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    題名: Improving airline service quality based on rough set theory and flow graphs
    作者: James J. H. Liou;Yen-Ching Chuang;Chao-Che Hsu
    關鍵詞: rough set;flow graph;service quality;airline;data mining
    日期: 2015-11-26
    上傳時間: 2016-04-22 13:24:18 (UTC+8)
    出版者: Taylor & Francis Asia Pacific (Singapore)
    摘要: 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.
    關聯: Journal of Industrial and Production Engineering 33(2), pp.123-133
    DOI: 10.1080/21681015.2015.1113571
    顯示於類別:[運輸管理學系暨研究所] 期刊論文

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