Serious Gaming Learning

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Dublin Institute of Technology

ARROW@DIT
Conference Papers School of Management

2012-11-19

SERIOUS GAMING LEARNING: SUPPLY CHAIN MULTI-AGENT WEB-BASED SIMULATION GAME Ayman Tobail
Dublin Institute of Technology

John Crowe
Dublin Institute of Technology, john.crowe@dit.ie

Amr Arisha
Dublin Institute of Technology

Follow this and additional works at: http://arrow.dit.ie/buschmancon Part of the Business Administration, Management, and Operations Commons, and the Curriculum and Instruction Commons Recommended Citation Tobail, A, Crowe, J and Arisha, A. (2012). Serious Gaming Learning: Supply Chain Multi-Agent Web-Based Simulation Game, ICERI 2012 (pp. xxxx-xx). Madrid.

This Conference Paper is brought to you for free and open access by the School of Management at ARROW@DIT. It has been accepted for inclusion in Conference Papers by an authorized administrator of ARROW@DIT. For more information, please contact yvonne.desmond@dit.ie, arrow.admin@dit.ie.

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SERIOUS GAMING LEARNING: SUPPLY CHAIN MULTI-AGENT WEB-BASED SIMULATION GAME Ayman Tobail, John Crowe, Amr Arisha
3S Group, College of Business, Dublin Institute of Technology (DIT), Dublin (IRELAND) ayman.tobail@dit.ie

Abstract
High levels of complexity and uncertainty, and various sources of risks, create challenges for supply chain networks in achieving satisfactory performance, but advances in Information Technology can help supply chain decision makers predict the magnitude and impact of the risks related to their decisions. The framework proposed in this paper offers a solution that integrates intelligent-agents, simulation modelling, and optimisation. Its friendly, animated, interactive web-based interface is especially designed to engage the user in a ‘serious game’ environment. Each user plays a specific role in the supply chain network, and encounters the consequences of their decisions. The optimisation engine embedded in the framework advises users about the optimum decisions and their anticipated performance outcomes. Genetics Algorithm (GA) and Case-Based Reasoning (CBR) are used to enhance the decision quality. A high-level communication protocol has been designed, developed and implemented to facilitate client/server communications, and allow intelligent-agents to inter-communicate easily and efficiently. The tool we develop offers equal value in supporting management decision-making, or in educating trainees in the realities of supply chain management. Keywords: Serious Gaming, Multi-Agents, Web-Based Simulation.

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INTRODUCTION

When the business world thinks of risk, they are generally financial, and refer to areas such as insurance, investments, futures, options and swaps [1]. But, since major disruptions to global supply such as the 9/11 terrorist attacks and Hurricane Katrina in the US, foot and mouth disease in the UK, the SARS and bird flu outbreaks in Eastern Asia, the volcanic ash clouds over Iceland and the tsunami that hit Japan in 2011 - supply chain risk has received ever-greater attention from both academic and industry experts [2-4]. The high level of complexity and uncertainty across supply chain (SC) networks, and the variety in the sources of risk, create challenges for supply chain partners and customers in achieving and sustaining satisfactory performance. One of the barriers to implement a successful SC risk management plan is the varying levels of awareness and overall knowledge held by different managers and actors throughout the SC network, and the lack of recognition of common terminologies across SCs [5]. Numerous tools are now available to analyse risks and assist in their management, but the supply chain sector lacks interactive educational tools that can give trainees an understanding of a complete SC environment, and develop their ability to identify, asses, manage and control the various processes...
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