IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v21y2019i4d10.1007_s10796-017-9775-x.html

Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling

Author

Listed:
  • Sujeet Kumar Sharma

    (Sultan Qaboos University)

Abstract

Higher penetration of smartphones and 3G and 4G mobile networks have led to the higher usage of smartphones for mobile banking activities. This paper identifies key antecedents influencing the mobile banking acceptance. The research extends the original Technology Acceptance Model, by incorporating two cognitive antecedents, namely, autonomous motivation and controlled motivation, in addition to trust components for understanding adoption. Data were collected from 225 mobile banking users and analyzed using an innovative two-stage research methodology. In the first stage, structural equation modeling was employed to test the research hypotheses and identify significant antecedents influencing mobile banking acceptance. In the second stage, the significant antecedents obtained from the first stage were input to a neural network model for ranking. The results showed that trust and autonomous motivation are the two main predictors influencing mobile banking acceptance. Theoretical and practical implications of findings are discussed.

Suggested Citation

  • Sujeet Kumar Sharma, 2019. "Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling," Information Systems Frontiers, Springer, vol. 21(4), pages 815-827, August.
    • Handle: RePEc:spr:infosf:v:21:y:2019:i:4:d:10.1007_s10796-017-9775-x
    DOI: 10.1007/s10796-017-9775-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-017-9775-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-017-9775-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Yee-Loong Chong, Alain & Liu, Martin J. & Luo, Jun & Keng-Boon, Ooi, 2015. "Predicting RFID adoption in healthcare supply chain from the perspectives of users," International Journal of Production Economics, Elsevier, vol. 159(C), pages 66-75.
    2. Yvonne O’ Connor & Philip O’ Reilly, 0. "Examining the infusion of mobile technology by healthcare practitioners in a hospital setting," Information Systems Frontiers, Springer, vol. 0, pages 1-21.
    3. 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.
    4. Kawaljeet Kaur Kapoor & Yogesh K. Dwivedi & Michael D. Williams, 2015. "Examining the role of three sets of innovation attributes for determining adoption of the interbank mobile payment service," Information Systems Frontiers, Springer, vol. 17(5), pages 1039-1056, October.
    5. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    6. Jessie De Naeghel & Hilde Van Keer & Maarten Vansteenkiste & Leen Haerens & Nathalie Aelterman, 2016. "Promoting elementary school students' autonomous reading motivation: Effects of a teacher professional development workshop," The Journal of Educational Research, Taylor & Francis Journals, vol. 109(3), pages 232-252, May.
    Full references (including those not matched with items on IDEAS)

    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. Yu-Sheng Kao & Kazumitsu Nawata & Chi-Yo Huang, 2019. "An Exploration and Confirmation of the Factors Influencing Adoption of IoT-Based Wearable Fitness Trackers," IJERPH, MDPI, vol. 16(18), pages 1-31, September.
    2. Shaik, Aqueeb Sohail & Nazrul, Asif & Alshibani, Safiya Mukhtar & Agarwal, Vaishali & Papa, Armando, 2024. "Environmental and economical sustainability and stakeholder satisfaction in SMEs. Critical technological success factors of big data analytics," Technological Forecasting and Social Change, Elsevier, vol. 204(C).
    3. Zhunzhun Liu & Shenglin Ben & Ruidong Zhang, 2019. "Factors affecting consumers’ mobile payment behavior: a meta-analysis," Electronic Commerce Research, Springer, vol. 19(3), pages 575-601, September.
    4. Liébana-Cabanillas, Francisco & Marinkovic, Veljko & Ramos de Luna, Iviane & Kalinic, Zoran, 2018. "Predicting the determinants of mobile payment acceptance: A hybrid SEM-neural network approach," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 117-130.
    5. James Agyei & Shaorong Sun & Eugene Abrokwah & Emmanuel Kofi Penney & Richmond Ofori-Boafo, 2020. "Mobile Banking Adoption: Examining the Role of Personality Traits," SAGE Open, , vol. 10(2), pages 21582440209, June.
    6. Nripendra P. Rana & Yogesh K. Dwivedi & Banita Lal & Michael D. Williams & Marc Clement, 2017. "Citizens’ adoption of an electronic government system: towards a unified view," Information Systems Frontiers, Springer, vol. 19(3), pages 549-568, June.
    7. Nripendra P. Rana & Yogesh K. Dwivedi & Banita Lal & Michael D. Williams & Marc Clement, 0. "Citizens’ adoption of an electronic government system: towards a unified view," Information Systems Frontiers, Springer, vol. 0, pages 1-20.
    8. Komlan Gbongli & Yongan Xu & Komi Mawugbe Amedjonekou, 2019. "Extended Technology Acceptance Model to Predict Mobile-Based Money Acceptance and Sustainability: A Multi-Analytical Structural Equation Modeling and Neural Network Approach," Sustainability, MDPI, vol. 11(13), pages 1-33, July.
    9. Rajak, Manindra & Shaw, Krishnendu, 2021. "An extension of technology acceptance model for mHealth user adoption," Technology in Society, Elsevier, vol. 67(C).
    10. Marjan Shamsi & Tatiana Iakovleva & Espen Olsen & Richard P. Bagozzi, 2021. "Employees’ Work-Related Well-Being during COVID-19 Pandemic: An Integrated Perspective of Technology Acceptance Model and JD-R Theory," IJERPH, MDPI, vol. 18(22), pages 1-22, November.
    11. Philippe Cohard, 2020. "Information Systems Values: A Study of the Intranet in Three French Higher Education Institutions," Post-Print hal-02987225, HAL.
    12. Zhixin Liu, 2025. "The Impact of User Experience on Continuous Usage Intention for AI-Generated Digital Music Platforms: Examining the Mediating Roles of Emotional Attachment and Technology Self-Efficacy," SAGE Open, , vol. 15(4), pages 21582440251, December.
    13. Casaló, Luis V. & Flavián, Carlos & Guinalíu, Miguel, 2010. "Determinants of the intention to participate in firm-hosted online travel communities and effects on consumer behavioral intentions," Tourism Management, Elsevier, vol. 31(6), pages 898-911.
    14. Dahlberg, Tomi & Öörni, Anssi, 2006. "Finnish consumers' expectations on developments and changes in payment habits: survey in connection with the research project "Finnish payment habits 2010"," Bank of Finland Research Discussion Papers 32/2006, Bank of Finland.
    15. Melih Engin & Fatih Gürses, 2019. "Adoption of Hospital Information Systems in Public Hospitals in Turkey: An Analysis with the Unified Theory of Acceptance and Use of Technology Model," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(06), pages 1-19, October.
    16. Hasan, Rajibul & Lowe, Ben & Petrovici, Dan, 2020. "Consumer adoption of pro-poor service innovations in subsistence marketplaces," Journal of Business Research, Elsevier, vol. 121(C), pages 461-475.
    17. Morosan, Cristian, 2016. "An empirical examination of U.S. travelers’ intentions to use biometric e-gates in airports," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 120-128.
    18. Tsung Teng Chen, 2012. "The development and empirical study of a literature review aiding system," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(1), pages 105-116, July.
    19. Abdesamad Zouine & Pierre Féniès, 2014. "The Critical Success Factors Of The ERP System Project: A Meta-Analysis Methodology," Post-Print hal-01419785, HAL.
    20. Debora Bettiga & Lucio Lamberti & Emanuele Lettieri, 2020. "Individuals’ adoption of smart technologies for preventive health care: a structural equation modeling approach," Health Care Management Science, Springer, vol. 23(2), pages 203-214, June.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:infosf:v:21:y:2019:i:4:d:10.1007_s10796-017-9775-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.