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1 – 10 of 179This chapter wants to understand under which circumstances and conditions non-traditional aids are effective in the strategic process. This study builds an agent-based…
Abstract
This chapter wants to understand under which circumstances and conditions non-traditional aids are effective in the strategic process. This study builds an agent-based computational simulation model – the S-uFUNK 2.1.0 – to explore the research question. The model features a group of managers that seeks to interpret environmental cues using both traditional and non-traditional tools. When interpretations converge, the group then settles on different focus areas to define a business strategy for their organization. The process is set in a way such that 11 parameters can be manipulated to explore the different conditions under which non-traditional aids are of use. Results suggest that non-traditional aids differ from traditional aids only in limited circumstances and that social dynamics and dispositions within the group are crucial. In general, the simulation helps us reflect on the way in which we consider traditional aids to strategy. In fact, if they are no different than non-traditional aids, their effectiveness is directly challenged.
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This bibliometric mapping study aimed to provide comprehensive insights into the global research landscape of cybernetics. Utilizing the biblioshiny function in R Studio, we…
Abstract
Purpose
This bibliometric mapping study aimed to provide comprehensive insights into the global research landscape of cybernetics. Utilizing the biblioshiny function in R Studio, we conducted an analysis spanning 1958 to 2023, sourcing data from Scopus. This research focuses on key terms such as cybernetics, cybernetics systems, complex adaptive systems, viable system models (VSM), agent-based modeling, feedback loops and complexity systems.
Design/methodology/approach
The analysis leveraged R Studio’s biblioshiny function to perform bibliometric mapping. Keyword searches were conducted within titles, abstracts and keywords, targeting terms central to cybernetics. The timespan, 1958–2023, provides a comprehensive overview of the evolution of cybernetics-related literature. The data were extracted from Scopus to ensure a robust and widely recognized source.
Findings
The results revealed a rich and interconnected global research network in cybernetics. The word cloud analysis highlights prominent terms such as “agent-based modeling,” “complex adaptive systems,” “feedback loop,” “viable system model” and “cybernetics.” Notably, the journal Kybernetes has emerged as a focal point, with significant citations, solidifying its position as a key source within the cybernetics research domain. The bibliometric map provides visual clarity regarding the relationships between various concepts and their evolution over time.
Originality/value
This study contributes original insights by employing advanced bibliometric techniques in R Studio to map the cybernetics research landscape. The comprehensive analysis sheds light on the evolution of key concepts and the global collaborative networks shaping cybernetics research. The identification of influential sources, such as Kybernetes, adds value to researchers seeking to navigate and contribute to the dynamic field of cybernetics. Furthermore, this study highlights that cybernetics not only provides a useful framework for understanding and managing major economic shocks but also offers perspectives for understanding phenomena in various fields such as economics, medicine, environmental sciences and climate change.
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Michail Katsigiannis, Minas Pantelidakis and Konstantinos Mykoniatis
With hybrid simulation techniques getting popular for systems improvement in multiple fields, this study aims to provide insight on the use of hybrid simulation to assess the…
Abstract
Purpose
With hybrid simulation techniques getting popular for systems improvement in multiple fields, this study aims to provide insight on the use of hybrid simulation to assess the effect of lean manufacturing (LM) techniques on manufacturing facilities and the transition of a mass production (MP) facility to incorporating LM techniques.
Design/methodology/approach
In this paper, the authors apply a hybrid simulation approach to improve an educational automotive assembly line and provide guidelines for implementing different LM techniques. Specifically, the authors describe the design, development, verification and validation of a hybrid discrete-event and agent-based simulation model of a LEGO® car assembly line to analyze, improve and assess the system’s performance. The simulation approach examines the base model (MP) and an alternative scenario (just-in-time [JIT] with Heijunka).
Findings
The hybrid simulation approach effectively models the facility. The alternative simulation scenario (implementing JIT and Heijunka LM techniques) improved all examined performance metrics. In more detail, the system’s lead time was reduced by 47.37%, the throughput increased by 5.99% and the work-in-progress for workstations decreased by up to 56.73%.
Originality/value
This novel hybrid simulation approach provides insight and can be potentially extrapolated to model other manufacturing facilities and evaluate transition scenarios from MP to LM.
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Steven Alexander Melnyk, Matthias Thürer, Constantin Blome, Tobias Schoenherr and Stefan Gold
This study focuses on (re-)introducing computer simulation as a part of the research paradigm. Simulation is a widely applied research method in supply chain and operations…
Abstract
Purpose
This study focuses on (re-)introducing computer simulation as a part of the research paradigm. Simulation is a widely applied research method in supply chain and operations management. However, leading journals, such as the International Journal of Operations and Production Management, have often been reluctant to accept simulation studies. This study provides guidelines on how to conduct simulation research that advances theory, is relevant, and matters.
Design/methodology/approach
This study pooled the viewpoints of the editorial team of the International Journal of Operations and Production Management and authors of simulation studies. The authors debated their views and outlined why simulation is important and what a compelling simulation should look like.
Findings
There is an increasing importance of considering uncertainty, an increasing interest in dynamic phenomena, such as the transient response(s) to disruptions, and an increasing need to consider complementary outcomes, such as sustainability, which many researchers believe can be tackled by big data and modern analytical tools. But building, elaborating, and testing theory by purposeful experimentation is the strength of computer simulation. The authors therefore argue that simulation should play an important role in supply chain and operations management research, but for this, it also has to evolve away from simply generating and analyzing data. Four types of simulation research with much promise are outlined: empirical grounded simulation, simulation that establishes causality, simulation that supplements machine learning, artificial intelligence and analytics and simulation for sensitive environments.
Originality/value
This study identifies reasons why simulation is important for understanding and responding to today's business and societal challenges, it provides some guidance on how to design good simulation studies in this context and it links simulation to empirical research and theory going beyond multimethod studies.
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Xiaobo Shi, Yaning Qiao, Xinyu Zhao, Yan Liu, Chenchen Liu, Ruopeng Huang and Yuanlong Cui
Modern subway transportation systems need to satisfy increasing safety demands to rapidly evacuate passengers under hazardous emergency circumstances, such as fires, accidents or…
Abstract
Purpose
Modern subway transportation systems need to satisfy increasing safety demands to rapidly evacuate passengers under hazardous emergency circumstances, such as fires, accidents or terrorist attacks, to reduce passenger injuries or life losses. The emergency evacuation capacity (EEC) of a subway station needs to be revised timely, in case passenger demand increases or the evacuation route changes in the future. However, traditional ways of estimating EEC, e.g. fire drills are time- and resource-consuming and are difficult to revise from time to time. The purpose of this study is to establish an intuitive modelling approach to increase the EEC of subway stations in a stepwised manner.
Design/methodology/approach
This study develops an approach to combine agent-based evacuation modelling and building information modelling (BIM) technology to estimate the total evacuation time of a subway station.
Findings
Evacuation time can be saved (33% in the studied case) from iterative improvements including stopping escalators running against the evacuation flow and modifying the geometry around escalator exits. Such iterative improvements rely on integrating agent-based modelling and BIM.
Originality/value
The agent-based model can provide a more realistic simulation of intelligent individual movements under emergency circumstances and provides precise feedback on locations of evacuation bottlenecks. This study also examined the effectiveness of two rounds of stepwise improvements in terms of operation or design to increase the EEC of the station.
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Anchal Patil, Vipulesh Shardeo, Jitender Madaan, Ashish Dwivedi and Sanjoy Kumar Paul
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
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.
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Jingqi Zhang, Shaohua Jiang and Xiaomin Qi
The purpose of this paper is to conduct a comprehensive study on building, fire and evacuation, so as to effectively improve the efficiency of building fire evacuation and the…
Abstract
Purpose
The purpose of this paper is to conduct a comprehensive study on building, fire and evacuation, so as to effectively improve the efficiency of building fire evacuation and the management level of fire evacuation site. Make up for the difficulties of BIM technology in effectively connecting building information and fire data.
Design/methodology/approach
First, this paper establishes a fire model and an evacuation model based on BIM information. Then, the safety index (SI) is introduced as a comprehensive index, and the IRI is established by integrating the SI function to evaluate the safety of evacuation routes. Based on these two indices, the IRI-based fire evacuation model is established.
Findings
This study offers an Improved Risk Index (IRI)-based fire evacuation model, which may achieve effective evacuation in fire scenes. And the model is verified by taking the fire evacuation of a shopping center building as an example.
Originality/value
This paper proposes a fire evacuation principle based on IRI, so that the relevant personnel can comprehensively consider the fire factors and evacuation factors to achieve the optimization of building design, thereby improving the fire safety of buildings.
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Vikram Singh, Nirbhay Sharma and Somesh Kumar Sharma
Every company or manufacturing system is vulnerable to breakdowns. This research aims to analyze the role of Multi-Agent Technology (MAT) in minimizing breakdown probabilities in…
Abstract
Purpose
Every company or manufacturing system is vulnerable to breakdowns. This research aims to analyze the role of Multi-Agent Technology (MAT) in minimizing breakdown probabilities in Manufacturing Industries.
Design/methodology/approach
This study formulated a framework of six factors and twenty-eight variables (explored in the literature). A hybrid approach of Multi-Criteria Decision-Making Technique (MCDM) was employed in the framework to prioritize, rank and establish interrelationships between factors and variables grouped under them.
Findings
The research findings reveal that the “Manufacturing Process” is the most essential factor, while “Integration Manufacturing with Maintenance” is highly impactful on the other factors to eliminate the flaws that may cause system breakdown. The findings of this study also provide a ranking order for variables to increase the performance of factors that will assist manufacturers in reducing maintenance efforts and enhancing process efficiency.
Practical implications
The ranking order developed in this study may assist manufacturers in reducing maintenance efforts and enhancing process efficiency. From the manufacturer’s perspective, this research presented MAT as a key aspect in dealing with the complexity of manufacturing operations in manufacturing organizations. This research may assist industrial management with insights into how they can lower the probability of breakdown, which will decrease expenditures, boost productivity and enhance overall efficiency.
Originality/value
This study is an original contribution to advancing MAT’s theory and empirical applications in manufacturing organizations to decrease breakdown probability.
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Navid Hooshangi, Navid Mahdizadeh Gharakhanlou and Seyyed Reza Ghaffari-Razin
The duration of an urban search and rescue (USAR) operation directly depends on the number of rescue teams involved. The purpose of this paper is to simplify the earthquake…
Abstract
Purpose
The duration of an urban search and rescue (USAR) operation directly depends on the number of rescue teams involved. The purpose of this paper is to simplify the earthquake environment and determine the initial number of rescuers in earthquake emergencies in USAR operation.
Design/methodology/approach
In the proposed methodology, four primary steps were considered: evaluation of buildings damage and the number of injured people by exerting geospatial information system (GIS) analyses; determining service time by means of task allocation; designing the simulation model (queuing theory); and calculation of survival rate and comparison with the time of rescue operations.
Findings
The calculation of buildings damage for an earthquake with 6.6 Richter in Tehran’s District One indicated that 18% of buildings are subjected to the high damage risk. The number of injured people calculated was 28,856. According to the calculated survival rate, rescue operations in the region must be completed within 22.33 h to save 75% of the casualties. Finally, the design of the queue model indicated that at least 2,300 rescue teams were required to provide the calculated survival rate.
Originality/value
The originality of this paper is an innovative approach for determining an appropriate number of rescue teams by considering the queuing theory. The results showed that the integration of GIS and the simulation of queuing theory could be a helpful tool in natural disaster management, especially in terms of rapid vulnerability assessment in urban districts, the adequacy and appropriateness of the emergency services.
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