The development of better methods for the improvement of airline performance is crucial, but this type of problem is difficult to solve because of the large number of complex factors involved making this inherently a multiple criteria decision making (MCDM) problem. In current studies, the factors to be evaluated are considered based upon a literature review or expert opinions. This study proposes an integrated model that combines data mining and MCDM to extract the critical factors for the improvement of airline performance. We apply the dominance-based rough set approach to extract the essential factors. The decision-making trial and evaluation laboratory method with the concepts of the analytic network process (DANP) is then used to construct the complex evaluation system. Finally, the VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, meaning multicriteria optimization and compromise solution) method is applied to select the suitable improvement alternative goals with the corresponding weights provided by the DANP method. The results show that the current model can be used as the basis for a benchmark industry improvement index which can be used to evaluate each airline individually with defined planning goals to achieve financial efficiency by improving operational efficiency.

Introduction

The past 10 years have seen large fluctuations and extreme changes in airline companies’ financial and operational performance. The reasons for these are numerous, including problems caused by management and government regulators, as well as company mergers, restructuring and financial interventions and changes in the markets. For example, inappropriate financial and operational management decisions can affect internal costs, leading to chaotic high-risk situations, which if not dealt with appropriately could result in a declaration of bankruptcy or closing of the airline. Airline managers need a useful tool to identify, diagnose, and evaluate the company’s financial and operational performance and rank goals for improvement. An airline’s business performance depends upon customer service and internal operations to maximize financial efficiency. How to improve operational and financial performance and overcome problems is a particularly critical challenge for airline managers. The improvement of an airline’s financial and operational performance involves a complex decision-making process requiring a systematic approach. Making such decisions entails dealing with a large number of conflicting criteria, which may not be clearly defined, as well as the consideration of interrelated criteria, mixing quantitative and qualitative criteria with subjective judgments (Gomes et al., 2014). All of these factors make airline performance improvement an inherently multiple criteria decision making (MCDM) problem. These multiple dimensions and criteria have motivated several scholars to search other fields to find advanced quantitative methods which can be adapted to create feasible approaches for performance optimization (Fethi and Pasiouras, 2010). Decisions for improving an airline’s operational and financial performance, regardless of whether problems have been caused by external (e.g., fuel cost and consumption) or internal (e.g., net income) factors, are critical and unavoidable challenges which must be dealt with by management in order to survive in the air transportation industry. Any alterations in the criteria (factors) for operational efficiency can cause a number of reactions which impact financial efficiency especially because of the interrelationship between the criteria.