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The aviation industry confronts two primary challenges: achieving net-zero emissions and undergoing digital transformation. This study examines the role of Smart Information Management Systems (SIMS) as a governance intermediate in addressing sustainability strategy discrepancies between airports and airlines. A multi-criteria decision-making (MCDM) framework was utilised, incorporating the Fuzzy Delphi Method (FDM) and the Analytic Hierarchy Process (AHP). Data was gathered from 17 experts, averaging 15.6 years of experience, encompassing representatives from airlines (35.3%), airport authorities (23.5%), academia (17.6%), government policy departments (11.8%), and ESG specialists (11.8%). The research assesses governance maturity across six dimensions: data transparency, carbon monitoring, decision support, compliance governance, interdepartmental collaboration, and resource optimisation. The findings indicate a systemic "technical vs. institutional" disparity in governance capabilities: Airlines exhibit markedly greater maturity in data transparency (+55.26%) and resource optimisation (+34.52%), propelled by real-time operational agility. Airports demonstrate enhanced proficiency in decision support (+38.80%) and compliance and risk governance (+35.89%), indicating a regulation-focused institutional framework. This paper presents a comprehensive ESG–SIMS governance paradigm that clarifies the mediating function of digital technologies in enhancing data openness, decision-making agility, and governance resilience in the aviation sector. 

The airline industry faces persistent profitability pressure stemming from high fixed costs, intense competition, and macroeconomic volatility. Since the entry of low-cost carriers (LCCs), ancillary revenue—defined as income generated from services and products supplementary to the core ticket—has evolved from a peripheral activity into a strategic financial pillar for both full-service and low-cost airlines. This study investigates the determinants of passenger willingness to pay (WTP) for à la carte ancillary services and identifies behavioural and demographic profiles that predict purchase frequency. Using a survey of 254 air travellers and a multi-method statistical approach (Chi-square tests, Mann–Whitney U tests, and Kruskal–Wallis with Bonferroni-corrected pairwise comparisons), six hypotheses are tested. The results demonstrate that (i) passengers familiar with à la carte services allocate significantly larger travel budgets to such services (p < .05); (ii) frequent travellers (>5 flights/year) are significantly more likely to purchase à la carte services (χ² = 8.44, p < .01); (iii) frequent-flyer programme (FFP) members purchase ancillary services at substantially higher rates (χ² = 9.70, p < .01); and (iv) contrary to common managerial intuition, short-haul passengers purchase à la carte services more frequently than long-haul passengers (χ² = 4.51, p < .05). Wi-Fi access is valued across all age cohorts without statistically significant differences. The findings extend the revenue management literature by empirically validating familiarity and loyalty-programme membership as the strongest behavioural predictors of à la carte WTP, and offer actionable guidance for targeted personalisation, segmentation, and dynamic pricing strategies. Implications for machine-learning-driven ancillary recommendation systems are also discussed in light of recent advances in offer management (2022–2025).