TELOS Feasibility Analysis for Application Development Project using System Dynamics Approach

This study used a system dynamics methodology to identify correlation and nonlinear feedback structures among factors affecting adolescent cyberbullying victims (CV) in Korea and to construct and verify a simulation model. Factors affecting CV were identified by reviewing a theoretical background in existing literature and referencing various statistical data. Related variables were identified through content validity verification by an expert group, after which a causal loop diagram (CLD) was constructed based on the variables. A stock-flow diagram (SFD) using Vensim Professional 7.3 was used to establish a CV model. Based on the literature review and expert verification, 22 variables associated with CV were identified and the CLD was prepared. Next, a model was developed by converting the CLD to an SFD. The simulation results showed that the variables such as negative emotions, stress levels, high levels of conflict in schools, parental monitoring, and time spent using new media had the strongest effects on CV. The model's validity was verified using equation check, sensitivity analysis for time-step and simulation with 4 CV adolescent. The system dynamics model constructed in this study can be used to develop intervention strategies in schools that are focused on counseling that can prevent cyberbullying and assist in the victims' recovery by formulating a feedback structure and capturing the dynamic changes observed in CV. To prevent cyberbullying, it is necessary to develop more effective strategies such as prevention education, counseling and treatment that considers factors pertaining to the individual, family, school, and media.

Background: Some studies have shown that Return on Total Assets is a strategy to increase market share. Other studies have also shown that social media like WeChat can increase market share. However, no studies have considered Instagram engagement in increasing market share. Objective: This study aims to identify variable linkage that increases market share through a dynamic system approach in small and medium-sized enterprises (SMEs). Methods: Using a System Dynamics approach, this study presents a model simulation with a proposed increase in market share by considering Instagram features. This approach creates a Causal Loop Diagram converted into a simulated Stock Flow Diagram. The value generated from the simulation is validated with the mean comparison and % error variance formulas. Results: Instagram engagement increases market share from 0.009 to 0.018. Such engagement can be increased by posting regularly and doing more activities, such as increasing post frequency, holding contests, and maximizing all features. Conclusion: This study has successfully modeled information technology, i.e., a promotion module on social media. However, this work has not yet demonstrated how the features can gain more market share, so future research is needed. Keywords: Causal Loop Diagram, Engagement, Market Share, Stock Flow Diagram, System Dynamics

Economic and environmental analysis of EVs' in urban transportation using system dynamics

Human resource development is an essential part of human resource management in construction projects. Generally, planning in this area consist of employment, skills improvement and development of workforces. Meanwhile, human resource development is based on training and motivation. In this paper, the role of training and motivation in human resource management of construction projects is investigated. Next, the Causal Loop Diagram (CLD) of human resource development along with complex relationships between factors is obtained using system dynamics approach. Thereafter, the Stock-Flow Diagram (SFD) of human resources development of construction projects has been developed. The information needed to quantify the simulated model has been gathered for a mass housing project. The archived simulation results demonstrate that implementation of financial incentives results in 12% productivity improvement. Besides, delays in labor payment decreased 18% of productivity. The productivity has been also improved about 20% by applying training policy. The presented model has the potential to evaluate the training and motivation of human resources as two main strategies of human resource development, taking into account the dynamics of the project. Finally, the effect of applying human resources development policies on project performance in terms of time can be evaluated using this model. It is also possible to plan the human resource development of the project and to improve the labor productivity and project performance.

This study investigated the status of appropriability mechanisms and relevant policy measures as an option to secure the returns on R&D investment, which businesses employ to create new knowledge and competitiveness for knowledge-based management. Also, it conducted the AHP analysis of responses from a range of ICT-related experts surveyed. Moreover, to explore the dynamic structure of appropriability mechanisms from a holistic dynamic perspective, this study drew up a causal loop diagram (CLD) about system dynamics methodology. System dynamics is an approach to realistically modeling a series of causalities and analytically simulating their dynamic variation. System dynamics incorporates those causalities into a cognitive map, plots the status and change of variables on a stock-flow diagram, and applies historical data to derive realistic coefficients. Also, system dynamics has an advantage of drawing up scenarios in line with changing external environment factors or top management’s strategic orientation and simulating scenario-specific outcomes. Finally, to compare the combined options in terms of the effects of different scenarios on the growth of appropriability over time, a simulation model was developed based on the CLD and AHP analysis results. This paper derived some policy implications for knowledge-based management from the analytic simulation based on different scenarios and suggested responsive measures.

Recent dramatic project failures have weaknesses in the traditional approaches to project management and in particular their failure to cope System dynamics models provide a useful tool for a more systematic management of these strategic issues. There have been a number of applications of system dynamics in project management; this experience permits a tentative comparison with the more traditional approaches and to examine the particular benefits of system dynamics. The conflicts of opinion between their supporters stress the different perspectives underlying the two approaches. The comparison of the approaches is focused on the “view” of the project management process. Although, ultimately, they both assume a system perspective, a cycle of planning, implementation and control, the level of detail in which they consider the project system is different. Traditional models . highlighted The increasing rate of change and the complexity of the new technologies and markets impose the need for quick and effective responses. As a consequence many organisations are now adopting “management by projects” as a general approach (Turner 1993) and project success is a primary factor for the survival and prosperity of organisations. However, projects are also becoming more complex and project failure is unfortunately another major trend. Over-runs of 40 to 200 per cent are common, while other projects are cancelled before completion but after considerable expenditure (Morris and Hough 1987). The important role of project management in modern life has highlighted some of the deficiencies of traditional techniques and the search for an alternative. Traditional techniques can encourage a narrow, operational view of the project, concentrating on the detailed planning and several studies (Davidson and Huot 1991; Morris and Hough 1987) have identified the need for a more strategic approach. Systems dynamics appears to offer this strategic alternative, assuming a holistic view of the organisation with an emphasis on the behavioural aspects of projects and their relation with managerial strategies. This paper addresses the need for a better understanding of the nature, differences, similarities, and purposes of traditional and system dynamics approaches. If system dynamics models are to play a core role in the future developments of project management, it is important to understand their distinctive contribution to the current body of knowledge and their place in a future methodology.

Modelling Rural Healthcare Supply Chain in India using System Dynamics

Sustainable supply chain management (SSCM) involves the managing of information, materials, cash flows, and collaboration among enterprises along the supply chain, integrating sustainable development goals. This research paper aims to determine challenges in SSCM adoption and to address related complexity using the system dynamics (SD) approach utilizing modeling and simulation techniques. This research identified challenges from the literature using content analysis. Causality among these identified challenges was determined using interviews and questionnaire surveys that led to the development of a causal loop diagram (CLD), which was used in the development of the SD model. Among the 19 shortlisted variables, CLD had IV reinforcing and II balancing loops. Moreover, CLD was used to build an SD model with two stocks, and a new stock named ‘project performance’ was added to envisage the cumulative impact of all stocks. The model was simulated for five years, and the results predict that the lack of top management commitment and corporate social responsibility adversely affects project performance. This implies that there is a need to improve numerous factors, in particular corporate social responsibility and top management commitment, which would lead to the adoption of SSCM, thus leading to a performance improvement for the construction industry (CI). The model was validated using boundary adequacy, structure, and parametric verification tests, which showed that the developed model is logical and approximately replicates the industry’s actual system. The research findings will help the CI practitioners to adopt sustainability principles in terms of the supply chain and will not only enhance productivity and performance but will also help in the minimization of delays, promote long-term relations, and reduce communication gaps and project complexities.

Chronic kidney disease (CKD) is a growing health problem in the United States. Patients with CKD have had critical care gaps that have perhaps led to a more rapid progression of CKD toward end stage renal disease. To improve CKD outcomes, an interdisciplinary project has been initiated. This article describes how system dynamics supported the planning of the project. We developed a causal loop diagram through discussions with a panel advisory group and health providers. The model is particularly effective because it can demonstrate the interrelationships among patients, providers, and policies, and predict the effects of the interventions. This preliminary work may overcome the common linear approaches to care and helped design sustainable interventions through an understanding of system complexities. Future work on the project will develop a stock-flow diagram with empirical data to support the effective implementation of proposed interventions.

Introduction:This preliminary assessment of a grey-box model, was predicated on system dynamics principles and developed using Vensim® DSS software. The purpose is to predict biogas production under anaerobic conditions for energy utilization at the design stage.Objective:To describe the process of a developed system dynamics model to predict biogas production under anaerobic conditions.Methods:This method involves two-stage kinetics of the biogas production process in anaerobic conditions using the first-order and Gompertz functions. The model is depicted in two parts: causal loop diagram and stock–flow diagram. The causal loop diagram describes the anaerobic digestion process a substrate undergoes for the production of biogas, while stock–flow diagram depicts basic building blocks of the dynamic behavior of an anaerobic digestion process. Primary data is from a laboratory-scale experiment of biogas production using vegetal wastes, while the secondary one is from the literature on studies using similar substrates.Results:Primary and secondary data are used to validate and stimulate the developed model. The kinetic model shows the substrate being reduced exponentially with increasing time; consumption of substrate and production of methane and carbon dioxide follows exponential growth and decay pattern, with carbon dioxide production starting early compared to methane, and was produced at a rate faster due to the strong and resilient characteristics of fermentative microorganisms.Discussion:Comparing data from empirical and model simulation shows some close relationship, though not too perfectly. Both results reflect signs of inhibitions occurring within the substrates in the digester under anaerobic conditions explaining the low methane yield or instability.

Ponte Academic JournalFeb 2023, Volume 79, Issue 2 IMPLEMENTING SYSTEM DYNAMICS AND PARTICIPATORY ACTION RESEARCH AT THE NEXUS OF PATIENT CARE FACTORSAuthor(s): Maseeha Mahomed Farouk Ansermeah ,Cecile Gerwel ProchesJ. Ponte - Feb 2023 - Volume 79 - Issue 2 doi: 10.21506/j.ponte.2023.2.7 Abstract:Purpose: Factors influencing patient care were analyzed in a public health setting in a bid to enhance patient experience and identify areas of health care delivery which could be improved upon. Methods: Patients and members of health care staff were interviewed by means of purposeful sampling. Causal loop diagrams and stock flow diagrams were merged with the use of Systems archetypes under the broad purview of System Dynamics and Participatory Action Research. Results and Conclusion: System Dynamics heuristics unmasked flaws in the system which were then acted upon utilizing Participatory Action Research interventions. Overall there has been a homogenous improvement in understanding the factors which contribute to patient care. Download full text:Check if you have access through your login credentials or your institution Username Password

Supply chain management covers integrated activities of planning, coordinating, and controlling of all business processes and practices in the supply chain to meet the demands of consumers at the lowest possible cost. Sustainable supply chain can be achieved by taking into account three pillars of sustainable development, namely, economy, social, and environment. Passion fruit agro-industry supply chain actors consist of farmers, collectors, agro-industries, and retailers. This study aims at identifying factors affecting the passion fruit agro-industry supply chain performance for sustainable micro, small, and medium enterprises and designing a supply chain performance measurement model of MSME passion fruit agro-industry with system dynamics. This research used a survey method through observations, in-depth interviews, and expert opinions. Data were processed using a combination of the hard system (system dynamics analysis) and soft system (expert opinions).The feedback structure along the passion fruit syrup agro-industry system was modeled in a causal loop diagram using system dynamics through version 10 of Powersim Studio software. It was then translated into a stock-flow diagram as the implementation of the simulation model. The model was verified using a computerized statistical analysis (Absolute Means Error) technique. To formulate recommendations and development strategy scenarios for sustainable MSME passion fruit agro-industry supply chain, a system approach method was used and expected to produce an effective and operational decision in accordance with the objectives previously set. The results obtained through expert opinions and Analytic Hierarchy Process (AHP) which have the highest weight with various conditions for each variable. Seven key variables were proven to influence the performance of passion fruit agro-industry supply chain, which were also used to design a sustainable MSME supply chain development scenario. The behavior of the sustainable passion fruit agro-industry supply chain model took the form of positive growth and the error rate of 7.43. Developing a sustainable MSMEPFASCPM can be carried out with a moderate strategy by developing: 1) pattern of good relationships among the actors, 2) gradual increase in the availability of raw materials, 3) environmental support capability, 4) gradual increase of profits, 5) moderate skills, 6) employment opportunities, and 7) land availability.

Dynamic cycles of unsold new housing stocks, investment in housing, and housing supply–demand

This study aims to determine the impact of Indonesian government policies on the supply chain resilience of the ferronickel industry in Indonesia. The existing problem is that the law prohibits nickel ore exports, and the policy of industrial downstream causes delays in the process of nickel processing. The problems happen because Indonesia's nickel industry is still incapable of downstream. As a result, the nickel supply chain faces dynamic and complex events that can disrupt operational activities. At the same time, supply chains need to withstand and recover from disruptions quickly. Therefore, Supply Chain Resilience, which is the ability to survive, adapt, and recover from disruptions to meet customer needs, is needed. This study uses system dynamics to analyze complex and dynamic systems to provide more practical policy advice. The system dynamics model starts by building a conceptual model through a system diagram. Inside the model is a causal loop diagram, then proceeds with developing a quantitative stock flow diagram (SFD) model. Finally, this SFD model operated with several scenarios used as policy suggestions for the Indonesian government.

System dynamics (SD) is a complex systems modeling and simulation approach with wide ranging applications in various science and engineering disciplines. While subject matter experts lead most of the model building, recent advances have attempted to bring system dynamics closer to fast growing fields such as data sciences. This may prove promising for the development of novel support methods that augment human cognition and improve efficiencies in the model building process. A few different directions have been explored recently to support individual modeling stages, such as the generation of model structure, model calibration and policy optimization. However, an integrated approach that supports across the board modeling process is still missing. In this paper, a prototype integrated modeling support system is presented for the purpose of supporting the modelers at each stage of the process. The proposed support system facilitates data-driven inferring of causal loop diagrams (CLDs), stock-flow diagrams (SFDs), model equations and the estimation of model parameters using computational intelligence (CI) techniques. The ultimate goal of the proposed system is to support the construction of complex models, where the human power is not enough. With this goal in mind, we demonstrate the working and utility of the proposed support system. We have used two well-known synthetic reality case studies with small models from the system dynamics literature, in order to verify the support system performance. The experimental results showed the effectiveness of the proposed support system to infer close model structures to target models directly from system time-series observations. Future work will focus on improving the support system so that it can generate complex models on a large scale.