Selecting cloud database services provider through multi-attribute group decision making: a probabilistic uncertainty linguistics TODIM model

Abstract

Cloud database services platforms (CDSP) have aided in both the generation of new ideas and the reduction of costs. Choosing the finest CDSP is a critical part of enterprise management for helping businesses respond to increasing market pressure and client demand. This study tried to solve this problem and proposed the integration concept of the TODIM (TOmada de Decisão Interativa e Multicritério) and the probability uncertain linguistic (PUL), which is a typical decision-making technique focused on the theory of prospects (PT-PUL-TODIM). The concept of probability uncertainty linguistic term sets (PULTS) is discussed. The cumulative weight of probabilistic double hierarchy linguistic knowledge is then determined by using the following cumulative prospect theory. Based on the experts’ opinions, complex expressions with experience in the Vietnam market were collected and further transformed into a PULTS matrix. However, the CRiteria Importance Through Inter-Criteria Correlation (CRITIC) technique is implemented to calculate the objective criteria weights. The PT-PUL-TODIM optimization approach is developed and adopted for the CDSP. Finally, we compared other methods and conducted a sensitivity analysis to compare the PT-PUL-TODIM approach with other ways to assess the validity, practicality, and usefulness of the technique, and the comparison revealed the merits and limitations of the model.

Keywords

• multiple attribute group decision making
• probability uncertainty linguistic todim
• theory of prospects
• cloud database service providers’ selection
• critic