Factors Influencing the Willingness to Adopt Internet of Things in Supply Chain Management: A Study on Bangladeshi Manufacturing Firms

Main Article Content

Saiful Islam

Abstract

This study explores the factors influencing the willingness to adopt the Internet of Things (IoT) in Bangladeshi manufacturing firms' supply chain management (SCM). Using a quantitative research approach, data is collected from 162 firm-specific SCM professionals through purposive sampling. Applying the partial least squares structural equation modeling (PLS-SEM), the four primary constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) model- performance expectancy, effort expectancy, social influence, and facilitating conditions are examined to find their influence on the willingness to adopt IoT in the SCM of Bangladeshi manufacturing firms. Findings enumerate that these four constructs explain 42% of the variance in the willingness to adopt IoT. Performance expectancy, social influence, and facilitating conditions are statistically significant, while effort expectancy is insignificant in influencing the willingness to adopt IoT in the SCM. These findings bring several theoretical and practical contributions and suggest scope for future research.

Article Details

Section

Articles

How to Cite

Factors Influencing the Willingness to Adopt Internet of Things in Supply Chain Management: A Study on Bangladeshi Manufacturing Firms. (2026). Dhaka University Journal of Business Studies, 44(1), 77-105. https://dujbs.du.ac.bd/index.php/about/article/view/28

References

Agrawal, P., & Narain, R. (2018). Digital supply chain management: An overview. In IOP Conference Series: Materials Science and Engineering.

Alam, M. Z., Hu, W., Kaium, M. A., Hoque, M. R., & Alam, M. M. D. (2020). Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM–neural network approach. Technology in Society, 61(1), 101255.

Alkawsi, G., Ali, N. A., & Baashar, Y. (2021). The moderating role of personal innovativeness and user experience in smart meter adoption. Applied Sciences, 11(8), 3297.

Al-Saedi, K., Al-Emran, M., Abusham, E., & El Rahman, S. A. (2019). Mobile payment adoption: A systematic review of the UTAUT model. In Proceedings of the International Conference on Fourth Industrial Revolution (ICFIR).

Andrews, J. E., Ward, H., & Yoon, J. (2021). UTAUT as a model for understanding AI adoption among librarians. Journal of Academic Librarianship, 47(6), 102437.

Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787–2805.

Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of Things and supply chain management: A literature review. International Journal of Production Research, 57(15–16), 4719–4742.

Centenaro, M., Costa, C. E., Granelli, F., Sacchi, C., & Vangelista, L. A. (2021). Survey on technologies, standards and challenges in satellite IoT. IEEE Communications Surveys & Tutorials, 23(3), 1693–1720.

Chataut, R., Phoummalayvane, A., & Akl, R. (2023). IoT applications and future prospects. Journal of Sensors, 23, 7194.

Chong, A. (2013). A two-staged SEM–neural network approach for m-commerce adoption. Expert Systems with Applications, 40, 1240–1247.

Cohen, J. (1977). Statistical power analysis for the behavioral sciences. Academic Press.

Davis, F. D., Granić, A., & Marangunić, N. (2023). The technology acceptance model: 30 years of TAM. Technology.

Dymitrowski, A., & Mielcarek, P. (2021). Business model innovation and competitive advantage. Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 2110–2128.

Fatorachian, H., & Kazemi, H. (2021). Industry 4.0 and supply chain performance. Production Planning & Control, 32(1), 63–81.

Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., & Babin, B. J. (2016). Common method variance detection. Journal of Business Research, 69(8), 3192–3198.

Ghadge, A., Er Kara, M., Moradlou, H., & Goswami, M. (2020). Industry 4.0 implementation in supply chains. Journal of Manufacturing Technology Management, 31(4), 669–686.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2013). A primer on partial least squares structural equation modeling (PLS-SEM). Sage.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). Sage.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Sage.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and report PLS-SEM results. European Business Review, 31(1), 2–24.

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). Assessing discriminant validity in SEM. Journal of the Academy of Marketing Science, 43(1), 115–135.

Islam, M., Mamun, A. A., Afrin, S., Quaosar, G. A. A., & Uddin, M. A. (2022). AI adoption in HRM in Bangladesh. South Asian Journal of Human Resources Management, 9(2), 324–349.

Kasilingam, D., & Krishna, R. (2022). Adoption of IoT services. International Journal of Consumer Studies, 46(1), 102–131.

Katoch, R. (2022). IoT research in supply chain and logistics. Materials Today: Proceedings, 56, 2505–2515.

Khan, S., Singh, R., Khan, S., & Ngah, A. H. (2023). Barriers of IoT adoption in food supply chains. Green Technologies and Sustainability, 1(2), 100023.

Khan, Y., Su’ud, M. B. M., Alam, M. M., Ahmad, S. F., Ahmad, A. Y. B., & Khan, N. (2022). IoT in sustainable supply chain management. Sustainability, 15(1), 694.

Landaluce, H., Arjona, L., Perallos, A., Falcone, F., Angulo, I., & Muralter, F. (2020). IoT sensing applications using RFID. Journal of Sensors, 20, 2495.

Lee, I., & Lee, K. (2015). The Internet of Things: Applications and challenges. Business Horizons, 58(4), 431–440.

Martins, C., & Pato, M. (2019). Supply chain sustainability: A literature review. Journal of Cleaner Production, 225, 995–1016.

Núñez-Merino, M., Maqueira-Marín, J. M., Moyano-Fuentes, J., & Martínez-Jurado, P. J. (2020). Industry 4.0 and lean supply chain management. International Journal of Production Research, 58(16), 5034–5061.

Olhager, J., & Selldin, E. (2004). Supply chain management survey. International Journal of Production Economics, 89(3), 353–361.

Palmaccio, M., Dicuonzo, G., & Belyaeva, Z. S. (2021). IoT and corporate business models. Journal of Business Research, 131, 610–618.

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method bias. Journal of Applied Psychology, 88(5), 879–903.

Ronaghi, M. H., & Forouharfar, A. (2020). IoT usage in smart farming. Technology in Society, 63, 101415.

Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students. Pearson.

Sharma, A., Sharma, A., Singh, R. K., & Bhatia, T. (2023). Blockchain adoption in agri-food supply chains. Business Process Management Journal, 29(3), 737–756.

Sheel, A., & Nath, V. (2020). Blockchain adoption in supply chain. International Journal of Business Innovation and Research, 21(4), 564–584.

Shi, Y., Siddik, A. B., Masukujjaman, M., Zheng, G., Hamayun, M., & Ibrahim, A. M. (2022). IoT adoption in agriculture using UTAUT2. Sustainability, 14(11), 6640.

Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015). Mobile payment adoption using UTAUT. Psychology & Marketing, 32(8), 860–873.

Taherdoost, H. (2018). Technology adoption models and theories. Procedia Manufacturing, 22, 960–967.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of IT. MIS Quarterly, 27(3), 425–478.

Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). UTAUT: A literature review. Journal of Enterprise Information Management, 28(3), 443–488.

Xu, L. D., He, W., & Li, S. (2014). IoT in industries: A survey. IEEE Transactions on Industrial Informatics, 10(4), 2233–2243.

Yee, M. L. S., & Abdullah, M. S. (2021). UTAUT in education research. Jurnal Pendidikan Sains dan Matematik Malaysia, 11(1), 1–20.

Most read articles by the same author(s)

Similar Articles

You may also start an advanced similarity search for this article.