THE IMPACT OF INTERNET OF THINGS (LOT) ON OPERATIONAL EFFICIENCY OF COMMERCIAL BANKS: PERCEIVED USEFULNESS AND EASE OF USE AS MEDIATORS

Authors

  • Alfred Akakpo University of Northampton, Waterside Campus, University Dr, Northampton NN1 5PH, United Kingdom
  • Foyeke Bukunola Ekpo-Aniefiok University of Northampton, Waterside Campus, University Dr, Northampton NN1 5PH, United Kingdom
  • Xavier Matieni University of Northampton, Waterside Campus, University Dr, Northampton NN1 5PH, United Kingdom

DOI:

https://doi.org/10.11113/ijibs.v21.204

Keywords:

Internet of things, Operational efficiency, Perceived Usefulness, Banking Employees, Nigeria

Abstract

The advent of the Internet of Things (IoT) has sparked a technological revolution that is profoundly impacting numerous sectors, including banking. Despite this, there is limited studies on its application in commercial banks in Nigeria. This research is among the few to examine the impact of IoT adoption and its challenges on business operational efficiency, with perceived usefulness and perceived ease of use of IoT as mediating factors. This study draws on the Technology Acceptance Model (TAM) and integrates challenges of IoT adoption into the TAM to examine the impact of IoT adoption on business operational efficiency. This paper utilised a purposive sampling method and collected 181 data from bank employees in Nigeria. The data was statistically analysed using Jamov/R Studio with the Lavaan package to test the hypotheses. The findings revealed a positive and significant relationship between perceived usefulness and IoT adoption, perceived ease of use and IoT adoption, and IoT adoption and operational efficiency, but showed an insignificant relationship between the challenges encountered and operational efficiency. The study concludes that the adoption of IoT has a significant impact on the operational efficiency in the banking sector. This study contributes to existing literature by offering a nuanced understanding of how IoT can catalyse operational efficiency within the commercial banking sector. The findings highlight the dual-pathway mediation of perceived usefulness and perceived ease of use of IoT adoption and efficiency hierarchy as its central theoretical contributions.

Author Biography

  • Foyeke Bukunola Ekpo-Aniefiok, University of Northampton, Waterside Campus, University Dr, Northampton NN1 5PH, United Kingdom

    University of Northampton

References

Abu-Dalbouh, H.M. (2013). ‘A Questionnaire Approach Based on the Technology Acceptance Model for Mobile Tracking on Patient Progress Applications’. Journal of Computer Science, [online] 9(6), pp.763–770. doi:https://doi.org/10.3844/jcssp.2013.763.770.

Adejuwon, K. D. (2018) Internet of Things and Smart City Development: Is Nigeria Leveraging on Emerging Technologies to Improve Efficiency in Public Service Delivery? Journal of Public Administration, Finance and Law. (13), 7–20.

Akrong, G. B., Shao, Y., & Owusu, E. (2022). Evaluation of the quality constructs of a tax management system based on DeLone and McLean IS success model. Africa Journal of Management, 9(1), 46–69. https://doi.org/10.1080/23322373.2022.2155116

Al-Emran, M. and Granić, A. (2021). Is It Still Valid or Outdated? A Bibliometric Analysis of the Technology Acceptance Model and Its Applications From 2010 to 2020. In: Al-Emran, M., Shaalan, K. (eds) Recent Advances in Technology Acceptance Models and Theories. Studies in Systems, Decision and Control, 335. Springer, Cham. https://doi.org/10.1007/978-3-030-64987-6_1

Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M. and Ayyash, M. (2015). ‘Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications’. IEEE Communications Surveys & Tutorials, 17(4), pp.2347–2376. https://doi.org/10.1109/comst.2015.2444095.

Alhasan, A., Hussein, M. H., Audah, L., Al-Sharaa, A., Ibrahim, I., & Mahmoud, M. A. (2023). A case study to examine undergraduate students’ intention to use internet of things (IoT) services in the smart classroom. Education and Information Technologies, 28(8), 10459–10482. https://doi.org/10.1007/s10639-022-11537-z

Al-Khatib, A.W. (2022). ‘Internet of things, big data analytics and operational performance: the mediating effect of supply chain visibility’. Journal of Manufacturing Technology Management. https://doi.org/10.1108/jmtm-08-2022-0310.

Almaiah, M.A., Alfaisal, R., Salloum, S.A., Al-Otaibi, S., Shishakly, R., Lutfi, A., Alrawad, M., Mulhem, A.A., Awad, A.B. and Al-Maroof, R.S. (2022). ‘Integrating Teachers’ TPACK Levels and Students’ Learning Motivation, Technology Innovativeness, and Optimism in an IoT Acceptance Model’. Electronics, 11(19), p.3197. https://doi.org/10.3390/electronics11193197.

Almazroi, A. A. (2023). An Empirical Investigation of Factors Influencing the Adoption of Internet of Things Services by End-Users. Arabian Journal for Science and Engineering (2011), 48(2), 1641–1659. https://doi.org/10.1007/s13369-022-06954-8

Ameer Alhasan, Hussein, M.H., Lukman Audah, Ammar Al-Sharaa, Ibrahim, I. and Mahmoud, M.A. (2023). ‘A case study to examine undergraduate students’ intention to use internet of things (IoT) services in the smart classroom’. Education and Information Technologies, 28(2), 10459–10482. https://doi.org/10.1007/s10639-022-11537-z.

Ammirato, S., Sofo, F., Felicetti, A.M. and Raso, C. (2019a). ‘A methodology to support the adoption of IoT innovation and its application to the Italian bank branch security context’. European Journal of Innovation Management, 22(1), pp.146–174. https://doi.org/10.1108/ejim-03-2018-0058.

Ammirato, S., Sofo, F., Felicetti, A.M. and Raso, C. (2019b), "The potential of IoT in redesigning the bank branch protection system: An Italian case study". Business Process Management Journal, 25 (7), pp. 1441-1473. https://doi.org/10.1108/BPMJ-04-2018-0099

Anderson, J.C. and Gerbing, D.W. (1988). ‘Structural equation modeling in practice: A review and recommended two-step approach’. Psychological Bulletin, 103(3), pp.411–423. https://doi.org/10.1037//0033-2909.103.3.411.

Arora, N. and Kaur, P.D. (2020). ‘Augmenting Banking and FinTech with Intelligent Internet of Things Technology’. 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). https://doi.org/10.1109/icrito48877.2020.9198018.

Bagozzi, R.P. and Yi, Y. (1988). ‘On the evaluation of structural equation models’. Journal of the Academy of Marketing Science, [online] 16(1), pp.74–94. https://doi.org/10.1007/bf02723327.

Baiyere, A., Salmela, H. and Tapanainen, T. (2020). ‘Digital transformation and the new logics of business process management’. European Journal of Information Systems, 29(3), pp.1–22. https://doi.org/10.1080/0960085X.2020.1718007

Bajaj, P., Anwar, I., Yahya, A.T. and Saleem, I. (2023). ‘Factors Influencing Adoption of IoT and Its Impact on CRM in Banks: Examining the Moderating Role of Gender, Age, and Bank Ownership Type’. Human Behaviour and Emerging technologies, pp.1–15. https://doi.org/10.1155/2023/5571508.

Balaji, S., Nathani, K. and Santhakumar, R. (2019). ‘IoT Technology, Applications and Challenges: A Contemporary Survey’. Wireless Personal Communications, 108(1), pp.363–388. doi:https://doi.org/10.1007/s11277-019-06407-w.

Beaujean, A. A. (2014). Latent Variable Modeling Using R. A Step-by-Step Guide. New York. Routledge. ISBN 9781848726994

Bojjagani, S., Rao, P.V.V., Vemula, D.R., Reddy, B.R. and Lakshmi, T.J. (2022). ‘A secure IoT-based micro-payment protocol for wearable devices’. Peer-to-Peer Networking and Applications, 15(2), pp.1163–1188. https://doi.org/10.1007/s12083-021-01242-y.

Bonett, D. G., & Wright, T. A. (2015). Cronbach's alpha reliability: Interval estimation, hypothesis testing, and sample size planning. Journal of organizational behavior, 36(1), 3-15. https://doi.org/10.1002/job.1960

Bothma, M. and Mostert, L. (2023). ‘Adopting the technology acceptance model: A Namibian perspective’. SA Journal of Information Management, 25(1). pp 1-10. https://doi.org/10.4102/sajim.v25i1.1624.

Botta, A., de Donato, W., Persico, V. and Pescapé, A. (2016). ‘Integration of Cloud computing and Internet of Things: A survey’. Future Generation Computer Systems, [online] 56, pp.684–700. https://doi.org/10.1016/j.future.2015.09.021.

Byrne, B.M. (2016). ‘Structural equation modeling with Amos : basic concepts, applications, and programming’. New York: Routledge, Taylor & Francis Group.

Chan, L.L. and Idris, N. (2017). ‘Validity and Reliability of The Instrument Using Exploratory Factor Analysis and Cronbach’s alpha’. International Journal of Academic Research in Business and Social Sciences, 7(10). https://doi.org/10.6007/ijarbss/v7-i10/3387.

Chatterjee, S. (2020). Factors Impacting Behavioral Intention of Users to Adopt IoT In India: From Security and Privacy Perspective. International Journal of Information Security and Privacy, 14(4), 92–112. https://doi.org/10.4018/IJISP.2020100106

Cheung, M. W. L. (2015). Meta-Analysis: A Structural Equation Modelling Approach. Chichester: Wiley.

Chiemeke, S.C., Evwiekpaefe, A. E. & Chete, F.O. (2006). ‘The Adoption of Internet Banking in Nigeria: An Empirical Investigation’. The Journal of Internet Banking and Commerce, 11(3), pp.1–9.

Davis, F.D. (1989). ‘Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology’. MIS Quarterly, 13(3), pp.319–340. https://doi.org/10.2307/249008.

Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. (1989). ‘User Acceptance of Computer Technology: a Comparison of Two Theoretical Models’. Management Science, [online] 35(8), pp.982–1003. https://doi.org/10.1287/mnsc.35.8.982.

Dayour, F., Adongo, C. A., & Agyeiwaah, E. (2020). Continuous intention to use mobile money (MM) services: Driving factors among small and medium-sized tourism and hospitality enterprises (SMTHEs). Africa Journal of Management, 6(2), 85–114. https://doi.org/10.1080/23322373.2020.1753495

Farhana, H. P., Nafisa, M., Ahsan, U. C. & Babar, K. (2024). Integration of IOT in strategic management: A review of current trends, future possibilities, and challenges. International Journal of Science and Research Archive, 12(2), 2634–2645. https://doi.org/10.30574/ijsra.2024.12.2.1565

Farooq, M.S., Riaz, S., Abid, A., Umer, T. and Zikria, Y.B. (2020). ‘Role of IoT Technology in Agriculture: A Systematic Literature Review’. Electronics, 9(2), p.319. https://doi.org/10.3390/electronics9020319.

Fornell, C. and Larcker, D.F. (1981). ‘Evaluating Structural Equation Models with Unobservable Variables and Measurement Error’. Journal of Marketing Research, 18(1), pp.39–50. https://doi.org/10.1177/002224378101800104.

Gao, L. and Bai, X. (2014). ‘A unified perspective on the factors influencing consumer acceptance of internet of things technology’. Asia Pacific Journal of Marketing and Logistics, [online] 26(2), pp.211–231. https://doi.org/10.1108/apjml-06-2013-0061.

Goumagias, N., Whalley, J., Dilaver, O. and Cunningham, J. (2021), "Making sense of the internet of things: a critical review of internet of things definitions between 2005 and 2019", Internet Research, 31(5), pp. 1583-1610. https://doi.org/10.1108/INTR-01-2020-0013

Gøthesen, S., Haddara, M. and Kumar, K. N. (2023). Empowering homes with intelligence: An investigation of smart home technology adoption and usage. Internet of Things, 24(100944). https://doi.org/10.1016/j.iot.2023.100944

Graf-Drasch, V., Röglinger, M., Wenninger, A. (2022) A Contextualized Acceptance Model for Proactive Smart Services. Schmalenbach Journal of Business Research, 74, 345–387. https://doi.org/10.1007/s41471-022-00139-7

Hair, J., Hollingsworth, C.L., Randolph, A.B. and Chong, A.Y.L. (2017). ‘An updated and expanded assessment of PLS-SEM in information systems research’. Industrial Management & Data Systems, 117(3), pp.442–458. https://doi.org/10.1108/imds-04-2016-0130.

Hair, J.F., Sarstedt, M., Ringle, C.M. and Mena, J.A. (2012). ‘An assessment of the use of partial least squares structural equation modeling in marketing research’. Journal of the Academy of Marketing Science, 40(3), pp.414–433. https://doi.org/10.1007/s11747-011-0261-6.

Henseler, J., Ringle, C.M. and Sarstedt, M. (2015). ‘A new criterion for assessing discriminant validity in variance-based structural equation modeling’. Journal of the Academy of Marketing Science, 43(1), pp.115–135.

Henseler, J. and Sarstedt, M. (2012). ‘Goodness-of-fit indices for partial least squares path modeling’. Computational Statistics, 28(2), pp.565–580. https://doi.org/10.1007/s00180-012-0317-1.

Janssen, M., Luthra, S., Mangla, S., Rana, N.P. and Dwivedi, Y.K. (2019), "Challenges for adopting and implementing IoT in smart cities: An integrated MICMAC-ISM approach", Internet Research, 29 (6), pp. 1589-1616. https://doi.org/10.1108/INTR-06-2018-0252

Kisanjara, S. (2023). ‘Internet of Things and organizational performance in the Tanzanian banks’. Information Discovery and Delivery. https://doi.org/10.1108/idd-04-2022-0031.

Kunle, O.J., Olubunmi, O.A. and Sani, S. (2017). ‘Internet of things prospect in Nigeria: Challenges and solutions’. 2017 IEEE 3rd International Conference on Electro-Technology for National Development (NIGERCON). https://doi.org/10.1109/nigercon.2017.8281942.

Langley, D.J., van Doorn, J., Ng, I. C. L., Stieglitz, S., Lazovik, A. and Boonstra, A. (2021). The internet of everything: Smart things and their impact on business models. Journal of Business Research, 122(1):853–863. https://doi.org/10.1016/j.jbusres.2019.12.035

Lee, K.L., Romzi, P.N., Hanaysha, J.R., Alzoubi, H.M. and Alshurideh, M. (2022). ‘Investigating the impact of benefits and challenges of IOT adoption on supply chain performance and organizational performance: An empirical study in Malaysia’. Uncertain Supply Chain Management, 10(2), pp.537–550. https://doi.org/10.5267/j.uscm.2021.11.009.

Li, S. , Da Xu, L. and Zhao, S. (2014), “The Internet of Things: a survey”, Information Systems Frontiers , 17 (2), pp. 243-259. https://doi.org/10.1007/s10796-014-9492-7

Luthra, S., Garg, D., Mangla, S.K. and Singh Berwal, Y.P. (2018). ‘Analyzing challenges to Internet of Things (IoT) adoption and diffusion: An Indian context’. Procedia Computer Science, 125, pp.733–739. https://doi.org/10.1016/j.procs.2017.12.094.

Mola and Abebe (2023). The effect of employees’ CSR engagement on work outcomes:Empirical evidence from Ethiopia. Africa Journal of Management, 9(4) 338-364. https://doi.org/10.1080/23322373.2023.2273745

Motlagh, N.H., Mohammadrezaei, M., Hunt, J. and Zakeri, B. (2020). ‘Internet of Things (IoT) and the Energy Sector’. Energies, 13(2), p.494. https://doi.org/10.3390/en13020494.

Nachum, L., & Ogbechie, C. (2019). Where have foreign banks in Nigeria gone? Market structure, competitive intensity and the capabilities of Nigeria banks. Africa Journal of Management, 5(3), 231–253. https://doi.org/10.1080/23322373.2019.1648999

Nunnally, J.C. and Bernstein, I.H. (1994). ‘Psychometric theory’. 3rd ed. New Delhi: Tata Mcgraw-Hill Ed.

Ohiani, A.S. (2021), "Technology innovation in the Nigerian banking system: prospects and challenges", Rajagiri Management Journal, 15(1), pp. 2-15. https://doi.org/10.1108/RAMJ-05-2020-0018

Okafor, C.L., Okonkwo, O. and Onwuka, U.P. (2022). ‘Social Engineering Attack, Its Effects and Countermeasures in Nigeria Banking System’. International Digital Organization for Scientific Research (IDOSR) Journal of Computer and Applied Sciences 7(1) pp.25-32, 2022.

Okoye, L. U, Ehimare Omankhanlen, A., I. Okoh, J., N. Ezeji, F. and Ibileke, E. (2020). ‘Impact of corporate restructuring on the financial performance of commercial banks in Nigeria’. Banks and Bank Systems, 15(1), pp.42–50. https://doi.org/10.21511/bbs.15(1).2020.05.

Priyadarshini, K.V.L., Nath, A., Saha, U., Saha, S., Chakravarty, G. and Mukherjee, D. (2022). ‘Pre and post changes of AI, IOT & cloud computing in financial services and banking sector during pandemic COVID-19’. International journal of health sciences, 6(s1), 11559–11574. https://doi.org/10.53730/ijhs.v6ns1.7859.

Rahman, Md.M. (2023). ‘The Effect of Business Intelligence on Bank Operational Efficiency and Perceptions of Profitability’. FinTech, 2(1), pp.99–119. https://doi.org/10.3390/fintech2010008.

Ramalingam, H. and Venkatesan, V. P. (2019). "Conceptual analysis of Internet of Things use cases in Banking domain," TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON), Kochi, India, 2019, pp. 2034-2039, https://doi.org/10.1109/TENCON.2019.8929473.

Rotsios, K., Folinas, D., Mouchtari, C., Andreou, A., Fotiadis, T., Folina, M.-T., & Gasteratos, A. (2025). Exploring the Factors Influencing the Acceptance of IoT Applications in Food Packaging. Foods, 14(4), Article 575. https://doi.org/10.3390/foods14040575

Saadé, R. and Bahli, B. (2005). ‘The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model’. Information & Management, 42(2), pp.317–327. https://doi.org/10.1016/j.im.2003.12.013.

Salami, S. O., Akande, F. I. and Alalade, Y.S.A. (2022). 'Determinants of Technological Innovation Adoption and Banking Operations of Selected Deposit Money Banks in Nigeria'. European Journal of Accounting, Auditing and Finance Research, [online] 10(2), pp.25–54. ISSN 2053-4086(Print), 2053-4094(Online). https://tudr.org/id/eprint/257

Saxena, S. and Ali Said Mansour Al-Tamimi, T. (2017). ‘Big data and Internet of Things (IoT) technologies in Omani banks: a case study’. Foresight, 19(4), pp.409–420. https://doi.org/10.1108/fs-03-2017-0010.

Scherer, R., Siddiq, F. and Tondeur, J. (2019). ‘The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education’. Computers & Education, [online] 128, pp.13–35. https://doi.org/10.1016/j.compedu.2018.09.009.

Sharma, V. and Sood, D. (2022), "Adoption of Internet of Things and Services in the Indian Insurance Industry", Sood, K., Dhanaraj, R.K., Balusamy, B., Grima, S. and Uma Maheshwari, R. (Ed.) Big Data: A Game Changer for Insurance Industry (Emerald Studies in Finance, Insurance, and Risk Management), Emerald Publishing Limited, Leeds, pp. 35-42. https://doi.org/10.1108/978-1-80262-605-620221003

Shoomal, A., Jahanbakht, M., Componation, P. J., and Ozay, D. (2024). Enhancing supply chain resilience and efficiency through internet of things integration: Challenges and opportunities. Internet of Things, 27(101324). https://doi.org/10.1016/j.iot.2024.101324

Singh, S. P., Singh, P. and Diwakar, M. (2024). Improving quality of service for Internet of Things (IoT) in real life application: A novel adaptation-based Hybrid Evolutionary Algorithm. Internet of Things, 27 (101323). https://doi.org/10.1016/j.iot.2024.101323

Tavakol, M. and Dennick, R. (2011). ‘Making Sense of cronbach’s Alpha’. International Journal of Medical Education, [online] 2(2), pp.53–55. https://doi.org/10.5116/ijme.4dfb.8dfd.

Tun, S.Y.Y., Madanian, S. & Mirza, F. (2020). Internet of things (IoT) applications for elderly care: a reflective review. Aging Clinical Experimental Research 33, 855–867. https://doi.org/10.1007/s40520-020-01545-9

Uwamariya, M., Loebbecke, C., & Cremer, S. (2021). Mobile money adoption in rural Rwanda: A domestication perspective. Africa Journal of Management, 7(2), 314–337. https://doi.org/10.1080/23322373.2021.1902209

Usendiah, E.J., E. K. Worlu, R., Okolo, S.J. and Ukpeibo, E.G. (2022). ‘Effects of Technological Change on Customers’ Satisfaction: A Study of Zenith Bank Headquarters, Lagos State’. IBIMA Business Review, Vol. 2022, Article ID 434605t, pp.1–11. https://doi.org/10.5171/2022.434605.

Whitmore, A., Agarwal, A. and Da Xu, L. (2014). ‘The Internet of Things—A survey of topics and trends’. Information Systems Frontiers, [online] 17(2), pp.261–274. https://doi.org/10.1007/s10796-014-9489-2.

Yilmaz, N.K. and Hazar, H.B. (2019). ‘The rise of internet of things (IoT) and its applications in finance and accounting’. Pressacademia, 10(10), pp.32–35. https://doi.org/10.17261/pressacademia.2019.1139.

Downloads

Published

2026-06-29

How to Cite

THE IMPACT OF INTERNET OF THINGS (LOT) ON OPERATIONAL EFFICIENCY OF COMMERCIAL BANKS: PERCEIVED USEFULNESS AND EASE OF USE AS MEDIATORS. (2026). International Journal of Innovation and Business Strategy (IJIBS), 21(1), 74-93. https://doi.org/10.11113/ijibs.v21.204