Identifying critical causal criteria of green supplier evaluation using heterogeneous judgements: An integrated approach based on cloud model and DEMATEL

Gao, Hengxia; Ju, Yanbing; Gonzalez, Ernesto D. R. Santibanez; Zeng, Xiao-Jun; Dong, Peiwu; Wang, Aihua

Abstract

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. (C) 2021 Elsevier B.V. All rights reserved.

Más información

Título según WOS: ID WOS:000760655500008 Not found in local WOS DB
Título de la Revista: APPLIED SOFT COMPUTING
Volumen: 113
Editorial: Elsevier
Fecha de publicación: 2021
DOI:

10.1016/j.asoc.2021.107882

Notas: ISI