Green supply chain management (GSCM) practitioners striving to create a healthier environment should first identify the key criteria pertinent to the process of implementing the appropriate sustainable policies, particularly in the most rapidly growing electronics sector. Since the decision to adopt GSCM in electronics industry is associated with the use of a multi-dimensional approach involving a number of qualitative criteria, the paper examines GSCM based on fifteen criteria expressed in five dimensions and proposes a multi-criteria evaluation framework for selecting suitable green suppliers. In real life, the assessment of this decision is based on vague information or imprecise data of the expert's subjective judgements, including the feedback from the criteria and their interdependence. Thus to treat this uncertainty in multi-criteria decision making (MCDM) process, rough number (RN) is applied here using only the internal knowledge in the operative data available to the decision-makers. In this way objective imprecisions and uncertainties are used and there is no need to rely on models of assumptions. Instead of different external parameters in the application of RN, the structure of the given data is used. Therefore, the identified components are incorporated into a rough DEMATEL-ANP (R'AMATEL) method, combining the Decision Making Trial and Evaluation Laboratory Model (DEMATEL) and the Analytical Network Process (ANP) in a rough context. In group decision making, a rough number-based approach aggregates individual judgements and handles imprecision. The structure of the relationships between the criteria expressed in different dimensions is determined by using the rough DEMATEL (R'DAMETEL) method and building an influential network relation mapping, based on which the rough ANP (R'ANP) method is implemented to obtain the respective criteria weights. Then, the rough multi-attribute Ideal-Real Comparative Analysis (R'MAIRCA) is used to evaluate the environmental performance of suppliers for each evaluation criterion. Sensitivity analysis is performed to determine the impact of the weights of criteria and the influence of the decision maker's preferences on the final evaluation results. Applying the Spearman's rank correlation coefficient and other ranking methods, the stability of the alternative rankings based on the variation in the criteria weights is checked. The results obtained in the study show that the proposed method significantly increases the objectivity of supplier assessment in a subjective environment.

致力于创造更健康环境的绿色供应链管理（GSCM）从业人员应首先确定与实施适当的可持续政策的过程相关的关键标准，尤其是在增长最快的电子领域。由于在电子行业中采用GSCM的决定与使用涉及许多定性标准的多维方法有关，因此本文基于五个维度中表达的15条标准对GSCM进行了研究，并提出了一个多标准评估框架来选择合适的标准。绿色供应商。在现实生活中，对该决策的评估是基于模糊的信息或专家的主观判断的不精确数据，包括来自标准及其相互依赖性的反馈。因此，为了处理多准则决策（MCDM）过程中的这种不确定性，此处仅使用决策者可用的操作数据中的内部知识来应用粗略数（RN）。这样，可以使用客观的不确定性和不确定性，并且无需依赖假设模型。在给定的数据中，使用了给定数据的结构，而不是在RN应用中使用不同的外部参数。因此，将识别出的组件合并到粗略的DEMATEL-ANP（R'AMATEL）方法中，在粗略的上下文中结合决策试验和评估实验室模型（DEMATEL）和分析网络过程（ANP）。在小组决策中，基于数字的粗略方法会汇总个人判断并处理不精确性。通过使用粗糙的DEMATEL（R'DAMETEL）方法并建立有影响力的网络关系映射，可以确定在不同维度中表达的标准之间的关系结构，在此基础上，可以实现粗糙的ANP（R'ANP）方法来获得各自的标准权重。然后，使用粗糙的多属性理想-真实比较分析（R'MAIRCA）来评估每种评估标准的供应商的环境绩效。进行敏感性分析以确定标准权重的影响以及决策者偏好对最终评估结果的影响。应用Spearman等级相关系数和其他排名方法，基于标准权重的变化来检查备选排名的稳定性。