Aircraft selection is an important issue in achieving long-term goals in the airline industry. For this issue in which multiple conflicting criteria are involved, the extant literature points to the use of multi-criteria decision-making (MCDM) methods. In this respect, this study aims to propose a systematic and comprehensive framework with a focus on the regional aircraft selection perspective. To achieve this, an integrated fuzzy Pivot Pairwise Relative Criteria Importance Assessment (F-PIPRECIA) and fuzzy Measurement Alternatives and Ranking according to the Compromise Solution (F-MARCOS) approach was employed. In this study, in which six regional aircraft alternatives were evaluated according to 14 criteria, data were collected from five decision experts. As a result, it was found that the most pivotal criterion is C33 (Operational Cost), and the least important criterion is C12 (NOx). In addition, CRJ1000 was identified as the most promising regional aircraft alternative. The results of the application were further validated by applying a three-stage sensitivity analysis. The proposed structure is anticipated to assist airline managers in aircraft selection decisions under uncertainty by offering a robust and systematic tool.

Delivering high-quality service to passengers can be critical for an airport’s survival, competitiveness, profitability, and long-term growth in a highly competitive environment. The present study aims to examine the relationship between airport service attributes and passenger satisfaction. To this end, we conducted multi-method research consisting of symmetric (multiple regression analysis—MRA) and asymmetric (necessary condition analysis—NCA) approaches. The research data consists of 1463 valid online reviews (n = 1463) of the top 50 busiest airports in Europe retrieved from Skytrax. The MRA was employed to examine the net effect of the eight airport service attributes on passenger satisfaction, while the NCA was used to explore the necessary conditions and level of necessity to achieve passenger satisfaction. Using MRA, the findings reveal that airport staff is the most influential predictor of passenger satisfaction, whereas airport shopping and airport Wi-Fi connectivity do not have a significant effect on passenger satisfaction. Moreover, the NCA results found that six of the eight conditions are necessary to achieve passenger satisfaction at the airport. To complement and comprehend the findings, this study also sheds light on the antecedents underlying airport passenger satisfaction in the post-COVID-19 era using NCA.

Purpose: Ground-handling services are important for effective aircraft operations in the air transportation system. Airlines often outsource these services to ground-handling agents through business-to-business (B2B) marketing decisions. Therefore, this paper aims to address the problem of ground-handling agent selection in the airline industry.Design/methodology/approach: A real-world case study was carried out to demonstrate the applicability of the integrated best worst method and fuzzy multi-attribute ideal real comparative analysis (F-MAIRCA) approach to solve ground-handling agent selection problems under uncertainty and imprecision. A two-stage sensitivity analysis was also conducted to ensure the credibility and validity of the application.Findings: In the weighting stage, “Quality” was determined as the most important criterion in terms of supplier performance. With regard to the performance of the ground-handling agents, A2 was found as the optimal supplier in terms of both credibility and validity.Practical implications: This study enumerated several criteria that ground-handling agents must meet in order to effectively supply services for the airlines. In addition, this study provides a novel framework from which managers can gain additional benefits from their businesses. Finally, it is concluded that this approach will help airline managers quantitatively in choosing the most appropriate ground-handling agent.Originality/value: The contributions of this study to the existing literature are twofold. First, we propose a novel multiple attribute decision-making approach to address the problem of supplier selection for airlines under uncertainty and imprecision. Second, the selection of ground-handling agents from the B2B perspective is addressed for the first time in literature.