دانلود رایگان مقاله انگلیسی روش تاپسیس فازی برای ارزیابی عملکرد تدارکات معکوس در سیستم عامل تجارت الکترونیک - الزویر 2018

عنوان فارسی
روش تاپسیس فازی برای ارزیابی عملکرد تدارکات معکوس در سیستم عامل های تجارت الکترونیک
عنوان انگلیسی
A fuzzy TOPSIS method for performance evaluation of reverse logistics in social commerce platforms
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
36
سال انتشار
2018
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
نوع مقاله
ISI
نوع نگارش
مقالات پژوهشی (تحقیقاتی)
رفرنس
دارد
پایگاه
اسکوپوس
کد محصول
E9912
رشته های مرتبط با این مقاله
مدیریت، مهندسی صنایع
گرایش های مرتبط با این مقاله
تحقیق در عملیات، بهینه سازی سیستم ها
مجله
سیستم های کارشناس با نرم افزار - Expert Systems With Applications
دانشگاه
Business Administration and Statistics Department - Technical University of Madrid (UPM) - Spain
کلمات کلیدی
مجموعه های فازی؛ لجستیک معکوس؛ تجارت اجتماعی؛ تاپسیس؛ آنالیز حساسیت؛ FLINTSTONES
doi یا شناسه دیجیتال
https://doi.org/10.1016/j.eswa.2018.03.003
چکیده

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.

نتیجه گیری

Conclusion


The return ratio of products has been significantly higher than before the Internet powered digital age (Liu, Chen, Li, & Liu, 2015). At the same time, the rapidly growing social media and Web 2.0 technology have transformed social commerce as an easy and fast tool to effectively manage the reverse logistics process. Social commerce is becoming increasingly popular with technological advances and consumers´ concerns for sustainability (Khor, Udin, Ramayah, & Hazen, 2016). This unique environment brings many opportunities for value creation from reverse logistics. Businesses can obtain a significant competitive advantage if they can leverage social commerce platforms effectively (Alptekin et al., 2015). Therefore, the social commerce platform as an important support system of reverse logistics should be a strategic goal for businesses. To adapt to the reverse logistics market environment, it is imperative to conduct research on the reverse logistics network and highly integrated social commerce platforms (Li, Lu, & Liu, 2014). From this perspective, evaluating reverse logistics performance in social commerce platforms is important for companies, customers, and researchers. In this study, importance weights of social commerce platform determinants are analyzed by the fuzzy TOPSIS method to evaluate the four main criteria for effective reverse logistics in the social commerce platform. The study contributes to the literature of reverse logistics in several ways. First, the study results identified the important determinants (criteria) for effective reverse logistics. Secondly, a new methodology for evaluating reverse logistics in the social commerce platform is developed based on fuzzy TOPSIS in conjunction with FLINTSTONES. Here a sensitivity analysis is also performed to verify the robustness of the proposed method.


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