  This paper introduces a novel approach to enhance uncertainty representation,
offering decision-makers a more comprehensive perspective for improved
decision-making outcomes. We propose Generalized Orbicular (m,n,o) T-Spherical
Fuzzy Set (GO-TSFS), a flexible extension of existing fuzzy set models
including Globular T-spherical fuzzy sets (G-TSFSs), T-spherical fuzzy sets
(T-SFSs), (p,q,r) Spherical fuzzy sets, and (p,q) Quasirung orthopair fuzzy
sets (QOFSs). The framework employs three adjustable parameters m, n, and o to
finely tune the influence of membership degrees, allowing for adaptable
weighting of various degrees of membership. By utilizing spheres to represent
membership, indeterminacy, and non-membership levels, the model enhances
accuracy in depicting vague, ambiguous, and imprecise data. Building upon the
foundation of GO-TSFSs, we introduce essential set operations and algebraic
operations for GO-TSF Values (GO-TSFVs). Moreover, we also develop score
functions, accuracy functions, and basic distance measures such as Hamming and
Euclidean distances to further enhance the analytical capabilities of the
framework. Additionally, we propose GO-TSF Hamacher Weighted Averaging
(GO-TSFHWA) and GO-TSFH Weighted Geometric (GO-TSFHWG), aggregation operators
tailored for our proposed sets. To demonstrate the practical applicability of
our approach, we apply our proposed aggregation operators namely GO-TSFHWA and
GO-TSFHWG to solve a Multi-Criteria Group Decision Making (MCGDM) problem,
specifically for selecting the most suitable e-commerce online shopping
platform from the top-rated options. Sensitivity analysis is also conducted to
validate the reliability and efficacy of our results, affirming the utility and
robustness of the proposed methodology in real-world decision-making scenarios.
