Smart Home Subcontractor Selection Using the Integration of AHP and Evidential Reasoning Approaches

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• 作者：Gul Polat ; ^{polatgu@itu.edu.tr} ; Fatih Cetindere ; Atilla Damci ; Befrin Neval Bingol
• 关键词：Analytic hierarchy process ; case study ; evidential reasoning ; smart home ; subcontractor selection
• 刊名：Procedia Engineering
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：164
• 期：Complete
• 页码：347-353
• 全文大小：361 K
• 卷排序：164

文摘

Subcontracting is a very common practice in the construction industry. The large portions of actual production work are carried out by subcontractors. Therefore, main contractors have focused on selection of the appropriate subcontractors to increase the performance of their business. Finding the most suitable alternative among these subcontractors is another complex task because assimilating a large number of aspects is not simple without using any selection tools. In order to understand this better, breaking down the problem into smaller parts and building a model is one of the best ways in the selection process. Companies want to make differences to increase buyers’ interest; this is to obtain better position in the competitive construction market. Recently, the popularity of smart home and home automation has importantly increased in modern societies in Turkey. This has lead construction companies to import the smart home system into their business investments. This study aims to propose an integrated model for selection of smart home subcontractor. The proposed model integrates Analytic Hierarchy Process (AHP) and Evidential Reasoning (ER) techniques. In this study, AHP is used to find the weights of the criteria that are considered in the smart home subcontractor evaluation process and ER is employed to rank the alternative subcontractors. The proposed approach is applied in a construction company that has completed many projects in Turkey. In the case study, twenty evaluation criteria are considered and eight alternative smart home companies are evaluated. The result of this study demonstrated that the suggested model is applicable.