An agent-based fuzzy cognitive map approach to the strategic marketing planning for industrial firms

This is the post-print version of the final paper published in Industrial Marketing Management. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Industrial marketing planning is a typical example of an unstructured decision making problem due to the large number of variables to consider and the uncertainty imposed on those variables. Although abundant studies identified barriers and facilitators of effective industrial marketing planning in practice, the literature still lacks practical tools and methods that marketing managers can use for the task. This paper applies fuzzy cognitive maps (FCM) to industrial marketing planning. In particular, agent based inference method is proposed to overcome dynamic relationships, time lags, and reusability issues of FCM evaluation. MACOM simulator also is developed to help marketing managers conduct what-if scenarios to see the impacts of possible changes on the variables defined in an FCM that represents industrial marketing planning problem. The simulator is applied to an industrial marketing planning problem for a global software service company in South Korea. This study has practical implication as it supports marketing managers for industrial marketing planning that has large number of variables and their cause–effect relationships. It also contributes to FCM theory by providing an agent based method for the inference of FCM. Finally, MACOM also provides academics in the industrial marketing management discipline with a tool for developing and pre-verifying a conceptual model based on qualitative knowledge of marketing practitioners.Ministry of Education, Science and Technology (Korea

Toward future 'mixed reality' learning spaces for STEAM education

Digital technology is becoming more integrated and part of modern society. As this begins to happen, technologies including augmented reality, virtual reality, 3d printing and user supplied mobile devices (collectively referred to as mixed reality) are often being touted as likely to become more a part of the classroom and learning environment. In the discipline areas of STEAM education, experts are expected to be at the forefront of technology and how it might fit into their classroom. This is especially important because increasingly, educators are finding themselves surrounded by new learners that expect to be engaged with participatory, interactive, sensory-rich, experimental activities with greater opportunities for student input and creativity. This paper will explore learner and academic perspectives on mixed reality case studies in 3d spatial design (multimedia and architecture), paramedic science and information technology, through the use of existing data as well as additional one-on-one interviews around the use of mixed reality in the classroom. Results show that mixed reality can provide engagement, critical thinking and problem solving benefits for students in line with this new generation of learners, but also demonstrates that more work needs to be done to refine mixed reality solutions for the classroom

Using the Internet to improve university education: Problem-oriented web-based learning and the MUNICS environment

Up to this point, university education has largely remained unaffected by the developments of novel approaches to web-based learning. The paper presents a principled approach to the design of problem-oriented, web-based learning at the university level. The principles include providing authentic contexts with multimedia, supporting collaborative knowledge construction, making thinking visible with dynamic visualisation, quick access to content resources via Information and Communication Technologies (ICT), and flexible support by tele-tutoring. These principles are used in the Munich Net-based Learning In Computer Science (MUNICS) learning environment, which is designed to support students of computer science to apply their factual knowledge from the lectures to complex real-world problems. For example, students can model the knowledge management in an educational organisation with a graphical simulation tool. Some more general findings from a formative evaluation study with the MUNICS prototype are reported and discussed. E.g., the students' ignorance of the additional content resources is discussed in the light of the well-known finding of insufficient use of help systems in software applicationsBislang wurden neuere Ansätze zum web-basierten Lernen in nur geringem Maße zur Verbesserung des Universitätsstudiums genutzt. Es werden theoretisch begründete Prinzipien für die Gestaltung problemorientierter, web-basierter Lernumgebungen an der Universität formuliert. Zu diesen Prinzipien gehören die Nutzung von Multimedia-Technologien für die Realisierung authentischer Problemkontexte, die Unterstützung der gemeinsamen Wissenskonstruktion, die dynamische Visualisierung, der schnelle Zugang zu weiterführenden Wissensressourcen mit Hilfe von Informations- und Kommunikationstechnologien sowie die flexible Unterstützung durch Teletutoring. Diese Prinzipien wurden bei der Gestaltung der MUNICS Lernumgebung umgesetzt. MUNICS soll Studierende der Informatik bei der Wissensanwendung im Kontext komplexer praktischer Problemstellungen unterstützen. So können die Studierenden u.a. das Wissensmanagement in einer Bildungsorganisation mit Hilfe eines graphischen Simulationswerkzeugs modellieren. Es werden Ergebnisse einer formativen Evaluationsstudie berichtet und diskutiert. Beispielsweise wird die in der Studie festgestellte Ignoranz der Studierenden gegenüber den weiterführenden Wissensressourcen vor dem Hintergrund des häufig berichteten Befunds der unzureichenden Nutzung von Hilfesystemen beleuchte

Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded. The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded

The Repast Simulation/Modelling System for Geospatial Simulation

The use of simulation/modelling systems can simplify the implementation of agent-based models. Repast is one of the few simulation/modelling software systems that supports the integration of geospatial data especially that of vector-based geometries. This paper provides details about Repast specifically an overview, including its different development languages available to develop agent-based models. Before describing Repast’s core functionality and how models can be developed within it, specific emphasis will be placed on its ability to represent dynamics and incorporate geographical information. Once these elements of the system have been covered, a diverse list of Agent-Based Modelling (ABM) applications using Repast will be presented with particular emphasis on spatial applications utilizing Repast, in particular, those that utilize geospatial data

Using the Internet to improve university education

Up to this point, university education has largely remained unaffected by the developments of novel approaches to web-based learning. The paper presents a principled approach to the design of problem-oriented, web-based learning at the university level. The principles include providing authentic contexts with multimedia, supporting collaborative knowledge construction, making thinking visible with dynamic visualisation, quick access to content resources via information and communication technologies, and flexible support by tele-tutoring. These principles are used in the MUNICS learning environment, which is designed to support students of computer science to apply their factual knowledge from the lectures to complex real-world problems. For example, students may model the knowledge management in an educational organisation with a graphical simulation tool. Some more general findings from a formative evaluation study with the MUNICS prototype are reported and discussed. For example, the students' ignorance of the additional content resources is discussed in the light of the well-known finding of insufficient use of help systems in software applications

Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

The EnTrak system : supporting energy action planning via the Internet

Recent energy policy is designed to foster better energy efficiency and assist with the deployment of clean energy systems, especially those derived from renewable energy sources. To attain the envisaged targets will require action at all levels and effective collaboration between disparate groups (e.g. policy makers, developers, local authorities, energy managers, building designers, consumers etc) impacting on energy and environment. To support such actions and collaborations, an Internet-enabled energy information system called 'EnTrak' was developed. The aim was to provide decision-makers with information on energy demands, supplies and impacts by sector, time, fuel type and so on, in support of energy action plan formulation and enactment. This paper describes the system structure and capabilities of the EnTrak system

A virtual environment to support the distributed design of large made-to-order products

An overview of a virtual design environment (virtual platform) developed as part of the European Commission funded VRShips-ROPAX (VRS) project is presented. The main objectives for the development of the virtual platform are described, followed by the discussion of the techniques chosen to address the objectives, and finally a description of a use-case for the platform. Whilst the focus of the VRS virtual platform was to facilitate the design of ROPAX (roll-on passengers and cargo) vessels, the components within the platform are entirely generic and may be applied to the distributed design of any type of vessel, or other complex made-to-order products

Investigating grid computing technologies for use with commercial simulation packages

As simulation experimentation in industry become more computationally demanding, grid computing can be seen as a promising technology that has the potential to bind together the computational resources needed to quickly execute such simulations. To investigate how this might be possible, this paper reviews the grid technologies that can be used together with commercial-off-the-shelf simulation packages (CSPs) used in industry. The paper identifies two specific forms of grid computing (Public Resource Computing and Enterprise-wide Desktop Grid Computing) and the middleware associated with them (BOINC and Condor) as being suitable for grid-enabling existing CSPs. It further proposes three different CSP-grid integration approaches and identifies one of them to be the most appropriate. It is hoped that this research will encourage simulation practitioners to consider grid computing as a technologically viable means of executing CSP-based experiments faster