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This paper aims to present a systematic review of the published literature on building information model (BIM)-based simulation tools used for occupant evacuation over the past 23 years.

A literature review was conducted on BIM-based simulation tools used for occupant evacuation over the past 23 years. The search identified a total of 37 relevant papers, which were reviewed. The paper describes the use of BIM-based simulation tools over the years and identifies the research gaps.

BIM-based simulation tools have undergone progressive development, with constant improvements through the integration of advanced tools and collection of more data. These tools can assist in identifying faults in the building design. The outcomes of the simulation were not entirely accurate, as real-life scenarios vary depending on the various building types and the behavior of their occupants.

This study contributes to the literature through reviewing the capabilities of BIM-based simulation tools and the different simulation methods along with their limitations.

Fire safety engineers and architects can comprehend the utilization of BIM-based simulation tools to enhance the fire evacuation in light of their shortcomings and flaws.

BIM-based simulation tools are becoming more advanced and widely used. There has not been a comprehensive evaluation of the capabilities of the integration of BIM tools and simulation modeling for occupant evacuation. This study guides researchers on the capabilities and efficiencies of integrated solutions for occupant evacuations and their inherent shortcomings. The study identifies future research areas in BIM-based tools for occupant evacuation.

Existing literature points out that conventional educational modes are not sufficiently motivational for students. Concurrently, the contemporary society requires awareness of sustainability within project management. The purpose of this paper is to investigate how the use of simulations in project management education can positively impact students’ awareness of sustainability and enhance their ability to navigate projects in a sustainable way.

Experiment where 26 experienced professionals with different backgrounds engaged in three extensive project management simulations with sustainable aspects and participated in pre- and post-assessments.

Our research shows that simulations have a high potential for enhancing learning on project management with sustainable aspects. We conclude that simulations can significantly contribute to enhancing student awareness of sustainability. This is through directly confronting them with three areas in which sustainability impacts project management, that is the management of environmental, social, and economic aspects; through handling opportunities, complexities, and adaptability; and by assuming responsibility for sustainable development in the simulation case.

We have shown that simulations – as a part of project management education – are highly likely to augment students' capacity to navigate their projects in a sustainable way.

This paper offers results of an empirical study on simulations as a means to create awareness of ability to navigate projects in a sustainable way. The paper provides extensive qualitative statements from participants, and thereby gives the reader insights into the raw data leading to insightful conclusions for the field of project management education.

Higher education institutions are undergoing a change in their teaching–learning practices, with the core goal of giving students the necessary skills and competencies to succeed in a complex and uncertain society. This study aims to evaluate the effectiveness of business simulation as a pedagogical strategy for teaching 21st-century competencies to undergraduate students. The study looks at students’ self-perception on how business simulation impacts future skills such as entrepreneurship, employability and sustainability.

The research incorporates a one-week workshop for undergraduate business students using AnyLogic business simulation. For this study, a 24-item skills-based survey was used as the instrument for eliciting input about students’ self-perceptions. To measure the impact of business simulation on overall student learning, a theoretical framework was developed and tested using SmartPLS version 4 for construct reliability, validity and hypotheses testing.

Based on the students’ feedback, the finding shows that most of the 24 soft skills were facilitated by the business simulation used. The simulation significantly affects the development of entrepreneurial and employable skills. On the contrary, it has little effect on enhancing sustainability skills. In addition, the study suggests that factors like gender and expertise had little overall impact on the results.

The most apparent practical implication of this study is that business schools should focus more on skill development by stressing on experiential teaching methods like business simulation to help students build various skills and become more prepared for the actual world of business.

The research presents fresh empirical data that add to the continuing discussion on active learning in business education and assist educators in avoiding some potential drawbacks of these innovative teaching techniques. With the right direction and criticism throughout the simulation, this learning experience has shown to be useful for everyone involved.

The purpose of this study is to create an extended equivalent circuit model for a compound DC motor, consisting completely of electrical parameters and quantities.

The dynamic model of the compound DC motor is obtained by establishing the voltage equations for the armature and excitation circuit and the mechanical equation for the mechanical part. The mechanical parameters in the dynamic model are converted into electrical parameters with an electrical circuit proposed for the mechanical part. By combining the armature and excitation circuits with the electrical circuit created for the mechanical part, the extended equivalent circuit model of the compound DC motor is obtained. Because the proposed extended equivalent model is completely an electrical circuit, simulations can be made in the circuit simulation programme. Simulations of the proposed compound DC motor circuit were carried out, and the accuracy of the proposed circuit was verified by performing experimental studies with an existing compound motor.

When comparing speed and current profiles in experiments and simulations, it is seen that compound DC motor can be modelled with the proposed equivalent circuit including completely electrical elements in a simulation programme for the circuits. The results show that the proposed equivalent circuit satisfies the dynamic model of the compound motor.

In DC machine models, armature and excitation circuits are given as an electrical circuit, and mechanical part of the machine is modelled by only mechanical equations. The originality of this study is converting the dynamic model of an electrical machine consisting of electrical and mechanical equations into a completely electrical circuit. With the proposed method, the dynamic model of many motors can be converted into a completely electrical circuit. In this way, motors can be simulated as an electrical circuit in simulation programmes for the circuits, and the dynamic behaviour of motors can be obtained.

The objective of this study is to mitigate the risks of a blood shortage. The authors designed two simulation studies to identify the superior methodology that can decrease the impact of a massive national donor shortage.

The simulation designs are triggered by the COVID-19 pandemic. The first simulation examines the company’s choice of strategic partners (regionally and nationally), and the second inspects creating a national coordinated effort to organize a pooled blood inventory that would require blood centers to contribute a small percentage of their monthly donations to become a member.

The results indicate that both methods can significantly manage the risk of stockouts regardless of the availability of safety inventory in a blood center; however, although more effective in reducing the number of shortages per month, creating a national blood pool causes the shortages to be recognized earlier than desired.

The authors contribute to the literature by focusing on the potential risk of blood shortage because it directly impacts healthcare, hospitals’ costs and their ability to provide care. Though a handful of researchers have targeted the study of the blood supply chain, there is not any article that is similar to this study.

Despite the growing importance of visual information, user-generated photos in product reviews have received relatively little attention. We investigate whether the contextual background of a product image can influence consumers' perceptions of review helpfulness and product evaluation.

Online experiments were conducted using a scenario technique. A single factor (contextual background: low vs. high) between-subjects design was conducted in Study 1. A 2 (contextual background: low vs. high) × 2 (mental simulation: outcome vs. process) between-subjects design was conducted in Study 2.

A photo with a high (vs. low) contextual background enhances mental imagery, increasing perceived helpfulness and product evaluation. Furthermore, mental simulation plays a significant moderating role in the relationship between contextual background and mental imagery.

Based on cue utilization theory, this study identifies how the contextual background of product images affects consumers' perception and product evaluation by uncovering the underlying mechanism of mental imagery. Furthermore, the research examines the moderating effect of mental simulation while reviewing user-generated photos.

This study aims to evaluate the dynamics between healthcare resource capacity expansion and disease spread. Further, the study estimates the resources required to respond to a pandemic appropriately.

This study adopts a system dynamics simulation and scenario analysis to experiment with the modification of the susceptible exposed infected and recovered (SEIR) model. The experiments evaluate diagnostic capacity expansion to identify suitable expansion plans and timelines. Afterwards, two popularly used forecasting tools, artificial neural network (ANN) and auto-regressive integrated moving average (ARIMA), are used to estimate the requirement of beds for a period when infection data became available.

The results from the study reflect that aggressive testing with isolation and integration of quarantine can be effective strategies to prevent disease outbreaks. The findings demonstrate that decision-makers must rapidly expand the diagnostic capacity during the first two weeks of the outbreak to support aggressive testing and isolation. Further, results confirm a healthcare resource deficit of at least two months for Delhi in the absence of these strategies. Also, the study findings highlight the importance of capacity expansion timelines by simulating a range of contact rates and disease infectivity in the early phase of the outbreak when various parameters are unknown. Further, it has been reflected that forecasting tools can effectively estimate healthcare resource requirements when pandemic data is available.

The models developed in the present study can be utilised by policymakers to suitably design the response plan. The decisions regarding how much diagnostics capacity is needed and when to expand capacity to minimise infection spread have been demonstrated for Delhi city. Also, the study proposed a decision support system (DSS) to assist the decision-maker in short- and long-term planning during the disease outbreak.

The study estimated the resources required for adopting an aggressive testing strategy. Several experiments were performed to successfully validate the robustness of the simulation model. The modification of SEIR model with diagnostic capacity increment, quarantine and testing block has been attempted to provide a distinct perspective on the testing strategy. The prevention of outbreaks has been addressed systematically.

The purpose of this study is to address why managers enter the excessive market. A comparison of the facts and perceptions of entrants relative to success in the market shows that many entrants are confident about the viability of their businesses and enter the market. Accordingly, the authors simulate market entry decisions to detect behavioral biases.

The authors adapted the entry decisions simulation method, which is supported by the theoretical foundations of signal detection theory (SDT) and signaling theory. The simulation model is implemented on the Anaconda platform and written in Python 3.

The results of this study suggest that overestimation relates to excess market entry. Also, the proportion of excess entry under difficult conditions is always higher than under easy conditions.

This research helps managers and firms think about their and their competitors' abilities and evaluate them before entering the market. Policymakers and practitioners can also design programs such as experiential learning to help entrants assess their skills.

So far, no research has investigated the role of overconfidence under different market conditions. Accordingly, this study contributes to the current market entry literature by disentangling the debate between absolute and relative confidence and by considering the role of task difficulty.

Influencer marketing mediated by social media is prevalent in social commerce. Micro-, meso- and macro-influencers all play an irreplaceable role in marketing. The purpose of this paper is to explore how companies with limited budgets choose influencers according to products' various levels of brand familiarity.

This study constructs an evolutionary game model of influencer marketing based on evolutionary game theory on complex networks. This model initiates various networks to demonstrate how influencers disseminate information and constructs update mechanisms to depict how individuals react to this information based on individuals' information utility and friends' strategies.

Simulation results suggest that companies should invest more in macro-influencers than in meso-influencers, however investing all in macro-influencers is not a good choice. The investment in meso-influencers will increase as brand familiarity decreases, whereas it will not exceed investment in macro-influencers. Furthermore, the accumulation of micro-influencers can accelerate the marketing process.

This study examines the combined effects of micro-influencers, meso-influencers and macro-influencers in marketing by simulating the marketing process initiated by influencers on social media.

The purpose of this research is to examine how a change in team dynamics impacts an individual's motivation to engage in helping behavior and operational performance.

An online vignette experiment and a hybrid discrete event and agent-based simulation model are used.

Study findings demonstrate how a non-core worker's perception of team dynamics influence engagement in helping behavior and system performance.

This study provides a further understanding on how team members react to changes in team processes. This study theorizes on how an individual team member responds to fairness concerns. This study also advances our understanding of the critical importance of helping behavior in a retail logistics setting. This research illustrates how the theory of strategic core and procedural justice literature can be adopted to explain team dynamics in supply chain management.