System Dynamics Modelling Approach Research Articles

A participatory system dynamics model to investigate sustainable urban water management in Ebbsfleet Garden City

Growing urban populations, changes in rainfall patterns and ageing infrastructure represent significant challenges for urban water management (UWM). There is a critical need for research into how cities should adapt to become resilient to these impacts under uncertain futures. UWM challenges in the Ebbsfleet Garden City (UK) were investigated via a participatory process and potential sustainable solutions were explored using a System Dynamics Model (SDM). Collaborative development of the SDM by the Ebbsfleet Learning and Action Alliance developed stakeholders’ understanding of future UWM options and enabled a structured exploration of interdependencies within the current UWM system. Discussion by stakeholders resulted in a focus on potable water use and the development of the SDM to investigate how residential potable water consumption in the Ebbsfleet Garden City might be reduced through a range of interventions, e.g., socio-environmental and economic policy incentives. The SDM approach supports decision-making at a strategic, system-wide level, and facilitates exploration of the long-term consequences of alternative strategies, particularly those that are difficult to include in quantitative models. While an SDM can be developed by experts alone, building it collaboratively allows the process to benefit from local knowledge, resulting in a collective learning process and increased potential for adoption.

Growth Kinetic Model for Microalgae Cultivation in Open Raceway Ponds: A System Dynamics Tool

Abstract Microalgae culture has the potential to play an essential role in the application of circular economy principles. Microalgae cultivation allows utilizing industrial side-waste streams while ensuring biomass for a wide range of applications in the industrial sector. Specifically, cultivation in outdoor open raceway ponds are a preferred solution due to low costs, ease of operation and large-scale application. However, the economic viability of the cultivation system largely depends on the amount of biomass produced, the technology implemented and the microalgae species and strains. For this purpose, screening of numerous physical, chemical, and environmental factors affecting microalgae growth must be performed before implementing large-scale microalgae cultivation systems. Furthermore, to obtain the highest biomass yield, the design and operating parameters for open raceway pond cultivation must be investigated in depth. Therefore, this study proposes a kinetic growth model for microalgae cultivation in open raceway ponds based on System Dynamics modelling approach. The proposed model aims at overcoming the major problems of existing growth evaluation tools such as separate assessment of different parameters, high complexity, time consumption and other challenges. The proposed system dynamics model proves to be a simple yet powerful tool for modelling the behaviour of algae biomass in an open raceway pond.

The Role of Mitigation Options for Achieving a Low-Carbon Economy in the Netherlands in 2050 Using a System Dynamics Modelling Approach

To reach a low-carbon economy in the Netherlands, the level of greenhouse gases (GHG) emissions has to be reduced by 80–95% CO2 emissions compared to 1990 (223.1 MtCO2-equivalents). This study aims to address how investment subsidies combined with carbon levies could be deployed to support technological mitigation options to achieve a low-carbon economy in the Netherlands in 2050. A system dynamic model has been built including demographic-economic, energy and environmental sub-systems of the Netherlands. The model has been validated with earlier projections of the EU for the energy and climate policy in 2050. Next to the business-as-usual scenario, there are four policy scenarios simulated from 2010 to 2050. In all policy scenarios a carbon levy was imposed on non-renewable energy to finance subsidies on mitigation options. Results show that imposing subsidies on the mitigation option renewable energy is most effective in combination with the carbon levy.

How to Ameliorate the Surgical Workforce Crisis: A System Dynamic Modeling Approach

Marie Oslock, Wendelyn BA; Maurer, Julie PhD; Tamer, Robert MPH, MPA; Baselice, Holly MPH; Satiani, Bhagwan MD, MBA, FACS; Christopher Ellison, E. MD, FACS; Santry, Heena P. MD MS FACS Author Information

How COVID-19 shock will drive the economy and climate? A data-driven approach to model and forecast.

The pandemic shock puts the world on quarantine and paused economic operations that affected energy consumption and economic output. This study analyzed the impact of the COVID-19 shock on GDP, energy consumption, and climate change then forecasted the situation until 2032 using the system dynamic modeling approach. The outcomes reveal that the pandemic shock will decrease the growth by 1.3% in 2020 and 1.32% in 2021. The current shortfall, low energy consumption, and delay in completion of energy-related projects can reduce the GDP by 5.2% in 2020. The effect will penetrate the system and will cause further losses in the upcoming years. The energy consumption and quarantine situation will improve the climate situation and drop the average temperature by 0.049 and 0.021 oC in 2020 and 2021. The aggregate demand and supply side measures such as national spending, lowering the lending rate, and cuts in income taxes can help in diffusing the situation. The government should start operations on ongoing energy projects, give relaxation to SME’s with tight SOPs to secure jobs, and prevent possible GDP losses. The decline in oil prices provides an opportunity to cut fossil fuel subsidies and implement a carbon pricing mechanism.

A System Dynamics Modelling for Converting Existing Tanker to FPSO

Floating, Production, Storage, and Offloading (FPSO) is an offshore installation that is used to process and store crude oil from wells and then transport it using tankers to oil refineries. One common scheme in the construction of an FPSO is by converting a tanker into FPSO. The project to convert a tanker to an FPSO requires a very well planning considering that this facility is a very important facility in the upstream oil and gas industry. This study aims to determine aspects that can reduce costs in the project of converting a tanker to FPSO. In this study, the variables that can influence the cost of conversion of a tanker into FPSO project are determined by approaching the principle of customer satisfaction, called Quality, Cost, and Delivery. The solution to the problem is carried out using a system dynamics model approach to determine the causality relationship between variables and its effect on the cost of conversion. The analysis is taken by sensitivity analysis and give the result of the biggest variables that lead in cost of conversion respectively are shipyard class, penalty during production, lead time, subcon factor, amount of worker, and the accuracy of pricing. The simulation model produced using system dynamics modelling is expected to be able to provide a solution to reduce the project cost of conversion a tanker to FPSO to support oil and gas exploitation activities in Indonesia.

Development of a construction performance index in the construction industry: system dynamics modelling approach

Being on competitive edge, many companies plan to enhance their work performance in different areas. It is important to capture causal relationships among the key factors and their interactions in the dynamics environment. This study utilizes the system dynamics (SD) modelling approach to develop the dynamics model of the construction performance index (CPI) to examine and improve the performance index, and progress through to higher performance maturity levels in the long-term. The study results show that the construction companies can progress through to higher levels of performance maturity with support from management level to improve time, cost, quality, safety and health, and client satisfaction. These, in turn, lead to better financial performance of the companies. The results also reveal the importance of the internal stakeholders in achieving higher CPI and maturity levels. Teamwork and good working environment are crucial in successfully implement the performance improvement plan. It is also found that to compete in the global market, the companies should include the environmental policies in their business plans to raise their performance standards in the long-term.

A dynamic model-based framework to test the effectiveness of biocontrol targeting a new plant invader– the case of Alternanthera philoxeroides in the Iberian Peninsula

Biological invasions are one of the major threats to biodiversity at the global scale, causing numerous environmental impacts and having high direct and indirect costs associated with their management, control and eradication. In this work, we present a system-dynamic modelling approach for the biocontrol of the invasive plant species Alternanthera philoxeroides using its natural predator, Agasicles hygrophila, as a biocontrol agent. We have simulated different scenarios in the Finisterre region (Spain), where a single population of the invasive plant has been recently described. To assess the effectiveness of A. hygrophila as a biocontrol agent in the region, a population dynamic model was developed in order to include the life-cycle of both species, as well as the interaction among them. The results of the simulations indicate that the control of this new invasive plant is possible, as long as several releases of the biocontrol agent are made over time. The proposed model can support the control or even the eradication of the population of A. philoxeroides with a minimal impact on the environment. Additionally, the proposed framework also represents a versatile dynamic tool, adjustable to different local management specificities (objectives and parameters) and capable of responding under different contexts. Hence, this approach can be used to guide eradication efforts of new invasive species, to improve the applicability of early management measures as biocontrol, and to support decision-making by testing several alternative management scenarios.

A Subregional Model of System Dynamics Research on Surface Water Resource Assessment for Paddy Rice Production under Climate Change in the Vietnamese Mekong Delta

Effective water management plays an important role in socioeconomic development in the Vietnamese Mekong Delta (VMD). The impacts of climate change and human activities (that is, domestic consumption and industrial and agricultural activities) vary in different subregions of the delta. In order to provide intersectoral data for determining the significantly impacted subregions of the VMD, the present study simulated interactions between local climatic patterns, human activities, and water resources using a system dynamics modeling (SDM) approach with each subregion as an agent of the developed model. The average rainfall and temperature of 121 subregions in the VMD were collected during 1982–2012, and the future changes of climate by provinces were based on the Representative Concentration Pathways (RCP) scenarios (RCP4.5 and RCP8.5) by the end of 21st century. The assessment was based on the levels of impact of various factors, including (1) water consumption, (2) differences between evapotranspiration and rainfall, and (3) spatial distribution of salinity intrusion over the delta scale. In the coastal areas, as well as the central and upstream areas, water resources were projected to be affected by environmental changes, whereas the former, characterized by the lack of surface freshwater, would be affected at a greater scale during the dry season. Besides, the sea level rise would lead to an increase in negative impacts in the eastern coastal areas, suggesting that water-saving techniques should be applied not only for agriculture, but also for industry and domestic water consumption during the dry season. In addition, the south subregions (that is, the western subregions of the Hau River except for An Giang) were likely to be flooded due to the simulated high rainfall and seasonal rises of sea level during the wet season. Therefore, the alternative forms of settlement and livelihood should be considered toward balance management with changing delta dynamics.

Low Carbon Transition of Residential Electricity Consumption in Nigeria: A System Dynamics Modeling Approach

It is imperative that Nigeria reduces wastage in residential electricity consumption and motivate energy saving behaviors through energy efficiency measures. These strategies aim to minimize frequent power sheds, which in turn increase reliability, thus benefiting the environment and electricity consumers. This article examines the effects of such innovative approaches to electricity savings in Nigeria through: 1) prepaid electricity metering systems and 2) fast replacements of inefficient and aging appliances. Relationships between residential electricity consumption, energy efficiency, and carbon footprint were also assessed vis-a-vis the replacement of old energy appliances and analogue electricity billing systems with more efficient devices and through prepaid metering systems, respectively. These techniques intend to promote energy saving behaviors. A System Dynamics model built on Stella platform, is used to analyze the implication of energy efficiency policy implementation on residential electricity consumption based on a simulation period of 41 years (2010 - 2050). Secondary data were sourced from the Bureau of Statistics, published articles, Nigerian power sector, World Bank, and primary data using cross sectional surveys of residential electricity consumers. Results, not only revealed that availability and utilization of prepaid electric meters and efficient appliances would motivate electricity saving behaviors, but also showed that efficient technologies could be the main drivers to future energy savings. Results also showed that carbon emissions were cut down by 45% in 2050. In addition, changes in electricity tariffs did not have any consequential effect on electricity consumption, but would rather influence electricity demand. Also, large number of occupant per house might have a negative impact on the Nigerian economic growth. Finally, results suggest that subsidies should be used on new household appliances as an effective energy policy measures. The developed model can be replicated in similar sectors in other emerging economies.

A system dynamics analysis of the alternative roofing market and its potential impacts on urban environmental problems: A case study in Orlando, Florida

Recent advances in sustainable construction and development methods have allowed urban developers to significantly reduce urban environmental problems caused by buildings such as increased energy consumption and greenhouse gas emissions, urban runoff, and the urban heat island effect. Newer forms of green infrastructure, including alternative roofing (green roofs, solar BIPV systems, etc.), have emerged as potential solutions to these urban environmental problems. However, a number of practical and socioeconomic factors are currently limiting their market penetration to a marginal share. This study employs a System Dynamics modeling approach to analyze these hindrances in Orlando’s alternative roofing market, as well as the potential of societal, economic, and developmental investments in different alternative roofing markets to address these issues. Conventional roofs have been found to remain predominant in Orlando’s roofing market under all policy scenarios, with solar roof system being the most mature out of the three alternative roofing markets considered, and consequently has the most potential for future market penetration. It has been found that the studied alternative roof systems (ARSs) reach only a marginal market share in the year 2040, and for this reason, could not result in significant improvements in the studied impact categories at the city level. However, the studied ARSs yield important reductions in all of the impact categories when analyzed at the building level. The results of this study indicate that the alternative roofing market has significant growth potential, but further research, development, and improvement will be essential to achieve more effective, long-term benefits in Orlando.

System Dynamics Simulation Model to Increase Paddy Production for Food Security

Background: Food security is a world problem that often affects developing countries, one of them in Indonesia. Along with the increasing population growth population in Indonesia, this will affect the level of demand for rice for food needs. The problem of rice consumption and its fulfillment is an important agenda. If Indonesia does not want to depend on rice imports, then paddy production must continue to be increased. Therefore, food availability in each region is maintained to realize food security. Objective: The purpose of this study is to analyze the factors that influence the increase paddy production in terms of cultivation and postharvest using a system dynamics model approach as the basis for policy strategy preparation.Methods: System Dynamics (SD) approach with the consideration that this framework offers the ability to study and manage complex feedback systems and the ability to model non-linear behavior. Then do a series of decision scenarios to get the best results using computer assistance.Results: Scenario results indicate that increasing paddy production to meet demand in Indonesia can be done by increasing the adoption of postharvest harvesting mechanisms coupled with the application of appropriate GAP (Good Agricultural Practice). It will increase paddy production in East Java so that it will make a large contribution to rice production in East Java.Conclusion: This research can be used to improve paddy production to food security by improving harvesting mechanisms. For further research, we can consider increasing rendement paddy in supporting increased rice production.

Integrating Real Options Analysis with long-term electricity market models

In liberalized electricity markets, the investment postponement option is deemed decisive for understanding the addition of new generating capacity. Basically, it refers to the possibility for investors to postpone projects for a period while waiting for the arrival of new and better information about the market evolution. When such development involves major uncertainties, the generation business becomes riskier, and the investors' “wait-and-see” behavior might limit the timely addition of new power plants. In that sense, the literature provides solid empirical evidence about the occurrence of construction cycles in the deregulated electricity industry. However, the strategic flexibility inherent to the option to defer new power plants has not yet been rigorously incorporated to investment signals in existing market models. Therefore, this paper proposes a novel methodology to assess the long-term development of liberalized power markets based on a more realistic approach for valuing generation investments. The work is based on a stochastic dynamic market model, built upon System Dynamics simulation approach. The decision-making framework considers that the addition of new capacity is driven by the economic value of the strategic flexibility associated with deferring investments under uncertainties. Thus, the value of the postponement option is quantified in monetary terms through Real Options Analysis. Simulations confirm the cyclical behavior of the energy-only market in the long run, as suggested by the empirical evidence found in the literature. In addition, sensitivity analysis regarding some relevant exogenous variables depicts an even more fluctuating evolution of the capacity due to the combination of strong demand growth rates with large volatilities. Finally, the model validity is assessed through a formal procedure according to the scope of System Dynamics modeling approach.

Integration of an individual-oriented model into a system dynamics model: An application to a multi-species system

Although the system dynamics (SD) modeling approach has been used frequently to model various systems, there is little research on the development of hybrid SD–individual-oriented (IO) modeling. The aim of this study is to demonstrate the use of an array variable for the hybrid SD–IO modeling approach using the SD platform, and to provide a detailed modeling process of an algae–daphnid system consisting of two freshwater algal species and Daphnia. Our study showed that the array variable in the SD approach is useful for modeling multiple individuals and as a function to control the switch and integration variable for the hybrid modeling approach. The proposed method can improve the usability of hybrid modeling by enabling hybrid SD–IO modeling without requiring extensive knowledge of programming. Given the ongoing development and advancement of the SD modeling approach, this modeling technique will be a useful method to study complex systems.

Understanding the Mississippi River Delta as a Coupled Natural-Human System: Research Methods, Challenges, and Prospects

A pressing question facing the Mississippi River Delta (MRD), like many deltaic communities around the world, is: Will the system be sustainable in the future given the threats of sea level rise, land loss, natural disasters, and depleting natural resources? An integrated coastal modeling framework that incorporates both the natural and human components of these communities, and their interactions with both pulse and press stressors, is needed to help improve our understanding of coastal resilience. However, studying the coastal communities using a coupled natural-human system (CNH) approach is difficult. This paper presents a CNH modeling framework to analyze coastal resilience. We first describe such a CNH modeling framework through a case study of the Lower Mississippi River Delta in coastal Louisiana, USA. Persistent land loss and associated population decrease in the study region, a result of interplays between human and natural factors, are a serious threat to the sustainability of the region. Then, the paper describes the methods and findings of three studies on how community resilience of the MRD system is measured, how land loss is modeled using an artificial neural network-cellular automata approach, and how a system dynamic modeling approach is used to simulate population change in the region. The paper concludes by highlighting lessons learned from these studies and suggesting the path forward for analysis of coupled natural-human systems.

Modelling energy production flexibility: system dynamics approach

Article shows how system dynamics modelling (SDM) approach could be used in modelling the energy transition towards low carbon energy system. SDM can be used to combine the techno-economic and socio-technical analysis. The study considers flexibility issues related to integration of renewable energy sources. Simplified model structure is made to illustrate how flexibility as well as other socio-technical aspects might be modelled. Results of the model correspond to the behavior anticipated from the model structure. Namely, model imitates effects of technological disruption which rises the limits of intermittent power production from renewable sources which can be integrated into power system. The limits are increased stepwise, as a share of intermittent power production reaches certain threshold value, resulting in sequence of S-shaped growth. This study presents flexibility increase of a power system conceptually and more detailed study should uncover leverage points which could stimulate this increase and thus, transition to sustainable energy system.

First Attempt Toward a Holistic Understanding of the Interdependent Rippled Impacts Associated with Out-of-Sequence Work in Construction Projects: System Dynamics Modeling Approach

Abstract Out-of-sequence (OOS) work during construction is a major cause of productivity losses, cost and schedule overruns, and quality decline, either directly or indirectly. Given the complexity...

An empirical evaluation of policy options for inclusive dairy value chain development in Nicaragua: A system dynamics approach

Achieving inclusive value chain development is a challenging task due to the complex and dynamic nature of interconnected value chains and their social, economic, and ecological dimensions. While many policies and intervention options exist to upgrade value chains, there are fewer methods that can be used to understand and quantify the multidimensional impacts that value chain policies and interventions may have throughout the value chain. This paper addresses this methodological gap by employing a system dynamics (SD) modeling approach. SD models allow us to model and quantify the processes and relationships inherent in the value chain through simulations, serving as a policy laboratory for the empirical assessment of intervention options. An SD model of the Matiguás dairy value chain in Nicaragua was developed and tested through a participatory modeling process. Our research tested and evaluated the short-, medium-, and long-term impacts of specific interventions and policies in the Matiguás dairy value chain with the goal of strengthening the competitiveness and inclusion of small- and medium-scale producers. These interventions centered on improving the feeding system, which was identified by stakeholders as the critical constraint to competitiveness. The policy analysis reveals that both improved pastures and increased use of concentrates raise producer milk productivity by 5% and 11%, respectively in the long run, but are also expensive strategies for smallholder producers, leading to a reduction in profits relative to the baseline by 1% and 3%, respectively. Consequently, policymakers should identify strategies that help to reduce concentrate costs and support producers with investments in improved pasture, while also promoting training in pasture management skills. Indeed, in the long-run, model results reveal that investment and training in pasture management results in a 30% and 35% increase in milk production during the wet and dry season, respectively. Simulation results further highlighted that intensifying the feeding system to improve cow milk yields is mainly profitable in the long term, and thus requires a longer-term perspective by policymakers. The model provides a deeper understanding of the complex and dynamic nature of the Matiguás dairy value chain and the interactions between markets, coordination aspects, biophysical phenomena, and income. The system dynamics approach to value chain analysis further addresses a major analytical shortcoming in value chain analysis and provides decision makers with an improved platform for planning and policy formulation.

Reflections on Teaching System Dynamics Modeling to Secondary School Students for over 20 Years

This paper contains the description of a successful system dynamics (SD) modeling approach used for almost a quarter-century in secondary schools, both in algebra classes and in a year-long SD modeling course. Secondary school students have demonstrated an ability to build original models from the news, write technical papers explaining their models, and present a newfound understanding of dynamic feedback behavior to an audience. The educational learning theory and instructional methods used for both the algebra and modeling courses are detailed, with examples. Successful student SD modeling experiences suggest the SD approach can expand the sophistication of topics that secondary school students can understand.

Forecasting the shortage of neurosurgeons in Iran using a system dynamics model approach.

CONTEXT:Shortage of physicians particularly in specialty levels is considered as an important issue in Iran health system. Thus, in an uncertain environment, long-term planning is required for health professionals as a basic priority on a national scale.AIMS:This study aimed to estimate the number of required neurosurgeons using system dynamic modeling.SETTING AND DESIGN:System dynamic modeling was applied to predict the gap between stock and number of required neurosurgeons in Iran up to 2020.SUBJECTS AND METHODS:A supply and demand simulation model was constructed for neurosurgeons using system dynamic approach. The demand model included epidemiological, demographic, and utilization variables along with supply model-incorporated current stock of neurosurgeons and flow variables such as attrition, migration, and retirement rate.STATISTICAL ANALYSIS USED:Data were obtained from various governmental databases and were analyzed by Vensim PLE Version 3.0 to address the flow of health professionals, clinical infrastructure, population demographics, and disease prevalence during the time.RESULTS:It was forecasted that shortage in number of neurosurgeons would disappear at 2020. The most dominant determinants on predicted number of neurosurgeons were the prevalence of neurosurgical diseases, the rate for service utilization, and medical capacity of the region.CONCLUSIONS:Shortage of neurosurgeons in some areas of the country relates to maldistribution of the specialists. Accordingly, there is a need to reconsider the allocation system for health professionals within the country instead of increasing the overall number of acceptance quota in training positions.