Green supplier evaluation and selection plays a crucial role in the green supply chain management of any organization to reduce the purchasing cost of materials and increase the flexibility and quality of products. An interval neutrosophic set (INS)-which is a generalization of fuzzy sets, intuitionistic fuzzy sets (IFS) and neutrosophic sets (NS)-can better handle the incomplete, indeterminate and inconsistent information than the other sets. This paper proposes a new integrated Quality Function Deployment (QFD) in support of the green supplier evaluation and selection process. In the proposed approach, INS is used to assess the relative importance of the characteristics that the purchased product should have (internal variables "WHATs") in order to satisfy the company's needs, the relevant supplier assessment criteria (external variables "HOWs"), the "HOWs"-"WHATs" correlation scores, the resulting weights of the "HOWs" and the impact of each potential supplier. The normalized weighted rating is then defined and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is developed to obtain a final ranking of green suppliers. A case study is applied to demonstrate the efficiency and computational procedure of the proposed method.
Supplier selection and segmentation are crucial tasks of companies in order to reduce costs and increase the competitiveness of their goods. To handle uncertainty and dynamicity in the supplier segmentation problem, this research thus proposes a new dynamic generalized fuzzy multi-criteria group decision making (MCGDM) approach from the aspects of capability and willingness and with respect to environmental issues. The proposed approach defines the aggregated ratings of alternatives, the aggregated weights of criteria, and the weighted ratings by using generalized fuzzy numbers with the effect of time weight. Next, we determine the ranking order of alternatives via a popular centroid-index ranking approach. Finally, two case studies demonstrate the efficiency of the proposed dynamic approach. The applications show that the proposed appoach is effective in solving the MCGDM in vague environment.
The objective of this research is to determine the priority levels of criteria for evaluating the digital transformation level of businesses in Vietnam. In this study, the Analytic Hierarchy Process (AHP) method using fuzzy numbers is employed. Data for the research is collected through interviews with a group of experts and managers. Six criteria are used to assess the digital transformation level of businesses in Vietnam, including infrastructure and digital technology, data and information assets, strategy, digital transformation of corporate culture, digital experience for customers, and operations. The analysis results indicate that the infrastructure and digital technology criterion plays the most important role in assessing the digital transformation level of businesses in Vietnam.
Keywords: AHP, Digital Transformation Level, Fuzzy Numbers.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.