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The Disaster-Oriented Assessment of Urban Clusters for Locating Production Systems in China

The Disaster-Oriented Assessment of Urban Clusters for Locating Production Systems in China
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Author(s): Zhen Chen (Liverpool John Moores University, UK), Heng Li (The Hong Kong Polytechnic University, China), Qian Xu (Liverpool John Moores University, UK)and Szu-Li Sun (The University of Reading, UK)
Copyright: 2008
Pages: 19
Source title: Encyclopedia of Decision Making and Decision Support Technologies
Source Author(s)/Editor(s): Frederic Adam (University College Cork, Ireland)and Patrick Humphreys (London School of Economics, UK)
DOI: 10.4018/978-1-59904-843-7.ch030

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Abstract

The choice of location is one of the most important decisions usually taken in the procedure of building any production system (Pavic & Babic, 1991). In order to solve the problem of location choice, Pavic and Babic indentified a group of location indicators, including basic location factors such as transportation costs, production costs, and duration of transport, and additional factors such as bottleneck time, building costs, infrastructure costs, labour costs, weather conditions, expansion possibility, and transportation possibilities. Based on these criteria, Pavic and Babic used the preference ranking organisation method for enrichment evaluation (PROMETHEE) method (Mattioli, 2005) to support decision making in location choice. However, there are two concerns about their study. The first concern is that whether those indicators are enough and appropriate in the location choice of production systems. In fact, they have lost some relevant important factors. For example, geographic and geological conditions; environmental pollution; climate change; industrial and technology policies; disaster containment; and emergency services are all necessary considerations before locating production systems. The second concern is that whether the PROMETHEE method is an appropriate approach to effectively and efficiently deal with problems in which structured hierarchies of indicators are used in modelling. In fact, researchers have begun to explore alternatives to overcome the weaknesses of the PROMETHEE method in multi-criteria decision making. For example, Macharis, Springael, De Brucker, and Verbeke (2004) discussed the strengths and weaknesses of the PROMETHEE method and recommended the integration of a number of useful features of the analytic hierarchy process (AHP) method (Saaty, 1980) into the PROMETHEE process; especially in regards to the design of the decision-making hierarchy (ordering of goals, sub-goals, dimensions, criteria, projects, etc.) and the determination of weights. Based on these two concerns, the authors think there are potentials in conducting operations research into the location choice problem by modelling the hierarchies or network of indicators.

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