With the increasing awareness of environmental protection, green supplier selection as an indispensable part of green supply chain management has received extensive attention. Effective and reliable green supplier evaluation criteria are crucial to the success of green supplier selection. Therefore, identifying the critical criteria and determining the causality of these criteria is an important requirement of stakeholders. However, the existing approaches on identifying critical causal criteria suffer at least two weaknesses: firstly it assumes the same cognitive levels between different decision makers by using a pre-determined and uniformed formation to characterize evaluation judgements, which may cause potential decision bias; secondly there is a lack of effective methods to analyse and identify critical causal criteria in the face of heterogeneous judgements, potentially causing the duplication consideration of the impacts of some criteria in green supplier selection. To address these issues, this study proposes a new approach integrating cloud model and DEMATEL (decision making trial and evaluation laboratory) to determine critical causal criteria for green supplier evaluation with qualitative heterogeneous judgements. The contribution of this study is threefold. First, to address the difficulty in processing uncertain and heterogeneous judgements, the cloud model theory is utilized and further developed to convert heterogeneous qualitative judgements into homogeneous quantitative data with the form of interval integrated clouds, which realizes the flow of uncertainty from qualitative judgements to quantitative data. Second, to enable the identification of critical causal criteria, the DEMATEL method is extended to accommodate the cloud model environment to solve the identification problem. Third, a case study, followed by a comparison analysis is provided to illustrate the applicability and advantages of the proposed approach. The results indicate that the proposed approach can handle heterogeneous judgements effectively as well as that staff environmental training, green production innovation, green marketing and green corporate culture are the critical causal criteria for the given application.

随着环保意识的增强，绿色供应商选择作为绿色供应链管理中不可或缺的一部分受到了广泛关注。有效和可靠的绿色供应商评价标准是绿色供应商选择成功的关键。因此，识别关键标准并确定这些标准的因果关系是利益相关者的重要要求。然而，现有的识别关键因果标准的方法至少存在两个弱点：首先，它通过使用预先确定的统一形式来表征评估判断，从而假设不同决策者之间具有相同的认知水平，这可能会导致潜在的决策偏差；其次，缺乏有效的方法来分析和识别面临异质性判断的关键因果标准，可能导致在绿色供应商选择中对某些标准的影响进行重复考虑。为了解决这些问题，本研究提出了一种集成云模型和 DEMATEL（决策试验和评估实验室）的新方法，通过定性异质判断确定绿色供应商评估的关键因果标准。这项研究的贡献有三方面。首先，针对不确定性和异质性判断处理难的问题，利用并进一步发展云模型理论，将异质性定性判断转化为均匀的定量数据，以区间集成云的形式，实现了不确定性从定性判断到定量数据的流动。其次，为了能够识别关键的因果标准，扩展了 DEMATEL 方法以适应云模型环境以解决识别问题。第三，提供了一个案例研究，然后进行了比较分析，以说明所提出方法的适用性和优势。结果表明，所提出的方法可以有效地处理异质判断，并且员工环境培训、绿色生产创新、绿色营销和绿色企业文化是给定应用的关键因果标准。DEMATEL 方法被扩展以适应云模型环境来解决识别问题。第三，提供了一个案例研究，然后进行了比较分析，以说明所提出方法的适用性和优势。结果表明，所提出的方法可以有效地处理异质性判断，并且员工环境培训、绿色生产创新、绿色营销和绿色企业文化是给定应用的关键因果标准。DEMATEL 方法被扩展以适应云模型环境来解决识别问题。第三，提供了一个案例研究，然后进行了比较分析，以说明所提出方法的适用性和优势。结果表明，所提出的方法可以有效地处理异质判断，并且员工环境培训、绿色生产创新、绿色营销和绿色企业文化是给定应用的关键因果标准。