Work

A Novel Integrated Fuzzy Analytic Hierarchy Process with a 4-Tuple Hedge Algebra Semantics for Assessing the Level of Digital Transformation of Enterprises

Year: 2025

Type: article

Abstract: Hedge algebra is a powerful and flexible tool for handling linguistic information, enabling precise quantitative computations and enhancing the effectiveness of multi-criteria decision-making (MCDM). This study proposes a novel integrated fuzzy MCDM approach that combines an enhanced fuzzy analytic hierarchy process (EFAHP) with a 4-tuple hedge algebra semantics model to assess digital transformation in retail enterprises. In this approach, the EFAHP method is integrated with hedge algebra to determine the priorities of pillars and criteria while providing a rigorous mathematical mechanism to transform ambiguous linguistic evaluations into numerical values. This transformation leverages the semantic structure of linguistic variable domains and incorporates fuzziness measures for both atomic words and intensity-modifying words (hedges). Furthermore, a new consistency index formula is introduced to evaluate the reliability of the EFAHP results, with validation being limited to the case study dataset. The 4-tuple hedge algebra semantic model is then employed to assess and rank the digital transformation levels of retail enterprises in Vietnam. Finally, a sensitivity analysis verifies the robustness of the proposed approach by illustrating how variations in pillar and criterion weights influence enterprise rankings.

Source: Mathematics

DOI: 10.3390/math13213539

Authors: Nhu Van Kien, Hoang Van Thong, Nguyen Cat Ho, Luu Quoc Dat

Institutions: University of Transport and Communications, Hanoi University of Industry, Duy Tan University, Vietnam National University, Hanoi, VNU University of Economics and Business

Language: English

Topic: Multi-Criteria Decision Making

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $3,137

Funder: VNU Science and Technology Development Fund