Research Information System
4th International Conference on the Leadership and Management of Projects in the Digital Age, ICLAMP 2025, Al Eker, Bahrain, 13 - 14 April 2025, vol.1548 LNNS, pp.420-430, (Full Text)
Multi-Criteria Decision-Making (MCDM) approaches are extensively utilized in intricate decision-making processes to assess options based on competing criteria. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a recognized multi-criteria decision-making (MCDM) method that evaluates alternatives by measuring their proximity to the ideal and negative-ideal solutions. Nonetheless, conventional TOPSIS encounters difficulties in managing uncertainty and subjective assessments. To overcome these constraints, fuzzy logic-based methods have been implemented, providing more accurate and flexible assessments when traditional decision-making techniques are insufficient. In this context, Q-Rung Orthopair Fuzzy TOPSIS (Q-ROF TOPSIS) offers a more comprehensive framework for modeling uncertainty, enabling decision-makers to articulate membership and non-membership degrees across a wider spectrum. This study assesses the viability of Q-ROF TOPSIS in multi-criteria decision-making (MCDM) processes under uncertainty. Forty-three decision-makers of various seniority evaluated five country-specific options based on 10 factors, including logistics, warehousing expenses, commission rates, digital marketing, brand recognition, and market share. The findings demonstrate that Asia was the most advantageous option, succeeded by the United Arab Emirates and Kazakhstan. A sensitivity analysis further validated the model’s robustness, indicating that rankings persisted consistently despite fluctuations in criteria weights. These findings underscore the efficacy of Q-ROF TOPSIS in multi-criteria decision-making and indicate its prospective uses in investment decisions, supply chain management, and corporate strategy.