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The growing number of connected vehicles has led to an increased focus on Vehicle-to-Everything (V2X) communication in the field of transport research. This communication paradigm facilitates cooperation between vehicles and infrastructure to address traffic challenges such as efficiency, sustainability and safety. The development and standardisation of such Cooperative Intelligent Transport Systems (C-ITS) has been pursued in several projects. Beyond technical considerations, assessing the effect of these applications in terms of various impact categories is of paramount importance. However, existing research tends to examine impact categories such as efficiency, sustainability, safety, psychological or socioeconomic impacts separately, often overlooking potential interactions and interdependencies. This approach is inadequate as impacts on one category can have both cascading effects on others and rebound effects. To address this gap, this paper proposes a system dynamics approach using Causal Loop Diagrams (CLD) to illustrate the interconnectedness of impact categories and the potential impacts of C-ITS services. By depicting general relationships, interdependencies and feedback loops between impact category elements, the model accommodates the introduction of single or multiple C-ITS services as separate modules, allowing an analysis of their combined effects on the overall system. To this end, two use cases demonstrate the applicability of the developed CLD and illustrate some of the multiple interrelations between the effects of C-ITS services. The results of this paper support road operators and researchers when setting up the impact assessment of C-ITS services by revealing the dynamic and intertwined nature of different impact categories. [ABSTRACT FROM AUTHOR]

This research investigates the benefits of the dairy value chain beyond food provision, and its contribution to inclusive sustainable development (ISDH) in European highlands. Transdisciplinary teams interviewed and analysed 11 cases related to the dairy value chain sourced from three highland regions in Europe: Alps (Austria, France, Italy), Massif Central (France), Pyrenees (Spain). Actors interviewed were farmers, cooperatives, retailers and associations. A systems thinking approach was applied to develop a conceptual map (Causal Loop Diagram, CLD) describing the contribution of the dairy value chain to ISDH, through the interpretation of the viewpoints of interviewed actors. For each case, the factors contributing to ISDH were identified, then clustered within related topics. Topics from all the cases were used to develop a CLD, and subsystems and leverage points identified. Six interconnected subsystems were identified: local resources, environment, dairy production, collaboration, supply chain and socio-economic. Four leverage points were also identified: public subsidies, feed autonomy, certification of product, and added value. In conclusion, the dairy value chain provides the following benefits aligned with the dimensions of ISDH: landscape maintenance and ecosystem services, quality of dairy products and added value, inclusive governance for actors, reduction of environmental impact, and local development. This model delivers a decision-making tool for the actors involved in the dairy value chain, to prioritise strategic interventions. [ABSTRACT FROM AUTHOR]

Traceability in equipment rental systems enhances security, reliability, and operational transparency by providing the ability to accurately track leased equipment. Challenges in implementing traceability include difficulties in collecting accurate data, the absence of standardized recording practices, and the complexities of integrating technology to ensure complete tracking. This research aims to identify variables affecting the traceability system thinking to improve its efficiency in ongoing business processes. A qualitative descriptive approach is used to offer comprehensive insights into implementing traceability in equipment rental systems, focusing on oil and gas support companies. The study employs the causal loop diagram (CLD) method to dynamically map and identify traceability process variables. Findings show that traceability enables more precise tracking of equipment movement and usage, enhancing inventory management and streamlining maintenance. The CLD method reveals the dynamic relationships between system variables such as equipment availability, maintenance needs, and customer satisfaction, which guide continuous improvement. These results provide stakeholders with valuable insights for optimizing efficiency and service quality in equipment rental operations, particularly in oil and gas support companies. Enhanced traceability can significantly boost operational effectiveness and customer satisfaction. [ABSTRACT FROM AUTHOR]

Sustainable tourism is a dynamic, complex system in which continuous interaction between economic, social, and environmental components will take place. The complexity of the system occurs because of nonlinear interactions between these components. Further, in a dynamic condition, econometric models based on historical data will not provide a realistic solution. However, the plan towards achieving tourism sustainability is mostly based on the past behaviour of heterogeneous factors and assumes that these factors will behave in the same way in the future as well. This approach is inefficient for understanding the underlying structure of the complex system and fails to address the issue of sustainability in a feasible way. Therefore, the present study addresses the issue of sustainable tourism using a system dynamic approach for Mussoorie, India. The results of the study reveal that the existing tourism policy is more in favour of enhancement of tourism at the cost of degrading air quality through increase in carbon emissions, loss of water spring bodies, increase in noise pollution, over exploitation of natural resources and reflecting the myopic approach of the existing policy. This study confirms that the existing approach will emasculate the objective of sustainable tourism. [ABSTRACT FROM AUTHOR]

In Egypt, planning practice is physical and rooted in design principles, resulting in plans that seldom consider the impact of land use and land cover changes on the environment. Most used planning models are static. The paper offers urban metabolism and dynamic modeling as an alternative mode for decision making. It models population growth and expanded economic activities that characterize rapid urbanization and induce changes in land use affecting various urban economic sectors using the Greater Cairo Region (GCR) as a case study. Urban transportation contributes to climate change. The authors used secondary data and satellite images to detect land use and cover changes since 2005. After building a stock-flow diagram to describe the system's structure, they used dynamic modeling and GIS to assess the impact of transportation on air quality. Results indicate that the population of GCR will range from 33.348 to 40.334 million in 2050. The emissions from transportation will be around 52,521.2 Gg, which is beyond the ability of the region's ecosystems to store carbon. These findings shed doubt about the ability of GCR to reach carbon neutrality and, therefore, call for strict measures to control emitting GHGs and change in planning practices and education. [ABSTRACT FROM AUTHOR]

Evaluating whether sustainability indicator schemes contribute to better sustainable destination management has proven challenging. We adopt a systems thinking approach to shed light on the elusive impacts of sustainable tourism indicator schemes. We conduct online participatory workshops with 19 experts in sustainable tourism monitoring, to produce a causal loop diagram that illustrates how destination systems behave when indicator schemes are implemented. The results show that until now, these schemes have been expected to follow utopian, evidence-based, policy pathways to change, but we now understand that this linear-thinking approach fails to recognize the complex interplay of factors that occur during implementation. We find that indicator schemes can spark a rich, yet unappreciated, series of conceptual, instrumental, and structural dynamics. We conclude that the hidden power of these schemes lies in their ability to foster dialog, stimulate learning, incentivize network development, challenge stakeholder worldviews, and steer systems change toward sustainable destination management. [ABSTRACT FROM AUTHOR]

Over the years, the process of studying, exploring, and extracting oil has undergone numerous transformations. On the one hand, the limitations arising from the depletion of oil reserves and the increasing global demand for this valuable commodity, and on the other hand, the growing dependence of industries on fossil fuels, lack of integration in optimal consumption patterns, labor strikes in the oil sector, wars, and political unrest, and instability in the oil market have led major oil-producing countries to implement a wide range of policies to achieve optimal conditions for oil exploration, extraction, and consumption. Moreover, global concerns about the depletion of strategic oil reserves and worries about achieving sustainable and lasting security in the supply of this product make it imperative to seriously address policy-making in the field of exploration and supply. This paper attempts to study the past and present trends of oil exploration and extraction, examine the main and root causes influencing this process through a system dynamics model, and conduct a content analysis on the best policy-making approach for oil exploration and extraction. The Vensim PLE 7.3.5 software was used to analyze the model components. [ABSTRACT FROM AUTHOR]

Purpose: Despite the wide use of quantitative assessment to identify the relationship between green logistics (GL) practices and the sustainability performance (SP) of firms, results of these studies are inconsistent. A lack of theoretical foundation has been cited as a potential reason for these contradictory findings. This study aims to explore the relationship between GL practices and SP qualitatively and to provide a theoretical foundation for this link. Design/methodology/approach: Following a multi-methodology approach, the authors used the grounded theory method (GTM) to investigate perceived relationships through qualitative analysis and adopted the system thinking (ST) approach to identify causal relationships using causal loop diagrams (CLDs). Findings: The authors identified different sustainability practices under three major categories: logistics capabilities, resource-related practices and people-related practices. This analysis showed the relationships among these practices are non-linear. Based on the results, the authors developed three propositions and introduced a theoretical foundation for the relationship between GL practices and SP. Practical implications: Managerial personnel can use the theoretical foundation provided by this study when making decisions on GL practices adoption. This theoretical foundation suggests applying a holistic approach that can help optimize SP by selecting suitable practices. On the other hand, researchers can use a multi-methodology approach suggested by this study to explore complex social issues. Originality/value: This study contributes to the knowledge from a methodology perspective as no previous studies have been conducted to identifying the relationship between GL practices and SP by combining GTM and ST approaches. This combination can be extended to build system dynamics models for sustainable logistics impacts bringing novelty to the research field of sustainable logistics. [ABSTRACT FROM AUTHOR]

Abstract The growing number of connected vehicles has led to an increased focus on Vehicle-to-Everything (V2X) communication in the field of transport research. This communication paradigm facilitates cooperation between vehicles and infrastructure to address traffic challenges such as efficiency, sustainability and safety. The development and standardisation of such Cooperative Intelligent Transport Systems (C-ITS) has been pursued in several projects. Beyond technical considerations, assessing the effect of these applications in terms of various impact categories is of paramount importance. However, existing research tends to examine impact categories such as efficiency, sustainability, safety, psychological or socioeconomic impacts separately, often overlooking potential interactions and interdependencies. This approach is inadequate as impacts on one category can have both cascading effects on others and rebound effects. To address this gap, this paper proposes a system dynamics approach using Causal Loop Diagrams (CLD) to illustrate the interconnectedness of impact categories and the potential impacts of C-ITS services. By depicting general relationships, interdependencies and feedback loops between impact category elements, the model accommodates the introduction of single or multiple C-ITS services as separate modules, allowing an analysis of their combined effects on the overall system. To this end, two use cases demonstrate the applicability of the developed CLD and illustrate some of the multiple interrelations between the effects of C-ITS services. The results of this paper support road operators and researchers when setting up the impact assessment of C-ITS services by revealing the dynamic and intertwined nature of different impact categories.

Abstract This research investigates the benefits of the dairy value chain beyond food provision, and its contribution to inclusive sustainable development (ISDH) in European highlands. Transdisciplinary teams interviewed and analysed 11 cases related to the dairy value chain sourced from three highland regions in Europe: Alps (Austria, France, Italy), Massif Central (France), Pyrenees (Spain). Actors interviewed were farmers, cooperatives, retailers and associations. A systems thinking approach was applied to develop a conceptual map (Causal Loop Diagram, CLD) describing the contribution of the dairy value chain to ISDH, through the interpretation of the viewpoints of interviewed actors. For each case, the factors contributing to ISDH were identified, then clustered within related topics. Topics from all the cases were used to develop a CLD, and subsystems and leverage points identified. Six interconnected subsystems were identified: local resources, environment, dairy production, collaboration, supply chain and socio-economic. Four leverage points were also identified: public subsidies, feed autonomy, certification of product, and added value. In conclusion, the dairy value chain provides the following benefits aligned with the dimensions of ISDH: landscape maintenance and ecosystem services, quality of dairy products and added value, inclusive governance for actors, reduction of environmental impact, and local development. This model delivers a decision-making tool for the actors involved in the dairy value chain, to prioritise strategic interventions.

Over the years, the process of studying, exploring, and extracting oil has undergone numerous transformations. On the one hand, the limitations arising from the depletion of oil reserves and the increasing global demand for this valuable commodity, and on the other hand, the growing dependence of industries on fossil fuels, lack of integration in optimal consumption patterns, labor strikes in the oil sector, wars, and political unrest, and instability in the oil market have led major oil-producing countries to implement a wide range of policies to achieve optimal conditions for oil exploration, extraction, and consumption. Moreover, global concerns about the depletion of strategic oil reserves and worries about achieving sustainable and lasting security in the supply of this product make it imperative to seriously address policy-making in the field of exploration and supply. This paper attempts to study the past and present trends of oil exploration and extraction, examine the main and root causes influencing this process through a system dynamics model, and conduct a content analysis on the best policy-making approach for oil exploration and extraction. The Vensim PLE 7.3.5 software was used to analyze the model components.

This paper presents causal loop diagrams (CLDs) as tools for studying complex public health problems like health inequality. These problems often involve feedback loops—a characteristic of complex systems not fully integrated into mainstream epidemiology. CLDs are conceptual models that visualize connections between system variables. They are commonly developed through literature reviews or participatory methods with stakeholder groups. These diagrams often uncover feedback loops among variables across scales (e.g. biological, psychological and social), facilitating cross-disciplinary insights. We illustrate their use through a case example involving the feedback loop between sleep problems and depressive symptoms. We outline a typical step-by-step process for developing CLDs in epidemiology. These steps are defining a specific problem, identifying the key system variables involved, mapping these variables and analysing the CLD to find new insights and possible intervention targets. Throughout this process, we suggest triangulating between diverse sources of evidence, including domain knowledge, scientific literature and empirical data. CLDs can also be evaluated to guide policy changes and future research by revealing knowledge gaps. Finally, CLDs may be iteratively refined as new evidence emerges. We advocate for more widespread use of complex systems tools, like CLDs, in epidemiology to better understand and address complex public health problems. [ABSTRACT FROM AUTHOR]

There is a gap in the literature regarding the complex interrelationships among hamstring injury (HI) risk factors. System dynamics (SD) modeling is considered an appropriate approach for understanding the complex etiology of HI for effective injury prevention. This study adopted the SD method and developed a causal loop model (CLD) to elucidate the intricate relationships among HI risk factors. This is performed by combining literature evidence and insights from expert stakeholders through a group model building (GMB) approach. The GMB methodology facilitated the identification of sixty-five critical factors influencing the HI risk, revealing the dynamic interplay between factors. Stakeholder engagement underscored the importance of previous injury characteristics (level of influence of previous injury, severity of previous injury, quality and size of scar tissue) and the quality of rehabilitation. HI-CLD revealed that many factors had indirect effects on HI risk. The HI-causal loop model establishes a foundation for a future stock and flow quantitative SD model aiming to advance HI prevention strategies through an interdisciplinary collaborative effort. These findings underscore the complexity of HI prevention, necessitating a holistic approach that integrates the views of diverse professional expertise. Appropriate inter-professional collaboration and continuous athlete screening are important for effective injury prevention strategies. [ABSTRACT FROM AUTHOR]

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Purpose: Electrification is a promising solution for decarbonising the road freight transport system, but it is challenging to understand its impact on the system. The purpose of this research is to provide a system-level understanding of how electrification impacts the road freight transport system. The goal is to develop a model that illustrates the system and its dynamics, emphasising the importance of understanding these dynamics in order to comprehend the effects of electrification. Design/methodology/approach: The main methodological contribution of the study is the combination of the multi-layer model with system dynamics methodology. A mixed methods approach is used, including group model building, impact analysis, and literature analysis. Findings: The study presents a conceptual multi-layer dynamic model, illustrating the complex causal relationships between variables in the different layers and how electrification impacts the system. It distinguishes between direct and induced impacts, along with potential policy interventions. Moreover, two causal loop diagrams (CLDs) provide practical insights: one explores factors influencing electric truck attractiveness, and the other illustrates the trade-off between battery size and fast charging infrastructure for electric trucks. Originality/value: The study provides stakeholders, particularly policymakers, with a system-level understanding of the different impacts of electrification and their ripple effects. This understanding is crucial for making strategic decisions and steering the transition towards a sustainable road freight transport system. [ABSTRACT FROM AUTHOR]

Due to the acceleration of global environmental change and urbanization, landscape sustainability assessment and optimization have become key tasks in urban planning and management. Computer simulation technology, especially System Dynamics (SD) models, can simulate the dynamic behavior of landscape systems and provide scientific basis for decision-making. This study used the SD model to construct a landscape sustainability assessment model. Firstly, key factors affecting landscape sustainability, such as land use, water resource management, and biodiversity conservation, were identified through literature review and expert interviews. Then, the Causal Loop Diagram (CLD) was used to analyze the interactions between these factors. Next, the model in SD modeling software was built; parameters and initial conditions were set; model validation and calibration were performed. Research has found that the SD model can effectively simulate the dynamic changes of landscape systems, providing a comprehensive, dynamic, and quantitative method for landscape sustainability assessment. In addition, compared to traditional management strategies, the ecological service value of the same location under the SD method could increase by 91€; the Shannon Wiener index could increase by 0.97; the soil organic matter content could increase by 11.27g/kg. The comparative experimental data results indicated that the SD model had significant advantages in landscape sustainability assessment and optimization, and could provide sustained support for landscape sustainability. Therefore, computer simulation technology has important application value in landscape sustainability assessment and optimization. [ABSTRACT FROM AUTHOR]

Banyumas is one of the famous tourist destinations in Central Java with its natural attractions. Tourism growth in Banyumas requires capable and sustainable transportation infrastructure. However, current policies and investments in Banyumas are inappropriate for developing transportation and tourism infrastructure that creates non-significant impact. Therefore, the development of tourism projection should consider environmental, social, economics, and technology interrelated in developing transportation and tourism infrastructure issues. The tourism supply chain has a unique structure that is different from typical supply chains with high complexity because many stakeholders are involved. This research aims to project Banyumas tourism development with the impact of transportation system improvement. This conceptual model was developed from literature reviews and other necessary sources, and then validated by experts. The conceptual model examines the relationship between variables involved in the tourism supply chain and transportation system in Banyumas that can be developed into a quantitative model using Causal Loop Diagram, an initial stage of system dynamics. This model used to analyze the behavior of visitor projection of the Banyumas tourism supply chain system in Indonesia. [ABSTRACT FROM AUTHOR]

Tingting Qin, Xingming Li, Kun Qiao, Xinyuan Bai, Mingyu Gu, Yao Wang School of Public Health, Capital Medical University, Beijing, People’s Republic of ChinaCorrespondence: Xingming Li, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmenwai, Fengtai District, Beijing, 100069, People’s Republic of China, Email xingmingli@ccmu.edu.cnPurpose: Group Model Building (GMB) is a qualitative method that refers to a participatory process. This project aims to identify barriers and facilitators of hypertension management in primary health care in China, through which, the leverage point for intervention may be found.Methods: The GMB was used to identify the factors influencing hypertension management. Graphs over time and causal loop diagram (CLD) were main tools of GMB. To propose the influencing factors, key stakeholders were invited to participate in a workshop. During the workshop, stakeholders were encouraged to plot the graphs over time of the variables about research issues and give a descriptive explanation. And based on this, a CLD was initially developed to establish a model of the interaction of factors. After the workshop, the research group further improved the CLD through repeated mutual discussions, and gave feedback to the participants. The Vensim PLE 9.0 software package was used to build CLD.Results: A total of 14 key stakeholders were invited to participate in the workshop. Finally, 26 influencing factors were identified, which were divided into three dimensions, including the institutional, the community health workers (CHWs), and the patient level. And 5 reinforcing loops and 4 balancing loops were formed in the CLD. Promoting the building of the Medical Community/Regional Medical Association, implementing the family doctor contract service (FDCS), and enhancing the motivation of CHWs may be potential leverage points for hypertension management in China.Conclusion: By using GMB, we have identified key factors in the management of hypertension in primary health care and provided comprehensive suggestions to overcome the obstacles.Keywords: group model building, hypertension management, primary health care, causal loop diagram, system dynamics

Transportation is crucial for the progress of a nation, and sustainable transportation policies are necessary for long-term development. Among these policies, fuel and vehicle pricing strategies significantly impact the economy, society, and environment. To effectively formulate transportation policies, policymakers must understand the factors influencing policy implementation and explore different approaches to fuel pricing, vehicle pricing, and sustainable transportation. This study aims to develop a comprehensive causal loop diagram (CLD) using the System Dynamics (SD) approach to identify factors and interrelationships within the transportation system. The CLD provides a holistic overview of the complexities and feedback loops inherent to fuel and vehicle pricing policies. The findings contribute to evidence-based decision-making and facilitate the formulation of effective and sustainable transportation policies in the country.

Abstract Background Healthy sleep is crucial for the physical and mental wellbeing of adolescents. However, many adolescents suffer from poor sleep health. Little is known about how to effectively improve adolescent sleep health as it is shaped by a complex adaptive system of many interacting factors. This study aims to provide insights into the system dynamics underlying adolescent sleep health and to identify impactful leverage points for sleep health promotion interventions. Methods Three rounds of single-actor workshops, applying Group Model Building techniques, were held with adolescents (n = 23, 12–15 years), parents (n = 14) and relevant professionals (n = 26). The workshops resulted in a multi-actor Causal Loop Diagram (CLD) visualizing the system dynamics underlying adolescent sleep health. This CLD was supplemented with evidence from the literature. Subsystems, feedback loops and underlying causal mechanisms were identified to understand overarching system dynamics. Potential leverage points for action were identified applying the Action Scales Model (ASM). Results The resulting CLD comprised six subsystems around the following themes: (1) School environment; (2) Mental wellbeing; (3) Digital environment; (4) Family & Home environment; (5) Health behaviors & Leisure activities; (6) Personal system. Within and between these subsystems, 16 reinforcing and 7 balancing feedback loops were identified. Approximately 60 potential leverage points on different levels of the system were identified as well. Conclusions The multi-actor CLD and identified system dynamics illustrate the complexity of adolescent sleep health and supports the need for developing a coherent package of activities targeting different leverage points at all system levels to induce system change.

Background: This study takes on the challenge of quantifying a complex causal loop diagram describing how poverty and health affect each other, and does so using longitudinal data from The Netherlands. Furthermore, this paper elaborates on its methodological approach in order to facilitate replication and methodological advancement. Methods: After adapting a causal loop diagram that was built by stakeholders, a longitudinal structural equation modelling approach was used. A cross-lagged panel model with nine endogenous variables, of which two latent variables, and three time-invariant exogenous variables was constructed. With this model, directional effects are estimated in a Granger-causal manner, using data from 2015 to 2019. Both the direct effects (with a one-year lag) and total effects over multiple (up to eight) years were calculated. Five sensitivity analyses were conducted. Two of these focus on lower-income and lower-wealth individuals. The other three each added one exogenous variable: work status, level of education, and home ownership. Results: The effects of income and financial wealth on health are present, but are relatively weak for the overall population. Sensitivity analyses show that these effects are stronger for those with lower incomes or wealth. Physical capability does seem to have strong positive effects on both income and financial wealth. There are a number of other results as well, as the estimated models are extensive. Many of the estimated effects only become substantial after several years. Conclusions: Income and financial wealth appear to have limited effects on the health of the overall population of The Netherlands. However, there are indications that these effects may be stronger for individuals who are closer to the poverty threshold. Since the estimated effects of physical capability on income and financial wealth are more substantial, a broad recommendation would be that including physical capability in efforts that are aimed at improving income and financial wealth could be useful and effective. The methodological approach described in this paper could also be applied to other research settings or topics. [ABSTRACT FROM AUTHOR]

Reintroducing locally extinct/extirpated species has been considered as an approach for restoring ecosystems. Although such projects share the same goals of rebuilding previously affected ecosystems, the overall impacts that such reintroductions generate on both ecosystems and human society, i.e., on the social-ecological system, are difficult to measure. We propose a system dynamics approach, a platform on which both natural and social scientists could collaborate to identify the social-ecological impacts of species reintroduction as well as factors that affect such decision making. We use cases in Japan to demonstrate the potential applicability of system dynamics in terms of (1) understanding the impacts of a previously reintroduced species, the Oriental Stork (Ciconia boyciana), and (2) predicting the impacts of reintroduction of wolves (Canis lupus). We present a causal loop diagram of the social and ecological effects of Oriental Stork reintroduction, and we discuss how the relationships between factors could be articulated based on empirical data and ongoing projects in Japan. The model demonstrates how local residents began to appreciate the rich biodiversity, including the Oriental Stork, following its reintroduction, and how public support toward such reintroduction enhanced further projects to reintroduce these species in different parts of Japan. A similar diagram, created to illustrate the social and ecological effects of the potential reintroduction of wolves to Japan, demonstrates how social factors such as environmental education and public attitudes could affect decision making as well as ecological factors such as predator-prey dynamics and overall biodiversity. Further, humanwolf conflicts could negatively affect the overall loop. Creating causal loop diagrams can help managers and stakeholders understand that species reintroduction projects need to be considered via an interdisciplinary approach. The models illustrate that these problems are dynamic and that the factors affecting or affected by such projects change over time, implying the importance of both the spatial and temporal scales in managing reintroduction projects. [ABSTRACT FROM AUTHOR]

As part of the global efforts to mitigate climate change, policymakers are designing measures to reduce the carbon emissions of the freight transport system. As global agreements for decarbonisation specify strict time windows, it is important to understand the speed at which the transport system is capable of changing. Our paper proposes a causal loop diagram based on System Dynamics that qualitatively maps the system's causal and dynamic responses to five key decarbonisation strategies. As the main contribution, this conceptual model provided a broad overview of the freight system, formed by subsystems that interact with each other through feedback loops, forming its dynamic behaviour. Through this conceptual modelling effort, we can identify the rebound effects of policies over the whole system, which could defeat the desired decarbonisation results. The model pointed out policies and feedback loops as the dynamic levers to promote freight decarbonisation and influence the system's dynamic responses. [ABSTRACT FROM AUTHOR]

The research is expected to provide in-depth insight into how the role of the project owner affects the success of port infrastructure projects using a design-build approach, as well as provide a basis for increased efficiency and effectiveness in the implementation of the project. This research proposes a causal loop diagram model to provide an overview of the influence of the Owner's role in achieving the cost, time, and quality success of the Port Infrastructure Design-Build project. Research variables are obtained through in-depth literature studies and interviews with project owners and project practitioners experienced in design-build projects. Based on the literature study in this study, it has been formulated that the critical role of the owner is an essential factor of the owner in carrying out the project to achieve the goals that have been set. [ABSTRACT FROM AUTHOR]

Desert locust (Schistocerca gregaria) infestations cause significant damage to crops and pastureland, impeding food security and livelihoods globally. In recent years, some East African countries have suffered severe desert locust outbreaks, causing significant harm to agriculture and local communities. To comprehensively understand and mitigate the socio‐economic impacts of this pest, an integrated assessment approach is crucial. This study proposes an integrated assessment model that combines ecological, economic, and social dimensions to analyze the multifaceted impacts of the desert locust on the rate of urbanization changes, farming expansion, and food production and how they lead to food unavailability (demand, supply, and price) and food and nutrition insecurity in Eastern Africa. A system dynamics‐based assessment model was first developed for Sudan using the dynamic relations among the factors and their variations over time and how they affect the socio‐economic variables. The developed model was used to spatially simulate the impacts over the entire Eastern Africa. Various scenarios were further simulated and analyzed, incorporating different policy options to effectively mitigate the impacts. Results demonstrated that in all the countries, desert locusts extensively contribute to the slowing down of farming expansion and food production and supply. Consequently, these factors lead to increased urbanization rates through people rural‐urban migration and food demand at different magnitudes across different countries. By considering both short‐term and long‐term effects, this approach aims to provide policymakers, researchers, and practitioners with a holistic understanding of the complex dynamics involved and inform effective management strategies. For example, communities equipped with accurate breeding detection tools and employing an integrated pest management strategy combining chemical pesticides and biopesticides had the highest potential for effectively mitigating the future impacts of desert locusts for enhancing community livelihood. Plain Language Summary: Desert locusts are a major problem for agriculture and communities in East Africa. They eat crops and grasslands, which can lead to food shortages and higher prices. To better understand and deal with this issue, we have created a model that looks at how locusts affect things like farming, urbanization, and food supply. We studied this in Sudan and then applied it to the whole of East Africa. The results showed that locusts make farming harder and push more people to move from rural areas to cities. This causes more demand for food in cities. The study tested different ways to deal with locusts and found that communities with good tools for detecting locusts and using both chemical and biopesticide control methods were the best at reducing the impact of locusts on their lives. This study gives policymakers and others a better understanding of how locusts affect communities and how to manage them effectively in the future. Key Points: In Eastern Africa, desert locusts swarm in vast numbers, devouring crops, and vegetation, causing crop production losses ranging from 42% to 69%The system dynamics model was employed for a comprehensive analysis of the impacts, scenarios, and policy options for mitigating desert locust effectsDesert locusts hinder farming, reduce food production, spur urbanization, and heighten food insecurity across affected Eastern African countries [ABSTRACT FROM AUTHOR]

Background: Healthy sleep is crucial for the physical and mental wellbeing of adolescents. However, many adolescents suffer from poor sleep health. Little is known about how to effectively improve adolescent sleep health as it is shaped by a complex adaptive system of many interacting factors. This study aims to provide insights into the system dynamics underlying adolescent sleep health and to identify impactful leverage points for sleep health promotion interventions. Methods: Three rounds of single-actor workshops, applying Group Model Building techniques, were held with adolescents (n = 23, 12–15 years), parents (n = 14) and relevant professionals (n = 26). The workshops resulted in a multi-actor Causal Loop Diagram (CLD) visualizing the system dynamics underlying adolescent sleep health. This CLD was supplemented with evidence from the literature. Subsystems, feedback loops and underlying causal mechanisms were identified to understand overarching system dynamics. Potential leverage points for action were identified applying the Action Scales Model (ASM). Results: The resulting CLD comprised six subsystems around the following themes: (1) School environment; (2) Mental wellbeing; (3) Digital environment; (4) Family & Home environment; (5) Health behaviors & Leisure activities; (6) Personal system. Within and between these subsystems, 16 reinforcing and 7 balancing feedback loops were identified. Approximately 60 potential leverage points on different levels of the system were identified as well. Conclusions: The multi-actor CLD and identified system dynamics illustrate the complexity of adolescent sleep health and supports the need for developing a coherent package of activities targeting different leverage points at all system levels to induce system change. [ABSTRACT FROM AUTHOR]

The purpose of this report is to provide a perspective on the use of qualitative systems mapping, provide examples of physical activity (PA) systems maps, discuss the role of PA systems mapping in the context of iterative learning to derive breakthrough interventions, and provide actionable recommendations for future work. Systems mapping methods and applications for PA are emerging in the scientific literature in the study of complex health issues and can be used as a prelude to mathematical/computational modeling where important factors and relationships can be elucidated, data needs can be prioritized and guided, interventions can be tested and (co)designed, and metrics and evaluations can be developed. Examples are discussed that describe systems mapping based on Group Model Building or literature reviews. Systems maps are highly informative, illustrate multiple components to address PA and physical inactivity issues, and make compelling arguments against single intervention action. No studies were identified in the literature scan that considered cardiorespiratory fitness the focal point of a systems maps. Recommendations for future research and education are presented and it is concluded that systems mapping represents a valuable yet underutilized tool for visualizing the complexity of PA promotion. [ABSTRACT FROM AUTHOR]

Project risk management (PRM) involves identifying risks, assessing their impact, and developing a contingency plan. A structured contingency management (CM) approach prevents subjective biases in analyzing risks and developing responses. Previous studies have either focused on improving the accuracy of risk estimates or analyzed, from a qualitative perspective, the relationships between perceived risk and project performance. This study aimed to improve PRM by providing a risk-perception-based contingency management framework (CMF). The CMF guides contingency depletion based on two short- and long-term cost overrun indicators and their respective thresholds. Thresholds and the initial contingency reserve amount are determined by applying the Monte Carlo method to a stochastic, discrete-event, finite-horizon, dynamic project simulation model. The study developed the CMF through a structured approach, validating the simulation model on eight specific project configurations. The results prove that the framework can be applied to any project, shaping the risk response strategy. This study contributes to PRM by explaining the relationships between risk perception and risk responses and providing a prescriptive CM tool. [ABSTRACT FROM AUTHOR]

Sustainable development (SD) is of prime importance in the present world, where resources are depleting fast and causing conflicts among nations to control essential resources. Since the construction industry (CI) consumes most of these resources, Construction Sustainability (CS) is a key focus of SD. Among the three pillars of sustainability, i.e., economic, environmental, and social, the first two have been amply addressed by researchers. However, the social aspects have been neglected or under-researched so far. The current research humbly attempts to fill this gap. Accordingly, a System Dynamics Model (SDM) has been developed to address this issue. After a comprehensive literature review, questionnaire survey, content analysis, and gathering the opinions of ten experts from CI, 11 key factors of social CS were identified. Using the system thinking approach, a causal loop diagram (CLD) was developed to assess the intensity and polarity of these factors. The CLD encompassed eight reinforcing loops and one balancing loop. Based on the CLD, an SDM was developed and simulated over 3 years. Primarily, the SDM had two stocks: "Government support for sustainable construction" and "Stakeholder awareness and knowledge". An additional stock named "Construction Sustainability" was added to observe the combined effect of the system. The results showed that CS increased over time. The CLD and resulting SDM help in understanding the complex interaction of the social CS factors and thereby addressing the associated complexity of the effects of these varied factors on a project. Such knowledge can be valuable for anyone dealing with projects where social factors play a significant role. The proposed SDM provides a structured approach to understanding and visualizing the intricate relationships and feedback loops within a social system, aiding in more effective decision making and problem solving. [ABSTRACT FROM AUTHOR]

Banyumas is one of the famous tourist destinations in Central Java with its natural attractions. Tourism growth in Banyumas requires capable and sustainable transportation infrastructure. However, current policies and investments in Banyumas are inappropriate for developing transportation and tourism infrastructure that creates non-significant impact. Therefore, the development of tourism projection should consider environmental, social, economics, and technology interrelated in developing transportation and tourism infrastructure issues. The tourism supply chain has a unique structure that is different from typical supply chains with high complexity because many stakeholders are involved. This research aims to project Banyumas tourism development with the impact of transportation system improvement. This conceptual model was developed from literature reviews and other necessary sources, and then validated by experts. The conceptual model examines the relationship between variables involved in the tourism supply chain and transportation system in Banyumas that can be developed into a quantitative model using Causal Loop Diagram, an initial stage of system dynamics. This model used to analyze the behavior of visitor projection of the Banyumas tourism supply chain system in Indonesia.

Abstract Background Interest in applying a complex systems approach to understanding socioeconomic inequalities in health is growing, but an overview of existing research on this topic is lacking. In this systematic scoping review, we summarize the current state of the literature, identify shared drivers of multiple health and health behavior outcomes, and highlight areas ripe for future research. Methods SCOPUS, Web of Science, and PubMed databases were searched in April 2023 for peer-reviewed, English-language studies in high-income OECD countries containing a conceptual systems model or simulation model of socioeconomic inequalities in health or health behavior in the adult general population. Two independent reviewers screened abstracts and full texts. Data on study aim, type of model, all model elements, and all relationships were extracted. Model elements were categorized based on the Commission on Social Determinants of Health framework, and relationships between grouped elements were visualized in a summary conceptual systems map. Results A total of 42 publications were included; 18 only contained a simulation model, 20 only contained a conceptual model, and 4 contained both types of models. General health outcomes (e.g., health status, well-being) were modeled more often than specific outcomes like obesity. Dietary behavior and physical activity were by far the most commonly modeled health behaviors. Intermediary determinants of health (e.g., material circumstances, social cohesion) were included in nearly all models, whereas structural determinants (e.g., policies, societal values) were included in about a third of models. Using the summary conceptual systems map, we identified 15 shared drivers of socioeconomic inequalities in multiple health and health behavior outcomes. Conclusions The interconnectedness of socioeconomic position, multiple health and health behavior outcomes, and determinants of socioeconomic inequalities in health is clear from this review. Factors central to the complex system as it is currently understood in the literature (e.g., financial strain) may be both efficient and effective policy levers, and factors less well represented in the literature (e.g., sleep, structural determinants) may warrant more research. Our systematic, comprehensive synthesis of the literature may serve as a basis for, among other things, a complex systems framework for socioeconomic inequalities in health.

To achieve the goals of carbon peaking and carbon neutrality, China is actively promoting carbon reduction in many areas. Agriculture is one of the main sources of greenhouse gas emissions, and promoting the development of low-carbon agriculture is a critical way to achieve carbon reduction targets. Taking Chongming District in Shanghai as an example, this study summarizes the experience of low-carbon agricultural development in Chongming and analyzes the problems and challenges faced during its development. Finally, based on the system dynamics method, the causal relationship of carbon emission in Chongming's agricultural development is constructed, and feasible loop optimization suggestions are put forward. [ABSTRACT FROM AUTHOR]

Background: Interest in applying a complex systems approach to understanding socioeconomic inequalities in health is growing, but an overview of existing research on this topic is lacking. In this systematic scoping review, we summarize the current state of the literature, identify shared drivers of multiple health and health behavior outcomes, and highlight areas ripe for future research. Methods: SCOPUS, Web of Science, and PubMed databases were searched in April 2023 for peer-reviewed, English-language studies in high-income OECD countries containing a conceptual systems model or simulation model of socioeconomic inequalities in health or health behavior in the adult general population. Two independent reviewers screened abstracts and full texts. Data on study aim, type of model, all model elements, and all relationships were extracted. Model elements were categorized based on the Commission on Social Determinants of Health framework, and relationships between grouped elements were visualized in a summary conceptual systems map. Results: A total of 42 publications were included; 18 only contained a simulation model, 20 only contained a conceptual model, and 4 contained both types of models. General health outcomes (e.g., health status, well-being) were modeled more often than specific outcomes like obesity. Dietary behavior and physical activity were by far the most commonly modeled health behaviors. Intermediary determinants of health (e.g., material circumstances, social cohesion) were included in nearly all models, whereas structural determinants (e.g., policies, societal values) were included in about a third of models. Using the summary conceptual systems map, we identified 15 shared drivers of socioeconomic inequalities in multiple health and health behavior outcomes. Conclusions: The interconnectedness of socioeconomic position, multiple health and health behavior outcomes, and determinants of socioeconomic inequalities in health is clear from this review. Factors central to the complex system as it is currently understood in the literature (e.g., financial strain) may be both efficient and effective policy levers, and factors less well represented in the literature (e.g., sleep, structural determinants) may warrant more research. Our systematic, comprehensive synthesis of the literature may serve as a basis for, among other things, a complex systems framework for socioeconomic inequalities in health. [ABSTRACT FROM AUTHOR]

Complexity science and systems thinking are increasingly recognized as relevant paradigms for studying systems where biology, psychology, and socioenvironmental factors interact. The application of systems thinking, however, often stops at developing a conceptual model that visualizes the mapping of causal links within a system, e.g., a causal loop diagram (CLD). While this is an important contribution in itself, it is imperative to subsequently formulate a computable version of a CLD in order to interpret the dynamics of the modeled system and simulate "what if" scenarios. We propose to realize this by deriving knowledge from experts' mental models in biopsychosocial domains. This article first describes the steps required for capturing expert knowledge in a CLD such that it may result in a computational system dynamics model (SDM). For this purpose, we introduce several annotations to the CLD that facilitate this intended conversion. This annotated CLD (aCLD) includes sources of evidence, intermediary variables, functional forms of causal links, and the distinction between uncertain and known-to-be-absent causal links. We propose an algorithm for developing an aCLD that includes these annotations. We then describe how to formulate an SDM based on the aCLD. The described steps for this conversion help identify, quantify, and potentially reduce sources of uncertainty and obtain confidence in the results of the SDM's simulations. We utilize a running example that illustrates each step of this conversion process. The systematic approach described in this article facilitates and advances the application of computational science methods to biopsychosocial systems. Systems thinking is essential to study complex problems that arise from many interacting system parts at different levels. An example of a complex problem is depression, related to individual biological and psychological characteristics, but also our society and environment. To schematically describe which system parts are important in explaining a complex problem, it is common to draw a visual representation of the system that produces the problem, i.e., a causal loop diagram (CLD). Even though a CLD can tell us a lot about the origins of a complex problem, it cannot show what the effect would be if a system part were changed. For example, even if the CLD indicates that income inequality is an important system part in explaining depression, we still cannot tell from just this visual representation whether depression rates would change if income inequality were reduced. To answer such questions, we need to develop a computational model reflecting the CLD: a computer program that can calculate what would happen under different conditions. This article describes how to create a CLD that can be converted into a computational system dynamics model. We propose to achieve this conversion by asking experts to communicate their knowledge about individual system parts and storing this information within the CLD. This expert knowledge then helps us calculate what happens when all system parts interact simultaneously. This method can aid in answering questions about the effects of changes in system parts for a broader range of complex problems. [ABSTRACT FROM AUTHOR]

The discourse surrounding digital transformation (DT) and sustainable development (SD) is pervasive in contemporary business and organizational operations, with both processes considered indispensable for sustainability. The success or failure of these endeavors hinges significantly on factors such as the behavior and skill sets of individuals within organizations. Thus, the purpose of the paper is twofold: to investigate the perceptions of organizations on digital transformation and sustainable development with regards to skills and education, and, secondly, to use the insights from these perceptions as a starting point for the use of systems thinking as a tool that could assist in achieving these states. To achieve the objective, a research effort was conducted that included desktop research, interviews with experts, and the development of a survey that was disseminated across Europe with questions on digital transformation and sustainable development. Finally, a general causal loop diagram was designed, illustrating the processes of digital transformation and sustainable development within organizations from a top-down view. The study reveals commonalities between DT and SD, recognizing both processes as advantageous with shared deficiencies in specific skill sets. It highlights a synergistic relationship between initiating DT and fostering SD activities. Furthermore, the research underscores the temporal aspects of these processes, acknowledging delayed positive effects and immediate implementation costs that challenge decision-makers to balance long-term benefits with short-term viability. In conclusion, the exploration emphasizes the dynamic nature of DT and SD, urging continual attention to the evolving landscape and the imperative for a shared understanding within organizational contexts. [ABSTRACT FROM AUTHOR]