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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.

Logistics systems used in companies that perform multiple roles are expected to be able to manage conflicting objectives. Nevertheless, the literature suggests that many existing logistics performance measurement system (PMS) frameworks are not optimized to provide mechanisms to reveal dynamic relationships between conflicting performance indicators. The purpose of this paper is to develop a new logistics PMS by linking the system dynamics model with a set of balanced performance indicators.

The logistics PMS is developed through a literature review and case study of a company that plays multiple roles. The interrelationships between logistics factors and their links to end results are modeled in diagrams through in-depth interviews with stakeholders. The developed model is then used to build a simulation tool to analyze factors that cause poor performance.

The new logistics PMS developed by incorporating system dynamics offers decision makers ways to identify dynamic relationships among factors and conflicting indicators, in turn helping them to understand holistic logistics performance, objectively analyze why logistics systems perform in a certain way and foster a common shared view.

Stakeholders of companies that play multiple roles can use the new PMS model to comprehensively evaluate the performance of logistics systems. In addition, the increased visibility of logistics systems may support decision-making while preventing local optimization.

A logistical PMS based on the system dynamics model for managing logistics systems in companies performing multiple roles has not yet been identified. This paper fills this theoretical gap and contributes to the academic literature by proposing a novel PMS model based on the system dynamics model to address the limitations of existing PMS frameworks.

This paper aims to focus on the development of a “dynamic Balanced Scorecard” and to demonstrate that matching the traditional Balanced Scorecard (BSC) architecture with system dynamics principles offers better support for strategic management decisions.

The paper is based on a case study related to a service‐based business. The maps, the mathematical model and the BSC developed according to system dynamics modelling principles are discussed.

A system dynamics‐based BSC, particularly if embedded into a management flight simulator, would allow exploration and understanding of features of complexity and dynamics, consideration of feedback loops rather than unidirectional causality, the use of mapping tools for a more comprehensive design of the strategy maps, the facilitation of a process of organisational learning; and support for policy design and strategic analysis performed by managers.

The value of this paper is two‐fold: first, it shows that by using system dynamics modelling principles it is possible to overcome positively some limitations of the original BSC framework; second, the paper provides information and suggestions that are helpful for companies that are interested in developing strategic management systems based on both BSC architecture and on system dynamics principles and simulation tools (e.g. the management flight simulator).

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 integration of System Dynamics with LP‐ and Input‐Output models is realized by means of simple examples. Aspects of programming techniques as well as the conceptual meaning of this model‐method integration are discussed. By the combination of the stated methods with System Dynamics models an improved flexibility of the System Dynamics method is obtained. The optimization of a Simulation model is represented by the integration of a System Dynamics model into a higher level feedback loop structure. The optimization algorithm, the Razor Search procedure, modifies the parameters of the control vector in order to generate the optimal behaviour of the state vector of the model in relation to an objective function.

A suspended wheeled mobile robot (SWMR) that consists of one or more manipulators can be exploited in various environmental conditions such as uneven surfaces. The purpose of this paper is to discuss the requirements for stable motion planning of such robotic systems to perform heavy object manipulation tasks.

First, a systematic procedure for dynamics modelling of such complicated systems for planar motion is presented and verified using ADAMS simulation software. Next, based on the new dynamic moment‐height stability (MHS) measure, the stability of such systems will be investigated using the obtained dynamics. To this end, introducing the concept of a virtual frame, the obtained model of SWMR has been employed for investigating the effect of the base suspension characteristics as well as terrain roughness on the stability of the system. Next, the stability evaluation of the system is investigated after toppling down which has been rarely addressed in the literature. In addition, using the aforementioned model, the effect of stiffness is examined after instability.

First, a systematic procedure for dynamics modelling of such complicated systems for planar motion is presented and verified using ADAMS simulation software. Next, based on the new dynamic MHS measure, the stability of such systems will be investigated using the obtained dynamics. To this end, introducing the concept of a virtual frame, the obtained model of SWMR has been employed for investigating the effect of the base suspension characteristics as well as terrain roughness on the stability of the system. Next, the stability evaluation of the system is investigated after toppling down which has been rarely addressed in the literature. In addition, using the aforementioned model, the effect of stiffness is examined after instability.

A general procedure for dynamics modelling of SWMRs is presented. To verify the obtained dynamics model, another model for the considered system has been developed by ADAMS software. Next, using the obtained dynamics, the postural stability of such systems is investigated, based on the new postural MHS measure extended for SWMRs. The obtained simulation results show that by decreasing the stiffness coefficients of suspension subsystem the stability of the system weakens.

Effective human resource planning allows management to recruit, develop and deploy the right people at the right place at the right time, to meet organizational internal and external service level commitments. Firms are constantly looking out for strategies to cope with skill shortages that are particularly acute in the “knowledge intense” industries due to high staff turnover. The purpose of this paper is to describe how system dynamics modeling allows management to plan to hire and develop right level of skills and competencies in the organizational inventory to meet desired service level targets.

An integrated system dynamics framework is used to develop various feedbacks and feed forward paths in the context of competence planning and development. The model is mapped onto an overseas process industry company's recruitment and attrition situations and tested using real data.

Strategies for human resource planning are developed by conducting time‐based dynamic analysis. Optimum design guidelines are provided to reduce the unwanted scenario of competence surplus and/or shortage, and therefore, to reduce disparity in between service level needs and availability of right competencies.

System dynamics type of modeling is usually suited for medium to long range timescale (two to five years scenarios). There is a need for the model to be tested in a high turnover industry such as IT to test its efficacy in short‐term time scale, where shortage in required talent is more acute. Also this model is tested for measuring the generic skill‐sets in here. There is a need to test the model for a mixture of generic and specialized skills‐set in a specific business operation.

The authors anticipate that system dynamics modeling would help the decision makers and HR professionals to devise medium to long‐term human resource planning strategies to anticipate and meet the service level expectations from the internal and external customers.

Such planning exercise will avoid the situation of customer dissatisfaction due to right competence shortages. Also this will reduce the staff surplus scenario that usually leads to knee‐jerk reaction to lay‐off unwanted skills, which is usually a costly exercise and impacts negatively on staff morale.

Use of the systems dynamics model introduced here is a novel way to analyze human resource planning function to meet the target service level demands. The idea that an organization can estimate the service level requirements for medium to long‐term situations, and conduct what‐if scenarios in a dynamic sense, can provide valuable information in strategic planning purposes.

The purpose of this paper is to propose a conceptual framework of customer expectation management and a reference model of service experience design which are regarded as the basic foundation to model the processes of service experience design for service operation strategies simulating and testing by employing a system dynamics approach.

System dynamics is the key approach which includes causal loop diagrams and stock and flow diagrams used to build the reference model of experience design. Simulations of the processes of service experience design have also been implemented by Vensim^®.

It is found that the proposed reference model involving customer expectation management can successfully capture the key elements of the service experience design within service operation strategies. The system dynamics approach can effectively enable a macro viewpoint of service experience design for service operation strategies and policies.

With the proposed reference model of service experience design and the system dynamics modeling approach, service providers cannot only comprehensively examine the processes of service experience design in detail but also accomplish the strategies testing and simulating. Hence, service providers can make correct decisions to achieve the business goals via the simulation results beforehand.

This paper contributes to analyze and combine the idea of customer expectation management with service experience design and give rise to a unique reference model of service experience design that is shown to be valuable to service operation strategies testing and simulating based on the system dynamics perspective.

A plethora of studies focused on the cause and solutions for the bullwhip effect, and consequently many have successfully experimented to dampen the effect. However, the feasibility of such studies and the actual contribution for supply chain performance are yet up for debate. This paper aims to fill this gap by providing a holistic system-based perspective and proposes a fuzzy logic decision-making implementation for a single-product, three-echelon and multi-period supply chain system to mitigate such effect.

This study uses system dynamics (SD) as the central modeling method for which Vensim® is used as a tool for hybrid simulation. Further, the authors used MATLAB for undertaking fuzzy logic modeling and constructing a fuzzy inference system that is later on incorporated into SD model for interaction with the main supply chain structure.

This research illustrated the usefulness of fuzzy estimations based on experts’ linguistically and logically defined parameters instead of relying merely on the traditional demand forecasting based on time series. Despite the increased complexity of the calculations and structure of the fuzzy model, the bullwhip effect has been considerably decreased resulting in an improved supply chain performance.

This dynamic modeling approach is not only useful in supply chain management but also the model developed for this study can be integrated into a corporate financial planning model. Further, this model enables optimization for an automated system in a company, where decision-makers can adjust the fuzzy variables according to various situations and inventory policies.

This study presents a systemic approach to deal with uncertainty and vagueness in dynamic models, which might be a major cause in generating the bullwhip effect. For this purpose, the combination between fuzzy set theory and system dynamics is a significant step forward.