An extended intuitionistic fuzzy ABAC method for evaluating innovative project ideas

Abstract

The innovation process typically follows a predefined sequence of phases: idea generation, screening, evaluation/selection, development, and launch/diffusion. This process exhibits a dynamic and cyclic structure. At each stage, potential ideas may undergo elimination or redefinition based on considerations such as their problem–solution fit or product–market fit. Consequently, the idea evaluation phase can be conducted continuously, involving varying numbers of potential ideas. To address the challenges associated with this process, a systematic approach for selecting the best new project ideas is essential. This study introduces the IF-ABAC method, which extends the alternative-by-alternative comparison-based (ABAC) method to the intuitionistic fuzzy (IF) environment. The proposed approach represents the first combination of fuzzy sets and ABAC within a group decision-making environment. The IF-ABAC method is employed during the evaluation phase, with the best–worst method determining the criteria weights. The study describes how the IF-ABAC approach adeptly manages changes in the set of alternatives after the decision process, addressing the dynamics inherent in decision-making environments. The study further includes an analysis of innovative business ideas in a real case study from Turkey, demonstrating the feasibility and efficiency of the proposed approach. A comprehensive sensitivity analysis is conducted to illustrate the stability and utility of the method. Finally, the results are compared with three other IF-based multi-criteria decision-making methods from the literature. The study concludes by asserting that the proposed IF-ABAC method provides a comprehensive and practical approach to select innovation project ideas in an environment of uncertainty and complexity.