A sustainable joint economic lot size model for supplier selection under carbon emissions: A case study

IF 6.8 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Niloofar Katiraee, Nicola Berti, Ilaria Isolan, Martina Calzavara, Daria Battini
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引用次数: 0

Abstract

Selecting suppliers strategically is a critical challenge in supply chain design, particularly in a dynamic global marketplace where maintaining competitiveness and sustainability is essential. Supplier location is a key factor that significantly impacts supply chain sustainability. Hence, this study proposes a new Sustainable Joint Economic Lot Size (S-JELS) model that integrates average annual cost and total amount of emissions associated with annual activities related to both buyer and supplier. The developed model accounts for costs and emissions from the buyer’s purchasing, inventory management, and transportation activities, as well as from the supplier’s production, packaging, and delivery processes. Additionally, the model incorporates various transportation modes, including shipping, trucking, and rail, to more accurately assess the environmental impact of different supply chain strategies. The proposed JELS model can support managers performing sustainable purchasing decisions and assess a sustainable supplier selection. The developed model is applied in a leather case study characterized by high resource intensity, significant environmental impacts, and complex global logistics to accomplish supplier selection between one domestic and one international supplier, aiming to determine the most sustainable strategy in terms of cost and emission.
碳排放下供应商选择的可持续联合经济批量模型:一个案例研究
战略性地选择供应商是供应链设计中的关键挑战,特别是在动态的全球市场中,保持竞争力和可持续性至关重要。供应商选址是影响供应链可持续性的关键因素。因此,本研究提出了一个新的可持续联合经济批量(S-JELS)模型,该模型集成了与买方和供应商相关的年度活动相关的平均年成本和排放总量。开发的模型考虑了买方的采购、库存管理和运输活动以及供应商的生产、包装和交付过程的成本和排放。此外,该模型结合了各种运输方式,包括海运、卡车运输和铁路运输,以更准确地评估不同供应链战略对环境的影响。提出的JELS模型可以支持管理者执行可持续采购决策和评估可持续供应商选择。将所建立的模型应用于资源强度高、环境影响大、全球物流复杂的皮革案例研究中,在一个国内供应商和一个国际供应商之间进行选择,以确定成本和排放方面最可持续的战略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.60
自引率
0.00%
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