Jawad Ali, Ahmad N. Al‐Kenani, Muhammad I. Syam
Selecting sustainable suppliers in the new energy vehicle industry is a complex decision-making problem due to diverse criteria, uncertainty in evaluations, and the need to prioritize certain factors. Addressing this gap, we propose a novel multi-criteria decision-making (MCDM) framework based on p, q-quasirung orthopair fuzzy ([Formula: see text]ROF) sets and enhanced with Aczel-Alsina-based prioritized aggregation operators. Specifically, we develop two base operators-the [Formula: see text]ROF AA prioritized average ([Formula: see text]ROFAAPA) and the [Formula: see text]ROF AA prioritized geometric ([Formula: see text]ROFAAPG)-along with their weighted prioritized counterparts, the [Formula: see text]ROF AA prioritized weighted average ([Formula: see text]ROFAAPWA) and the [Formula: see text]ROF AA prioritized weighted geometric ([Formula: see text]ROFAAPWG). The mathematical properties of these operators are established, and an MCDM algorithm is formulated to incorporate decision-makers' priority structures. The framework also integrates a mathematical formulation to objectively determine criteria weights, ensuring a balanced combination of subjective and data-driven inputs. A case study for a leading new energy vehicle manufacturer demonstrates the framework's effectiveness: among four evaluation criteria-Quality ([Formula: see text]), Cost ([Formula: see text]), Service level ([Formula: see text]), and Production capacity ([Formula: see text])-Cost ([Formula: see text]) received the highest weight (0.2789), and supplier [Formula: see text] emerged as the most sustainable choice. Comparative experiments against established MCDM techniques confirm the proposed approach's superior ranking stability and robustness. These results provide both a methodological advance for fuzzy decision-making research and a practical decision-support tool for industries pursuing environmentally responsible supply chain strategies.