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Airport Self-Service Technologies, Passenger Self-Concept, and Behavior: An Attributional View

Author

Listed:
  • Collins Opoku Antwi

    (Department of Psychology, Zhejiang Normal University, Jinhua 321004, China)

  • Jun Ren

    (Department of Psychology, Zhejiang Normal University, Jinhua 321004, China)

  • Wilberforce Owusu-Ansah

    (Business School, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi AK-039, Ghana)

  • Henry Kofi Mensah

    (Business School, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi AK-039, Ghana)

  • Michael Osei Aboagye

    (Department of Interdisciplinary Studies (DIS), Appiah-Minka University of Skills Training and Entrepreneurial Development, Kumasi AK-039, Ghana)

Abstract

Airports are rapidly deploying self-service technologies (SSTs) as a strategy to improve passenger experience by eliminating operational inefficiencies. This places some responsibility on the passengers to shape their experience. As service coproducers, passengers’ self-concepts and attributional tendencies are deemed instrumental in their consumption processes. Accordingly, drawing on the tenets of attribution theory, this study explores the interaction effects of passenger self-concept (am I competent at this?) and causal inference (who is responsible for SSTs’ performance?) on SST performance and satisfaction with airport SST link. Additionally, the probable spillover effect of passenger satisfaction with SST performance on satisfaction with airport and on electronic word-of-mouth (eWOM) is examined. The sample for the study consisted of 547 passengers departing from an airport in Shanghai, China. Structural equation modeling was utilized to test the study’s theoretical model. The findings indicate that airport SSTs’ performance influences passenger satisfaction with airport SSTs. The multiplicative effect of passenger self-concept (am I competent at this?) in the moderating role of passenger causal inference (who is responsible for SSTs’ performance?) in SST performance and satisfaction with SST link is demonstrated. Furthermore, the spillover effect of satisfaction with SST performance on satisfaction with airport and on electronic word-of-mouth (eWOM) is illustrated. Given the current need for contactlessness, the findings proffer critical managerial and research insights.

Suggested Citation

  • Collins Opoku Antwi & Jun Ren & Wilberforce Owusu-Ansah & Henry Kofi Mensah & Michael Osei Aboagye, 2021. "Airport Self-Service Technologies, Passenger Self-Concept, and Behavior: An Attributional View," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3134-:d:516115
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    References listed on IDEAS

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    2. Ki-Han Song & Solsaem Choi, 2021. "A Study on the Perception Change of Passengers on Sustainable Air Transport Following COVID-19 Progress," Sustainability, MDPI, vol. 13(14), pages 1-13, July.
    3. Xiaoqian Sun & Sebastian Wandelt, 2021. "Robustness of Air Transportation as Complex Networks:Systematic Review of 15 Years of Research and Outlook into the Future," Sustainability, MDPI, vol. 13(11), pages 1-19, June.
    4. Ampadu, Seth & Jiang, Yuanchun & Debrah, Emmanuel & Antwi, Collins Opoku & Amankwa, Eric & Gyamfi, Samuel Adu & Amoako, Richard, 2022. "Online personalized recommended product quality and e-impulse buying: A conditional mediation analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    5. Gajewicz, Šukasz & Walaszczyk, Ewa & Nadolny, Michał & Nowosielski, Krzysztof, 2022. "Criteria of quality assessment of regional airport services - A very last picture before the COVID-19 pandemic," Journal of Air Transport Management, Elsevier, vol. 103(C).
    6. Bakır, Mahmut & Özdemir, Emircan & Akan, Şahap & Atalık, Özlem, 2022. "A bibliometric analysis of airport service quality," Journal of Air Transport Management, Elsevier, vol. 104(C).
    7. Jiang, Yirui & Tran, Trung Hieu & Williams, Leon, 2023. "Machine learning and mixed reality for smart aviation: Applications and challenges," Journal of Air Transport Management, Elsevier, vol. 111(C).

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