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Using decision rules to achieve mass customization of airline services

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  • Liou, James J.H.
  • Yen, Leon
  • Tzeng, Gwo-Hshiung

Abstract

This paper uses the Dominance-based Rough Set Approach (DRSA) to formulate airline service strategies by generating decision rules that model passenger preference for airline service quality. DRSA could help airlines eliminate some services associated with dispensable attributes without affecting passenger perception of service quality. DRSA could also help airlines achieve mass customization of airline services and generate additional revenues by active or passive targeting of quality services to passengers.

Suggested Citation

  • Liou, James J.H. & Yen, Leon & Tzeng, Gwo-Hshiung, 2010. "Using decision rules to achieve mass customization of airline services," European Journal of Operational Research, Elsevier, vol. 205(3), pages 680-686, September.
    • Handle: RePEc:eee:ejores:v:205:y:2010:i:3:p:680-686
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    References listed on IDEAS

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    Cited by:

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    2. Vlachos, Ilias & Lin, Zhibin, 2014. "Drivers of airline loyalty: Evidence from the business travelers in China," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 1-17.
    3. Li, Wenhua & Yu, Suihuai & Pei, Huining & Zhao, Chuan & Tian, Baozhen, 2017. "A hybrid approach based on fuzzy AHP and 2-tuple fuzzy linguistic method for evaluation in-flight service quality," Journal of Air Transport Management, Elsevier, vol. 60(C), pages 49-64.
    4. Zhang, Ling & Zhang, Luping & Zhou, Peng & Zhou, Dequn, 2015. "A non-additive multiple criteria analysis method for evaluation of airline service quality," Journal of Air Transport Management, Elsevier, vol. 47(C), pages 154-161.
    5. Sung-Shun Weng & Yang Liu & Juan Dai & Yen-Ching Chuang, 2020. "A Novel Improvement Strategy of Competency for Education for Sustainable Development (ESD) of University Teachers Based on Data Mining," Sustainability, MDPI, vol. 12(7), pages 1-18, March.
    6. Seungju Nam & Chunghun Ha & Hyun Cheol Lee, 2018. "Redesigning In-Flight Service with Service Blueprint Based on Text Analysis," Sustainability, MDPI, vol. 10(12), pages 1-21, November.
    7. Fogliatto, Flavio S. & da Silveira, Giovani J.C. & Borenstein, Denis, 2012. "The mass customization decade: An updated review of the literature," International Journal of Production Economics, Elsevier, vol. 138(1), pages 14-25.
    8. Jiapeng Liu & Miłosz Kadziński & Xiuwu Liao, 2023. "Modeling Contingent Decision Behavior: A Bayesian Nonparametric Preference-Learning Approach," INFORMS Journal on Computing, INFORMS, vol. 35(4), pages 764-785, July.
    9. Haruvy, Ernan E. & Li, Tao & Sethi, Suresh P., 2012. "Two-stage pricing for custom-made products," European Journal of Operational Research, Elsevier, vol. 219(2), pages 405-414.
    10. Liu, Xiaotong & Zhang, Kai & Chen, Bokui & Zhou, Jun & Miao, Lixin, 2018. "Analysis of logistics service supply chain for the One Belt and One Road initiative of China," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 117(C), pages 23-39.
    11. Corne, David & Dhaenens, Clarisse & Jourdan, Laetitia, 2012. "Synergies between operations research and data mining: The emerging use of multi-objective approaches," European Journal of Operational Research, Elsevier, vol. 221(3), pages 469-479.
    12. Heradio, Ruben & Perez-Morago, Hector & Alférez, Mauricio & Fernandez-Amoros, David & Alférez, Germán H., 2016. "Augmenting measure sensitivity to detect essential, dispensable and highly incompatible features in mass customization," European Journal of Operational Research, Elsevier, vol. 248(3), pages 1066-1077.

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