Search results

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

System dynamics is a whole-system modelling and learning approach, useful for tackling non-linear problems, such as sustainable urban development. The purpose of this paper is to review system dynamics applications in the simulation of sustainable urban development over a period from 2005 to 2017.

The analysis reveals that the number of applications of system dynamics modelling in the area of urban sustainable development increased in the analysed period. Research has changed its focus from the modelling of environmental problems to more complex models, portraying the multidimensional socio-economic processes that have an impact on the sustainability of urban development. Analysed case studies most often use the behaviour reproduction test for model validation, but without a unified approach. In most cases, modelling has been done in China, Germany and the USA, while urban development in the Eastern European countries, Africa and Latin America has not often been investigated. This paper indicates the knowledge gaps and suggests future research directions.

Papers that report the use of system dynamics modelling reveal a wide range of applications in urban sustainability. The analysis shows significant emphasis on environmental problems, while the interest for modelling social problems has been increasing during the last several years. Most of the modelled problems examine the sustainability of resources (land, water) and waste management, which are used for insights into the reasons for the system behaviour, forecasting future behaviour and policy testing.

The presented models were developed in most cases for the purpose of understanding the phenomena examined, as well as the future use of the models in policy planning. This brings us back to the need for greater stakeholder involvement, not only in the initial phase, but also during the whole modelling process, which could increase understanding, use and ownership of the models in the future, and thus increase their practical application.

The purpose of this paper is to present a dynamic model to measure the degree of system’s leanness under dynamic demand conditions using a novel integrated metric.

The multi-stage production system model is based on a system dynamics approach. The leanness level is measured using a new developed integrated metric that combines efficiency, WIP performance as well as service level. The analysis includes design of experiment technique at the initial analysis to examine the most significant parameters impacting the leanness score and then followed by examining different dynamic demand scenarios. Two scenarios were examined: one focussed low demand variation with various means (testing the impact of demand volumes) while the second focussed on high demand variation with constant means (testing the impact of demand variability).

Results using the data from a real case study indicated that given the model parameters, demand rate has the highest impact on leanness score dynamics. The next phase of the analysis thus focussed on investigating the effect of demand dynamics on the leanness score. The analysis highlighted the different effects of demand variability and volumes on the leanness score and its different components leading to various demand and production management recommendations in this dynamic environment.

The presented lean management policies and recommendations are verified within the scope of similar systems to the considered company in terms of manufacturing settings and demand environment. Further research will be carried to extend the dynamic model to other dynamic manufacturing and service settings.

The developed metric can be used not only to assess the leanness level of the systems which is very critical to lean practitioners but also can be used to track lean implementation progress. In addition, the presented analysis outlined various demand management as well as lean implementation policies that can improve the system leanness level and overall performance.

The presented research develops a novel integrated metric and adds to the few literature on dynamic analysis of lean systems. Furthermore, the conducted analysis revealed some new aspects in understanding the relation between demand (variability and volume) and the leanness level of the systems. This will aid lean practitioners to set better demand and production management policies in today’s dynamic environment as well as take better decisions concerning lean technology investments.

This paper aims to analyze the socioeconomic impacts of infectious diseases based on uncertain behaviors of social and effective subsystems in the countries. The economic impacts of infectious diseases in comparison with predicted gross domestic product (GDP) in future years could be beneficial for this aim along with predicted social impacts of infectious diseases in countries.

The proposed uncertain SEIAR (susceptible, exposed, infectious, asymptomatic and removed) model evaluates the impacts of variables on different trends using scenario base analysis. This model considers different subsystems including healthcare systems, transportation, contacts and capacities of food and pharmaceutical networks for sensitivity analysis. Besides, an adaptive neuro-fuzzy inference system (ANFIS) is designed to predict the GDP of countries and determine the economic impacts of infectious diseases. These proposed models can predict the future socioeconomic trends of infectious diseases in each country based on the available information to guide the decisions of government planners and policymakers.

The proposed uncertain SEIAR model predicts social impacts according to uncertain parameters and different coefficients appropriate to the scenarios. It analyzes the sensitivity and the effects of various parameters. A case study is designed in this paper about COVID-19 in a country. Its results show that the effect of transportation on COVID-19 is most sensitive and the contacts have a significant effect on infection. Besides, the future annual costs of COVID-19 are evaluated in different situations. Private transportation, contact behaviors and public transportation have significant impacts on infection, especially in the determined case study, due to its circumstance. Therefore, it is necessary to consider changes in society using flexible behaviors and laws based on the latest status in facing the COVID-19 epidemic.

The proposed methods can be applied to conduct infectious diseases impacts analysis.

In this paper, a proposed uncertain SEIAR system dynamics model, related sensitivity analysis and ANFIS model are utilized to support different programs regarding policymaking and economic issues to face infectious diseases. The results could support the analysis of sensitivities, policies and economic activities.

• A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;

• Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;

• Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;

• An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;

• A real case study is considered to evaluate the performances of the proposed models.

A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;

Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;

Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;

An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;

A real case study is considered to evaluate the performances of the proposed models.

Successful future has inspired organizations to measure long-term and non-financial measurements and key performance indicators (KPIs). Kaplan and Norton proposed balanced scorecard (BSC) for this issue and have extended it to one of the most preferred strategic management system’s tools. However, available planning tools like BSC have some limitations, like dependency to the developer, weakness in showing time delays, and also mathematical relationships between lead and lag indicators. In this paper, the authors would present a new methodology for developing BSCs, which would be able to overcome these limitations. Therefore, the purpose of this paper is to develop an integrated framework for developing BSC with system dynamics approach (a dynamic BSC (DBSC)) which has lower limitation in compare with traditional BSC. The other purpose of this paper is developing a DBSC for an Iranian public transportation company.

Based on this purpose, related literature was thoroughly reviewed and the proposed methodology designed using the system dynamics and BSC concepts. This methodology is a composition of original BSC development methodology and system dynamics principles. An assumed organization has been used for showing methodology’s capability and procedure. Furthermore, a case study has been accomplished in this paper. This case study is a DBSC which has been developed for an Iranian public transportation company. The purpose of this case study is to ensure about proposed methodology implication in action.

The authors proposed a methodology which can be applied for developing BSCs. This methodology consists of six different steps which are: developing a system for organization, selecting stakeholders’ most important objectives and target, identifying organization’s objectives and their KPIs for different BSC aspects, developing strategy map, targeting, and selecting initiatives. In the proceeding of this paper, the proposed methodology and its steps would be explained in detail.

The system dynamic approach has precedents in business studies; however, this research makes this approach operational in BSC designing and analysis. BSCs, which developed by this methodology can show time delays between an organization’s objectives, its KPIs’ relationship and also planning for it. Selecting achievable and rational vision and objectives’ targets, change management, scenario planning and policy analysis are other values which can be achieved by DBSC deployment which need further researches. In summary, this research has shown an integrated framework for developing DBSC and then applies it to an Iranian public transportation company. Therefore, another contribution of this paper is the application of this method for an Iranian public transportation company.

The purpose of this paper is to propose a system dynamic simulated process model for maintenance work management incorporating the Fourth Industrial Revolution (4IR) technologies.

The extant literature in physical assets maintenance depicts that poor maintenance management is predominantly because of a lack of a clearly defined maintenance work management process model, resulting in poor management of maintenance work. This paper solves this complex phenomenon using a combination of conceptual process modeling and system dynamics simulation incorporating 4IR technologies. A process for maintenance work management and its control actions on scheduled maintenance tasks versus unscheduled maintenance tasks is modeled, replicating real-world scenarios with a digital lens (4IR technologies) for predictive maintenance strategy.

A process for maintenance work management is thus modeled and simulated as a dynamic system. Post-model validation, this study reveals that the real-world maintenance work management process can be replicated using system dynamics modeling. The impact analysis of 4IR technologies on maintenance work management systems reveals that the implementation of 4IR technologies intensifies asset performance with an overall gain of 27.46%, yielding the best maintenance index. This study further reveals that the benefits of 4IR technologies positively impact equipment defect predictability before failure, thereby yielding a predictive maintenance strategy.

The study focused on maintenance work management system without the consideration of other subsystems such as cost of maintenance, production dynamics, and supply chain management.

The maintenance real-world quantitative data is retrieved from two maintenance departments from company A, for a period of 24 months, representing years 2017 and 2018. The maintenance quantitative data retrieved represent six various types of equipment used at underground Mines. The maintenance management qualitative data (Organizational documents) in maintenance management are retrieved from company A and company B. Company A is a global mining industry, and company B is a global manufacturing industry. The reliability of the data used in the model validation have practical implications on how maintenance work management system behaves with the benefit of 4IR technologies' implementation.

This research study yields an overall benefit in asset management, thereby intensifying asset performance. The expected learnings are intended to benefit future research in the physical asset management field of study and most important to the industry practitioners in physical asset management.

This paper provides for a model in which maintenance work and its dynamics is systematically managed. Uncontrollable corrective maintenance work increases the complexity of the overall maintenance work management. The use of a system dynamic model and simulation incorporating 4IR technologies adds value on the maintenance work management effectiveness.

The existence of clearance in joints of positioning mechanism is inevitable and the movements of the real mechanism are deflected from the ideal mechanism due to the clearances. The purpose of this paper is to investigate the effects of clearance on the dynamic characteristics of dual-axis positioning mechanism of a satellite antenna.

The dynamics analysis of dual-axis positioning mechanism with clearance are investigated using a computational approach based on virtual prototyping technology. The contact model in joint clearance is established by using a hybrid nonlinear continuous contact force model and the friction effect is considered by using a modified Coulomb friction model. Then the numerical simulation of dual-axis positioning mechanism with joint clearance is carried out and four case studies are implemented for different clearance sizes.

Clearance leads to degradation of the dynamic performance of the system. The existence of clearance causes impact dynamic loads, and influences the motion accuracy and stability of the dual-axis positioning mechanism. Larger clearance induces higher frequency shakes and larger shake amplitudes, which will deteriorate positioning accuracy.

Providing an effective and practical method to analyze dynamic characteristics of dual-axis positioning mechanism of satellite antenna with joint clearance and describing the dynamic characteristics of the dual-axis positioning system more realistically, which improves the engineering application.

The paper is the basis of mechanism design, precision analysis and robust control system design of dual-axis positioning mechanism of satellite antenna.

This study investigates system dynamics (SD) applications in performance measurement (PM) research and practice. A bibliometric analysis was conducted to investigate the maturity of this research area and identify opportunities for development.

A systematic literature review (SLR) was conducted to provide a comprehensive and rigorous review of the existing literature. The search was conducted on 10 platforms identifying 97 publications, which were evaluated using bibliometric analysis.

The analysis revealed that applications of SD are most commonly used in the PM system design phase to model organisational performance. In addition, the bibliometric results showed a highly dispersed author set, with most studies using exploratory methods, suggesting that the research is in a relatively early stage of development. The results also showed that over 50 per cent of the causal models were not validated, emphasizing an important methodological gap in this research area.

This SLR is limited to indexed publications on 10 platforms, the search strategy was relatively precise and only available papers in English language were used for the literature review.

PM systems supported by SD can help managers understand and improve organisational behaviours by addressing dynamic complexities and relationship between variables. This study evaluates the maturity of this research area including information about the current development of this area and opportunities to build on existing knowledge.

This study identifies how SD approaches are applied to PM and highlights areas that require further research consideration. This paper is the first of two publications to result from this study and focuses on evaluating the current state of this research area.

The purpose of this paper is to propose a combination of forecasting methods that enables a holistic understanding of a future situation, given certain influencing variables by a combination of real data and expert knowledge.

The proposal combines two well-known methods: first, system archetypes that correspond to generic structures, allowing us to handle model management issues, and second, system dynamics that offers technical support on a computational level to assess different scenarios or problem solutions.

The case study considers the situation of the mining industry in Chile and its related variables, including four different scenarios. Based on the proposed methodology, the results indicate that: first, the price of copper is paramount for the industry and its effects are not limited to company profits; second, a long period of downfall in copper prices could halt exploration and development projects.

Systemic archetypes are still a subject of research and their application in different fields of knowledge continues to increase to improve this simulation approach.

The case study illustrates the combination of a Vester matrix and initial system archetype models that are enriched using the system dynamics approach. Indeed, the case study aims to understand the consequences of different scenarios based on the problem-driven approach provided by Vester.

The goal of prospective studies of large-scale and complex situations is to model the real situation to obtain solutions that may enhance social welfare.

The proposed methodology contributes to the existing literature by integrating techniques such as the Vester matrix, system archetype modelling and system dynamics simulation, all of which were proposed previously in the literature as independent techniques.

Este artículo propone una combinación de métodos de pronósticos que permite una comprensión holística de una situación futura, dadas ciertas variables de influencia mediante una combinación de datos reales y conocimiento de expertos.

La propuesta combina dos métodos conocidos: (i) arquetipos de sistemas que corresponden a estructuras genéricas, lo que nos permite manejar los modelos, y (ii) la dinámica de sistemas que ofrece soporte técnico a nivel computacional para evaluar diferentes escenarios o soluciones de problemas.

El caso de estudio considera la situación de la industria minera en Chile y sus variables relacionadas, incluidos cuatro escenarios diferentes. Según la metodología propuesta, los resultados indican que i) el precio del cobre es primordial para la industria y sus efectos no se limitan a las ganancias de la empresa; ii) un largo período de caída en los precios del cobre podría detener los proyectos de exploración y desarrollo.

Los arquetipos sistémicos siguen siendo un tema de investigación y su aplicación en diferentes campos del conocimiento continúa aumentando para mejorar este enfoque de simulación.

El estudio de caso ilustra la combinación de una matriz de Vester y los modelos de arquetipos del sistema inicial que se enriquecen utilizando el enfoque de dinámica de sistemas. De hecho, el caso de estudio apunta a comprender las consecuencias de diferentes escenarios basados en el enfoque orientado a los problemas proporcionado por Vester.

El objetivo de los estudios prospectivos para situaciones de gran escala y complejas es modelar la situación real para obtener soluciones que puedan mejorar el bienestar social.

La metodología propuesta contribuye a la literatura existente mediante la integración de técnicas como la matriz de Vester, el modelado de arquetipos del sistema y la simulación de dinámica de sistemas, todo lo cual se propuso anteriormente en la literatura como técnicas independientes.

This study aims to describe in detail, a system dynamics-based study that was used to show how a large vertically integrated aquaculture company should approach its stepwise capacity expansion program, without undermining its financial performance or affecting the performance of the value chain.

The company and its aquaculture value chain are used as case study. A system dynamics model is developed on the basis of generic end-to-end agribusiness and aquaculture supply chain models. The model includes the unique dynamics relating to an aquaculture supply chain. Also modelled is the working capital management rules of the company, with the effects of the capacity expansion program on its working capital, market share and its supply chain obligations. The model is used to determine the long-term impact of the company’s working capital management under different modes of financing and rate of expanding the capacity.

For a large vertically integrated company that wants to increase its capacity, there is a systematic approach to working capital management that can be used to avoid financial distress or value chain distortion.

Extended the scope of system dynamics modelling within multiple disciplines, namely, agribusiness supply chain finance, supply chain capacity investment, financial management in large companies, supply chain working capital management and aquaculture value chain.

The developed model can be used to manage supply chain working capital in large vertically integrated agribusinesses, and also to assess supply chain financial risk.

To enhance the model build, discrete event simulation was used to model aspects of the system. The eventual system dynamics-discrete event simulation model is a form of hybrid simulation modelling that was used to provide a deeper understanding of how supply chain financial decisions affect an entire value chain system.