Marine Biodiversity Records最新文献

英文中文

Double hierarchy hesitant fuzzy linguistic information based framework for personalized ranking of sustainable suppliers. 基于双层次犹豫模糊语言信息的可持续供应商个性化排名框架。

IF 5.8 Q1 Agricultural and Biological Sciences

Marine Biodiversity Records

Pub Date : 2022-09-01 Epub Date: 2022-04-29 DOI: 10.1007/s11356-022-20359-y

Raghunathan Krishankumar, Dragan Pamucar, Alok Pandey, Samarjit Kar, Kattur Soundarapandian Ravichandran

With the growing appetite for reducing carbon footprint, organizations are tirelessly working towards green practices and one such crucial practice is purchasing raw materials from sustainable suppliers (SSs). Inspired by the drift in purchase habits, several sustainable suppliers emerged in the market and a rational selection of a suitable sustainable supplier is a complex decision problem. There are many criteria associated with the evaluation of sustainable suppliers, and double hierarchy hesitant fuzzy linguistic (DHHFL) structure is a popular preference style that accepts complex linguistic expressions in the natural language form. Earlier studies on sustainable supplier selection infer that (i) complex linguistic expressions are not properly modeled, (ii) interrelationship among criteria must be considered during importance assessment, (iii) direct assignment of attitudinal values of experts causes bias and subjectivity, and (iv) nature of criteria play a crucial role in ranking SSs. To overcome these limitations, a novel MCMD framework is proposed in this study in which the attitudinal characteristic values of experts are calculated by using a variance approach. Besides, importance of diverse sustainable criteria is calculated by proposing novel attitude-CRITIC approach that supports proper capturing of interrelationship among criteria along with experts' attitude values. Later, weighted distance approximation algorithm is presented to DHHFL setting for personalized and cumulative ranking of SSs by properly considering nature of criteria. These methods are integrated to form a framework under DHHFL setting, and its usefulness is exemplified by using a case study of SS selection in an automotive firm. A comprehensive sensitivity analysis as well performed to test the validity of the proposed model approves the applicability, validity, and robustness of the model. Lastly, comparison is done with other methods to understand the merits and shortcomings of the proposal.

随着减少碳足迹的呼声日益高涨，各组织都在孜孜不倦地致力于绿色实践，其中一个重要的实践就是向可持续供应商（SSs）采购原材料。受采购习惯变化的启发，市场上出现了多家可持续供应商，如何合理选择合适的可持续供应商是一个复杂的决策问题。与可持续供应商评价相关的标准有很多，双层次犹豫模糊语言（DHHFL）结构是一种流行的偏好风格，它接受自然语言形式的复杂语言表达。早期关于可持续供应商选择的研究推断：(i) 复杂的语言表达没有被正确建模；(ii) 在重要性评估过程中必须考虑标准之间的相互关系；(iii) 专家态度值的直接分配会导致偏差和主观性；(iv) 标准的性质在可持续供应商排序中起着至关重要的作用。为了克服这些局限性，本研究提出了一个新颖的 MCMD 框架，其中专家的态度特征值是通过方差法计算得出的。此外，通过提出新颖的态度-CRITIC 方法来计算不同可持续标准的重要性，该方法支持正确捕捉标准之间的相互关系以及专家的态度值。随后，针对 DHHFL 设置提出了加权距离近似算法，通过适当考虑标准的性质，对 SS 进行个性化累积排序。在 DHHFL 设置下，这些方法被整合成一个框架，并通过一个汽车公司 SS 选择的案例研究来说明其实用性。此外，还进行了全面的灵敏度分析，以检验建议模型的有效性，从而证明了模型的适用性、有效性和稳健性。最后，还与其他方法进行了比较，以了解该建议的优缺点。

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