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Investigation of the Effects of Task Technology Fit, Attitude and Trust on Intention to Adopt Mobile Banking: Placing the Mediating Role of Trialability

Author

Listed:
  • Gao Changchun
  • Muhammad Jamal Haider
  • Tayyaba Akram

Abstract

The purpose of this study was to investigate the proposed model in which effect of trust, attitude and task technology fit are taken as independent variables and intention to m-banking adoption as dependent variable. The study also analyzes the mediating role of trialability between the independent and dependent variables. To find out how much variance each of the independent variables contribute in dependent variable, Structural equation modeling (SEM) approach is applied on the data sample of 271 respondents from Pakistan. The confirmatory factor analysis (CFA) suggested a good model fit. The results from SEM analysis revealed a model R-square of 0.55. It suggested the significant effect of attitude and task technology fit on intention to adopt m-banking. The analysis further explained the presence of mediating role of trialability between the relationship of intention to adopt m-banking and trust, attitude and task technology fit. The study also provides implications, limitations and future research suggestions.

Suggested Citation

  • Gao Changchun & Muhammad Jamal Haider & Tayyaba Akram, 2017. "Investigation of the Effects of Task Technology Fit, Attitude and Trust on Intention to Adopt Mobile Banking: Placing the Mediating Role of Trialability," International Business Research, Canadian Center of Science and Education, vol. 10(4), pages 77-91, April.
  • Handle: RePEc:ibn:ibrjnl:v:10:y:2017:i:4:p:77-91
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    References listed on IDEAS

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    1. Editors, 2014. "International Journal of Systems Science," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(12), pages 1-1, December.
    2. Dale L. Goodhue, 1995. "Understanding User Evaluations of Information Systems," Management Science, INFORMS, vol. 41(12), pages 1827-1844, December.
    3. Bagozzi, Richard P & Yi, Youjae, 1991. "Multitrait-Multimethod Matrices in Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 17(4), pages 426-439, March.
    4. World Bank, 2016. "Pakistan Development Update, November 2016," World Bank Publications - Reports 25358, The World Bank Group.
    5. Stephen W. Wang & Waros Ngamsiriudom & Chia-Hung Hsieh, 2015. "Trust disposition, trust antecedents, trust, and behavioral intention," The Service Industries Journal, Taylor & Francis Journals, vol. 35(10), pages 555-572, July.
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    Cited by:

    1. Frederick Pobee, 2022. "Non-Probabilistic Approach to e-Banking Adoption: The Moderating Impact of Trialability," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 47(2), pages 183-198, May.
    2. Yaser Hasan Al-Mamary & Adel Abdulmohsen Alfalah & Mohammad Mulayh Alshammari & Aliyu Alhaji Abubakar, 2024. "Exploring factors influencing university students’ intentions to use ChatGPT: analysing task-technology fit theory to enhance behavioural intentions in higher education," Future Business Journal, Springer, vol. 10(1), pages 1-17, December.

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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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