Uncertainty is a common occurrence in real-world issues that often make decision-making difficult. Specifically, when it comes to managing a supply chain, the decision of which supplier to choose is complicated by a lack of information and knowledge, which leads to different levels of uncertainty in the attributes and alternatives, making it hard to make the right decision. In this article, a multi attribute decision-making method within a qualitative reasoning framework, where the assessment of problem attributes is carried out using different backgrounds and levels of experts' knowledge, is presented, and the score of the alternatives by evaluation a K-dimensional vector of qualitative labels is determined. To achieve it, the qualitative reasoning framework is first described, and then the proposed method in the same framework is described. The validity of the proposed method was verified by two practical examples. An example demonstrated the effectiveness of the proposed model and the results were compared with other methods. Finally, a real example was employed to select the best supplier. The conditions for the practical example are chosen in such a way, that it cannot be solved by using the previous methods. The results of this study explain the advantage of using multiscale linguistic space over other linguistic methods and also by analyzing two practical examples, the validity of the proposed method and its advantage over other methods in the qualitative reasoning space is confirmed.