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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.

Induction machines for traction applications are operated at working points of high ferromagnetic saturation. Depending on the working point, a broad spectrum of harmonic frequencies appears in the magnetic flux density of induction machines. Detailed loss analysis therefore requires local and temporal highly resolved nonlinear field computation. This loss analysis can be performed in the post processing of nonlinear transient finite element simulations of the magnetic circuit. However, it takes a large number of transient simulation time steps to build up the rotor flux of the machine.

In this paper, hybrid simulation approaches that couple static FEA, transient FEA and analytic formulations to significantly decrease the number of simulation time steps to calculate the magnetic field in steady state are discussed, analyzed and compared.

The proposed hybrid simulation approaches drastically decrease the simulation time by shortening the transient build-up of the rotor flux. Depending on the maximum error of the rotor flux linkage amplitude compared to the steady state value, a reduction of simulation time steps in the range of 55.5 to 98 per cent is found.

The presented hybrid simulation approaches allow efficient performing of the transient FE magnetic field simulations of induction machines operated as traction drives.

This study aims to propose a hybrid simulation approach for site layout and material laydown planning in construction projects considering both the project’s continuous and discrete state.

Efficient site layout planning (SLP) is a critical task at the early stages of the project to enhance constructability and reduce safety risks, construction duration and cost. In this paper, external and internal conditions affecting SLP gets identified. Then dynamic features of project conditions and project operations are analyzed by using a hybrid simulation approach combining continuous simulation (CS) and discrete event simulation (DES).

An efficient site layout plan regarding the project conditions results in cost efficiency. Instead of using DES or CS alone, this paper uses a hybrid simulation approach. Such a hybrid method leads to more accurate results that enable construction managers to make better decisions, such as material management variables. The proposed approach is implemented in a real construction project (i.e. earthmoving operation) to evaluate the hybrid simulation approach’s performance.

The proposed approach is implemented in a real construction project (i.e. earthmoving operation) to evaluate the performance of the hybrid simulation approach.

Although DES is used widely in construction simulation, it involves some limitations or inefficiencies. On the other hand, modeling resource interactions and capturing the construction project’s holistic nature with CS or system dynamics face some challenges. This study uses a hybrid DES and CS approach to enhance commercial construction projects’ SLP.

It is argued that problem‐based learning (PBL) is a valuable approach to teaching operations management, as it allows learners to apply their knowledge and skills in an environment that is close to real‐life. In fact, many simulations currently exist in the teaching of operations management. However, these simulations lack a connection to real‐life, as they are typically turn‐based and do not use real‐life IT support. The current paper seeks to address this issue by presenting an innovative pedagogical approach designed to provide learners with an authentic problem‐solving experience in operations management within an enterprise resource planning (ERP) system.

The paper proposes a simulation game called ERPsim whereby students must operate an enterprise in a simulated economic environment using in real time a real‐life ERP system, namely SAP. Based on a survey with instructors, it assesses the extent to which this proposed simulation is aligned with the five characteristics of the PBL approach.

Survey respondents confirm that significant improvements in student evaluations, learner motivation, attendance, and engagement, as well as increased learner competence with the technology can be achieved by using the proposed approach.

For more than five years this pedagogical approach has been used by more than 250 professors, lecturers, and professional trainers in over 160 universities worldwide. Between September 2009 and June 2011, more than 3,000 simulations games were played by over 16,000 university student teams.

Results and observations on using the proposed pedagogical approach are presented and compared to the main characteristics of the PBL approach (authenticity, ill structured problems, student‐centered, small group settings and facilitator dimensions).

The aim of this paper is to offer agent‐based modelling (ABM) as an alternative approach to advance research in entrepreneurship. It argues that ABM allows entrepreneurship researchers (i.e. the designers) to find better ways in generating entrepreneurial outcomes by understanding alternative histories and examining a plausible future.

This paper begins with an overview of ABM, and discusses the shared conceptual foundations of entrepreneurship and ABM as the motives for the adoption of ABM as an appropriate methodology to study entrepreneurship. It offers a roadmap in using ABM approach for entrepreneurship research and illustrates this using a contemporary research question in entrepreneurship: the study of success/failure in business venturing.

This paper suggests the shared foundations between ABM and entrepreneurship as the basis for bringing the methodology and research domain closer. It offers a roadmap for advancing entrepreneurship research using agent‐based simulation approach and explains the contribution of ABM to further advance entrepreneurship research.

This paper addresses the methodological gap in entrepreneurship research and develops the argument for a wider adoption of ABM simulation approach to study entrepreneurship. It bridges the gap by examining the possibility of formalizing entrepreneurship processes by grounding an agent‐based model on empirical facts and generally‐accepted foundations of entrepreneurship. It offers a contribution to the literature by showing that ABM is a useful and appropriate methodological approach for entrepreneurship research in addition to the conventional variance and process approach.

This chapter compares the performance of the maximum simulated likelihood (MSL) approach with the composite marginal likelihood (CML) approach in multivariate ordered-response situations. The ability of the two approaches to recover model parameters in simulated data sets is examined, as is the efficiency of estimated parameters and computational cost. Overall, the simulation results demonstrate the ability of the CML approach to recover the parameters very well in a 5–6 dimensional ordered-response choice model context. In addition, the CML recovers parameters as well as the MSL estimation approach in the simulation contexts used in this study, while also doing so at a substantially reduced computational cost. Further, any reduction in the efficiency of the CML approach relative to the MSL approach is in the range of nonexistent to small. When taken together with its conceptual and implementation simplicity, the CML approach appears to be a promising approach for the estimation of not only the multivariate ordered-response model considered here, but also for other analytically intractable econometric models.

The purpose of this study is to numerically simulate the Lamb wave propagation through a clamp-on ultrasonic gas flowmeter (UGF) in contact mode, using a new semi three-dimensional approach. Moreover, experimental and analytical modeling results for transit time difference method have been used to confirm the simulation results at different gas flow velocities from 0.3 to 2.4 m/s.

The new semi three-dimensional approach involves the simulation of the flow field of the gas in a three-dimensional model and subsequently the simulation of wave generation, propagation and reception in a two-dimensional (2D) model. Moreover, the analytical model assumes that the wave transitions occur in a 2D mode.

The new approach is a semi three-dimensional approach used in this work, has better accuracy than a complete 2D simulation while maintaining the computing time and costs approximately constant. It is faster and less expensive than a complete 3D simulation and more accurate than a complete 2D simulation. It was concluded that the new approach could be extended to simulate all types of ultrasonic gas and non-gas flowmeters, even under harsh conditions.

In this work, a new approach for the numerical simulation of all types of ultrasonic flowmeters is introduced. It was used for simulation of a Lamb wave ultrasonic flow meter in contact mode.

Virtual organisations (VOs) in manufacturing represent a promising approach for dealing with today's difficult markets. The selection of the right partners during the creation phase is a prerequisite for their success. Owing to the complexity of the underlying networks as well as the need to react immediately to market opportunities, tool support is necessary for finding a suitable consortia for a given business purpose while reducing the immanent risk of failure. The purpose of this paper is to exemplify the conception and realisation of such a tool.

The approach taken in this work consists of four steps: first of all, the requirements to be fulfilled by the tool are derived from the main characteristics of VOs. Subsequently, existing approaches which could serve as a technical basis for the tool are presented and ranked. To conclude, a tool design is introduced and applied to a brief case study.

It is shown that simulation appears as very suitable within the considered problem domain. It is further pointed out that simulation requires user‐friendly components addressing modelling, simulation execution and analysis in order to be applicable and accepted by domain experts as end‐users.

The paper presents an overview of technical approaches supporting partner identification during the establishment phase of VOs. It describes a concept for a simulation environment addressing the needs of practitioners from industry. Finally, it depicts necessary extensions for model verification and solution finding.

Conventionally, various levels of decisions with regard to production are made in a number of sequential stages such as system design, production/process planning, production scheduling, system reconfiguration and system restructure. This paper aims to present an integrated approach for modelling, restructuring and simulating manufacturing systems to suit changing manufacturing situations as quickly as possible.

An agent‐based approach is employed where each manufacturing resource is represented by an agent. Simply speaking, the approach enables the machines in a manufacturing system to manage themselves efficiently and effectively.

The agent‐based modelling and interaction approach enables manufacturing resources to be allocated dynamically in an optimal manner. The modelling approach also enables alternative system configurations to be identified and evaluated using distributed discrete event simulation system. Resource allocation and manufacturing system control can take place simultaneously with simulation.

This paper presents a successful integration of agent‐based modelling, process planning, scheduling, control, identification of alternative system configurations, simulation and analysis of the configurations and PLC reprogramming within a coherent framework for improved manufacturing responsiveness.

The purpose of this paper is to propose a novel hybrid approach called as Markov System Dynamics (MSD) approach which combines the Markov approach with system dynamics (SD) simulation approach for availability modeling and to study the dynamic behavior of repairable systems.

In the proposed approach the identification of the single unit repairable system all possible states has been performed by using the Markov approach. The remaining stages of traditional Markov analysis are highly mathematically intensive. The present work proposes a hybrid approach called as MSD approach which combines the Markov approach with SD simulation approach to overcome some of the limitations of Markov process in a simple and efficient way for availability modeling and to study the dynamic behavior of this system.

The proposed framework is illustrated for a single unit repairable system. The worked out example shows the steady state point and also it gives the point, interval and steady state availabilities and also the dynamic behavior of the system. However this methodology can be extended easily for more complex multi-state maintainable systems. The results of the simulation when compared with that obtained by traditional Markov analysis clearly validate the proposed approach as an alternative approach for availability modeling of repairable systems.

In many practical situations we require to find the time at which our system reaches steady state conditions for planning maintenance activities. The proposed MSD method in this paper is capable of finding this steady state point very easily.

The proposed approach clearly indicates the time at which the system reaches its steady state and calculates the point, interval availabilities for planning maintenance activities. The different parties, i.e., engineers and machine operators, can jointly work with this model in order to understand the dynamic behavior of repairable systems.