A method identifying key optimisation points for aircraft seat comfort 

Seating is the overriding factor influencing aircraft cabin comfort. To efficiently enhance seat comfort, this paper proposes a method to identify key optimisation points for seat comfort. Seat discomfort indicators are recognised based on a comparison of perceived performance with expectation. Confirmatory factor analysis is used to explore the latent variables of discomfort indicators, and a structural model was used to analyse correlations between latent variables. Finally, the most important latent variable influencing seat comfort was clarified. Analysis results of survey data from narrow-body aircraft show that seat discomfort indicators centre on the physical performance of the seat and include four latent variables: support performance, personal space, contact surface features, and safety and stability. Support performance determines body posture while travelling and is the overriding latent variable influencing seat comfort. This research establishes aircraft seat discomfort indicators, latent variables formed through the mutual linkage of discomfort indicators, and the structural relations between latent variables. The results can assist in the formulation of comfort optimisation procedures for aircraft seats. Practitioner summary: A method identifying the key points of aircraft seat comfort optimisation was proposed, which includes three steps: recognising discomfort indicators, exploring the relationship between discomfort indicators, and confirming the most important variable influencing seat comfort. Results provide guidance for aircraft seat optimisation. Abbreviations: SEM: structural equation modelling; EFA: exploratory factor analysis; CFA: confirmatory factor analysis; PA-OV: path analysis with observed variables; CR: construct reliability; AVE: average variance extracted; CMIN: likelihood-ratio chi-square; DF: degrees of freedom; GFI: goodness-of –fit index; AGFI: adjusted goodness-of –fit index; RMSEA: root mean square error of approximation; NNFI: non-normed fit index; RFI: relative fit index; CFI: comparative fit index; CN: critical N

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    • © 2021 Informa UK Limited, trading as Taylor & Francis Group. Abstract reprinted with permission of Taylor & Francis.
  • Authors:
    • Wang, Jin
    • Zhi, Jin-Yi
    • Du, Yang
    • Xiang, Ze-Rui
    • Feng, Shu
    • Chen, Jian-Ping
  • Publication Date: 2021-3


  • English

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  • Accession Number: 01769459
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Feb 24 2021 3:01PM