مقاله انگلیسی رایگان در مورد انتخاب عرضه کننده سبز بر پایه کربن تحت محیط دینامیک ( الزویر )

 

مشخصات مقاله
عنوان مقاله  Carbon footprint based green supplier selection under dynamic environment
ترجمه عنوان مقاله  انتخاب تامین کننده سبز بر پایه کربن تحت محیط پویا
فرمت مقاله  PDF
نوع مقاله  ISI
سال انتشار  مقاله سال 2018
تعداد صفحات مقاله  21 صفحه
رشته های مرتبط محیط زیست، اقتصاد و مهندسی صنایع
گرایش های مرتبط  مدیریت زنجیره تامین
مجله  مجله تولید پاک کننده – Journal of Cleaner Production
دانشگاه  زنجیره تامین سبز، انتخاب تامین کننده، سیستم های چند عامل، رد پای کربن
کلمات کلیدی  Institute of logistics science & Engineering, Shanghai Maritime University, China
کد محصول  E5171
نشریه  نشریه الزویر
لینک مقاله در سایت مرجع  لینک این مقاله در سایت الزویر (ساینس دایرکت) Sciencedirect – Elsevier
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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1. Introduction

Integrating environmental issues into an organization’s purchasing activities becomes necessary due to the escalating deterioration of the environment and the increased awareness about environmental concerns(Govindan and Sivakumar (2016); Luthra et al. (2017)). It has become increasingly imperative for organizations facing competitive, regulatory and community pressures to search for a balance between the economic and environmental performance (Yazdani et al. (2017)). Green supplier selection plays a crucial role for enterprises in the green supply chain (GSC) (Qin et al. (2017)). Consequently, the green related supplier selection catches more and more attentions.

Main environmental criteria for green supplier selections are related to the level of waste water discharge, level of solid waste generation, noise level, recycling utilization level of waste material, carbon dioxide (CO2) emissions, level of harmful material utilization, and so on. Both researchers and practitioners make efforts to contribute to the green supplier selection. Although various evaluation and selection methods were proposed, there is few work focused on proposing an incentive mechanism which urges the participants in the GSC initiatively improve their strategies to reduce the harm to the environment. Yu et al. proposed an incentive selection mechanism which was verified to be useful in reducing the harmful effects on the environment (Yu et al. (2016)). The determinations of green factors were only related to the selected suppliers’ green factors, the determination of CO2 emissions were only related to the product transportation distances, and the purpose was to maximize the participants’ profits. However, the participant’s investment on the environment protection and the CO2 emissions during production processes are important factors to evaluate the participant’s green degree as well. Moreover, each participant in the GSC has a different preference on the profit, green factor, and CO2 emissions. Thus, different models are required to satisfy the personalized demands. In this research, the work of (Yu et al. (2016)) was extended. Both the selected suppliers’ green factors and the environmental investments will be considered during the determinations of green factors. The CO2 emissions during production processes will be taken into account as well. In addition, three selection models will be proposed to maximize the profit, maximize the green factor, and minimize CO2 emissions,.

Main contributions of this research can be summarized as follows. Firstly, an incentive supplier selection mechanism based on the carbon footprint is proposed, which can urge participants in the GSC to make greener decisions initiatively. Secondly, both economic attributes (i.e. price and quantity) and environmental attributes (i.e. green factors and CO2 emissions) are considered in the calculations of profits. A reward function and a penalty function are introduced into awarding the participants with high green factors, and punishing the participants with high CO2 emissions, respectively. Thirdly, new determination mechanisms for the green factor and the CO2 emissions are proposed to promote participants to select greener suppliers. Fourthly, three models are proposed for different preferences on the profit, green factor, and CO2 emissions. Moreover, the proposed models provide top management with flexibility in giving more or less importance weight to the economic or environmental attributes according to the participants’ preferences. On the other hand, this research contributes to construct a simple but effective mathematical model which is good at reducing CO2 emissions and increasing the green factors of participants. In addition, the proposed models can be used for the government to verify the effects of the determined reward/penalty threshold values to the reduction of the harmful impact on the environment.

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