مقاله انگلیسی رایگان در مورد روش تاپسیس فازی برای ارزیابی عملکرد تدارکات معکوس – الزویر 2018

 

مشخصات مقاله
ترجمه عنوان مقاله روش تاپسیس فازی برای ارزیابی عملکرد تدارکات معکوس در سیستم عامل های تجارت الکترونیک
عنوان انگلیسی مقاله A fuzzy TOPSIS method for performance evaluation of reverse logistics in social commerce platforms
انتشار مقاله سال 2018
تعداد صفحات مقاله انگلیسی 36 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله
مقاله پژوهشی (Research article)
مقاله بیس این مقاله بیس نمیباشد
نمایه (index) scopus – master journals – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
3.768 در سال 2017
شاخص H_index 145 در سال 2018
شاخص SJR 1.271 در سال 2018
رشته های مرتبط مدیریت، مهندسی صنایع
گرایش های مرتبط تحقیق در عملیات، بهینه سازی سیستم ها
نوع ارائه مقاله
ژورنال
مجله / کنفرانس سیستم های کارشناس با نرم افزار – Expert Systems With Applications
دانشگاه Business Administration and Statistics Department – Technical University of Madrid – Spain
کلمات کلیدی مجموعه های فازی؛ لجستیک معکوس؛ تجارت اجتماعی؛ تاپسیس؛ آنالیز حساسیت؛ FLINTSTONES
کلمات کلیدی انگلیسی Fuzzy sets; reverse logistics; social commerce; TOPSIS; sensitivity analysis; FLINTSTONES
شناسه دیجیتال – doi
https://doi.org/10.1016/j.eswa.2018.03.003
کد محصول E9912
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Highlights
Abstract
Keywords
1 Introduction
2 Literature review
3 Fuzzy TOPSIS
4 Application
5 Discussion
6 Conclusion
Appendix. Supplementary materials
References

بخشی از متن مقاله:
Abstract

Reverse logistics initiatives with social commerce not only provide opportunities for firms to create new sources of revenue but also demonstrate their corporate social responsibility via social, green, and environmental activities. Thus, a growing number of companies are attempting to streamline their social commerce platforms to effectively handle reverse logistics. The purpose of this study is to identify the criteria that should be used in designing and evaluating social commerce based reverse logistics processes by firms. We tested the effectiveness of the identified criteria by using them to evaluate the reverse logistics practices of three major global firms that use social commerce platforms. First, we identified the criteria from a thorough review of the literature. Then, we invited five experts to provide (linguistic) ratings of these firms on the selected criteria, using a fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique with FLINTSTONES (a software tool) to generate aggregate scores for the assessment and evaluation of reverse logistics practices in social commerce platforms. Sensitivity analysis was also provided to monitor the robustness of the approach. The results of the study identified that four dominant criteria (reverse logistics performance indicators) in the social commerce platform: Customer relationship, Usage risk, Reviews, and Quality control.

Introduction

The forceful drivers for the fast growth of reverse logistics are many, including the increasing shortage of natural resources, environmental law, the realization of backward flow value, ebusiness development, good reputation requirement, customer satisfaction, and the population of information systems (Škapa & Klapalová, 2012). Rogers and Tibben-Lembke (1999) defined reverse logistics as “The process of planning, implementing, and controlling the efficient, costeffective flow of raw materials, in-process inventory, finished goods and related information from the point of consumption to the point of origin for the purpose of recapturing value or proper disposal” (Roger & Tibben-Lembke, 1999). The goal of reverse logistics is to focus on the reverse flow of materials by maximizing their value (G. Kannan, Pokharel, & Kumar, 2009). Products are returned through the supply chain for a variety of reasons: commercial returns, warranty returns, reusable articles, product recalls, end-of-use returns (EOU) and end-of-life returns (EOL) (Han & Ponce-Cueto, 2016). The rate of returns has increased by 57% for retailers and 43% for manufacturers respectively over the past three to five years, as surveyed by Accenture (Zaarour, Melachrinoudis, Solomon, & Min, 2014). Many businesses suffer significantly from poor management of the returns. Only returned products, as reported by CNBC, cost firms more than $260 billion a year and an average profit loss of 10% (McKevitt, 2016). The efficient implementation of reverse logistics requires an appropriate communication platform. Social commerce, a new business model of e-commerce, makes use of Web 2.0 technologies and social media to support social-related exchange activities. It offers a platform connecting consumers and companies integrating e-business, customer relationship management, technology support, and information systems. Given the enormous effect of returned items on the company‟s bottom line and social commerce´s popularity, an increasing number of firms have made efforts to streamline their reverse logistics process in social commerce platforms (Tavana, Zareinejad, Caprio, & Kaviani, 2016). This study focuses on identifying the criteria for effective management of returns through social commerce platforms and evaluating the reverse logistics efficiency of top global companies that use social commerce platforms. Firstly, a previous study, based on a thorough review of literature, identified four main criteria with sixteen sub-criteria from social commerce activities (Han & Trimi, 2017). Then, this research invited five experts to evaluate the reverse logistics performance of three top global companies on these criteria. The identification and evaluation of key evaluation criteria will help researchers and managers in strategic decisionmaking for reverse logistics implementation. In this study, we applied a fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique with FLINTSTONES (a software tool) to assess how efficient companies use social commerce platforms for their reverse logistics process. TOPSIS is based on the notion that the chosen alternative should have the shortest distance from the positive ideal solution and the farthest distance from the negative ideal solution (Hwang & Yoon, 1981). While effective management of reverse logistics is vital to enhance customer satisfaction and improve organizational performance, it is difficult to evaluate the performance of the system due to lack of measurable standards and limited data.

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