Improving airline service quality based on rough set theory and flow graphs

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Abstract
This study differs from previous studies by applying multivariate statistical analysis and multi-criterion decision-making methods to the improvement of service quality. We use the rough set theory (RST) with a flow graph approach to determine customer attitudes regarding service quality, which can assist managers in developing strategies to improve service quality and thus satisfy the needs of customers. A set of rules is derived from a large sample of airline customers, and its predictive ability is evaluated. The flow graph and the cause-and-effect relationship of the decision rules are heavily exploited in service quality characteristics. As compared with the results of other data-mining analyses, our results are encouraging. This study demonstrates that the combination of the RST model and flow graphs assists in identifying the needs of customers, determining their characteristics, and facilitating the development of an improvement strategy.

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