System Dynamics Tools Research Articles

Participatory Causal Loop Mapping of the Adoption of Organic Farming in Nigeria.

Contrary to the expectations of promoters of organic agriculture, the adoption of the technology by smallholder farmers in Africa has been low and slow, for reasons not well understood. Existing studies on the topic mostly estimated the effect of some variables on the adoption of the technology. But adoption is characterized by complex and dynamic interactions of many interconnected factors, which existing studies overlooked. The underlying causal structures and feedback mechanisms that dynamically interact to affect the adoption of organic farming in urban and rural Africa are also not well known. To bridge these gaps, we used a system dynamics tool called participatory causal loop diagraming to map the underlying causal factors and feedback mechanisms driving the adoption of organic farming in rural and urban Nigeria. We conducted loop and network analyses of the group causal loop diagrams, which were created during the participatory system dynamics modeling workshops with the organic farmers in our study areas. Our findings underscore the importance of the knowledge of organic farming, demand- and supply-side-oriented awareness creation, and the economic viability of organic farming for widespread adoption of the technology. We suggested the potential leverages around which interventions can be built to boost the adoption rates of the technology.

Payments flows system-dynamic model for assessing the efficiency of leasing operations

Introduction. The relevance of the financial leasing effeciency issues for Ukraine is due to the fact that its economic and social development is largely influenced by the amount of investment in the fixed assets of enterprises, which ensures their competitiveness, contributes to the development of small and medium-sized businesses and the creation of new jobs. The main factor in the attractiveness of leasing operations for the lessee is the amount of leasing payments. The efficiency of leasing operations for the lessee can be determined by comparing the total amount paid under the leasing agreement with the cost of the bank credit. In this context, the application of simulation modeling, in particular such an approach as system dynamics, is relevant to support decision-making in the field of financial leasing. The purpose of the work is to investigate the theoretical and practical aspects of the calculation of leasing payments, to build a system-dynamic model of payment flows for assessing the efficiency of leasing operations, in the calculation of which depreciation assignments are сonsidered according to current legislation. Methodology. To achieve the goal, general scientific methods of theoretical generalization and comparison, methods of induction and deduction were applied – for the analysis of methodical approaches to the calculation of leasing payments, tools of system dynamics – for the analysis and modeling of payment flows of financial leasing and bank credit. We used the methods of calculating depreciation of leased property provided by the current legislation in the calculations of leasing payments. Results. The article discusses the issue of system-dynamic modeling of payment flows of financial leasing and bank credit for assessing the effeciency of leasing operations. The main problems related to the calculation of leasing payments are summarized. It has been established that the use of non-linear depreciation methods in calculations, in particular the method of reducing the residual value, leads to lower costs for the lessee and an increase in the efficiency of the leasing operation for the lessee.

Bioeconomy in the Shade of Green Deal: The System Dynamic Approach

Abstract At the end of 2019, the European Commission launched a new growth strategy called ‘The European Green Deal’ (GD), which aims to ‘transform the European Union (EU) into a fair and prosperous society with a modern, resource-efficient a competitive economy with no net greenhouse gas emissions in 2050 and where economic growth is decoupled from resource use’. This study present developed system dynamic (SD) tool for determining bioeconomy development until 2030 and impact of different GD strategy activities on achieved progress. The bioeconomy index the created and used to measure bioeconomy progress for all scenarios. The optimal scenario was identified between reaching climate goals and adding value to the agricultural, forestry and fisheries resources.

A Systems Framework for International Development: The Data‐Layered Causal Loop Diagram

Meeting the United Nations Sustainable Development Goals (SDGs) will require adapting or redirecting a variety of very complex global and local human systems. It is essential that development scholars and practitioners have tools to understand the dynamics of these systems and the key drivers of their behavior, such as barriers to progress and leverage points for driving sustainable change. System dynamics tools are well suited to address this challenge, but they must first be adapted for the data‐poor and fragmented environment of development work. Our key contribution is to extend the causal loop diagram (CLD) with a data layer that describes the status of and change in each variable based on available data. By testing dynamic hypotheses against the system's actual behavior, it enables analysis of a system's dynamics and behavioral drivers without simulation. The data‐layered CLD was developed through a 4‐year engagement with USAID/Uganda. Its contributions are illustrated through an application to agricultural financing in Uganda. Our analysis identified a lack of demand for agricultural loans as a major barrier to broadening agricultural financing, partially refuting an existing hypothesis that access to credit was the main constraint. Our work extends system dynamics theory to meet the challenges of this practice environment, enabling analysis of the complex dynamics that are crucial to achieving the SDGs.

Modelling transformative adaptation: Case of post-earthquake Lyttelton, New Zealand

There has been an increasing awareness of the unsustainable trends in human interaction with the environment and its hazards. Research over the years has been able to establish a relationship between human activities and the increasing rate of climate change based on empirical evidence. The effects of human activities on the environment are not only limited to the rapid change in climate but has resulted in a range of other complex problems which includes the rising occurrence of disasters and other associated losses. This calls for a holistic approach for understanding these complex interactions and identifying ways for integrated planning towards sustainability. Hence, this study aims at developing a hybrid model that explains the bottom-up and top-down processes of transformative adaptation in Lyttelton New Zealand after the 2010/2011 earthquakes. To achieve this, we explored existing literature on the appropriate modelling tools for adaptation studies, used agent-based modelling and system dynamics tools to simulate transformative adaptation in Lyttelton, performed some sensitivity tests and discussed the results. The research concludes that transformation is a process, not an event. The model also provides a valuable tool for fail-safe experimentation and for informing policy decisions.

Dynamic modeling of strategic thinking for top management teams and its impact on firm performance: a system dynamics approach

PurposeThe purpose of this study is to model the strategic thinking process, considering the different psychological traits of TMTs (top management teams) and how the technological dynamism affects the strategies framed together impacting the performance of the firm.Design/methodology/approachModeling and simulation are done in this study using the system dynamics (SD) tool. The data are extracted using social media analytics, and the same is given as an input for the SDmodel, which is used for modeling and simulation of the interdependencies between the psychological factors, technological dynamism and firm performance. The analysis decodes how a change in the thinking process of a TMT has an impact on the performance of the company in an automobile market.FindingsThe study has explained how different psychological traits affect the thinking process of a TMT and how the strategies framed with this thinking behavior have an impact on firm performance.Research limitations/implicationsThe study is limited only to the automobile industry in India, and only partial psychological constructs were considered to examine their impact on firm performance. This study can be further extended by analyzing the same to various other industries along with many other psychological constructs.Practical implicationsThe findings identify the change in behavior of the performance due to the thinking process and technological dynamism. This helps the top management to take into consideration different factors that affect the strategies framed for the company and what are the threshold points in the system that are to be focused on during the framing of a strategy.Originality/valueThe study fills the unattended gaps in the literature regarding how the psychological traits are interdependent and how their relationship is affecting the thinking process, which is going to have an impact on the behavior of the firm performance. It also adds to the literature of systems thinking.

Ex-ante evaluation of interventions to upgrade pork value chains in Southern Myanmar

CONTEXTMyanmar has made rapid economic progress since the country began its transition to a more integrated market economy in the late 2000s. Although these gains are led by positive developments in the agricultural sector, agricultural productivity and profitability are among the lowest in Asia with high rates of poverty especially in rural areas. Small-scale farms dominate rural livelihoods in Myanmar, especially for the 87% of Myanmar's poor who live in rural areas. Hence, these small-scale farms are critical development leverage points as they are an important source of rural incomes to both farm and non-farm households. OBJECTIVEThis study is part of a larger, five-year agricultural research and development project intended to upgrade pork and rice value chains and strengthen rural livelihoods in southern Myanmar's Tanintharyi Region. We evaluated producer-focused interventions to upgrade the pork value chain using tools that consider the dynamic and complex nature of the chain. METHODSThis research used systems thinking and participatory methods to develop a system dynamics model of the pork value chain in southern Myanmar. The model integrated modules of animal production, marketing, investment, finance, and collective action. Scenario analysis with the model guided recommendations for pro-poor interventions for implementation within the five-year development project. RESULTS AND CONCLUSIONSSimulation results indicated that a mix of technical interventions implemented by functional producer groups showed promise in delivering sustained financial benefits to the target community and outperformed the short-term gains generated by these interventions in the absence of collective action. The model also highlighted specific interventions, such as improved financial services, animal health workers, and training that enabled poorer households to benefit from pig livelihoods while reducing risks from environmental and economic shocks. Within complex agri-food systems such as the pork value chain in Tanintharyi, a multi-pronged intervention strategy is recommended to address problems faced by small-scale agribusiness value chain participants. SIGNIFICANCEDevelopment interventions tend to be implemented in complex environments, often with scarce data to inform decision-making. This research shows how system dynamics tools and spatial group model building processes could help overcome these inherent challenges by creating virtual laboratories where plausible project interventions can be tested and modified, bringing increased confidence to implementation choices.

System dynamics for humanitarian operations revisited

PurposeThe purpose of this study is to show that the current complexity of humanitarian operations has only increased the usefulness of system dynamics (SD) in helping decision-makers better understand the challenges they face.Design/methodology/approachA critical analysis to evaluate how SD methodology has been applied to humanitarian operations.FindingsToday's humanitarian operations are characterized by huge complexity given the increased number of stakeholders, feedback loops, uncertainty, scarce resources and multiple objectives. The authors argue that SD's tools (causal-loop diagram, data layer, simulation model) have the capacity to appropriately capture this complexity, thereby enhancing intuition and understanding.Originality/valueResearchers and practitioners hesitate to use system dynamics when data is missing. The authors suggest alternatives to deal with this common situation.

A systems dynamics approach to the bottom-up simulation of residential appliance load

Residential demand from real residences can be resource intensive to collect. There is need to generate synthetic residential load in energy research, and new approaches are welcome. Most of the simulation models of synthetic residential load that output realistic loads are tightly coupled to historic correlations. This paper presents a high-resolution simulation model that generates a residential appliance load using the tools of System Dynamics via a bottom-up approach. In addition to being realistic, the model aims to minimise historic coupling. Whilst the intermediary outputs of the modelling process are subjected to systematic scrutiny, the final output is validated by comparing statistical characteristics of the model’s output to a validated model and data from real residences. The aims of the model were sufficiently met, and the modelling approach shows potential to simplify; by driving the model on average frequency of appliance use instead of probability distributions of human activities. Other outputs from the model, specifically distribution of appliances’ activation and operation, as well as complexity are discussed. Some benefits of the model are also discussed especially with regard to cost of modelling, interpretability of model and potential for transdisciplinary research. This study represents the first attempt to develop a bottom-up simulation model of residential load based on a System Dynamics approach.

A dynamic simulation approach to support the evaluation of cyber risks and security investments in SMEs

The growing amount of cyberspace threats highlights the need to evaluate cybersecurity risks and to plan for effective investments. One internationally recognized document for cybersecurity risk management is the framework for Improving Critical Infrastructure Cybersecurity by the US National Institute of Standards and Technology (NIST). It provides guidelines, best practices and standards for cybersecurity risk management. Nevertheless, as other self-assessment frameworks, it produces a static view of an organization's cyber posture and does not capture the dynamics of organizational changes and cyberattacks. Moreover, the current situation sees small and medium enterprises (SMEs) in a critical position since they need to manage their cybersecurity while usually not being skilled or equipped enough to internalize this process. Therefore, there is a need for a practical and easily applicable model able to identify a cybersecurity risk profile and its dynamics. This study proposes a system dynamics methodology and tool (SMECRA - SME Cyber Risk Assessment) for supporting cybersecurity investment decisions for SMEs through the evaluation of cyber risk and previous investments. SMECRA addresses dynamic organizational complexity and can be used to assess cyber risks and related dynamics over time. Three case studies demonstrate its capability to assess a SME's cybersecurity status and to evaluate investments impacts on an organization's risk profile, raising cybersecurity awareness. This study is important for SMEs wishing to manage their own cybersecurity risk and for insurance companies in their economic evaluation of residual risks that SMEs wish to externalize.

A bibliometric-qualitative study about the use of System Dynamics in the areas of Project and Program Management

Abstract Despite the proliferation as well as great advances in the development of dynamic models applied to project management, research that applies system dynamics principles to program management does not seem to be as fertile. The objective of this paper is to obtain a more accurate vision of how the system dynamics theory is being used in the development of the program management field. The bibliometric-qualitative study confirms there is a robust use of system dynamics tools in the project management area, with a wide range of applications as well as solid results. The study, however, also shows that for programs, despite a noticeable increase regarding the interest in program management by organizations, clearly there is much less research uniting program management and system dynamics. More importantly, some dynamic models are being used to improve the performance of programs, however, few studies take into consideration the specific variables from program management. Thus, we conclude that current research on these two topics can only be viewed as fragmented and in its early stages, offering ample room for improvement.

Концепция имитационной модели развития агропродовольственных рынков

Цель: статья посвящена вопросам использования системно-динамического инструментария для имитационного моделирования рынков сельскохозяйственного сырья и продовольствия. Обсуждение: предлагаемый в исследовании подход основан на непрерывно-детерминированном моделировании процессов производства, распределения и потребления продукции, формирования цен, спроса и предложения. В качестве основных гипотез модели приняты: частичное равновесие на рынке, складывающееся в результате взаимовлияния цен, спроса и предложения; динамичный характер предпочтений (в т.ч. неценовых) потребителей и производителей продукции; специфический характер предложения, связанный с особенностями аграрных отраслей; возможность вмешательства в процессы со стороны государственных регуляторов. В соответствии с данными гипотезами разработаны ключевые механизмы модели: механизм частичного рыночного равновесия на основе модифицированной модели Эванса, механизмы импорта и экспорта на основе модели Армингтона, механизм замедленной реакции предложения, механизм ценовых шоков и др. Результаты: предлагаемая модель визуализирована и параметризирована в соответствии с идеологией системной динамики. Намечены основные направления ее апробации и проведения направленных вычислительных экспериментов.

Assessment of Urban Resilience to Natural Disasters with a System Dynamics Tool: Case Study of Latvian Municipality

Abstract Research focuses on linking climate adaptation and disaster risk reduction strategies. The aim of the research is to test an urban resilience assessment tool through a local case study. The tool is based on integrating two methods. Multi-criteria analysis and system dynamics model is used to create a dynamic Urban Resilience Index. For the case study a local medium sized town is chosen in Latvia that is subject to flood risk. The results of the model simulation show that the model is suitable for both short term and long term resilience assessment. Future studies must focus on the precision of such a tool, which in this study could not be evaluated. Overall, the tool presented can contribute to offsetting the existing knowledge gaps between climate adaptation and disaster risk reduction for better policy planning and strengthening urban resilience on the local level.

A systems approach toward climate resilient livelihoods: A case study in Thai Nguyen province, Vietnam

This study aims to identify strategic actions towards climate resilient livelihoods and secure income for smallholder farmers in Thai Nguyen province of Vietnam using a systems approach and system dynamic modelling tools. Information and data for this research was collected through surveys, interviews, focus group discussions and workshops with relevant stakeholders and 187 farmers in two vulnerable districts during October 2019–April 2020. Findings of this study uncovered a number of shortcomings of the government policies and approaches in climate change adaptation. Local initiatives, community learning and ownership seem to be neglected. This research has substantiated the effectiveness and validity of systems approaches and tools in structuring and solving complex issues in agricultural research and development under the interwoven relationships between environmental and human factors. Climate resilient production models and practices are just part of the systemic interventions that need to be implemented in a coordinated manner towards a more resilient future of the farming communities. This study has addressed the current knowledge gap and the need for using integrated approaches and decision support systems for unravelling ill-structured and/or complex issues of climate change adaptation (CCA). It also provided practical recommendations for informed CCA policies and implementation.

The COVID-19 Pandemic-Can open access modeling give us better answers more quickly?

The COVID-19 Pandemic-Can open access modeling give us better answers more quickly?

Indoor temperature, relative humidity and CO2 monitoring and air exchange rates simulation utilizing system dynamics tools for naturally ventilated classrooms

This study reports the results of two-season (summer and winter) monitoring of indoor CO2, temperature (T) and relative humidity (RH) levels conducted in naturally ventilated classrooms of a primary school. Parameters were recorded at 1-min interval for one week including occupancy and non-occupancy hours. CO2, T and RH exceeded ASHRAE recommended limits for significant fraction of occupancy period. Minute-by-minute ventilation (VRs) and air exchange rates (AERs) were calculated for occupancy hours. Results showed significant variation (p < 0.05) of indoor parameters between occupancy and non-occupancy hours. Though Indoor CO2 levels did not vary between two seasons, thermal comfort parameters showed significant variation. Average AERs and VRs were found in range of 1.4–10.6 h-1 and 1.1–6.3 l/s/person respectively which were well below recommended ASHRAE standards. Second part of study includes development of a system dynamics (SD) based model which was used to estimate indoor CO2 concentrations utilizing calculated VRs (minute-by-minute and averaged) using VENSIM software. The developed SD based model results showed high correlation (>0.98 for all classrooms, using minute-by-minute VRs) with monitored CO2 concentration and low root mean square error. Similarly, minute-by-minute VRs input to models showed more accurate simulation as compared to VRs averaged for a session (Correlation coefficient <70 for all classrooms). Finally, ASHRAE and REHVA recommended VRs (8 and 3 l/s/person respectively) were input to SD based model to simulate CO2 concentration, in which the former successfully kept CO2 levels below 1000 ppm and later failed to maintain claimed limits of 1500 ppm.

Modelling carbon mitigation pathways by 2050: Insights from the Global Calculator

The Global Calculator (GC) can be used to assess a wide range of climate change mitigation pathways. The GC is an accessible integrated model which calculates the cumulative emissions of a basket of the main greenhouse gases that result from a set of technological and lifestyle choices made at the global level and as defined by the user within a single system dynamics tool. Using the GC, we simulated ambitious scenarios against business as usual trends in order to stay below 2 °C and 1.5 °C of maximum temperature change by the end of this century and carried out a sensitivity analysis of the entire GC model option space. We show that the calculator is useful for making broad simulations for energy, carbon and land use dynamics, and demonstrate how combined and sustained mitigation efforts across different sectors are urgently needed to meet climate targets.

Analysis of the water, energy, food and land nexus using the system archetypes: A case study in the Jatiluhur reservoir, West Java, Indonesia.

This paper applies the system archetypes to investigate water, energy, food, and land nexus (WEFLN) in the Jatiluhur reservoir, the largest reservoir in Indonesia. The Jatiluhur reservoir has multiple functions such as hydropower supply and water supply for different end users. Multiple functions and multiple users mean there are tradeoffs in fulfilling the needs of different end users. Through feedback loops, the system dynamics tools concern on the interdependencies and the complexities of the nexus elements. It is found that growth engines such as industrial development and residential development support industrial and residential sectors. However, water availability will be a crucial issue as water supply can bound the growth engines. This situation is called the limits to growth archetype. Another system archetype named the success to successful is also identified. The success to successful archetype reminds us to distribute water and energy properly to sustain the growth in all sectors. Finally, outputs of this study can be a basis to develop a computer model and to support sustainable functions of the other reservoirs.

Integrating complex systems science into road safety research and practice, Part 2: applying systems tools to the problem of increasing pedestrian death rates

ObjectivesTo provide a specific example of how systems dynamics tools can increase understanding of stakeholder ‘mental models’ and generate robust systems-based hypotheses about the escalating problem of rising pedestrian death...

Heat-Bath Algorithmic Cooling with optimal thermalization strategies

Heat-Bath Algorithmic Cooling is a set of techniques for producing highly pure quantum systems by utilizing a surrounding heat-bath and unitary interactions. These techniques originally used the thermal environment only to fully thermalize ancillas at the environment temperature. Here we extend HBAC protocols by optimizing over the thermalization strategy. We find, for any d-dimensional system in an arbitrary initial state, provably optimal cooling protocols with surprisingly simple structure and exponential convergence to the ground state. Compared to the standard ones, these schemes can use fewer or no ancillas and exploit memory effects to enhance cooling. We verify that the optimal protocols are robusts to various deviations from the ideal scenario. For a single target qubit, the optimal protocol can be well approximated with a Jaynes-Cummings interaction between the system and a single thermal bosonic mode for a wide range of environmental temperatures. This admits an experimental implementation close to the setup of a micromaser, with a performance competitive with leading proposals in the literature. The proposed protocol provides an experimental setup that illustrates how non-Markovianity can be harnessed to improve cooling. On the technical side we 1. introduce a new class of states called maximallyactivestates and discuss their thermodynamic significance in terms of optimal unitary control, 2. introduce a new set of thermodynamic processes, called β-permutations, whose access is sufficient to simulate a generic thermalization process, 3. show how to use abstract toolbox developed within the resource theory approach to thermodynamics to perform challenging optimizations, while combining it with open quantum system dynamics tools to approximate optimal solutions within physically realistic setups.