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A non-additive multiple criteria analysis method for evaluation of airline service quality

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  • Zhang, Ling
  • Zhang, Luping
  • Zhou, Peng
  • Zhou, Dequn

Abstract

Subjective preferences with interactive property are often involved in the evaluation of airline service quality. It may not be possible, however, to correctly evaluate service quality using conventional additive measures. The fuzzy measure, which is a non-additive measure, is more suitable for this situation. Given the presence of arduousness in current fuzzy measure identification and in the calculation of the comprehensive performance values of alternatives in terms of the Choquet integral, this paper proposes the λk fuzzy measure and introduces Marichal entropy of the λk fuzzy measure to reach a solution. This paper also presents the aggregator Choquet integral with respect to the λk fuzzy measure. To verify the method's effectiveness, an application study of the comprehensive performance of 15 US airlines was conducted, using data collected over a 10-year period. Our results show that the proposed method is a suitable multi-criteria analysis method, which can be used to evaluate the performance of airline service quality when man–made interaction phenomena are not existent.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:jaitra:v:47:y:2015:i:c:p:154-161
    DOI: 10.1016/j.jairtraman.2015.05.006
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    References listed on IDEAS

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    3. Tsionas, Mike G. & Chen, Zhongfei & Wanke, Peter, 2017. "A structural vector autoregressive model of technical efficiency and delays with an application to Chinese airlines," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 1-10.
    4. Atsalakis, George S. & Atsalaki, Ioanna G. & Zopounidis, Constantin, 2018. "Forecasting the success of a new tourism service by a neuro-fuzzy technique," European Journal of Operational Research, Elsevier, vol. 268(2), pages 716-727.

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