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Information Technology Journal

Year: 2013 | Volume: 12 | Issue: 24 | Page No.: 8141-8146
DOI: 10.3923/itj.2013.8141.8146
An ANP Approach to Multi-Criterial Decision-Making: Selection of Cleaner Production Alternatives for Construction Enterprises
Xu Feng and Chen Jianguo

Abstract: ANP is the most comprehensive framework for the analysis of societal,national and enterprise decision for the decision-maker today, allowing for all possible and potential dependencies. This study uses ANP model to select cleaner production alternatives on basis of enterprises’ capacity with internal and external dependences. Cleaner Production (CP) has been considered to be an important means for effective pollution control and lead to a win-win situation of improving economic and environmental benefits. It is operated widely by construction enterprises as a method to cut on environment negative impact. However, to select appropriate CP options have been a key issue for different enterprises to implement cleaner production successfully. CP options could be divided into three types: low-cost, mediate-cost, high-cost. Entensive research has studied on evaluation of CP option but most just considered economic and environmental performances of options. In fact,it is important to concider some CP option on basis of enterprises’ background such as CP capacity. This study focused on the relation between the CP capacity of enterprises and CP option, making two contributions: first,we established the evaluation index system of CP capacity in construction enterprises. There is dependence and feedback among elements, so ANP model was used to evaluate. Second, on basis of the complexity of computation process, SuperDesicion software was introduced to calculate the dates and gained the prioritization of the alternatives.

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How to cite this article
Xu Feng and Chen Jianguo, 2013. An ANP Approach to Multi-Criterial Decision-Making: Selection of Cleaner Production Alternatives for Construction Enterprises. Information Technology Journal, 12: 8141-8146.

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