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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.

Both system dynamics (SD) and agent-based modeling (ABM) have been used in simulation-based group dynamics research. To combine the advantages of both simulation approaches, the concept of SD-ABM hybrid simulation has been proposed. However, research efforts to compare the effectiveness of modeling approaches between the hybrid and non-hybrid models in the context of group dynamics study are rare. Against this background, this study aims to propose an agent-embedded SD (aeSD) modeling approach and demonstrate its advantages when compared to pure SD or ABM modeling approaches, based on a research case on construction workers’ social absenteeism.

The authors introduce an aeSD modeling approach to incorporate individual attributes and interactions among individuals in an SD model. An aeSD model is developed to replicate the behavior of an agent-based model previously developed by the authors to study construction workers’ group behavior regarding absenteeism. Then, the characteristics of the aeSD model in comparison with a pure ABM or SD model are demonstrated through various simulation experiments.

It is demonstrated that an aeSD model can capture the diversity of individuals and simulate emergent system behaviors arising from interactions among heterogeneous agents while holding the strengths of an SD model in identifying causal feedback loops and policy testing. Specifically, the effectiveness of the aeSD approach in policy testing is demonstrated through examples of simulation experiments designed to test various group-level and individual-level interventions to control social absence behavior of workers (e.g. changing work groupings, influencing workgroup networks and communication channels) under the consideration of the context of construction projects.

The proposed aeSD modeling method is a novel approach to how individual attributes of agents can be modeled into an SD model. Such an embedding-based approach is distinguished from the previous communication-based hybrid simulation approaches. The demonstration example presented in the paper shows that the aeSD modeling approach has advantages in studying group dynamic behavior, especially when the modeling of the interactions and networks between individuals is needed within an SD structure. The simulation experiments conducted in this study demonstrate the characteristics of the aeSD approach distinguishable from both ABM and SD. Based on the results, it is argued that the aeSD modeling approach would be useful in studying construction workers’ social behavior and investigating worker policies through computer simulation.

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.

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.

Globally, supply chains compete in a complex and rapidly changing environment. Hence, sustainable supplier selection has become a decisive variable in the firm’s financial success. This requires reliable tools and techniques to enhance understanding on how supplier behavior evolves with time and to select the best sustainable supplier. System dynamics (SD) is an approach to investigate the dynamic behavior in which the system alterations correspond to the system variable changes. Fuzzy logic usually solves the challenges of imprecise data and ambiguous human judgment. The paper aims to discuss these issues.

This work presents a novel modeling approach for integrating information on supplier behavior in fuzzy environment with SD simulation modeling technique. This results in a more reliable and responsible decision-support system. Supplier behavior with respect to relevant sustainability criteria were sourced through expert interviews and simulated in Vensim to select the best possible sustainable supplier. The simulation runs were carried out in four scenarios, namely, past, current, future and average time horizon for four different suppliers. A multi-criteria decision-making model was presented to compare results from the systems dynamics model.

An increase in the rate of investment in sustainability by the different suppliers causes an exponential increase in total sustainability performance of the suppliers. The growth rate of the total performance of suppliers outruns their rate of investment in sustainability after about 12 months.

While a significant work exists regarding supplier selection, little work has been found that investigates how to insure sustainable suppliers maintain their status for a long period of time.

Chapter 16 is an introduction to systems thinking and analyzing the system dynamics of relationships within an organization or between organizations. Systems thinking builds on the propositions that (1) all variables or conditions have both dependent and independent relationships, (2) lag effects occur in relationships, (3) feedback relationships occur (e.g., A→B→C→A), and (4) seemingly minor relationships (i.e., “hidden demons”) have huge influence in causing a set of relationships (i.e., a system) to implode or explode. The propositions of building and testing a set of relationships apply in many contexts; this chapter examines systems thinking and system dynamics in one context as an introduction to this stream of case study research. Hall (1976) provides details of an advanced application of systems dynamics research – do not be fooled by the date of the study; Hall (1976) is an exceptional up-to-date case research study using system dynamics modeling. This chapter describes the issues and criticisms concerning golf, tourism, and the environment and considers how golf–tourism–environment relationships might achieve economic well-being for a region while avoiding vicious cycles of destruction to local environments and the quality of life of local residents. The examination proposes the use of systems thinking, cause mapping, and system dynamics modeling and simulations of golf, tourism, and environmental relationships to help achieve workable solutions agreeable to all stakeholders. Sustainable relationships that include golf, tourism, and environmental objectives require crafting government policies via stakeholder participation of all parties that such relationships affect – recognizing and enabling this requirement needs to be done explicitly – to reduce conflicts among stakeholders and avoid system failures.

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.

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.

Design and build (D/B) construction methods have gained more importance in recent years for their potential advantages in improving project performance. There are, however, a number of problems that are commonplace in D/B procurement, which, when they interact with each other, can lead to project time and cost overrun problems. The most important among them are design changes, together with communication and coordination lapses among concerned parties. Past research has focused only on the characteristics of the traditional construction, or separate sub‐systems such as different phases or human resource input to projects. An attempt is made in this paper to improve D/B project time and cost performance. A generic system dynamics model is developed that incorporates major sub‐systems and their relationships inherent in D/B constructions projects. It is validated and calibrated for a typical large D/B infrastructure project using time and cost overrun problems experienced in Thailand. Extensive simulations with many policies, individually or in various combinations, show that improvement in time or cost can be made with proper policy combinations that reflect strong interactions between the whole design and build system and can be derived only if these interactions are accounted for. To achieve overall improvement in both time and cost, the combination of full overtime schedule, average material ordering, and fast track construction with moderate crashing of design is most appropriate. If cost is the focus, extending the construction schedule, combined with material ordering based on actual need, and design and build with traditional construction method is the best solution.

If the use of information technology (IT) supporting clinical trial projects offers opportunities to optimize the underlying information management process, the intricacy of the identification and evaluation of relevant IT options is generally seen as a complex task in healthcare. Hence, the purpose of this paper is to examine the problem of ex ante information system evaluation, and assess the impact of IT on the information management process underlying clinical trials.

Combining Unified Modeling Language (UML) and system dynamics modeling, a simulation model for evaluating IT was developed. This modeling effort relies on a case study conducted in a clinical research organization, which, at that time, faced an IT investment dilemma.

Some illustrative results of sensitivity analyzes conducted on error rates in clinical data transmission are presented. These simulation results allow for quantifying the impact of different IT options on human resources' efforts, time delays and costs of clinical trials projects. Notably, the results show that although the technology has no real influence on the duration of a clinical trial project, it impacts the number of projects that can be carried out simultaneously.

The research provides insights into the development of an innovative approach appropriate to the evaluation of IT supporting clinical trials, through the use of a mixed‐method based on qualitative and quantitative modeling. The results illustrate two critical issues addressed in the IS literature: the necessity to extend IT evaluation beyond the quantitative‐qualitative dichotomy; and the role of evaluation in organizational learning, and in learning about business dimensions.