System Dynamics Modelling Approach Research Articles

A system dynamics approach to management of water resources in Qatar

Rapid global population growth and extensive urbanization threaten water sustainability, hindering sustainable development. This issue is particularly acute in arid regions such as the Gulf Cooperation Council (GCC), where the scarce natural water resources are overexploited. Effective water resource management (WRM) is pivotal in overcoming this challenge. This holistic study presents an innovative approach to address water sustainability at a national scale by developing a WRM decision support system (DSS) leveraging system dynamics modeling (SDM). Employing a unique scenario design framework developed in this study, the DSS simulates Qatar's water resource system behavior for 2021 to 2070 according to nine clustered policy scenarios presenting different degrees of sustainability designed accounting for changes in physical, environmental, and socioeconomic patterns. Our results reveal that the “business-as-usual” (BAU) WRM policy can balance water supply and demand for only 32 years. According to the best policy scenario, the sustainability of the water supply could be ensured for up to 50 years by increasing the water supply by 10 % and reducing consumption by 10 %. Additionally, to aid policymakers in fostering water resource sustainability, groundwater conservation strategies are proposed using the unique scenario design framework by limiting the yield to the safe abstraction level and emphasizing the significance of preserving non-renewable groundwater resources as a “backstop” resource for the country. While marking the first holistic research study in Qatar by utilizing the SDM approach to tackle national-scale WRM challenges, the established WRM DSS model is equally applicable to other GCC countries and similar arid regions.

Climate Change-Related Disaster Risk Mitigation through Innovative Insurance Mechanism: A System Dynamics Model Application for a Case Study in Latvia

This study explores how the System Dynamics modeling approach can help deal with the problem of conventional insurance mechanisms by studying the feedback loops governing complex systems connected to the disaster insurance mechanism. Instead of addressing the disaster’s underlying risk, the traditional disaster insurance strategy largely focuses on providing financial security for asset recovery after a disaster. This constraint becomes especially concerning as the threat of climate-related disasters grows since it may result in rising long-term damage expenditures. A new insurance mechanism is suggested as a solution to this problem to lower damage costs while safeguarding insured assets and luring new assets to be protected. A local case study utilizing a System Dynamics stock and flow model is created and validated by examining the model’s structure, sensitivity analysis, and extreme value test. The results of the case study performed on a city in Latvia highlight the significance of effective disaster risk reduction strategies applied within the innovative insurance mechanism in lowering overall disaster costs. The logical coherence seen throughout the analysis of simulated scenario results strengthens the established model’s plausibility. The case study’s findings support the innovative insurance mechanism’s dynamic hypothesis and show the main influencing factors on the dynamics within the proposed innovative insurance mechanism. The information this study can help insurance firms, policy planners, and disaster risk managers make decisions that will benefit local communities and other stakeholders regarding climate-related disaster risk mitigation.

Current status of environmental water quality of Kappaphycus alvarezii seaweed cultivation in the Seribu Islands, Indonesia and the concept of sustainable development by using a System Dynamic Model approach

The aim of this research is to analyze the current status of water quality in seaweed cultivation environments related to the decline in seaweed production. Field research was conducted in the Seribu Islands Regency, DKI Jakarta, during April and May 2023. The analysis of environmental factors encompassed physical, chemical, and biological parameters at 12 designated sampling points. The results of the analysis of water quality parameters generally meet the requirements, except for oil and grease at 7-51 mg/L and nitrate at 1.60-6.3 mg/L, both of which exceed the quality standards for biota. Plankton analysis shows the total abundance of plankton reaches 36 to 9,070 ind/L. Evaluation of the suitability class shows that the waters are in class S (Suitable). The Pollution Index value ranges from 6.51 to 8.05, indicating a fairly polluted status. The high levels of oil and grease, nitrate, and the presence of index pollutants have a significant influence on the decline in seaweed production in the Seribu Islands Regency. The preparation of improvement strategies can be conducted using a System Dynamics Model approach, involving the creation of comprehensive Causal Loop Diagrams. This process considers four key factors: environmental water quality, human resources, technology, and seaweed.

Dynamic Modelling of Data Center Waste Heat Potential Integration in District Heating in Latvia

As demand for data centers (DC) has increased rapidly, so has their electricity consumption. Cooling DCs is essential to maintain optimal temperatures for the operation of servers and equipment. The consequence of the cooling process is that most of the electricity consumed in DCs, including cooling, is eventually dissipated as heat that is released into the atmosphere without any useful application. Recovering and reusing waste heat offers a sustainable solution to reduce primary energy consumption and minimize the environmental impact. Using waste heat from DCs to heat buildings can significantly improve the energy efficiency and environmental sustainability of DCs. Therefore, this research analyzes the existing potential of waste heat recovery from data centers in Latvia and proposes a system dynamic modelling approach for evaluation of the future impact of waste heat on the national heat supply. The overall waste heat generated by DCs in 2022 was 51.37 GWh at a temperature of 65 °C. By 2050, the total heat energy production potential from DCs will increase to 257 GWh, with 201 GWh being utilized.

A participatory systems dynamic modelling approach to understanding flood systems in a coastal community in Cameroon

In the face of increasing flood risks and the need for effective management both at national and local levels, this study highlights a participatory approach that transcends conventional stakeholder consultation but delves into drawing insights through conceptual models that unveil the potential of the Participatory System Dynamic Modelling approach to mitigate flood risks, even at the grassroots level effectively. Through active stakeholder engagement, the study focuses on identifying and analysing the intricate interdependencies and feedback loops within the Limbe flood risk management system that are crucial for recommending comprehensive and actionable flood risk mitigation strategies for Limbe's cross-sectoral dynamics. By including flood experts and community stakeholders in the conceptual model construction, the study utilises an evaluative framework that accounts for system processes and outcomes, ensuring a holistic understanding of the flood risk system, considering scientific knowledge and real-life experiences. The findings underscore the value of participatory modelling techniques in facilitating the identification and prioritisation of intervention options by diverse stakeholders, thereby promoting active engagement in local flood risk management, a vital step in addressing the escalating challenges posed by climate change and natural disasters.

Water pollution generated by tourism: Review of system dynamics models

This study delves into the intricate dynamics of tourism-induced water pollution through a systematic literature review, aiming to unravel complexities using a system dynamics (SD) modeling approach coupled with the PRISMA analysis methodology. Employing a comprehensive PRISMA analysis of 68 pertinent articles, the study establishes a metamodel for comprehending plastic pollution in water ecosystems resulting from tourism. The methodology emphasizes economic and environmental dimensions, causal conditions, and interventions, with a specific focus on the role of Information and Communication Technology (ICT). The results highlight integrated strategies as crucial in mitigating tourism-induced water pollution. These strategies advocate for the incorporation of environmental conservation and sustainable management practices. The study underlines the pivotal role of environmental education, awareness, and investments in protection as effective interventions. The findings offer valuable insights for policymakers and stakeholders in the tourism industry, emphasizing the necessity for proactive planning and management. The study advocates for knowledge-based decision-making to optimize tourism's environmental impacts and underscores the significance of quick and flexible responses to environmental challenges.

Model Penawaran Dan Permintaan Bawang Putih Indonesia: Pendekatan Sistem Dinamik

There is a reasonably high gap between the ability to supply garlic and demand that requires the government to carry out a garlic import policy to meet domestic needs. The high dependency on imported garlic supplies has caused garlic imports to increase. This study aims to analyze the supply and demand model for garlic and formulate policy recommendations regarding the supply and demand for Indonesian garlic using system dynamics model approach. The model in this study is simulated for the next 12 years (2022-2033). Based on the model simulation results, in the base conditions (before the scenario was implemented), the behavior pattern of garlic availability was goal-seeking. At the same time, demand had an exponential growth behavior pattern, and supply had an increasing trend. In 2033, it is estimated that the availability of garlic will experience a deficit, and garlic production and total farmers' income will continue to decline. Therefore, policies are needed to increase garlic farmers' availability, production, and total income in Indonesia through several policy scenarios. The policy scenario with the best results is a combination of an increase in area, productivity, and the realization of mandatory planting by importers because it can produce the highest availability and production of garlic compared to other scenarios. The most sensitive variable to the availability of Indonesian garlic is mandatory planting. Each increase in the realization of mandatory planting by importers by 10 percent can increase the availability of Indonesian garlic by 4.7 percent.

Environmental Assessment of Demolition Tools Used in Townhouse Demolition: System Dynamics Modeling

To accommodate population growth and migration to cities, many infrastructures have been demolished to build new residential units. Demolition processes cause various environmental problems globally and locally. The selection of methods used in demolition is crucial to reduce the long-term environmental impact. This study considers various combination tools used in townhouse demolition in Thailand, examines their environmental impacts, and suggests the combination of the tools to be used in the long term. The system dynamics (SD) modeling approach is utilized in this study to capture the changes in townhouse units, sizes, demolition tools, demolition time, and the work rates of tools and their effects on the environment. This approach has the capability to model complex relationships and examine long-term trends. Secondary data are employed to identify variables necessary for SD model development, such as the different sizes of townhouses in Thailand, the various types of demolition tools used in the construction industry, and environmental impacts from building demolition. The simulation results revealed that Combination 4, i.e., the use of demolition robots and hydraulic splitters, is the most effective combination to reduce the final impact percentage in the long term. Compared with the other three combinations, it generates the lowest CO2eq emissions, energy consumption, noise, dust, and heat. If demolition robots are not yet available, Combination 1 (i.e., the use of excavators, jackhammers, and flame-cutters) offers the lowest environmental impact in the long term. This study provides guidelines for decision-makers in the construction industry to make sustainable choices of demolition tools and techniques used for townhouse demolition to reduce long-term environmental impacts.

Assessing The Public Trust in The Indonesian National Police: A System Dynamics Model Approach

The importance of public trust in the police cannot be overstated, as it underpins social order, public safety, and the rule of law. Nevertheless, INP is facing its most difficult challenge yet after some senior police officers were involved in premeditated murder and drug trafficking. Therefore, it is necessary to provide an evaluation to improve public trust in the Indonesian National Police. This study aims to analyze the sustainability framework for enhancing public trust in the Indonesian National Police (INP). This research uses a descriptive statistical, qualitative approach with system dynamics modeling. The research was conducted between February to May 2023 with eight experts, including academicians and practitioners. The study findings project that INP public trust has a value of 3.567. Based on the scenario predicting 3.575 in 2027, indicating a medium trust status (level 3). However, there will be a slight decline in INP public trust from 2022 to 2025, followed by a gradual increase from 2025 to 2027, remaining within the medium trust range of 3.558. The repairing of public trust in INP is influenced by various dynamic and uncertain internal and external factors. Despite efforts to improve responsiveness, trustworthiness, and empathy, there is no significant positive trend observed in INP public trust, with only a marginal increase from 3.557 to 3.558 in medium trust level. Thus, the need to implement an accelerated strategy to improve trust becomes very important.

Examining the Chinese mobile phone industry in the reverse supply chains

This research aims to develop a simulation model for the Chinese mobile phone industry's reverse supply chain and analyses the effects of the trade-in program and the government subsidy on the system’s behaviour. We adopt a system dynamics (SD) modelling approach, an excellent tool for studying dynamic processes in which new decisions have to be made, and new policies appear. Key factors and their relationships are identified through literature review and observation. The research outcomes conclude that the trade-in program and the government subsidy have different effects on the system behaviour when collectors compete by taking different acquisition and recycling strategies. The former has a significantly positive impact on the formal recycling industry's economic performance, while the latter has a critical influence on alleviating the problem of uncontrollable disposal. The original primary contribution is to offer an observation and a comparison regarding the possible effects of the trade-in program and government subsidy on a reverse supply chain in the mobile phone industry when a competitive collection is involved.

Carbon Sequestration Potential of Biomass-Based Products: A System Dynamics Modeling Approach for Grassland Management

It is known that forests are significant carbon storage, as well as harvested wood products. Both sectors are included in the national greenhouse gas inventories. When wood or other types of biomass grow, it absorbs carbon dioxide through photosynthesis. If biomass is used in the production of new products, the carbon stored in them is effectively removed from the atmosphere and held in the product. Carbon stored in products is considered temporary because the products eventually will burn or decompose and release carbon dioxide back into the atmosphere. However, when products are used for long-lasting applications, the carbon stored in them can remain sequestered for many decades, which can significantly contribute to climate change mitigation. If it is possible to store carbon in wood products, the question arises as to whether it is also possible to promote carbon sequestration in products with other types of biomass. In this work perennial biomass was analyzed. It is a product of semi-natural grasslands, where grass cutting is necessary, which produces grass biomass that is often not fully used. A literature analysis was performed to select suitable products with different carbon storage periods and minimal production emissions, such as those made from biorefining, boards for packaging or building materials, and biochar for soil carbon sequestration. A system dynamics model was developed to estimate carbon stocks and flows between atmosphere, living biomass and products. The base scenario is modeled according to carbon flows in grasslands according to IPCC guidelines – grasslands are net carbon sources and the carbon concentration in the atmosphere only increases. The addition of a product-manufacturing scenario decreases the carbon concentration in the atmosphere.

Sustainability Assessment and Benchmarking Framework for Buildings Using a System Dynamics Modeling and Simulation Approach

Sustainability Assessment and Benchmarking Framework for Buildings Using a System Dynamics Modeling and Simulation Approach

Projecting the Electricity Demand of the Residential Sector in Thailand During and After the COVID-19 Pandemic

The residential sector in Thailand has been a fast-growing energy consumption sector since 1995 at a rate of 6% per year. This sector makes a significant contribution to Thailand’s rising electricity demand especially during the COVID-19 pandemic. This study projects Thailand’s residential electricity consumption characteristics and the factors affecting the growth of electricity consumption using a system dynamics (SD) modeling approach to forecast long-term electricity consumption in Thailand. Furthermore, the COVID-19 pandemic and the lockdown can be seen as a forced social experiment, with the findings demonstrating how to use resources under particular circumstances. Four key factors affecting the electricity demand used in the SD model development include (1) work and study from home, (2) socio-demographic, (3) temperature changing, and (4) rise of GDP. Secondary and primary data, through questionnaire survey method, were used as data input for the model. The simulation results reveal that changing behavior on higher-wattage appliances has huge impacts on overall electricity consumption. The pressure to work and study at home contributes to rises of electricity consumption in the residential sector during and after COVID-19 pandemic. The government and related agencies may use the study results to plan for the electricity supply in the long term.

A dynamic probabilistic risk assessment platform for nuclear power plants under single and concurrent transients

ABSTRACT Dynamic probabilistic risk assessment (DPRA) of nuclear power plants (NPPs) has become one of the most critical research areas, especially in the aftermath of the 2011 Fukushima Daiichi nuclear accident. Uncertainty in NPP behavior is key when considering its safety under different operating conditions. Such uncertainty typically results from operation parameters, system conditions, and modeling assumptions. This study integrates the system dynamics (SD) modelling approach with an uncertainty analysis method to quantify the dynamic probabilistic risk in NPPs. To demonstrate the approach’s applicability, the average fuel temperature is used to estimate the probability of reactor core damage under different transients, representing perturbations in reactivity and steam valve coefficient. A Monte Carlo simulation is employed to investigate the effect of uncertainties associated with the different model parameters. A global sensitivity analysis demonstrates that the total delayed neutron fraction, the heat transfer coefficient from fuel to coolant, the coolant temperature coefficient of reactivity, and the fuel temperature coefficient of reactivity are the primary controllers of the plant response variability under the transients considered. In summary, the integration of SD modelling and uncertainty analysis presents an effective DPRA approach that overcomes the limitations of static counterparts while minimizing the computational resources required.

The sustainability of Jatropha biodiesel production in Southwest China

Biodiesel is an ideal alternative to fossil fuels. To ensure sustainable development, the Chinese government and relevant market entities have conducted in-depth research and production practices on Jatropha biodiesel Southwest China for over a decade. However, few integrated and dynamic assessments of the sustainability of biodiesel projects have been conducted. Therefore, in this study, we constructed an integrated sustainability evaluation system (ISES) for Jatropha biodiesel projects, that applies the inclusive wealth (IW) and system dynamics (SD) modeling approach to analyze the integrated sustainability of Jatropha biodiesel projects. The results showed that: (1) the launch of the Jatropha biofuel project increased the IW by 826 million yuan; (2) the inclusive investment that represents the sustainability trends of the project was commonly positive, and the IW at the end of the project accumulated to about 29 billion yuan; and (3) the sensitivity analysis showed that the stable unit output and biodiesel output rate have a sensitive positive effect on inclusive investment. Finally, policy recommendations to promote the sustainable development of biodiesel production are proposed.

Mathematical Modelling of Combined Intervention Strategies for the Management and Control of Plasma Glucose of a Diabetes Mellitus Patient: A System Dynamic Modelling Approach

With the rapid increase of diabetes mellitus cases in the world, management and control of the disease has become a complex and highly dynamic process. This challenge requires a multifaceted approach to manage and control the complications associated with the hyperglycaemia or hypoglycaemia conditions. This paper presents a mathematical model for determining the influence of combined intervention strategies in the management and control for the plasma glucose of the type II diabetes. System dynamics (SD) techniques were used in modelling the sub-compartments of biological systems of an Identifiable Patient (IP). The system dynamic model developed gave an illustration on how typical glucose-insulin dynamics occur at different intervention strategies involving varying amounts of carbohydrates taken, intensity of physical exercises, stress levels and the amount of exogenous insulin administered. The model was conceptualized within a semi-closed loop system representing the patient ecosystem by extending the Bergman Minimal Model. Stochastic differential equations (SDE) were used to capture the non-linear, continuous time varying interactions of the measurements associated with plasma glucose-insulin dynamics. The estimated results from the model showed combined intervention strategies of reduced amounts of carbohydrates intake, reduced stress levels and varying moderately high-to-low exercise intensity at a constant unit of exogenous insulin produced good plasma glucose levels control.

Food-energy-water (FEW) nexus: Sustainable food production governance through system dynamics modeling

The transition challenge to sustainability is the governance of common use and property resources the commons. Climate change, as the prime mover of that transition processes, directly affects all sectors of society. Food production, and its relative resources – energy and water - is a relevant sector in the transition to sustainability, since it makes direct use of commons. Food production systems present different configurations and interrelations with the environment; however, they have as a similar character: the complexity regarding the interrelations with commons and with society. This complexity addresses the demand on understanding the dynamics of food, energy and water nexus (FEW Nexus) interrelated dimensions. In this context, this article models FEW Nexus using a System Dynamics Modelling (SDM) approach. The study was developed in the green belt of the peri-urban region of the city of São Paulo, located at the edge of the Atlantic Forest, a high-biodiversity forest in the south-eastern Brazil. The simulation of this complex system aims to support the sustainable governance policy of conventional and agroecological production systems. The innovative pattern of different food sustainable systems could be foresighted, from a set of socioeconomic and environmental multi-criteria ensemble of relevant indicators, as Water Footprint, Trophic State Index, Land Social Development Index, Carbon Footprint, Land Use Earnings. Policy tools, as Community Supported Agriculture strategies and Payment for Environmental Services are used to understand the different levels of sustainability under new innovative policies like them. The SDM tool enabled addressing predictive scenarios - seeing the interrelations and causalities of the set of indicators. The multi-criteria set of indicators modelling permits to understand the FEW Nexus sustainability level of the different food production systems. The results are strong guides to implementing strategies that lead to the dynamics of sustainable food systems, concerning FEW Nexus. SDM tool prove to be useful and effective in decision-making sustainable policy design processes and efficient alternatives in governance for sustainability and its transition process.

Correction to: Futures studies in Iran broadcasting, a system dynamic modeling approach

Correction to: Futures studies in Iran broadcasting, a system dynamic modeling approach

Methodological framework for a deeper understanding of airline profit cycles in the context of disruptive exogenous impacts

This paper combines the k-means clustering method in combination with PCA and the system dynamic modeling approach to derive a better insight into the behavior of airline profitability during the time span of 1995 until 2020. The model includes various explanatory variables that capture different aspects of airline economic and operational metrics, whose fluctuations may affect the airline profitability. By forecasting these exogenous variables, the system dynamic model is used to predict airline profitability through 2025 and answer the question of whether the US airline industry will return to its pre-COVID 19 pandemic state. The latter research question can be agreed with, as the effect of introducing a fourth dimension derived from Principal Component Analysis (PCA) to sufficiently cover the variation within the dataset during the years of COVID-19 pandemic diminishes towards the end of the forecast period. Furthermore, the key measures from PCA imply that under the assumption of continuous growth and a non-exogenous shock, future years will not cluster in past years. The six different clusters from 2019 to 2025 showed how the system stays in a certain state for a few years and then drifts further to a new state. There are only a few variables that change to transfer from one cluster to the next.

168 Impact of Connecticut’s Good Samaritan Laws in Preventing Opioid Overdose Deaths – An Applied System Dynamics Approach

168 Impact of Connecticut’s Good Samaritan Laws in Preventing Opioid Overdose Deaths – An Applied System Dynamics Approach