IDEAS home Printed from https://ideas.repec.org/a/gam/jijfss/v10y2022i4p90-d930808.html

Examining the Factors Affecting the Adoption of Blockchain Technology in the Banking Sector: An Extended UTAUT Model

Author

Listed:
  • Rabindra Kumar Jena

    (Institute of Management Technology, Nagpur 440013, India)

Abstract

Technology innovation has dramatically transformed banks over time. Digital innovation in the banking sector began with the introduction of money to replace barter systems, and then gradually replaced wax seals with digital signatures. One such disruptive innovation that is transforming the banking sector around the world is blockchain technology (BCT). The banking sector in India has also started adopting blockchain technology in various financial transactions. However, they are encountering some difficulties in adapting to and implementing this new technology. The successful and speedy adoption of blockchain in banking largely depends on the users’ intention to use the services. Therefore, this study extended “the unified theory of acceptance and use of technology” (UTAUT) to understand the significant predictors of the bankers’ intention to use blockchain technology. The data was collected from leading banking institutions and FinTech firms in the country to empirically test and validate the extended model. The results found that facilitating conditions, performance expectancy, and initial trust, are the significant antecedents to predicting the bankers’ intention to use blockchain in banking transactions. The study also established the significant mediating role of initial trust in predicting usage intention to use blockchain. This study’s results would help government authorities, decision-makers, and technocrats to improve banking instructions for the speedy and smooth adoption of blockchain technology. The study suggested an extended UTAUT model that incorporates contextual factors based on the scope and usage of blockchain in Indian banking activities. The study helped to identify the key factors influencing blockchain adoption among Indian bankers. The proposed model and the findings make more sense in promoting the adoption of blockchain in the Indian banking sector.

Suggested Citation

  • Rabindra Kumar Jena, 2022. "Examining the Factors Affecting the Adoption of Blockchain Technology in the Banking Sector: An Extended UTAUT Model," IJFS, MDPI, vol. 10(4), pages 1-20, September.
    • Handle: RePEc:gam:jijfss:v:10:y:2022:i:4:p:90-:d:930808
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7072/10/4/90/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7072/10/4/90/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fatemeh “Mariam” Zahedi & Jaeki Song & Suprasith Jarupathirun, 2008. "Web-Based Decision Support," International Handbooks on Information Systems, in: Handbook on Decision Support Systems 1, chapter 16, pages 315-338, Springer.
    2. Sanghyun Kim & Gary Garrison, 2009. "Investigating mobile wireless technology adoption: An extension of the technology acceptance model," Information Systems Frontiers, Springer, vol. 11(3), pages 323-333, July.
    3. Studener, Werner & Merriman, Niall & Karakitsos, Polychronis & Bunea, Daniela, 2016. "Profit distribution and loss coverage rules for central banks," Occasional Paper Series 169, European Central Bank.
    4. Heidari, Hamed & Mousakhani, Morteza & Alborzi, Mahmood & Divandari, Ali & Radfar, Reza, 2019. "Explaining the Blockchain Acceptance Indices in Iran Financial Markets: A Fuzzy Delphi Study," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 14(3), pages 335-365, July.
    5. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    6. Gupta, Somya & Ghardallou, Wafa & Pandey, Dharen Kumar & Sahu, Ganesh P., 2022. "Artificial intelligence adoption in the insurance industry: Evidence using the technology–organization–environment framework," Research in International Business and Finance, Elsevier, vol. 63(C).
    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. Minu Gupta & Ravi Kiran, 2024. "Sectoral Comparison of Sustainable Digital Financial Inclusion of Women Workforce with the Mediation of Digital Banking Adoption Intention: An Empirical Analysis," SAGE Open, , vol. 14(2), pages 21582440241, June.
    2. Meennapa Rukhiran & Napasorn Phaokla & Paniti Netinant, 2022. "Adoption of Environmental Information Chatbot Services Based on the Internet of Educational Things in Smart Schools: Structural Equation Modeling Approach," Sustainability, MDPI, vol. 14(23), pages 1-32, November.
    3. Sujata Seshadrinathan & Shalini Chandra, 2025. "Trusting the trustless blockchain for its adoption in accounting: theorizing the mediating role of technology-organization-environment framework," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-39, December.
    4. Ammar AL-Ashmori & Gunasekar Thangarasu & P. D. D. Dominic & Al-Baraa Abdulrahman Al-Mekhlafi, 2023. "A Readiness Model and Factors Influencing Blockchain Adoption in Malaysia’s Software Sector: A Survey Study," Sustainability, MDPI, vol. 15(16), pages 1-28, August.
    5. Francisco Liébana-Cabanillas & Ana Irimia-Diéguez & Gema Albort-Morant & Carmen Zarco, 2026. "Unlocking the future of paytech: exploring biometric payment card adoption patterns," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 12(1), pages 1-34, December.

    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. Leon Oldemeyer & Andreas Jede & Frank Teuteberg, 2025. "Influence of company size and AI implementation challenges in manufacturing companies," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 15(1), pages 1-24, December.
    2. Zhang, Xi-xi & Hao, Xing-lin, 2025. "Linkage mechanism of antecedents for employees' continuous adoption of artificial intelligence virtual assistants," Technological Forecasting and Social Change, Elsevier, vol. 220(C).
    3. Yoon, Junghyun & Lee, Hee Yong & Dinwoodie, John, 2015. "Competitiveness of container terminal operating companies in South Korea and the industry–university–government network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 1-14.
    4. Sousa, Carlos M.P. & Bradley, Frank, 2008. "Antecedents of international pricing adaptation and export performance," Journal of World Business, Elsevier, vol. 43(3), pages 307-320, July.
    5. Son K. Lam & Thomas E. DeCarlo & Ashish Sharma, 2019. "Salesperson ambidexterity in customer engagement: do customer base characteristics matter?," Journal of the Academy of Marketing Science, Springer, vol. 47(4), pages 659-680, July.
    6. Van Wijk, Raymond & Nadolska, Anna, 2020. "Making more of alliance portfolios: The role of alliance portfolio coordination," European Management Journal, Elsevier, vol. 38(3), pages 388-399.
    7. Jarle Aarstad & Olav Andreas Kvitastein & Stig-Erik Jakobsen, 2019. "What Drives Enterprise Product Innovation? Assessing How Regional, National, And International Inter-Firm Collaboration Complement Or Substitute For R&D Investments," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 23(05), pages 1-25, June.
    8. Aziz Barhmi & Omar Hajaji, 2023. "Multidisciplinary Approach to Supply Chain Resilience: Conceptualization and Scale Development," Central European Business Review, Prague University of Economics and Business, vol. 2023(5), pages 43-69.
    9. Chin-Shan Lu & Kuo-Chung Shang & Chi-Chang Lin, 2016. "Examining sustainability performance at ports: port managers’ perspectives on developing sustainable supply chains," Maritime Policy & Management, Taylor & Francis Journals, vol. 43(8), pages 909-927, November.
    10. Rehman, Anisur & Behera, Rajat Kumar & Islam, Md Saiful & Elahi, Yasir Arafat & Abbasi, Faraz Ahmad & Imtiaz, Asma, 2024. "Drivers of metaverse adoption for enhancing marketing capabilities of retail SMEs," Technology in Society, Elsevier, vol. 79(C).
    11. Van Gils, Anita & Huybrechts, Jolien & Minola, Tommaso & Cassia, Lucio, 2019. "Unraveling the impact of family antecedents on family firm image: A serial multiple-mediation model," Journal of Family Business Strategy, Elsevier, vol. 10(1), pages 17-27.
    12. Na Yu & Xiaolei Liu, 2024. "Online Dance Learning Satisfaction After the Pandemic: Lessons From the Crisis," SAGE Open, , vol. 14(1), pages 21582440241, January.
    13. Julia Eichholz & Thorsten Knauer & Sandra Winkelmann, 2023. "Digital Maturity of Forecasting and its Impact in Times of Crisis," Schmalenbach Journal of Business Research, Springer, vol. 75(4), pages 443-481, December.
    14. Mei, Maggie Qiuzhu & Wang, Le & Yan, Jie, 2023. "Maintaining product quality consistency when offshoring to emerging markets: The role of subsidiary control," Journal of International Management, Elsevier, vol. 29(1).
    15. Thomas, Rhodri & Wood, Emma, 2015. "The absorptive capacity of tourism organisations," Annals of Tourism Research, Elsevier, vol. 54(C), pages 84-99.
    16. Dominik M. Wielgos & Christian Homburg & Christina Kuehnl, 2021. "Digital business capability: its impact on firm and customer performance," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 762-789, July.
    17. Schneider, Christian O. & Bremen, Philipp & Schönsleben, Paul & Alard, Robert, 2013. "Transaction cost economics in global sourcing: Assessing regional differences and implications for performance," International Journal of Production Economics, Elsevier, vol. 141(1), pages 243-254.
    18. Chih-Ting Shih & Cheng-Chen Lin, 2014. "From good friends to good soldiers: A psychological contract perspective," Asia Pacific Journal of Management, Springer, vol. 31(1), pages 309-326, March.
    19. Sikandar Ali Qalati & Dragana Ostic & Gu Shuibin & Fan Mingyue, 2022. "A mediated–moderated model for social media adoption and small and medium‐sized enterprise performance in emerging countries," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(3), pages 846-861, April.
    20. Deeksha Singh & Sambashiva Rao Kunja, 2026. "Escaping the reality with humanized brands: Examining the role of anthropomorphized brands in fostering continued engagement," Electronic Commerce Research, Springer, vol. 26(2), pages 1071-1090, April.

    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:gam:jijfss:v:10:y:2022:i:4:p:90-:d:930808. 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.