1,721,001 research outputs found
Adult Social Care Workforce Analysis in England: A System Dynamics Approach
No full textThe changes in demographic and regulations in social care in England are expected to alter the social care landscape and to put increasing pressure on people working in the adult social care sector, especially those who deliver direct care services. While significant work has been done to understand the demand side of the adult social care system, the work on the supply side is considerably limited. Moreover, analysis has been dominated by methods such as macro- and micro-simulation. This paper demonstrates that system dynamics modelling can be used to understand the dynamics of the social care workforce who deliver direct care services in the formal sector, specifically, to identify the main feedback loops that govern the dynamics of the system, to identify sensitive and influential factors, and to show non-linearity in the system. Therefore, system dynamics should play a more important role in the analysis of adult social care system
Managing the social amplification of risk: a simulation of interacting actors
Full text linkA central problem in managing risk is dealing with social processes that either exaggerate or understate it. A longstanding approach to understanding such processes has been the social amplification of risk framework. But this implies that some true level of risk becomes distorted in social actors’ perceptions. Many risk events are characterised by such uncertainties, disagreements and changes in scientific knowledge that it becomes unreasonable to speak of a true level of risk. The most we can often say in such cases is that different groups believe each other to be either amplifying or attenuating a risk. This inherent subjectivity raises the question as to whether risk managers can expect any particular kinds of outcome to emerge. This question is the basis for a case study of zoonotic disease outbreaks using systems dynamics as a modelling medium. The model shows that processes suggested in the social amplification of risk framework produce polarised risk responses among different actors, but that the subjectivity magnifies this polarisation considerably. As this subjectivity takes more complex forms it leaves problematic residues at the end of a disease outbreak, such as an indefinite drop in economic activity and an indefinite increase in anxiety
Elements of a hybrid simulation model : a case study of the blood supply chain in low- and middle-income countries
No full textA hybrid simulation model is a simulation model that is formed from at least two different simulation modelling methods (e.g., discrete event, system dynamics, agent-based). The use of different simulation modelling methods in one model requires modellers to specify additional model elements. This paper discusses three elements, namely, the modules, module interfaces and updating rules. Each module may use a different simulation method. The interface between modules defines the information that will be passed between them (including aggregation and disaggregation). The updating rules define how the information sent by one module affects other modules. These three elements are explained using a case study of a blood-supply chain simulation model for low- and middle-income countries (LMIC) which has different characteristics and challenges in comparison to the typical blood supply chain in high-income countries (HIC)
Graphical representation of agent-based models in Operational Research and Management Science using UML
No full textAgent-Based Modelling and Simulation (ABM/S) is still struggling to become one of the main stream simulation methods in Operational Research (OR) and Management Science (MS), despite its generally accepted usefulness when it comes to representing human behaviour in human-centric systems. In other fields, as for example Business Studies, Economics, and Social Science, it is flourishing. One of the technical differences between ABM/S and the well-established OR/MS simulation methods System Dynamics Simulation (SDS) and Discrete Event Simulation (DES) is that ABM/S traditionally uses an equation based modelling approach while SDS and DES use a graphical notation for the model description. We believe that having a graphical notation for ABM/S would help establish it in OR/MS. The Unified Modelling Language (UML) is a graphical notation commonly used in software engineering for the purpose of software design. Use case and state machine diagrams, which are part of the UML notation seem to lend themselves particularly well to ABM/S. In this paper we introduce UML to the OR/MS community. First we explain step-by-step how to use UML for developing ABM/S models. Then we demonstrate the application of this graphical notation by presenting two conceptual models we built for real world OR/MS case studies
Modelling the impact of ambidextrous learning on team performance using agent-based simulation
No full textIn an increasingly competitive environment, organizations need to continuously innovate (explorative learning) while making steady improvements to their existing operations (exploitative learning). The capacity to pursue both exploratory and exploitative learning simultaneously is called ambidexterity. Therefore, ambidexterity has become one of the important research topics in the field of organizational study. This paper focuses on ambidexterity learning at the team level. The objective is to propose a generic agent-based simulation model that can be used to examine how ambidextrous learning affect team performance under different levels of task complexity, communication intensity and communication cost. The experiment shows that the model can reproduce what have been reported in the team performance literature.</p
Editorial: The green economy for sustainable development in Indonesia - The challenges and opportunities of a multidisciplinary approach
No full textIn this editorial we summarise and comment on papers on the general theme of the implementation of a Green Economy from an Indonesian perspective. We address the issue of the green economy and sustainable development in Indonesia which is one of the most dynamic countries in Southeast Asia (ASEAN). We have therefore compiled this special issue of the International Journal of Green Economics, to include seven papers, all of which use multidisciplinary approaches, the method which forms the bedrock of a Green Economics analysis. The papers build on the particular analysis found in the Green Economics Institute's Book, The Greening of Asia and China, which highlighted how (contrary to much of the economic literature) a green economics approach actually enhances, rather than slows down, economic development. Using the Green Economics Model, it illustrates a new perspective for understanding the contemporary and rapid Asian economic development as the new powerhouse of the entire global economy. The important elements of this process which this current volume here examines as constituent parts of this process include disaster recovery, environmental education, environmental urban planning, and environmental engineering. Additionally, in this special issue, we analyse the Indonesian experience, which has tried to adopt and to adapt to, a green economy model and to use it to drive the evolving economy. We explore some of the challenges and opportunities in this novel process.</p
A pilot survey on data identification and collection in simulation projects
No full textThe research into the collection of data for use in simulation is lacking. This is rather unfortunate since data quality and availability are two of the most challenging issues in many simulation projects. We have conducted a pilot survey to understand the data collection process in simulation, its issues, solutions and impact on project outcomes. The result reveals interesting insights. Some of them confirm what we believe to be happening in practice. A few of them contradict what we may have assumed to be happening in practice
Using agent-based simulation to analyse the effect of broadcast and narrowcast on public perception : a case in social risk amplification
No full textIndividuals often use information from broadcast news (e.g. media) and narrowcast news (e.g. personal social network) to form their perception on a certain social issue. Using a case study in social risk amplification, this paper demonstrates that simulation modelling, specifically agent-based simulation, can be useful in analysing the effect of broadcast and narrowcast processes on the formation of public risk perception. The first part of this paper explains the structure of a model that allows easy configuration for testing various behaviours about which the empirical literature cannot make definitive predictions. The second part of this paper discusses the effect of personal social network and the role of media in the dynamics of public risk perception. The results show the undesirable effect of the extreme narrowcast process in society and a media that simply broadcasts the average public risk perception
Data identification and collection methodology in a simulation project: An action research
No full textThere seems to be a paucity in the research into the collection of data for use in simulation. This is rather unfortunate since data quality and availability are two of the most challenging issues in many simulation projects. In this paper, we are interested to know how practitioners identify and collect data for simulation projects. An action research was conducted at the ORH Ltd, a management consultancy company to evaluate their data collection guidelines using a real project conducted for a UK Ambulance Service to recommend new staffing levels to deal with increasing calls and to incorporate the installation of a new operating system. We discuss the issues surrounding the identification and collection of data which can be divided into data-related and process-related issues. We propose an improvement to the data identification and collection methodology to reduce the number of cycles in the data collection process
Nuclear reprocessing: a simulation metamodelling approach
No full textSellafield Ltd is looking to improve the performance of the Magnox Reprocessing plant. To support the improvement programme The National Nuclear Laboratory was asked to use the existing simulation model to understand the impact of individual projects and the combined programme of proposed changes on a performance target. Historically, the approach to identifying a suitable portfolio of improvements has been through experience with the model and then a process of trial and error running the simulation model until the required performance target is met. This is time consuming and limits responsiveness to customer requirements. This paper reports our initial findings on the use of response surface methodology to develop simulation-based metamodel using smaller data sets. The results indicates that these type of metamodels can produce a good estimate for the mean and standard deviation of the performance target
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