Agent-based simulation of lock-in dynamics in a duopoly

Lock-in is observed in real world markets of experience goods; experience goods are goods whose characteristics are difficult to determine in advance, but ascertained upon consumption. We create an agent-based simulation of consumers choosing between two experience goods available in a virtual market. We model consumers in a grid representing the spatial network of the consumers. Utilising simple assumptions, including identical distributions of product experience and consumers having a degree of follower tendency, we explore the dynamics of the model through simulations. We conduct simulations to create a lock-in before testing several hypotheses upon how to break an existing lock-in; these include the effect of advertising and free give-away. Our experiments show that the key to successfully breaking a lock-in required the creation of regions in a consumer population. Regions arise due to the degree of local conformity between agents within the regions, which spread throughout the population when a mildly superior competitor was available. These regions may be likened to a niche in a market, which gains in popularity to transition into the mainstream.

Modelling e-business processes:a component-based simulation approach

With new and emerging e-business technologies to transform business processes, it is important to understand how those technologies will affect the performance of a business. Will the overall business process be cheaper, faster and more accurate or will a sub-optimal change have been implemented? The use of simulation to model the behaviour of business processes is well established, and it has been applied to e-business processes to understand their performance in terms of measures such as lead-time, cost and responsiveness. This paper introduces the concept of simulation components that enable simulation models of e-business processes to be built quickly from generic e-business templates. The paper demonstrates how these components were devised, as well as the results from their application through case studies.

Implementing an agent-based model with a spatial visual display in discrete-event simulation software

There has been an increasing interest in the use of agent-based simulation and some discussion of the relative merits of this approach as compared to discrete-event simulation. There are differing views on whether an agent-based simulation offers capabilities that discrete-event cannot provide or whether all agent-based applications can at least in theory be undertaken using a discrete-event approach. This paper presents a simple agent-based NetLogo model and corresponding discrete-event versions implemented in the widely used ARENA software. The two versions of the discrete-event model presented use a traditional process flow approach normally adopted in discrete-event simulation software and also an agent-based approach to the model build. In addition a real-time spatial visual display facility is provided using a spreadsheet platform controlled by VBA code embedded within the ARENA model. Initial findings from this investigation are that discrete-event simulation can indeed be used to implement agent-based models and with suitable integration elements such as VBA provide the spatial displays associated with agent-based software.

An enhanced scalable probe-based multicast admission control scheme

To guarantee QoS for multicast transmission, admission control for multicast sessions is expected. Probe-based multicast admission control (PBMAC) scheme is a scalable and simple approach. However, PBMAC suffers from the subsequent request problem which can significantly reduce the maximum number of multicast sessions that a network can admit. In this letter, we describe the subsequent request problem and propose an enhanced PBMAC scheme to solve this problem. The enhanced scheme makes use of complementary probing and remarking which require only minor modification to the original scheme. By using a fluid-based analytical model, we are able to prove that the enhanced scheme can always admit a higher number of multicast sessions. Furthermore, we present validation of the analytical model using packet based simulation. Copyright © 2005 The Institute of Electronics, Information and Communication Engineers.

Disseminating a warning message to evacuate:a simulation study of the behaviour of neighbours

Large-scale evacuations are a recurring theme on news channels, whether in response to major natural or manmade disasters. The role of warning dissemination is a key part in the success of such large-scale evacuations and its inadequacy in certain cases has been a 'primary contribution to deaths and injuries' (Hayden et al.; 2007). Along with technology-driven 'official warning channels' (e.g. sirens, mass media), the role of unofficial channel (e.g. neighbours, personal contacts, volunteer wardens) has proven to be significant in warning the public of the need to evacuate. Although post-evacuation studies identify the behaviours of evacuees as disseminators of the warning message, there has not been a detailed study that quantifies the effects of such behaviour on the warning message dissemination. This paper develops an Agent-Based Simulation (ABS) model of multiple agents (evacuee households) in a hypothetical community to investigate the impact of behaviour as an unofficial channel on the overall warning dissemination. Parameters studied include the percentage of people who warn their neighbours, the efficiency of different official warning channels, and delay time to warn neighbours. Even with a low proportion of people willing to warn their neighbour, the results showed considerable impact on the overall warning dissemination. © 2012 Elsevier B.V. All rights reserved.

Informal dissemination scenarios and the effectiveness of evacuation warning dissemination of households:a simulation study

Timely warning of the public during large scale emergencies is essential to ensure safety and save lives. This ongoing study proposes an agent-based simulation model to simulate the warning message dissemination among the public considering both official channels and unofficial channels The proposed model was developed in NetLogo software for a hypothetical area, and requires input parameters such as effectiveness of each official source (%), estimated time to begin informing others, estimated time to inform others and estimated percentage of people (who do not relay the message). This paper demonstrates a means of factoring the behaviour of the public as informants into estimating the effectiveness of warningdissemination during large scale emergencies. The model provides a tool for the practitioner to test the potential impact of the informal channels on the overall warning time and sensitivity of the modelling parameters. The tool would help the practitioners to persuade evacuees to disseminate the warning message informing others similar to the ’Run to thy neighbour campaign conducted by the Red cross.

Tool support for integrating extended enterprises

A current EPSRC project, product introduction process: a simulation in the extended enterprise (PIPSEE) is discussed. PIPSEE attempts to improve the execution of the product introduction process (PIP) within an extended enterprise in the aerospace sector. The modus operandi for accomplishing this has been to develop process understanding amongst a core team, spanning four different companies, through process modelling, review and improvement recommendation. In parallel, a web-based simulation capability is being used to conduct simulation experiments, and to disseminate findings by training others in the lessons that have been learned. It is intended that the use of the PIPSEE simulator should encourage radical thinking about the ‘fuzzy front end’ of the PIP. This presents a topical, exciting and challenging research problem.

Determining inventory service support levels in multi-national companies

Multi-national manufacturing companies are often faced with very difficult decisions regarding where and how to cost effectively manufacture products in a global setting. Clearly, they must utilize efficient and responsive manufacturing strategies to reach low cost solutions, but they must also consider the impact of manufacturing and transportation solutions upon their ability to support sales. One important sales consideration is determining how much work in process, in-transit stock, and finished goods to have on hand to support sales at a desired service level. This paper addresses this important consideration through a comprehensive scenario-based simulation approach, including sensitivity analysis on key study parameters. Results indicate that the inventory needs vary considerably for different manufacturing and delivery methods in ways that may not be obvious when using common evaluative tools.

The Application of Geographic Information Systems to climate change & land evaluation : a study of the effects of climate change upon crop productivity in a sub-tropical environment

This research investigates the contribution that Geographic Information Systems (GIS) can make to the land suitability process used to determine the effects of a climate change scenario. The research is intended to redress the severe under representation of Developing countries within the literature examining the impacts of climatic change upon crop productivity. The methodology adopts some of the Intergovernmental Panel on Climate Change (IPCC) estimates for regional climate variations, based upon General Circulation Model predictions (GCMs) and applies them to a baseline climate for Bangladesh. Utilising the United Nations Food & Agricultural Organisation's Agro-ecological Zones land suitability methodology and crop yield model, the effects of the scenario upon agricultural productivity on 14 crops are determined. A Geographic Information System (IDRISI) is adopted in order to facilitate the methodology, in conjunction with a specially designed spreadsheet, used to determine the yield and suitability rating for each crop. A simple optimisation routine using the GIS is incorporated to provide an indication of the 'maximum theoretical' yield available to the country, should the most calorifically significant crops be cultivated on each land unit both before and after the climate change scenario. This routine will provide an estimate of the theoretical population supporting capacity of the country, both now and in the future, to assist with planning strategies and research. The research evaluates the utility of this alternative GIS based methodology for the land evaluation process and determines the relative changes in crop yields that may result from changes in temperature, photosynthesis and flooding hazard frequency. In summary, the combination of a GIS and a spreadsheet was successful, the yield prediction model indicates that the application of the climate change scenario will have a deleterious effect upon the yields of the study crops. Any yield reductions will have severe implications for agricultural practices. The optimisation routine suggests that the 'theoretical maximum' population supporting capacity is well in excess of current and future population figures. If this agricultural potential could be realised however, it may provide some amelioration from the effects of climate change.

Modelling human performance within manufacturing systems design:from a theoretical towards a practical framework

Computer-based simulation is frequently used to evaluate the capabilities of proposed manufacturing system designs. Unfortunately, the real systems are often found to perform quite differently from simulation predictions and one possible reason for this is an over-simplistic representation of workers' behaviour within current simulation techniques. The accuracy of design predictions could be improved through a modelling tool that integrates with computer-based simulation and incorporates the factors and relationships that determine workers' performance. This paper explores the viability of developing a similar tool based on our previously published theoretical modelling framework. It focuses on evolving this purely theoretical framework towards a practical modelling tool that can actually be used to expand the capabilities of current simulation techniques. Based on an industrial study, the paper investigates how the theoretical framework works in practice, analyses strengths and weaknesses in its formulation, and proposes developments that can contribute towards enabling human performance modelling in a practical way.

The impact of coordination on the effectiveness of last mile relief distribution

Last mile relief distribution is the final stage of humanitarian logistics. It refers to the supply of relief items from local distribution centers to the disaster affected people (Balcik et al., 2008). In the last mile relief distribution literature, researchers have focused on the use of optimisation techniques for determining the exact optimal solution (Liberatore et al., 2014), but there is a need to include behavioural factors with those optimisation techniques in order to obtain better predictive results. This paper will explain how improving the coordination factor increases the effectiveness of the last mile relief distribution process. There are two stages of methodology used to achieve the goal: Interviews: The authors conducted interviews with the Indian Government and with South Asian NGOs to identify the critical factors for final relief distribution. After thematic and content analysis of the interviews and the reports, the authors found some behavioural factors which affect the final relief distribution. Model building: Last mile relief distribution in India follows a specific framework described in the Indian Government disaster management handbook. We modelled this framework using agent based simulation and investigated the impact of coordination on effectiveness. We define effectiveness as the speed and accuracy with which aid is delivered to affected people. We tested through simulation modelling whether coordination improves effectiveness.

Enabling long journeys in electric vehicles:design and demonstration of an infrastructure location model

This research develops a methodology and model formulation which suggests locations for rapid chargers to help assist infrastructure development and enable greater battery electric vehicle (BEV) usage. The model considers the likely travel patterns of BEVs and their subsequent charging demands across a large road network, where no prior candidate site information is required. Using a GIS-based methodology, polygons are constructed which represent the charging demand zones for particular routes across a real-world road network. The use of polygons allows the maximum number of charging combinations to be considered whilst limiting the input intensity needed for the model. Further polygons are added to represent deviation possibilities, meaning that placement of charge points away from the shortest path is possible, given a penalty function. A validation of the model is carried out by assessing the expected demand at current rapid charging locations and comparing to recorded empirical usage data. Results suggest that the developed model provides a good approximation to real world observations, and that for the provision of charging, location matters. The model is also implemented where no prior candidate site information is required. As such, locations are chosen based on the weighted overlay between several different routes where BEV journeys may be expected. In doing so many locations, or types of locations, could be compared against one another and then analysed in relation to siting practicalities, such as cost, land permission and infrastructure availability. Results show that efficient facility location, given numerous siting possibilities across a large road network can be achieved. Slight improvements to the standard greedy adding technique are made by adding combination weightings which aim to reward important long distance routes that require more than one charge to complete.

Quantitative risk assessment of groundwater quality utilizing GIS technology and coupled groundwater models

The thesis presents a two-dimensional Risk Assessment Method (RAM) where the assessment of risk to the groundwater resources incorporates both the quantification of the probability of the occurrence of contaminant source terms, as well as the assessment of the resultant impacts. The approach emphasizes the need for a greater dependency on the potential pollution sources, rather than the traditional approach where assessment is based mainly on the intrinsic geo-hydrologic parameters. The risk is calculated using Monte Carlo simulation methods whereby random pollution events were generated to the same distribution as historically occurring events or a priori potential probability distribution. Integrated mathematical models then simulate contaminant concentrations at the predefined monitoring points within the aquifer. The spatial and temporal distributions of the concentrations were calculated from repeated realisations, and the number of times when a user defined concentration magnitude was exceeded is quantified as a risk. The method was setup by integrating MODFLOW-2000, MT3DMS and a FORTRAN coded risk model, and automated, using a DOS batch processing file. GIS software was employed in producing the input files and for the presentation of the results. The functionalities of the method, as well as its sensitivities to the model grid sizes, contaminant loading rates, length of stress periods, and the historical frequencies of occurrence of pollution events were evaluated using hypothetical scenarios and a case study. Chloride-related pollution sources were compiled and used as indicative potential contaminant sources for the case study. At any active model cell, if a random generated number is less than the probability of pollution occurrence, then the risk model will generate synthetic contaminant source term as an input into the transport model. The results of the applications of the method are presented in the form of tables, graphs and spatial maps. Varying the model grid sizes indicates no significant effects on the simulated groundwater head. The simulated frequency of daily occurrence of pollution incidents is also independent of the model dimensions. However, the simulated total contaminant mass generated within the aquifer, and the associated volumetric numerical error appear to increase with the increasing grid sizes. Also, the migration of contaminant plume advances faster with the coarse grid sizes as compared to the finer grid sizes. The number of daily contaminant source terms generated and consequently the total mass of contaminant within the aquifer increases in a non linear proportion to the increasing frequency of occurrence of pollution events. The risk of pollution from a number of sources all occurring by chance together was evaluated, and quantitatively presented as risk maps. This capability to combine the risk to a groundwater feature from numerous potential sources of pollution proved to be a great asset to the method, and a large benefit over the contemporary risk and vulnerability methods.

Knowledge based improvement:simulation and artificial intelligence for identifying and improving human decision-making in an operations systems

The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as 'knowledge-based improvement' (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent decision-making. By linking the VIS and AI representation, it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant.

Using process mapping and business process simulation to support a process-based approach to change in a public sector organisation

A case study demonstrates the use of a process-based approach to change regarding the implementation of an information system for road traffic accident reporting in a UK police force. The supporting tools of process mapping and business process simulation are used in the change process and assist in communicating the current process design and people's roles in the overall performance of that design. The simulation model is also used to predict the performance of new designs incorporating the use of information technology. The approach is seen to have a number of advantages in the context of a public sector organisation. These include the ability for personnel to move from a traditional grouping of staff in occupational groups with relationships defined by reporting requirements to a view of their role in a process, which delivers a performance to a customer. By running the simulation through time it is also possible to gauge how changes at an operational level can lead to the meeting of strategic targets over time. Also the ability of simulation to proof new designs was seen as particularly important in a government agency were past failures of information technology investments had contributed to a more risk averse approach to their implementation. © 2004 Elsevier Ltd. All rights reserved.