直播电商模式下绿色包装供应商评价与选择——基于模糊VIKOR (Fuzzy VIKOR)方法

Evaluation and Selection of Green Packaging Suppliers in the Live-Streaming E-Commerce Model—Based on the Fuzzy VIKOR Method

摘要: 近年来，直播电商的迅猛发展在带来巨大商业价值的同时，也因其海量包装废弃物引发了严峻的环境问题。在“双碳”战略目标下，电商平台亟需从源头筛选绿色包装供应商以推动供应链绿色转型。然而，该评价过程涉及环保、功能与用户体验等多维准则，且大量指标存在模糊性，传统依赖精确数据的评价方法面临局限。为此，本研究旨在构建一个贴合直播电商模式的绿色包装供应商综合评价体系。首先，从环保属性、功能属性与体验属性三个准则层出发，建立了包含8个定性指标的评价指标体系。进而，针对评价信息的模糊性特点，引入三角模糊数理论将专家语言评价转化为可计算的模糊信息，并结合模糊VIKOR (Fuzzy VIKOR)方法构建评价模型。该模型通过计算各供应商的群体效用值、个体遗憾值及折衷评价值，能够在最大化群体效益与最小化个体遗憾之间寻求平衡，实现供应商的科学排序与择优。通过一个针对4家候选供应商的算例分析，验证了所提指标体系与决策模型的有效性与实用性。结果表明，该模型能够有效处理决策中的模糊语义信息，为直播电商平台在环保、功能、体验三类产品属性的模糊评价中提供了可操作的决策工具，有效适配场景化需求与模糊语义处理需求，对行业绿色转型具有实践指导意义。

Abstract: In recent years, the rapid development of live-streaming e-commerce has generated significant commercial value but also caused severe environmental problems due to the massive amount of packaging waste. Under the “Dual Carbon” strategic goals, e-commerce platforms urgently need to screen green packaging suppliers from the source to promote the green transformation of their supply chains. However, this evaluation process involves multi-dimensional criteria such as environmental protection, functionality, and user experience, with many indicators exhibiting inherent fuzziness, posing limitations for traditional evaluation methods relying on precise data. To address this, this study aims to construct a comprehensive evaluation system for green packaging suppliers tailored to the live-streaming e-commerce model. Firstly, based on three criterion layers—environmental attributes, functional attributes, and experiential attributes—an evaluation index system containing 8 qualitative indicators is established. Then, addressing the fuzziness of evaluation information, triangular fuzzy number theory is introduced to convert expert linguistic evaluations into computable fuzzy information, combined with an VIKOR (Fuzzy VIKOR) method to build an evaluation model. This model seeks a balance between maximizing group utility and minimizing individual regret by calculating each supplier’s group utility value, individual regret value, and compromise evaluation value, enabling scientific ranking and selection of suppliers. An example analysis involving four candidate suppliers verifies the effectiveness and practicality of the proposed index system and decision-making model. The results show that the model can effectively handle fuzzy semantic information in decision-making, providing an operable decision tool for live-streaming e-commerce platforms to select suppliers under complex multi-objective conditions, offering practical guidance for the industry’s green transformation.