System Dynamics Model Research Articles

Sustainable supply chains – Designing a requisite holistic model

AbstractOur study explored the relationships between supply chain (SC) members and their local and global stakeholders in achieving sustainability goals based on requisite holistic analysis and system dynamics modeling, which goes beyond the previous attempts to improve SC sustainability. In this research, we first developed a model that addresses the basic holistic treatment of SC sustainability; in a second model of sustainable SC (SSC), we then considered requisite holistic interactions among its stakeholders. We used the theory‐based viable system model to diagnose the proposed holistic model of SSC. The results show that especially the low‐tier SC members require supporting frameworks to develop and maintain the capacity for sustainable interactions with nature and society. These supportive frameworks should be provided by the regulatory bodies, society, and nature representatives to surpass the limited SC profit‐oriented incentives and structures. The implications of the proposed models are aimed at developing supportive SC sustainable policies and improving the capacities of SC members to coexist with local social and natural environments. Regulators, society, and the natural environment representatives can apply the proposed models to establish new policies for sustainable interactions between SC members and other societal stakeholders.

Testing a novel life cycle assessment based framework for produced water management from offshore oilfield operations

As worldwide reliance on the petroleum industry persists, environmental concerns associated with offshore oilfield operations continue to present a critical challenge for sustainable management. This study develops and tests a novel life cycle assessment (LCA)-based framework to examine strategies for produced water (PW) management from offshore oilfield operations. The framework encompasses experimental designs under a dynamic modelling system coupled with stepwise linear regression, multi-criteria decision analysis (MCDA), and fluctuating scenarios in Enhanced Oil Recovery (EOR) and other internal reuse options including cooling systems, drilling operations, and utility services. Two strategies for treatment train technologies were tested with various PW compositions, sludge management options, and variable EOR demands. When comparing conventional (corrugated plate interceptor, hydrocylone and nutshell filter) with recent treatment/disposal technologies (tubular separation, combined fiber coalescence and mechanical vapor compression), the LCA revealed that the latter increased operational efficiency (14%), reduced cost (6.5%) and the overall environmental impact categories (66%). The scenario that exhibited the lowest emissions incorporated recent treatment technologies and land application for sludge management. This configuration demonstrated considerable environmental advantages, evidenced by significant reductions in key impact indicators including freshwater eutrophication (74%), global warming (64%), marine ecotoxicity (58%), and stratospheric ozone depletion (44%) when compared to the baseline scenario with conventional treatment-disposal methods. The system dynamics model revealed that the internal reuse options exploited 23%–47% of PW inflow, indicating a significant annual surplus of unused PW that presents an opportunity for external applications to enhance sustainability. In closure, we argue that the proposed framework offers a valuable tool for waste management practitioners, facilitating the identification and selection of strategies with minimal environmental impacts for PW management.

From text to model: Leveraging natural language processing for system dynamics model development

AbstractTextual data is abundantly available, and natural language processing (NLP) facilitates its analysis. However, system dynamics (SD) modelling relies on the modeller to identify relevant information. We explore the ability of NLP models to support SD modelling by identifying causal sentences in texts. We provide a primer on the notion of causality in SD and on the linguistic properties of causality, followed by an introduction of NLP models suitable for this task. Using three test cases, we evaluate the performance of the NLP models using common evaluation metrics and an SD model completeness metric. We conclude that NLP models can add considerable value to SD modelling, provided that remaining challenges are addressed. One such caveat is the difference we observe between information regarded as causal and information relevant for describing system structure. We discuss how these challenges can be addressed through collaboration between the NLP and SD fields. © 2024 The Author(s). System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

Addressing Hospital Overwhelm During the COVID-19 Pandemic by Using a Primary Health Care-Based Integrated Health System: Modeling Study.

After strict COVID-19-related restrictions were lifted, health systems globally were overwhelmed. Much has been discussed about how health systems could better prepare for future pandemics; however, primary health care (PHC) has been largely ignored. We aimed to investigate what combined policies PHC could apply to strengthen the health care system via a bottom-up approach, so as to better respond to a public health emergency. We developed a system dynamics model to replicate Shanghai's response when COVID-19-related restrictions were lifted. We then simulated an alternative PHC-based integrated health system and tested the following three interventions: first contact in PHC with telemedicine services, recommendation to secondary care, and return to PHC for recovery. The simulation results showed that each selected intervention could alleviate hospital overwhelm. Increasing the rate of first contact in PHC with telemedicine increased hospital bed availability by 6% to 12% and reduced the cumulative number of deaths by 35%. More precise recommendations had a limited impact on hospital overwhelm (<1%), but the simulation results showed that underrecommendation (rate: 80%) would result in a 19% increase in cumulative deaths. Increasing the rate of return to PHC from 5% to 20% improved hospital bed availability by 6% to 16% and reduced the cumulative number of deaths by 46%. Moreover, combining all 3 interventions had a multiplier effect; bed availability increased by 683%, and the cumulative number of deaths dropped by 75%. Rather than focusing on the allocation of medical resources in secondary care, we determined that an optimal PHC-based integrated strategy would be to have a 60% rate of first contact in PHC, a 110% recommendation rate, and a 20% rate of return to PHC. This could increase health system resilience during public health emergencies.

Exploring spatial pattern optimization path of urban building carbon emission based on low-carbon cities analytical framework: A case study of Xi'an, China

Reducing carbon dioxide emissions has become a prominent issue in city construction. Here, with the objective of spatial pattern optimization, we propose a comprehensive evaluation framework for low-carbon cities. To shed further light on the mechanism by which green finance facilitates the low-carbon transformation of the economy, we chose Xi'an as a study area, used the system dynamics model, simulated the relationship between different factors in the development of low-carbon cities, and provided guidance for spatial planning of low-carbon cities. Through systematic analysis of results, we found that with the progress of urbanization and the improvement of people's living standards, the carbon emissions from urban buildings in Xi'an will increase annually and reach 2.47 million tons by 2030. In scenario 1, the faster pace of urbanization raises carbon emissions from urban buildings by 3 %, to 2.5543 million tons from the base. In contrast, in Scenario 2, the reduction in urbanization rate results in a decrease in urban building carbon emissions to 2.4243 million tons, a reduction of 2.26 % compared to the baseline scenario. Thus it can be seen that diverse modifications of parameters exert distinct effects on the ultimate carbon emissions from urban buildings.

Optimization of Aviation Biofuel Development as Sustainable Energy Through Simulation of System Dynamics Modeling

This study aims to optimize the development of aviation biofuel as a sustainable energy source by simulating system dynamics modeling. This study is based on the System Dynamics modeling approach, which is a set of conceptual tools designed to understand the structure and dynamics of complex systems. This study used the system dynamics method specifically designed to analyze complex systems. It has been applied to various sustainability-related issues, including urban area sustainable development modeling, sustainability of water resources, environmental management, and sustainable urbanization. The result obtained using the quantitative modeling showed that the contribution of aviation biofuel to flight intensity in Indonesia is still insignificant. The practical implications of this study are that palm oil has the potential to be a viable raw material for aviation biofuel production in Indonesia, and implementing policies to mitigate negative consequences and optimize land use for aviation biofuel fuel production can contribute to sustainable urban development. The originality of this study lies in its use of System Dynamics modeling to analyze the potential of palm oil as a raw material for aviation biofuel production and identify the various social, economic, environmental, and technological factors that impact it.

Tax Incentives for Economic Growth in the Russian Far East: Broad vs. Targeted Stimuli

The purpose of this study is to justify the choice of tax incentive policy instruments aimed at the economic development of the Russian Far East, which is facing acute demographic and environmental problems. To model the dynamics of the region’s real economic system, this study employed a mathematical model based on actual data from 2010 to 2021, covering economic, technological, and socio-ecological aspects. Using the versatile AnyLogic 8.0 platform for agent-based and system dynamics modeling, experiments on alternative tax incentive policy options involving both broad tax incentives and targeted economic development measures were conducted. Specifically, a 50% investment tax deduction for residents in special economic zones in the Russian Far East was implemented. The experimental results show that, despite comparable population dynamics, targeted stimulation of growth poles through public-private partnership programs outperforms broad tax incentives for economic entities in the Russian Far East. This is evident in higher economic growth rates in the region, particularly during the experimental period, except for 2040–2050, where adverse demographic trends constrain growth in both scenarios. The theoretical significance of the application of this method has shown that it allows us to obtain new significant results in the subject area of research due to the consideration of the complex interaction of factors of influence both at the micro- and macro-level, primarily behavioral factors that are fundamentally important for understanding the action of taxes. The practical implications of this study lie in defining the parameters of tax policy to target and stimulate growth poles in regions serving as hubs for generating and disseminating new technologies. The planned perspective is to encourage population growth and ensure sustained economic development in Russia’s Far East. It is advisable to explore comprehensive tax and budgetary regulations that simultaneously address economic, socio-demographic, and environmental issues in the region. Doi: 10.28991/ESJ-2024-08-03-021 Full Text: PDF

Study on multi-state of meshing-impacting dynamic characteristics of spur gear systems considering friction under localized tooth breakage

Localized tooth breakage is one of the common failures of spur gears, which affects the smooth and safe operation of spur gear transmission systems. The tooth collision cannot be neglected, and it is especially important to reveal the meshing-impacting dynamic characteristics of the gear system under localized tooth breakage to improve the safe and stable operation of the gear system. Based on the gear meshing principle and the dissipative collision contact force model, the drive-side tooth meshing model and back-side tooth impacting model are established with considering the transient nature of tooth back-side contact. The tooth surface meshing model and tooth back collision model under partial breakage are established. According to the contact state and force environment of the gear pair, the multi-state meshing-impacting behaviour under local breakage is classified, and the discrete meshing-impact dynamics model of an involute spur gear system under local breakage is established to explore the influence of local breakage on the meshing stiffness and load distribution. The mechanism of contact force under partial tooth breakage is revealed, and the influence of load coefficient and meshing frequency on the nonlinear dynamics is studied by defining two Poincaré maps. It is found that local tooth breakage affects the contact force of single-and double-tooth meshes and reduces gear load carrying capacity. Larger loads inhibit back-side impact, and smaller loads induce the coexistence behaviour and back-side impact. Larger or smaller meshing frequency induce back-side impact behaviour. The coexistence of chaotic and periodic motions induces back-side impact behaviour, and localized tooth breakage affects the coexistence phenomenon and aggravates the complexity of the dynamic behaviour. The dynamic model of gear system considering energy dissipation and nonlinear vibration under the presence of local tooth breakage of the pinion is explored, and the conditions of back-side impact are studied. This research provides new methods and ideas for nonlinear dynamic modelling and analysis of faulty gear systems.

A study of collaborative governance of online users tourism information (Revision 2)

ABSTRACT With the rapid development of the Internet, the spread of tourism information is more rapid, and tourism information governance is increasingly important. This research adopts a system dynamics approach to construct a system dynamics model of collaborative tourism information governance from government, netizens, tourism enterprises, and the information itself, using the Huangshan information as a case study. The results show that the impact of ‘information popularity’ is the largest, ‘government credibility’ in the second place; ‘emergency management capability of tourism enterprises’, ‘the intensity of information disposal efforts’ and ‘role of opinion leaders’ have the weak influence to the tourism information governance. It is proposed to improve the public’s judgment, strengthen its judgment, improve the efficiency of the use of official media, promote the openness of information, and encourage the government to take the initiative and increase the level of interaction, strengthen the emergency management training of tourism enterprises, improve the ability to respond to the leading role of opinion leaders, correct guidance and other strategies.

Unveiling the Energy Transition Process of Xinjiang: A Hybrid Approach Integrating Energy Allocation Analysis and a System Dynamics Model

Unveiling the Energy Transition Process of Xinjiang: A Hybrid Approach Integrating Energy Allocation Analysis and a System Dynamics Model

Modeling and vibration analysis of an aero-engine dual-rotor-support-casing system with inter-shaft rub-impact

In order to reveal the nonlinear dynamics of dual-rotor-support-casing system, a numerical procedure is proposed using the finite element method and the component mode synthesis method. Especially, the casing system is subdivided into the casings, struts and housings, which are modeled by shell elements, beam elements and rigid regions with mass elements, respectively. Furthermore, the inter-shaft rub-impact, which may occur in the aero-engine because of imbalance and other faulty, is considered in the dynamic model as a nonlinear excitation. The modal analysis verified the validity of the dual-rotor-support-casing system model. The motion equations are established using the reduced-order model and solved by Newmark-β method with Newton-Raphson iteration. The results show that larger rubbing stiffness will cause the rubbing to enter a self-excited vibration state, and the rotational speed ratio will change the speed region where the self-excited vibration occurs. Finally, the experiment is performed based on a real dual-rotor aeroengine under inter-shaft rub-impact and the results are consistent with the theoretical results, which proves the effectiveness of dual-rotor-support-casing system dynamic model.

Orbit-attitude coupled dynamics modeling and adaptive sliding mode control for detumbling large space debris

For non-cooperative large tumbling space debris, the use of detumbling techniques to reduce its angular velocity facilitates capturing and deorbiting operations. In our recent work, a new detumbling device combining three harpoons and a nanosatellite was designed. The device is released from the servicing satellite and attaches to the surface of the target. Then, the device's thrusters are actuated to reduce the target's angular velocity. In this paper, the dynamics and control issues involved in this strategy are further investigated. The collision model between the detumbling device and the target in the process of attachment is built based on the principle of momentum conservation. A high-precision orbit-attitude coupled dynamics model of the combined system during the detumbling mission is established, in which major external disturbances as well as inertial parameter variations due to the fuel consumption of the nanosatellite are taken into account. In addition, an adaptive sliding mode control scheme incorporating pulse-width pulse-frequency (PWPF) modulation is proposed for debris targets with parametric uncertainties and external disturbances. Finally, the effectiveness and robustness of the detumbling control scheme are demonstrated by numerical simulations. The results show that the detumbling device is capable of detumbling a large tumbling rocket upper stage within 4000s.

Enhancing Marine Comprehensive Carrying Capacity and Energy Assessment and Prediction Using an Improved Ant Colony Algorithm and System Dynamics Model

Enhancing Marine Comprehensive Carrying Capacity and Energy Assessment and Prediction Using an Improved Ant Colony Algorithm and System Dynamics Model

Modelling the behaviour in socio-technical systems for policy assessment - A comparison of modelling approaches using the example of Sponge City concept implementation

How are policies affecting the social behaviour of actors and thus the dynamics of the corresponding socio-technical systems? This question is of central relevance to understand what policies might be effective for sustainable transitions and transformation where social changes are immanent. Exploratory modelling approaches such as agent-based modelling (ABM) are suitable and established to analyse how individual, especially heterogeneous behaviour emerges to affect social systems. In contrast to this micro-level perspective of understanding how social behaviour influences system behaviour, System Dynamics models (SDM) focus on the macro-level perspective by analysing how system interactions drive complex system behaviour. Qualitative modelling approaches such as Causal Loop Diagrams belonging to the Systems Thinking Modelling (STM) toolbox remain descriptive but need much less effort for model development. In this article, we compare how the different approaches ABM, SDM and STM can model social behaviour in socio-technical systems and what different kind of insights can be gained to assess the efficacy of policies. It discusses the advantages and limitations of the different approaches for their application in behavioural public policy modelling for sustainability transition. Therefore, three exemplary models (STM, SDM, ABM) are created for the same topic of implementation dynamics of adaptation measures to foster rainwater retention (Sponge City concept) in a multi-residential quarter. As a result, the risk of green gentrification is identified. Three hypothetical policies are implemented to illustrate the differences between the three modelling approaches for their use in policy assessment. Based on that, we discuss how the three modelling approaches conceptualise behaviour in general.

A relational perspective on how and when follower attachment style impacts job performance: The moderating role of leader neuroticism

AbstractWe integrate insights from attachment theory and relational leadership to develop a novel interpersonal explanation of why, how and when followers' attachment anxiety and avoidance impact performance. Drawing on the attachment system dynamics model, we posit that attachment avoidance will be negatively related to LMX quality, whereas attachment anxiety will be positively related to LMX ambivalence. Furthermore, we predict that followers' anxious (and avoidant) attachment styles will interact with leader neuroticism leading to a hyperactivation (deactivation) of the attachment system, manifesting in greater LMX ambivalence (and lower LMX quality). Across three studies, we found consistent evidence for a positive relationship between follower attachment anxiety and LMX ambivalence, as well as an indirect effect between attachment anxiety and job performance. Leader neuroticism was especially likely to induce LMX ambivalence and, in turn, undermine job performance in anxiously attached followers. Attachment avoidance, although unaffected by leader neuroticism, was negatively related to LMX quality across all three studies and demonstrated an indirect effect on job performance in Study 3. Overall, our findings shed light on the unique explanatory power of relational mechanisms, beyond previously examined intrapersonal mechanisms, for understanding the attachment style–performance relationship as well as the role that leader characteristics play in triggering the attachment system in anxious followers.

Use of the National Climate and Energy Policy Simulation Tool in the Policy Making Process

Energy transition towards CO2 neutral energy systems is challenging as the national energy policy depends on numerous factors. In system dynamics approach these factors are identified as causal and feedback loops with lock-ins, as a result constituting stock-and-flow structure. Such a kind of structure is used in different simulation tools. This study analyses the use of the Latvian national climate and energy policy simulation tool in the policy making process. As a hypothesis of the study was set that the simulation tool, which is based on the principles of systemic thinking (explaining causal relationships) and an easy-to-use user interface, significantly improves the national energy and climate policy making process. Accordingly, to verify the hypothesis the task was to evaluate the use of the national climate and energy policy simulation tool in the policy-making process. For the evaluation the relevant literature was reviewed: climate and energy policy goals, policies and legislation in the European Union and Latvia; approaches to modeling national climate and energy policies, including optimization models, simulation models; the use of simulation models in the modeling of national climate and energy policies; the use of system dynamics models in the modeling of national climate and energy policies. Besides using the systemic thinking approach in the process of creating national climate and energy policies, the user experience in building simulation tools was used. Based on the literature analysis, improvements to the interface of the national climate and energy simulation tool developed by Riga Technical University, Institute of Energy Systems and Environment were made and developed training material for the use of the simulation tool, based on explaining the causal relationships built into the model.

Designing nickel smelter industry investment competitiveness policy in Indonesia through system dynamics model

Purpose This research is intended to assess the nickel smelter industry’s investment competitiveness in Indonesia and identify ways to improve its competitive advantage for the nation. Design/methodology/approach This research uses a sequential mixed-methods approach, expanding on a first qualitative phase with a second quantitative phase. Interviews are used in the qualitative phase to identify the underlying causes of issues and potential solutions to increase the competitiveness of the nickel smelter industry, while a system dynamics (SD) model is used to conduct the quantitative phase. This study uses the idea of a country’s competitive advantage from Porter’s diamond model (PDM). The model was tested and validated using SD simulation resulting in a new policy scenario, which was evaluated in metallurgy expert conferences and high policymaker discussion forums. Findings The results reveal the complexity of the nickel smelter industry in Indonesia and conclude that the integrated export duty beneficence policy is the most effective way to boost competitiveness. This policy gives a significant improvement both in the number of smelters and state revenue compared to the current policy. The industry’s investment competitiveness is enhanced by the six factors of the diamond model, with the first three factors being integrated strategy, limited export of excess production and export duty beneficence, while the remaining factors are metal price fluctuation, domestic demand and mineral supply which are related to mining conditions uncertainty. Research limitations/implications The research creates a SD model to support Indonesia’s competitive advantage in the smelter industry. Despite limitations like interpretations and distorted semantic analysis, it provides a useful framework for exploring complex industry themes, excluding social factors due to limited data and knowledge requirements. Practical implications The findings of this research offer a framework for policymaking by the government to enhance the competitiveness of investments in Indonesia’s nickel smelter industry. Originality/value This study delves into Indonesia’s nickel industry competitiveness using PDM. Using a more detailed SD model with quantitative analysis, it goes beyond strategy development to provide a comprehensive approach to the nickel smelter industry.

Adaptive Iterative Learning Constrained Control for Linear Motor-Driven Gantry Stage with Fault-Tolerant Non-Repetitive Trajectory Tracking

This article introduces an adaptive fault-tolerant control method for non-repetitive trajectory tracking of linear motor-driven gantry platforms under state constraints. It provides a comprehensive solution to real-world issues involving state constraints and actuator failures in gantry platforms, alleviating the challenges associated with precise modeling. Through the integration of iterative learning and backstepping cooperative design, this method achieves system stability without requiring a priori knowledge of system dynamic models or parameters. Leveraging a barrier composite energy function, the proposed controller can effectively regulate the stability of the controlled system, even when operating under state constraints. Instability issues caused by actuator failures are properly addressed, thereby enhancing controller robustness. The design of a trajectory correction function further extends applicability. Experimental validation on a linear motor-driven gantry platform serves as empirical evidence of the effectiveness of the proposed method.

Impact of industry 4.0 on supply chain management

This study aims to analyze the impact of Industry 4.0 implementation on the supply chain and develop an implementation framework that considers the potential drivers and obstacles of the Industry 4.0 paradigm. A literature search examined the main drivers and barriers to implementing Industry 4.0 in four business areas: strategy, organization, technology, law, and ethics. A system dynamics model will be developed to understand the impact of the implementation of Industry 4.0 on supply chain parameters, and the identified drivers and barriers to technological change will be included. In addition to the empirical basis of this connection, a proposal was a theoretical framework for utilizing Industry 4.0 within the supply chain. The opportunities and new challenges for future supply chains were expected in Industry 4.0. This study analyzed various challenges in implementation and process and proposed a framework for effectively adapting and transferring the model of Industry 4.0 towards supply chains. The research aims to understand the challenges of integrating Industry 4.0 into their networks because it aims to examine the advantages of supply chain management. The implementation impact of Industry 4.0 on the supply chain performance can be analyzed using simulation analysis, and the driving causes and obstacles of this technological transition can be investigated. This connection is provided on an empirical basis. It is proposed that a new industrial conceptual framework be developed. Incorporate Industry 4.0 into your supply chain.

Free Riding of Vehicle Companies under Dual-Credit Policy: An Agent-Based System Dynamics Model

The dual-credit policy promotes green transition in automobile companies. This paper investigates the dual-credit policy framework in the Chinese automotive industry, with a focus on the phenomenon of free riding. This occurs when traditional vehicle manufacturers within an alliance benefit from the excess credits generated by a transitioning vehicle company without fully committing to their own green transitioning. The focus of this study lies on an alliance constituted by a transitioning vehicle company in partnership with two traditional vehicle manufacturers, all interconnected via equity ties. Utilizing an agent-based system dynamics model, this study explores the strategic behaviors emerging from such credit collaborations and their consequent effects on operational efficiency and financial performance. The findings reveal that 1. free riding negatively impacts the transitioning company’s revenue but benefits the alliance by easing transition pressures and boosting collective performance; 2. stricter policies increase intra-alliance credit transfers and performance, while lower credit prices reduce transfer value and harm the transitioning company’s earnings. This study implies that transitioning vehicle companies with equity-linked partners can benefit from a nuanced understanding of how policy mechanisms interact with alliance dynamics under free riding. By adjusting credit transfer strategies in line with market conditions and policy trends, they can better navigate the dual-credit policy landscape, balancing individual profitability with the needs of the broader alliance and long-term sustainability goals.