Abstract
Supply chain management is an essential part of an organisation's sustainable programme. Understanding the concentration of natural environment, public, and economic influence and feasibility of your suppliers and purchasers is becoming progressively familiar as all industries are moving towards a massive sustainable potential. To handle such sort of developments in supply chain management the involvement of fuzzy settings and their generalisations is playing an important role. Keeping in mind this role, the aim of this study is to analyse the role and involvement of complex q-rung orthopair normal fuzzy (CQRONF) information in supply chain management. The major impact of this theory is to analyse the notion of confidence CQRONF weighted averaging, confidence CQRONF ordered weighted averaging, confidence CQRONF hybrid averaging, confidence CQRONF weighted geometric, confidence CQRONF ordered weighted geometric, confidence CQRONF hybrid geometric operators and try to diagnose various properties and results. Furthermore, with the help of the CRITIC and VIKOR models, we diagnosed the novel theory of the CQRONF-CRITIC-VIKOR model to check the sensitivity analysis of the initiated method. Moreover, in the availability of diagnosed operators, we constructed a multi-attribute decision-making tool for finding a beneficial sustainable supplier to handle complex dilemmas. Finally, the initiated operator's efficiency is proved by comparative analysis.