IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i15p8997-d869033.html
   My bibliography  Save this article

Understanding Consumer Buying Intention of E-Commerce Airfares Based on Multivariate Demographic Segmentation: A Multigroup Structural Equation Modeling Approach

Author

Listed:
  • Phaninee Naruetharadhol

    (International College, Khon Kaen University, Khon Kaen 40002, Thailand
    Center for Sustainable Innovation and Society, Khon Kaen University, Khon Kaen 40002, Thailand)

  • Sasichakorn Wongsaichia

    (International College, Khon Kaen University, Khon Kaen 40002, Thailand
    Center for Sustainable Innovation and Society, Khon Kaen University, Khon Kaen 40002, Thailand)

  • Shenying Zhang

    (International College, Khon Kaen University, Khon Kaen 40002, Thailand
    Center for Sustainable Innovation and Society, Khon Kaen University, Khon Kaen 40002, Thailand)

  • Chanchai Phonthanukitithaworn

    (Business Administration Division, Mahidol University International College, Mahidol University, Nakhon Pathom 73170, Thailand)

  • Chavis Ketkaew

    (International College, Khon Kaen University, Khon Kaen 40002, Thailand
    Center for Sustainable Innovation and Society, Khon Kaen University, Khon Kaen 40002, Thailand)

Abstract

The internet offers enormous development opportunities for airline firms and a lot of information for consumers to pick the finest available options. This research aims to study the consumer buying intention of e-commerce airfares in an emerging economy based on the technology acceptance model. This article employed a sample of 3064 respondents at six airports in Thailand. It used cluster analysis (a multivariate analysis approach) to determine two main customer segments and then used a structural equation modeling (SEM) technique utilizing demographic segmentation as a moderator to explain the behaviors of those two segments. The findings demonstrated two customer segments: (1) the older with high and middle-income segment, and (2) the young with low-income segment. The empirical results revealed that price sensitivity and perceived ease of use substantially impacted behavioral intention to use e-commerce airfares in both segments. The users from segment (1) are more likely to look for the fun experience and entertainment value of using e-commerce airfares than those from segment (2). However, perceived usefulness is unlikely to be a vital factor in consumers’ purchasing decisions about using e-commerce airfares. It is recommended that airline companies and online travel agencies should consider perceived ease of use, price sensitivity, and hedonic motivation when implementing e-commerce airline websites for selling tickets.

Suggested Citation

  • Phaninee Naruetharadhol & Sasichakorn Wongsaichia & Shenying Zhang & Chanchai Phonthanukitithaworn & Chavis Ketkaew, 2022. "Understanding Consumer Buying Intention of E-Commerce Airfares Based on Multivariate Demographic Segmentation: A Multigroup Structural Equation Modeling Approach," Sustainability, MDPI, vol. 14(15), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:8997-:d:869033
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/15/8997/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/15/8997/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yu, Shu-Fen, 2008. "Price perception of online airline ticket shoppers," Journal of Air Transport Management, Elsevier, vol. 14(2), pages 66-69.
    2. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    3. Kai-Ying Chen & Meng-Lin Chang, 2013. "User acceptance of ‘near field communication’ mobile phone service: an investigation based on the ‘unified theory of acceptance and use of technology’ model," The Service Industries Journal, Taylor & Francis Journals, vol. 33(6), pages 609-623, May.
    4. Moser, Andrea K., 2016. "Consumers' purchasing decisions regarding environmentally friendly products: An empirical analysis of German consumers," Journal of Retailing and Consumer Services, Elsevier, vol. 31(C), pages 389-397.
    5. Natarajan, Thamaraiselvan & Balasubramanian, Senthil Arasu & Kasilingam, Dharun Lingam, 2017. "Understanding the intention to use mobile shopping applications and its influence on price sensitivity," Journal of Retailing and Consumer Services, Elsevier, vol. 37(C), pages 8-22.
    6. Chanchai Phonthanukitithaworn & Phaninee Naruetharadhol & Nathatenee Gebsombut & Raoyrin Chanavirut & Wanwipada Onsa-ard & Pawanrut Joomwanta & Zou Chanyuan & Chavis Ketkaew, 2020. "An Investigation of the Relationship Among Medical Center’s Image, Service Quality, and Patient Loyalty," SAGE Open, , vol. 10(4), pages 21582440209, December.
    7. Chanchai Phonthanukitithaworn & Carmine Sellitto & Michelle W. L. Fong, 2016. "A Comparative Study of Current and Potential Users of Mobile Payment Services," SAGE Open, , vol. 6(4), pages 21582440166, November.
    8. Bilgihan, Anil & Barreda, Albert & Okumus, Fevzi & Nusair, Khaldoon, 2016. "Consumer perception of knowledge-sharing in travel-related Online Social Networks," Tourism Management, Elsevier, vol. 52(C), pages 287-296.
    9. Phaninee Naruetharadhol & Chavis Ketkaew & Niracha Hongkanchanapong & Piranat Thaniswannasri & Techin Uengkusolmongkol & Sirapassorn Prasomthong & Nathatenee Gebsombut, 2021. "Factors Affecting Sustainable Intention to Use Mobile Banking Services," SAGE Open, , vol. 11(3), pages 21582440211, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Teerapong Pienwisetkaew & Peerapong Wongthahan & Phaninee Naruetharadhol & Sasichakorn Wongsaichia & Chonnipa Vonganunsuntree & Siraphat Padthar & Santi Nee & Ping He & Chavis Ketkaew, 2022. "Consumers’ Intention to Purchase Functional Non-Dairy Milk and Gender-Based Market Segmentation," Sustainability, MDPI, vol. 14(19), pages 1-25, September.
    2. Kalisri Logeswaran Aravindan & Thurasamy Ramayah & Munusamy Thavanethen & Murali Raman & Narinasamy Ilhavenil & Sanmugam Annamalah & Yap Voon Choong, 2023. "Modeling Positive Electronic Word of Mouth and Purchase Intention Using Theory of Consumption Value," Sustainability, MDPI, vol. 15(4), pages 1-19, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kalinic, Zoran & Marinkovic, Veljko & Molinillo, Sebastián & Liébana-Cabanillas, Francisco, 2019. "A multi-analytical approach to peer-to-peer mobile payment acceptance prediction," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 143-153.
    2. Garima Malik & A. Sajeevan Rao, 2019. "Extended expectation-confirmation model to predict continued usage of ODR/ride hailing apps: role of perceived value and self-efficacy," Information Technology & Tourism, Springer, vol. 21(4), pages 461-482, December.
    3. Sohn, Stefanie, 2017. "A contextual perspective on consumers' perceived usefulness: The case of mobile online shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 38(C), pages 22-33.
    4. Zhang, Wenqing & Liu, Liangliang, 2022. "Exploring non-users' intention to adopt ride-sharing services: Taking into account increased risks due to the COVID-19 pandemic among other factors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 180-195.
    5. Gabriel JIPA, 2018. "Mobile Applications Buying Opinions Exploration using Topic Modeling," Expert Journal of Economics, Sprint Investify, vol. 6(2), pages 44-55.
    6. Su-Chen(Cecilia) Lin & Mei-Chen Chuang & Chen-Yuan Huang & Chia-En Liu, 2023. "Nursing Staff’s Behavior Intention to Use Mobile Technology: An Exploratory Study Employing the UTAUT 2 Model," SAGE Open, , vol. 13(4), pages 21582440231, November.
    7. Christino, Juliana Maria Magalhães & Silva, Thaís Santos & Cardozo, Erico Aurélio Abreu & de Pádua Carrieri, Alexandre & de Paiva Nunes, Patricia, 2019. "Understanding affiliation to cashback programs: An emerging technique in an emerging country," Journal of Retailing and Consumer Services, Elsevier, vol. 47(C), pages 78-86.
    8. Brusch, Ines & Rappel, Nina, 2020. "Exploring the acceptance of instant shopping – An empirical analysis of the determinants of user intention," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    9. Mohammad Tipu Sultan & Farzana Sharmin & Alina Badulescu & Darie Gavrilut & Ke Xue, 2021. "Social Media-Based Content towards Image Formation: A New Approach to the Selection of Sustainable Destinations," Sustainability, MDPI, vol. 13(8), pages 1-22, April.
    10. Kala Kamdjoug, Jean Robert & Wamba-Taguimdje, Serge-Lopez & Wamba, Samuel Fosso & Kake, Ingrid Bive'e, 2021. "Determining factors and impacts of the intention to adopt mobile banking app in Cameroon: Case of SARA by afriland First Bank," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    11. Lara Stocchi & Naser Pourazad & Nina Michaelidou & Arry Tanusondjaja & Paul Harrigan, 2022. "Marketing research on Mobile apps: past, present and future," Journal of the Academy of Marketing Science, Springer, vol. 50(2), pages 195-225, March.
    12. Miluska Murillo-Zegarra & Carla Ruiz-Mafe & Silvia Sanz-Blas, 2020. "The Effects of Mobile Advertising Alerts and Perceived Value on Continuance Intention for Branded Mobile Apps," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
    13. Natarajan, Thamaraiselvan & Balasubramanian, Senthil Arasu & Kasilingam, Dharun Lingam, 2018. "The moderating role of device type and age of users on the intention to use mobile shopping applications," Technology in Society, Elsevier, vol. 53(C), pages 79-90.
    14. Francisco Liébana-Cabanillas & Francisco Muñoz-Leiva & Sebastián Molinillo & Elena Higueras-Castillo, 2022. "Do biometric payment systems work during the COVID-19 pandemic? Insights from the Spanish users' viewpoint," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    15. Perengki Susanto & Mohammad Enamul Hoque & Verselly Nisaa & Md Asadul Islam & Yusniza Kamarulzaman, 2023. "Predicting m-Commerce Continuance Intention and Price Sensitivity in Indonesia by Integrating of Expectation-Confirmation and Post-acceptance Model," SAGE Open, , vol. 13(3), pages 21582440231, July.
    16. Luceri, Beatrice & (Tammo) Bijmolt, T.H.A. & Bellini, Silvia & Aiolfi, Simone, 2022. "What drives consumers to shop on mobile devices? Insights from a Meta-Analysis," Journal of Retailing, Elsevier, vol. 98(1), pages 178-196.
    17. Giang-Do Nguyen & Thu-Hien Thi Dao, 2024. "Factors influencing continuance intention to use mobile banking: an extended expectation-confirmation model with moderating role of trust," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    18. Krishna Moorthy & Loh Chun T'ing & Kwong Chea Yee & Ang Wen Huey & Lee Joe In & Poon Chyi Feng & Tan Jia Yi, 2020. "What drives the adoption of mobile payment? A Malaysian perspective," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 349-364, July.
    19. Nicky Terblanche & Martin Kidd, 2022. "Adoption Factors and Moderating Effects of Age and Gender That Influence the Intention to Use a Non-Directive Reflective Coaching Chatbot," SAGE Open, , vol. 12(2), pages 21582440221, May.
    20. Hartoyo & Fermico Karambut & Rita Nurmalina & Mukhamad Najib, 2019. "The Intention in Online Submission of Micro Credit," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 186-200.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:8997-:d:869033. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.