TOPSIS-AHP رویکرد مبتنی بر TOPSIS-AHP برای انتخاب ارائه دهنده خدمات لجستیک معکوس: مطالعه موردی صنعت تلفن همراه
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|51612||2014||10 صفحه PDF||سفارش دهید||5540 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Procedia Engineering, Volume 97, 2014, Pages 2147–2156
Reverse supply chain logistics, means mobility of goods from end consumers towards core manufacturer in the channel of product distribution. In the turbulent business environment, the companies must promote alternative uses of resources that may be cost-effective and ecology friendly by extending products’ routine life cycles. Reveres logistics activities i.e. storing, transporting and handling of used products poses a great challenge to reverse logistics managers as there is always chances of uncertainty in terms of quantity, quality and timing of return of EOL products in case of reverse supply chains. Business organizations including those of white/electronics goods manufacturing industries would like to focus on their core competency areas and there is need of making outsourcing decisions of their reverse logistics process to Third-Party reverse Logistics Providers (3PRLPs). Thus, most important strategic issue for top management is the evaluation and selection of third party logistics service provider who can effectively provide reverse logistics operation services to the firms. The objective of this work is to develop decision support system to assist the top management of the company in selection and evaluation of different 3PRL service providers by hybrid approach using Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. A real life case study of a mobile phone manufacturing company is presented to demonstrate the steps of the decision support system. Present study also enables the logistics managers to better understand the complex relationships of the key attributes in the decision making environment and subsequently improve the reliability of the decision making process.