. Subsequently, a causal loop diagram is constructed using the VENSIM software(VENSIM PLE 9.3.5 x64), a set of representative variables is selected, and the logical relationships among these variables are established through a multivariate statistical analysis, culminating in the development of a production forecasting model for China’s shale gas (stock and flow diagram). Finally, based on parameter assumptions, this study predicts the production trends in shale gas in China under multiple scenarios. The forecasting results reveal that China’s shale gas production is expected to grow at an average annual rate of 3.32% to 8.02%, with production under the reference scenario projected to reach 724.22 × 10⁸ m³ by 2040. However, the growth of shale gas production over the next two decades remains limited, accounting for a maximum of 12.07% of the total natural gas consumption, underscoring its transitional role in the low-carbon transformation. To address these challenges, this study proposes four policy recommendations: (1) prioritize the development of shallow, high-quality gas-bearing blocks while gradually transitioning to deeper formations; (2) intensify technological innovation in deep shale gas extraction to enhance recovery rates and mitigate production decline rates; (3) implement flexible production subsidies and moderately increase natural gas sales prices to incentivize production and optimize resource allocation; and (4) strengthen ecological conservation and improve water resource management to ensure the sustainable development of shale gas. Full article

Objective: The study aims to investigate the impact of patient-centric approaches on patient health outcomes, identify key leverage points for enhancing patient-centered care, and evaluate the effectiveness of systems thinking in guiding healthcare transformations. Methods and Procedures: The research utilizes system dynamics methodology, combining qualitative and quantitative data with causal loop diagrams and simulation models. Using Vensim software, the study examines dynamic interactions, feedback loops, and the effects of patient-centric interventions. Sensitivity analysis assesses the impact of variables such as access to healthcare improvements, and social determinants of health (SDOH), providing insights into the systemic behaviors of healthcare models. Results: Simulation analyses demonstrate the effectiveness of patient-centric interventions in improving engagement, satisfaction, communication, and health outcomes. Key leverage points, such as enhanced patient–provider communication and addressing SDOH, are critical for driving sustainable improvements. However, declining trends in outcomes over time indicate the need for adaptive strategies to maintain effectiveness. Conclusions: The study emphasizes the importance of maintaining patient centricity in healthcare settings. By leveraging systems thinking and addressing underlying factors such as SDOH, the research provides actionable insights to enhance care delivery and patient outcomes. Despite the limitations of simulated data, the findings contribute to understanding the dynamic interplay between patient-centric strategies and healthcare system performance, advocating for sustained efforts to ensure equitable and effective care. Full article

The Northern Gulf of Mexico hosts a severe dead zone, an oxygen-depleted area spanning 1,618,000 hectares, threatening over 40% of the U.S. fishing industry and causing annual losses of USD 82 million. Using a System Dynamics (SD) approach, this study examined the Mississippi–Atchafalaya River Basin (MARB), a major contributor to hypoxia in the Gulf. A dynamic model, developed with Vensim software version 10.2.1 andexisting data, represented the physical, biological, and chemical processes leading to eutrophication and simulated dead zone formation over time. Various policies were assessed, considering natural system variability. The findings showed that focusing solely on nitrogen control reduced the dead zone but required greater intensity or managing other inputs to meet environmental goals. Runoff control policies delayed nutrient discharge but did not significantly alter long-term outcomes. Extreme condition tests highlighted the critical role of runoff dynamics, dependent on nitrogen load relative to flow volume from upstream. The model suggests interventions should not just reduce eutrophication inputs but enhance factors slowing down the process, allowing natural denitrification to override anthropogenic nitrification. Full article

This research takes the construction companies and supervision units of megaprojects as the research objects and studies safety issues in construction decision-making for megaprojects. Using evolutionary game theory, we construct an evolutionary game model of safety decision-making behavior for construction companies and supervision units based on the bounded rationality assumption. The interaction and dynamic patterns of safety behaviors between the two construction entities are analyzed. Additionally, system dynamics Vensim PLE 10.2.1 software is employed to simulate and analyze the behavior of single entities as well as the impact of exogenous variables on the safety decision-making choices of both units. The research results indicate that positive choices in safety behavior decision-making contribute to enhancing the stability of megaproject construction. Exogenous variables significantly influence the safety behavior decisions of both the construction companies and the supervision units in megaprojects. An increase in cooperation benefits between the two parties fosters their active collaboration in completing mega engineering projects. This research promotes cooperation between construction companies and supervision units during a construction process and provides a reference for the safe and orderly implementation and development of megaprojects. Full article