Picture fuzzy complex proportional assessment approach with step-wise weight assessment ratio analysis and criteria importance through intercriteria correlation

Abstract

The concept of the picture fuzzy set (PiFS) significantly enhances the multi-criteria decision-making (MCDM) process by incorporating membership value (MV), non-membership value (NMV), and a neutral component. PiFS extends the capabilities of traditional fuzzy sets (FSs), intuitionistic fuzzy sets (IFSs), and other fuzzy models. This paper introduces a novel MCDM approach, the picture fuzzy SWARA-CRITIC-COPRAS (PiF-SCC) method, specifically designed to assist decision-makers (DMs) in evaluating and selecting dynamic digital marketing (DDM) technologies within PiFS settings. The proposed method integrates the strengths of PiFS with step-wise weight assessment ratio analysis (SWARA), criteria importance through intercriteria correlation (CRITIC), and complex proportional assessment (COPRAS), aiming to improve the precision and effectiveness of technology evaluations. To validate the approach, a case study is conducted on DDM technology assessment within a specific business context. The PiF-SCC technique is applied to rank technological options using linguistic terms (LTs), PiFS numbers, an accuracy function (AF), and a score function (SF). Additionally, a comprehensive sensitivity analysis is performed to evaluate the robustness of the proposed method under different input scenarios and uncertainties. A thorough comparison with existing techniques is also provided, demonstrating the superior decision-making capability of the new approach, which leads to more accurate and dependable technology selection results. The manuscript also discusses marginal implications and limitations, along with potential future research directions to further enhance the applicability and effectiveness of the proposed approach.