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Customers perspectives on adoption of cloud computing in banking sector

Author

Listed:
  • Shahla Asadi

    (Universiti Teknologi Malaysia)

  • Mehrbakhsh Nilashi

    (Universiti Teknologi Malaysia
    Islamic Azad University)

  • Abd Razak Che Husin

    (Universiti Teknologi Malaysia)

  • Elaheh Yadegaridehkordi

    (Universiti Teknologi Malaysia)

Abstract

The advent of cloud computing has transformed the role of the Internet in many businesses and organizations. Currently, banks are increasingly adopting cloud technologies to fulfil their varied purposes and to create a flexible and agile banking environment that can quickly respond to new business needs. However, past studies tend to focus more on the adoption issues of cloud computing from the organizational perspective with little attention paid on the users’ view of these cloud-based services. Therefore, this paper attempts to investigate the factors influencing cloud computing adoption in the banking sector from the customers’ perspective and to propose an adoption model for this purpose. The model is mainly developed based on the TAM-diffusion theory model (TAM-DTM) with the introduction of three new constructs namely trust, cost, and security and privacy. Questionnaires were randomly distributed to 162 bank customers in Malaysia. Survey data were analyzed using the partial least squares (PLS) method while SmartPLS was used to test the hypotheses and to validate the proposed model. The results suggest that trust, cost, and security and privacy can be successfully integrated within the TAM-TDM. The security and privacy constructs exhibited strong positive influence on perceived ease of use, perceived usefulness, and trust. The study concludes that perceived usefulness, perceived ease of use, cost, attitudes toward cloud and trust significantly influence users’ behavioral intention to adopt cloud computing. Thus, the finding of this study will enable banks to focus more on customer perspectives on cloud-based applications and identify their attitude towards their adoption.

Suggested Citation

  • Shahla Asadi & Mehrbakhsh Nilashi & Abd Razak Che Husin & Elaheh Yadegaridehkordi, 0. "Customers perspectives on adoption of cloud computing in banking sector," Information Technology and Management, Springer, vol. 0, pages 1-26.
    • Handle: RePEc:spr:infotm:v::y::i::d:10.1007_s10799-016-0270-8
    DOI: 10.1007/s10799-016-0270-8
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    References listed on IDEAS

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    Cited by:

    1. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2021. "Predicting diffusion dynamics and launch time strategy for mobile telecommunication services: an empirical analysis," Information Technology and Management, Springer, vol. 22(1), pages 33-51, March.
    2. Yadegaridehkordi, Elaheh & Hourmand, Mehdi & Nilashi, Mehrbakhsh & Shuib, Liyana & Ahani, Ali & Ibrahim, Othman, 2018. "Influence of big data adoption on manufacturing companies' performance: An integrated DEMATEL-ANFIS approach," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 199-210.
    3. Abumalloh, Rabab Ali & Asadi, Shahla & Nilashi, Mehrbakhsh & Minaei-Bidgoli, Behrouz & Nayer, Fatima Khan & Samad, Sarminah & Mohd, Saidatulakmal & Ibrahim, Othman, 2021. "The impact of coronavirus pandemic (COVID-19) on education: The role of virtual and remote laboratories in education," Technology in Society, Elsevier, vol. 67(C).
    4. Elaheh Yadegaridehkordi & Mehrbakhsh Nilashi & Liyana Shuib & Shahla Asadi & Othman Ibrahim, 2019. "Development of a SaaS Adoption Decision-Making Model Using a New Hybrid MCDM Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(06), pages 1845-1874, November.
    5. Santiago Carbo-Valverde & Pedro Cuadros-Solas & Francisco Rodríguez-Fernández, 2020. "A machine learning approach to the digitalization of bank customers: Evidence from random and causal forests," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-39, October.

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