Causal Loop Diagram Research Articles

Participatory Systems Thinking to Elucidate Drivers of Food Access and Diet Disparities among Minoritized Urban Populations.

The purpose of this study was to use participatory systems thinking to develop a dynamic conceptual framework of racial/ethnic and other intersecting disparities (e.g., income) in food access and diet in Philadelphia and to identify policy levers to address these disparities. We conducted three group model building workshops, each consisting of a series of scripted activities. Key artifacts or outputs included qualitative system maps, or causal loop diagrams, identifying the variables, relationships, and feedback loops that drive diet disparities in Philadelphia, Pennsylvania. We used semi-structured methods informed by inductive thematic analysis and network measures to synthesize findings into a single causal loop diagram. There were twenty-nine participants with differing vantages and expertise in Philadelphia's food system, broadly representing the policy, community, and research domains. In the synthesis model, participants identified 14 reinforcing feedback loops and one balancing feedback loop that drive diet and food access disparities in Philadelphia. The most highly connected variables were upstream factors, including those related to racism (e.g., residential segregation) and community power (e.g., community land control). Consistent with existing frameworks, addressing disparities will require a focus on upstream social determinants. However, existing frameworks should be adapted to emphasize and disrupt the interdependent, reinforcing feedback loops that maintain and exacerbate disparities in fundamental social causes. Our findings suggest that promising policies include those that empower minoritized communities, address socioeconomic inequities, improve community land control, and increase access to affordable, healthy, and culturally meaningful foods.

Compatible effects of adopting imaginary future generations and systems thinking in exploring future challenges: Evidence from a deliberation experiment

AbstractWe adopted an innovative methodology that combines systems thinking with “imaginary future generations” (IFGs), a method for activating “futurability” in people, to discussions about the issues and needs of a future society, and we verified the effectiveness and value of this methodology. We conducted a series of five debate experiments in which groups comprised of company employees and university students worked to formulate a vision of the future state, social issues, and social needs of society in 2050, and to investigate policies that should be adopted in the years ahead. The results of a text analysis of group debates and questionnaire surveys of debate participants showed that (1) adopting IFGs facilitates the exploration of new issues and needs when depicting the images of the future state of society; (2) adopting IFGs gives rise to recognized cognitive changes in debate participants; and (3) combining the IFG methodology with causal loop diagrams (CLDs), a systems thinking tool, makes it possible to generate the effects of systems thinking while simultaneously maintaining a “future generation” perspective. Most importantly, the results show that the IFG methodology and CLDs could be compatible. These findings demonstrate that a combination of IFGs and systems thinking can effectively be used in discussions and decision‐making that deal with complex issues related to the future of society.

Assessing nature’s contributions to people in a peri-urban protected area, southeast Brazil: integrating feedback loops and participatory scenario planning

ABSTRACT Urban expansion is a key driver of change that has been affecting nature’s contributions to people (NCP) in peri-urban regions near metropolitan areas. In southeast Brazil, Campinas Environmental Protected Area (EPA) is a peri-urban, sustainable-use protected area located within the metropolis of Campinas. Campinas EPA provides relevant NCP at the local and regional level, including water provision for 1.2 million people, nature-based tourism and food production. We conducted a participatory, qualitative assessment of past and future trends of NCP at Campinas EPA, in collaboration with the management council of the protected area. We collected data through direct observation, semi-structured interviews and scenario workshops. In our research process, we innovate using the NCP framework, a concept acknowledging multiple values and knowledge systems, coupled with ecosystem services, a concept already understood by management councilors. To assess past trends (2000–2020), we built a causal-loop diagram which depicts an amplifying feedback loop that fosters change towards an urban-dominated state. To assess future trends (2020–2040), we facilitated scenario planning workshops to create and contrast a business-as-usual and a desirable future for NCP, illustrated in the form of artistic panels. We identified a local agroecological farm that represents a seed of good anthropocenes – i.e. the farm is an innovative example of what a positive future could look like, thus providing relevant evidence on how to achieve a desirable scenario. Our findings shed light on how urban expansion within peri-urban areas impacts NCP and suggest strategies for positive transformations.

Artificial Intelligence and the Transformation of Higher Education Institutions: A Systems Approach

Artificial intelligence (AI) advances and the rapid adoption of generative AI tools, like ChatGPT, present new opportunities and challenges for higher education. While substantial literature discusses AI in higher education, there is a lack of a systems approach that captures a holistic view of the structure and dynamics of the AI transformation of higher education institutions (HEIs). To fill this gap, this article develops a causal loop diagram (CLD) to map the causal feedback mechanisms of AI transformation in a typical HEI. We identify important variables and their relationships and map multiple reinforcing and balancing feedback loops accounting for the forces that drive the AI transformation and its impact on value creation in a typical HEI. The model shows how, motivated by AI technology advances, the HEI can invest in AI to improve student learning, research, and administration while dealing with academic integrity problems and adapting to job market changes by emphasizing AI-complementary student skills. We explore model insights, scenarios, and policy interventions and recommend that HEI leaders become systems thinkers to manage the complexity of the AI transformation and benefit from the AI feedback loops while avoiding policy traps that may lead to decline. We also discuss the notion of HEIs influencing the direction of AI and directions for future research on AI transformation and the sustainability of HEIs.

Developing theoretically grounded causal maps to examine and improve policy narratives about global challenges

AbstractThe Sustainable Development Goals present a call to action for all countries to accelerate the implementation of solutions to address the world's biggest challenges. While policy portfolios to achieve such goals should be varied, often dominant policy narratives cluster around limited themes. We use a grounded theory approach to elicit causality from qualitative data to visualize interactions across variables spanning multiple domains influencing global challenges. We develop a comprehensive causal loop diagram, where we assess the impact of dominant policy narratives and expand the formulation of policy options. Our approach serves as an exemplar application of qualitative system dynamics to distill the operational logic of policy narratives that can subsequently be considered in model‐based policy analysis. We illustrate our approach by focusing on the interactions among poverty and hunger and compare policy implications arising from the dominant narratives only versus those arising from a more comprehensive understanding of the interactions. © 2024 The Author(s). System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

The causal loop diagram model of traceability system rental equipment in oil and gas supporting companies

The causal loop diagram model of traceability system rental equipment in oil and gas supporting companies

Socio-Demographic Factors Driving the Choice of Alternative Safe Water Sources and Their Implications for Public Health: Lessons from Goalmari, Bangladesh

This study examined how socio-economic driving forces influence households’ choice of water, ranging from a piped water supply provided by Veolia to untreated sources contaminated with high levels of arsenic and pathogens. Households fall into three cluster groups based on variations in socio-economic status and physical, infrastructure, and institutional elements. About 64% of the variations are related to differences in awareness, willingness, and ability to pay for safe water sources. Families with higher monthly income showed interest in accepting Veolia’s house connection options, resulting in the shutdown of six community tap points and ultimately affecting the low-income households’ accessibility to Veolia water. A causal loop diagram showed five feedback loops influencing the choice of drinking contaminated water. Bayesian Network models were sensitive to the ability, accessibility, and willingness to pay for safe water, deep tube well distributions, installation and maintenance costs, ownership of tube wells, household income level, and the level of awareness. Results suggest that the risks of drinking contaminated water can be minimized by raising awareness; accepting arsenic removal techniques; sharing expenses; training for deep tube well installations and maintenance; increasing Veolia pipeline coverage; and redesigning the tap point distributions. These results help identify the relative importance of such interventions to improve water security in safe water-poor areas.

Prevention of, and response to, sexual harassment at secondary school: A system map

BackgroundSexual harassment in secondary school is common but only recently acknowledged as a widespread problem in the United Kingdom. There is limited research on how schools respond to incidents of sexual harassment. The aim of this study was to understand how school systems shape the dynamics of disclosure, reporting and handling of sexual harassment in school (including behaviours, processes, norms), and to identify opportunities for effecting systems change. MethodsWe used participatory systems mapping to elicit school stakeholders' perspectives on systems factors and their connections. Researchers built the map based on in-person workshops with students (n = 18) and staff (n = 4) from three schools in Scotland. Survey data (n = 638 students; n = 119 staff) was used to augment participant perspectives. The map was validated via three workshops (two online, one in-person) involving students and staff from seven schools. ResultsThe final map (causal loop diagram) represents a hypothesised system of 25 causally connected factors and three feedback loops shaping the disclosure, reporting and handling of sexual harassment. We grouped these factors into four interlinked themes: 1] Knowledge and confidence; 2] Trust in reporting system and processes; 3] Communication, confidentiality and safeguarding; and, 4] Prioritisation of sexual harassment. Conclusions and implicationsThis study highlights the interconnectedness of factors shaping disclosure, reporting and handling of sexual harassment within secondary schools. The map surfaces key challenges for schools and provides a foundation for learning and discussions on where to focus efforts in future.

Adopting a systems-thinking approach to optimise dietary and exercise referral practices for cancer survivors

PurposeService referrals are required for cancer survivors to access specialist dietary and exercise support. Many system-level factors influence referral practices within the healthcare system. Hence, the aim of this study was to identify system-level factors and their interconnectedness, as well as strategies for optimising dietary and exercise referral practices in Australia.MethodsA full-day workshop involving national multidisciplinary key stakeholders explored system-level factors impacting dietary and exercise referral practices. Facilitated group discussions using the nominal group technique identified barriers and facilitators to referral practices based on the six World Health Organisation (WHO) building blocks. The systems-thinking approach generated six cognitive maps, each representing a building block. A causal loop diagram was developed to visualise factors that influence referral practices. Additionally, each group identified their top five strategies by leveraging facilitators and addressing barriers relevant to their WHO building block.ResultsTwenty-seven stakeholders participated in the workshop, including consumers (n = 2), cancer specialists (n = 4), nursing (n = 6) and allied health professionals (n = 10), and researchers, representatives of peak bodies, not-for-profit organisations, and government agencies (n = 5). Common system-level factors impacting on referral practices included funding, accessibility, knowledge and education, workforce capacity, and infrastructure. Fifteen system-level strategies were identified to improve referral practices.ConclusionThis study identified system-level factors and strategies that can be applied to policy planning and practice in Australia.

Evaluating the dynamics of fee-free higher education in South Africa: a causal loop diagram approach

Background This research investigated the dynamics of fee-free higher education in South Africa, aiming to elucidate the complexities surrounding its implementation and impact. By employing a causal loop diagram approach, the study examined the interplay of socioeconomic, political, and institutional factors influencing the provision of fee-free higher education. Method A participatory approach to developing the CLD was used. Through an extensive literature review, the research contextualised fee-free higher education enabling a preliminary CLD to be developed. Discussions were held to improve the preliminary model based on stakeholder and expert opinion. The model was then validated by stakeholders and experts. Results The CLD has explicitly mapped out the causal relationships which play a fundamental role in fee-free higher education in South Africa. Key findings revealed that fee-free higher education initiatives, such as managing funding constraints and administrative complexities, hold promise for fostering inclusivity and socioeconomic development but are hindered by bureaucratic policy establishments and inefficiencies. These challenges underscore the gap between policy formulation and implementation, highlighting the need for comprehensive reforms to streamline administrative processes and enhance financial sustainability within the higher education sector. Conclusion This research thoroughly examined the dynamics of fee-free higher education in South Africa, highlighting both the challenges and opportunities in its implementation. The study emphasized the need for systemic reforms to improve accessibility and effectiveness, while also underscoring the potential of such initiatives to promote social mobility and economic empowerment, aligning with global goals like the SDGs and the African Agenda 2063.

Modeling of impact of operations and maintenance on safety, availability, capacity, and cost of Railways-A System dynamics approach

the transport infrastructure, particularly the railway infrastructure plays a vital role in the delivery of freight and the transportation of people. The ability and reliability of the railway infrastructure to deliver goods and transport people are challenged by train derailments and collisions caused by infrastructure breakdowns. Lack of maintenance has been identified as one of the causes of infrastructure breakdowns leading to accidents. The current paper proposes that if the railway infrastructure safety, availability, capacity, and cost are modeled using system dynamics, the impact of infrastructure operation and maintenance on safety can be predicted more accurately. The paper follows systems thinking approach that aims to understand the railway infrastructure as a system, by defining the system structure, system component relationships, and system behavior. The impact on railway infrastructure is modeled using system dynamics by developing causal loop diagrams and stock and flow diagrams which define the system structure, and system component relationships, and models the system behavior of safety, availability, capacity, and cost.

A fix that may fail: A qualitative model to explore potential rebound effects of digital textile microfactories

AbstractFast fashion principles and mass production within globalised supply chains are pivotal in driving the economic success of the fashion industry, but they also contribute significantly to its severe environmental impacts, which must be mitigated. Digital textile microfactories are innovative small‐scale fully digitalised design and manufacturing systems that present a promising technological solution. These offer the companies that adopt them environmental and economic advantages. However, their widespread adoption in the industry may have unintended consequences. This study hypothesises a rebound effect within the industry and proposes a qualitative modelling approach based on causal loop diagrams. We present a model for identifying rebound mechanisms that may accelerate purchases, along with a mitigation strategy emphasising the consideration of customer behaviour. The contribution of this paper is twofold: Firstly, it provides a starting point for detailed quantitative studies, and secondly, it offers insights for policy‐making towards a sustainable transition in the industry.

From text to map: a system dynamics bot for constructing causal loop diagrams

AbstractWe introduce and test the System Dynamics Bot, a computer program leveraging a large language model to automate the creation of causal loop diagrams from textual data. To evaluate its performance, we ensembled two distinct databases. The first dataset includes 20 causal loop diagrams and associated texts sourced from the system dynamics literature. The second dataset comprises responses from 30 participants to a vignette, along with causal loop diagrams coded by three system dynamics modelers. The bot uses textual data and successfully identifies approximately 60% of the links between variables and feedback loops in both datasets. This article outlines our approach, provides examples, and presents evaluation results. We discuss encountered challenges and implemented solutions in developing the System Dynamics Bot. The bot can facilitate extracting mental models from textual data and improve model‐building processes. Moreover, the two datasets can serve as a test‐bed for similar programs. © 2024 The Author(s). System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

Enhancing dairy cow population through decreasing calf mortality and increasing calving rate in Indonesia: a system dynamics approach

Abstract The dairy industry in Indonesia is facing significant challenges due to the rates of calf mortality and low calving rates. Calf mortality and calving rate became critical factors that influence the sustainability of the dairy cow population. This study aimed to assess reproduction management by decreasing calf mortality and increasing calving rates to enhance the dairy cow population in Indonesia. This study employed secondary data in 2022 using technical parameter coefficients from previous research. A causal loop diagram and a simulation model using a system dynamics approach were developed to investigate the dynamics of the dairy cow population under different scenarios of calf mortality and calving rates from 2023 to 2030. The results showed that decreasing calf mortality by 2% may increase dairy cow population by 1,991 head/year (0.31%), heifer population by 417 head/year (0.63%), and adult female dairy cattle population by 389 head/year (0.09%). The finding of this study also showed that increasing calving rate by 5% may increase dairy cow population by 17,854 head/year (2.75%), heifer population by 3,698 head/year (5.56%), and adult female dairy cattle population by 2,137 head/year (0.51%). It is concluded that reducing calf mortality rates and improving calving rates should be prioritized to enhance the dairy cow population in Indonesia.

Regional Causal Loop Diagram With Action Ideas for Improving Child Diet Quality and Weight Status in the Children’s Healthy Living Food Systems (CHLFS) Program

Regional Causal Loop Diagram With Action Ideas for Improving Child Diet Quality and Weight Status in the Children’s Healthy Living Food Systems (CHLFS) Program

A System Dynamics Model for Rooftop Solar PV System Development in Indonesia

Despite of Indonesia’s vast solar energy potential according to the Indonesian Ministry of Energy and Mineral Resources, Indonesia’s total installed capacity of rooftop solar photovoltaic (PV) is very far from Indonesia’s target of 3.6 GW in 2025. Indonesia once applied net metering scheme for rooftop solar PV policy and was expected to be able to boost rooftop solar PV growth. A system dynamics approach is used in the research to develop an assessment model to evaluate the policies’ impact on residential rooftop solar PV system growth. A Causal Loop Diagram was established then transformed into Stock and Flow Diagram (SFD) using software Vensim PLE 10.1.3, which was used to simulate several policies’ scenarios related to residential rooftop solar PV adoption and CO2 emissions reduction. Ten scenarios were simulated in this study involving three groups of intervention: initial net metering tariff, reduction on initial solar PV cost, upper limit of ROI, and combination of initial net metering tariff and initial solar PV cost reduction. The simulations revealed that combination of increasing net metering tariff to 80% & initial cost reduction 30% has the highest potential solar PV installations, the highest CO2 emissions reduction, and the lowest accumulation cost of net metering in 2030. This study can be used as reference by the policy makers in Indonesia to formulate the optimum policy to boost rooftop solar PV growth as the simulations shows that residential rooftop solar PV with the right intervention can meet the government’s target of rooftop solar PV in 2030.

Using qualitative system dynamics modeling to understand overdose bystander behavior in the context of Connecticut’s Good Samaritan Laws and identify effective policy options

BackgroundGood Samaritan Laws are a harm reduction policy intended to facilitate a reduction in fatal opioid overdoses by enabling bystanders, first responders, and health care providers to assist individuals experiencing an overdose without facing civil or criminal liability. However, Good Samaritan Laws may not be reaching their full impact in many communities due to a lack of knowledge of protections under these laws, distrust in law enforcement, and fear of legal consequences among potential bystanders. The purpose of this study was to develop a systems-level understanding of the factors influencing bystander responses to opioid overdose in the context of Connecticut’s Good Samaritan Laws and identify high-leverage policies for improving opioid-related outcomes and implementation of these laws in Connecticut (CT).MethodsWe conducted six group model building (GMB) workshops that engaged a diverse set of participants with medical and community expertise and lived bystander experience. Through an iterative, stakeholder-engaged process, we developed, refined, and validated a qualitative system dynamics (SD) model in the form of a causal loop diagram (CLD).ResultsOur resulting qualitative SD model captures our GMB participants’ collective understanding of the dynamics driving bystander behavior and other factors influencing the effectiveness of Good Samaritan Laws in the state of CT. In this model, we identified seven balancing (B) and eight reinforcing (R) feedback loops within four narrative domains: Narrative 1 - Overdose, Calling 911, and First Responder Burnout; Narrative 2 - Naloxone Use, Acceptability, and Linking Patients to Services; Narrative 3 - Drug Arrests, Belief in Good Samaritan Laws, and Community Trust in Police; and Narrative 4 - Bystander Naloxone Use, Community Participation in Harm Reduction, and Cultural Change Towards Carrying Naloxone.ConclusionsOur qualitative SD model brings a nuanced systems perspective to the literature on bystander behavior in the context of Good Samaritan Laws. Our model, grounded in local knowledge and experience, shows how the hypothesized non-linear interdependencies of the social, structural, and policy determinants of bystander behavior collectively form endogenous feedback loops that can be leveraged to design policies to advance and sustain systems change.

Are we there yet? Saturation analysis as a foundation for confidence in system dynamics modeling, applied to a conceptualization process using qualitative data

AbstractSaturation is a useful concept for system dynamics, yet it has not been widely explored or integrated into the modeling process. In this article, we describe saturation as a metaphor describing the point at which a conceptual representation of a system meets the study purpose and no longer requires modification. When saturation is reached, additional data about the problem would not offer added information, thus indicating that additional data gathering and analysis would likely be redundant. We discuss two visualization techniques, “saturation curves” and “shared understanding diagrams,” for assessing saturation when conceptualizing with causal loop diagrams and show their application in a case example. Using saturation analysis during a system dynamics research process has many advantages, including: (i) identifying model structures potentially needing revisions, (ii) observing the extent to which evidence supports the current conceptualization, (iii) reflecting extensively, (iv) documenting important modeling decisions, and (v) potentially improving the problem statement. © 2024 The Author(s). System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

Modeling Pospay and Multi-Lane Free Flow Integration for Revenue Increase

The rise of e-commerce in Indonesia has made digital payment systems increasingly important. One such system is PT. Pos Indonesia’s Pospay application. However, the app is not very popular among users as indicated by its low download numbers and ratings. To address this issue, the potential benefits of combining the Pospay application with Cantas to facilitate toll road transactions were examined. The aim was to increase public awareness of the Pospay application, which would lead to increased revenue. A dynamic system approach was used to develop an optimal strategy for improving Pospay services in the Public Transport sector and integrating it as a toll payment method in the MLFF (Multi-Lane Free Flow) system. The initial dynamic system modeling, using a Causal Loop Diagram (CLD), revealed that service innovation, customer satisfaction, and company revenue are interrelated variables that influence each other. The results of this research can be used as suggestions for companies in developing service innovation strategies.

Interconnectedness of Health and Economy in Post-COVID-19: A Systems Thinking Approach to Synergies, Trade-Offs, and Policy Responses in Nepal.

This study addresses the economic challenges posed by the Coronavirus Disease 2019 (COVID-19) pandemic, with a specific focus on Nepal. Employing a Systems Thinking approach, the study develops a comprehensive model that integrates macroeconomic interventions, exploring the trade-offs and synergies among various economic sectors. The interconnectedness of health, economic, and policy domains highlights the need for a holistic understanding of the pandemic's effects. An exploratory research design was used. The model introduces three primary subsystems-import, local demand, and local production-illustrating their interdependence. The causal loop diagram depicts the implications of fiscal and monetary policies on the economy, emphasizing the synergy and trade-offs resulting from policy interventions. Findings reveal the significant economic impact of the pandemic on Nepal, leading to its negative growth rate in FY 2020/21, the first time Nepal has experienced this in the last two decades. The results show that both intended and unintended consequences are observed following the adoption of fiscal and monetary policy that aimed at minimizing the spread of virus suggesting a complex nature of relationship among the policy variables. The fiscal policy induced negative consequences on the increasing loan, slow revenue growth, while positive feedbacks are observed on increased investment opportunities, and boosting of local economy. The monetary measures yielded unintended consequences on the rising land prices, surge in share market. The study concludes by emphasizing the crucial role of informed policymaking in navigating the complex landscape, offering insights for creating a resilient and sustainable post-pandemic future.