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Although researchers have demonstrated a keen interest in knowledge collaboration in online encyclopedias, previous studies have seldom explored the dynamic interrelations in online encyclopedias over time that involve the iteratively melding of individual cognitive system and knowledge collaboration system. Therefore, this paper aims to reveal the structure and dynamics of knowledge collaboration in online encyclopedias from a perspective of system dynamics (SD).

This paper proposes a general activity system of knowledge collaboration in online encyclopedias based on Engeström’s activity theory. According to the SD methodology proposed by Forrester, this study develops a holistic SD model by identifying interactions of knowledge collaboration factors based on behavioral theories; validating the SD model by structural tests and behavior tests involving historical data of English Wikipedia; and conducting simulation to capture the interactive dynamics of the salient factors of knowledge collaboration.

According to the SD methodology, this study develops and validates an SD model to explore interesting dynamic interrelations among core factors (contributors, conflicts, discussions, entries quantity and entries quality) that are neglected by previous research. The results show that there is a significant negative feedback relationship between inactive contributors and entries quality, between contributors and conflicts and between edit conflicts and entries quality. There is a complicated nonlinear feedback relationship between active contributors and entries quality, and between edit conflicts and discussions.

Different from prior empirical studies that normally investigate the unidirectional linear relationships among prominent factors of knowledge collaboration in online encyclopedias from a static perspective, this study captures a dynamic picture of their interrelations by unfolding their behavior patterns over time. The main contribution of this study is to develop a holistic SD model and to reveal and elaborate on the complex dynamics involved online encyclopedias based on activity theory.

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.

This research studies the development of the evolving dynamic system model and explores the important elements or factors and what detailed attributes are the main influences model in achieving the success of a business, industry and management. It also identifies the real and major differences between static and dynamic business management models and the detailed factors that influence them. Later, this research investigates the benefits/advantages and limitations/disadvantages of some research studies. The studies conducted in this research put more emphasis on the capabilities of system dynamics (SD) in modeling and the ability to measure, analyse and capture problems in business, industry, manufacturing etc.

The research presented in this work is a qualitative research based on a literature review. Publicly available research publications and reports have been used to create a research foundation, identify the research gaps and develop new analyses from the comparative studies. As the literature review progressed, the scope of the literature search was further narrowed down to the development of SD models. Often, references to certain selected literature have been examined to find other relevant literature. To do so, a supporting tool (that connects related articles) provided by Google Scholar, Scopus, and particular journals has been used.

The dynamic business and management model is very different from the static business model in complexity, formality, flexibility, capturing, relationships, advantages, innovation model, new goals, updated information, perspective and problem-solving abilities. The initial approach of a static system was applied in the canvas business model, but further developments can be continued with a dynamic system approach.

Based on this study, which shows that businesses are developing more towards digitalisation, wanting the ability to keep up with the era that is moving so fast and the desire to increase profits, an instrument is needed that can help describe the difficulties of the needs and developments of the future world. This instrument, or tool of SD, is also expected to assist in drawing future models and in building a business with complex variables that can be predicted from the beginning.

This study will contribute to the SD study for many business incubator research studies. Many practical in business incubator management to have a benefit how to achieve the business performance management (BPM) in SD review.

The significant differences between static and dynamics to be used for business research and strategic performance management. This comparative study analyses some SD models from many authors worldwide. Their goals behind their strategic business models and encounter for their respective progress.

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 shed light on improving value creation from intellectual capital (IC) through reducing causal ambiguity and finding effective IC interventions.

First, several guiding rules demonstrating the contribution of system dynamics (SD) to the field of IC management are introduced. Second, evidence for modelling resource dynamics is provided across a knowledge-based industry, insurance. Third, a management problem of an insurance company is modelled and then simulated using SD tools to monitor and improve the alignment of key resources with the firm’s market growth strategy.

The modelling and further simulation practice demonstrated the advantages of applying SD for analysing resource management problems to identify the critical IC components, intervention points and decision rules that may stimulate value-creating loops. Specifically for the case of an insurance company’s failure in market growth, it led to recognising the critical role of agency sales productivity as a key component of company’s relational capital and the intellectual liabilities that can lead to value destruction.

Reducing causal ambiguity in IC value creation through modelling and simulating firm resource dynamics is the main contribution of this paper. It enables finding the best intervention points for developing IC-based initiatives to stimulate value-creation mechanisms, as well identifying possible points of value destruction.

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.

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.

Although researchers have demonstrated a significant interest in motivation factors of knowledge collaboration, previous studies have seldom explored the dynamic interrelations in virtual communities of practice (VCoPs) over time that involve the iteratively melding of knowledge collaboration motivations and behaviours. Therefore, this study aims to unveil the interactive dynamics amongst motivation factors of knowledge collaboration in VCoPs from a perspective of system dynamics (SD).

According to the SD method proposed by Forrester, this paper develops an SD model of motivation factors of knowledge collaboration in VCoP by identifying interactions of motivation factors based on behavioural theories, validating the proposed model by structural tests and behaviour tests involving historical data from 939 Wikipedians and analysing the impacts of policy regulations on knowledge collaboration behaviours in Wikipedia.

In accordance with current literature, this study categorises intrinsic, extrinsic and community motivation factors of knowledge collaborations in VCoPs. According to the SD method, this study develops and validates an SD model to reveal interesting non-linear dynamics of these motivation factors which are neglected by prior studies. This study also conducts dynamic what-if analyses to suggest policy regulations to promote knowledge collaborations in the context of Wikipedia.

Different from prior empirical studies which normally take on a snapshot of motivation factors, this study discloses a dynamic picture of their interrelations by unfolding their behaviour patterns over time. The main contribution of this paper is to develop and validate an SD model of motivation factors of knowledge collaboration in VCoP and to reveal and elaborate their dynamics for policy regulations in VCoPs based on simulation results.

This study aims to contribute to the ongoing debate on behavioral operational research (BOR), specifically discussing the potential of system dynamics (SD) models to analyze decision-making heuristics. In more detail, the study suggests using an SD model as an ex-post research tool adopted not only to mimic a role-playing game (RPG) – reproducing the whole physical structure, and the complete set of decision rules specified for a supply chain (SC) management game – but also, and specifically, to replicate and analyze the players’ in-game behavior and decision-making.

After presenting a brief literature review devoted to highlighting the key concepts of the emerging streams of research named BOR and behavioral system dynamics (BehSD), the study presents the characteristics and results of an SC management-based RPG and describes the SD model that was developed to mimic the game and provide the base-run. A triangulation of data sources (which included feedback questionnaires and reports drawn up by 86 participants, as well as notes collected through direct observation of one of the authors) was used to infer information about and in-game decisions. Subsequently, four alternative versions of the SD model were calibrated to reproduce, investigate and explain ex-post the players’ in-game behavior and decision-making heuristics; this study specifically refers to one of them.

The SD model can be considered as the first output of this research. The model was calibrated to mimic the game and subsequently used to develop a few alternative models, helpful to replicate players’ behavior and analyze decision-making heuristics. The findings reveal not fully rational decisions taken by the players and share common findings with previous literature on the emergence of sub-optimal strategies (e.g. phantom ordering and hoarding strategies). The data collected from questionnaires, reports and direct observation additionally revealed that stress and behavioral factors played a role in affecting in-game decision-making.

Considering a specific RPG setting, the SD model developed in this study replicated and captured the range of factors affecting decision-making heuristics, allowing an ex-post analysis of in-game decisions. Notably, the research design presented and used in this study can be considered a generic one, which could be applied subsequently in a variety of contexts, also in combination with simulation/gaming tools and techniques different from role-playing, and both for educational and training purposes, and for research validation.

This study builds on and makes a contribution to the debate related to the emerging stream of research of BOR and more specifically, provides insights and evidence for the yet growing field of BehSD, at the same time advocating and suggesting further research in this area. Overall, the research revealed that behavioral factors may play a relevant role in driving and affecting human decision-making in simulation/gaming contexts.

The international community recognizes the role of entrepreneurship education in fostering economic growth and sustainable development. However, preparing the next generation of entrepreneurs is not an easy task, since today’s complexity requires the creation of skills and capabilities for which the traditional programs reveal their inadequacy. Some scholars remark how entrepreneurship education and entrepreneurial intention are not necessarily related and, in line with policy makers’ concerns, call for educational programs more routed in financial skills’ enhancement. The purpose of this paper is to explore the potential of system dynamics (SD) for entrepreneurial education, investigating the relationships between financial and entrepreneurial skills’ formation and business development.

The paper introduces the main elements of SD, describes literature streams of SD applications fitting the entrepreneurial education spheres and proposes an SD’ insight model based on selected literature and declined in terms of stock-and-flow and causal loop structures.

The study provides a causal model capturing the links between the processes of entrepreneurial skill formation and firms’ start-ups and closures. Such model introduces a double effect of financial literacy on entrepreneurial orientation and locates the contribution of simulated entrepreneurial decisions in formal and informal educational contexts.

The paper displays how SD can contribute to entrepreneurship and presents an original causal model highlighting the accumulation of financial and non-financial skills through education and experience, their impact on business development and the usefulness of SD methodology for skill achievement.