The Illusion of Readiness: Deconstructing Performative Compliance in Supply Chain Digital Transformation
Downloads
Digital transformation has become a critical strategy for improving supply chain resilience, operational efficiency, and organizational competitiveness. However, significant investments in digital technologies do not always produce proportional improvements in operational outcomes, creating a productivity paradox in which technological adoption exceeds actual utilization. This study aims to examine the behavioral mechanisms underlying Digital Transformation Implementation (DTI) by investigating the roles of Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and Employees’ Intentional Digital Readiness (EIDR) among supply chain personnel. This study employed a quantitative cross-sectional research design using a structured questionnaire distributed to employees involved in supply chain and logistics functions within Indonesian manufacturing firms and logistics service providers. Data from 247 valid respondents were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The findings reveal that Perceived Usefulness and Perceived Ease of Use significantly influence Digital Transformation Implementation, indicating that employees primarily adopt digital systems when they provide practical benefits and operational convenience. Conversely, Employees’ Intentional Digital Readiness does not significantly affect implementation, suggesting a gap between employees’ expressed readiness and actual digital adoption behavior. The study concludes that successful supply chain digital transformation depends more on technological utility and usability than psychological readiness alone. These findings contribute to digital transformation literature by highlighting the importance of evaluating actual operational integration rather than relying solely on self-reported readiness indicators.
Akhtar, P., De Silva, M., Khan, Z., Tarba, S., Amankwah-Amoah, J., & Wood, G. (2025). Digital transformation in public-private collaborations: The success of humanitarian supply chain operations. International Journal of Production Economics, 279, 109461. https://doi.org/10.1016/j.ijpe.2024.109461
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010). On making causal claims: A review and recommendations. The Leadership Quarterly, 21(6), 1086–1120. https://doi.org/10.1016/j.leaqua.2010.10.010
Bouckenooghe, D., Devos, G., & Van den Broeck, H. (2009). Organizational change questionnaire–climate of change, processes, and readiness: Development of a new instrument. The Journal of Psychology: Interdisciplinary and Applied, 143(6), 559–599. https://doi.org/10.1080/00223980903218216
Chaudhry, S. (2018). Managing employee attitude for a successful information system implementation: A change management perspective. Journal of International Technology and Information Management, 27(1), 57–90. https://doi.org/10.58729/1941-6679.1364
Chwi?kowska-Kubala, A., Cyfert, S., Malewska, K., Mierzejewska, K., & Szumowski, W. (2023). The impact of resources on digital transformation in energy sector companies. The role of readiness for digital transformation. Technology in Society, 74, 102315. https://doi.org/10.1016/j.techsoc.2023.102315
Felin, T., Foss, N. J., & Ployhart, R. E. (2015). The microfoundations movement in strategy and organization theory. Academy of Management Annals, 9(1), 575–632. https://doi.org/10.1080/19416520.2015.1007651
Hair, J. F. J. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), Third Edition.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. In European Business Review (Vol. 31, Number 1). https://doi.org/10.1108/EBR-11-2018-0203
Henseler, J., Ringle, C. M., & 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). https://doi.org/10.1007/s11747-014-0403-8
Höyng, M., & Lau, A. (2023). Being ready for digital transformation: How to enhance employees’ intentional digital readiness. Computers in Human Behavior Reports, 11, 100314. https://doi.org/10.1016/j.chbr.2023.100314
Hussain, A. (2025). The mediating effects of perceived usefulness and perceived ease of use on nurses’ intentions to adopt advanced technology. BMC Nursing, 24(1), 33. https://doi.org/10.1186/s12912-024-02648-8
I, M. H., & Deloitte. (2025). Top supply chain trends: The digital supply chain ecosystem. 2025 MHI annual industry report (Key findings). MHI.
Kane, G. C., Nguyen Phillips, A., Copulsky, J. R., & Andrus, G. R. (2019). The technology fallacy: How people are the real key to digital transformation. The MIT Press. https://doi.org/10.7551/mitpress/11661.001.0001
Kaufmann, L., & Gaeckler, J. (2015). A structured review of partial least squares in supply chain management research. Journal of Purchasing and Supply Management, 21(4), 259–272. https://doi.org/10.1016/j.pursup.2015.04.005
Malik, M., Andargoli, A., Ali, I., & Chavez, R. (2024). A socio-cognitive theorisation of how data-driven digital transformation affects operational productivity. International Journal of Production Economics, 277, 109403. https://doi.org/10.1016/j.ijpe.2024.109403
Michelotto, F., & Joia, L. A. (2024). Organizational digital transformation readiness: An exploratory investigation. Journal of Theoretical and Applied Electronic Commerce Research, 19(4). https://doi.org/10.3390/jtaer19040159
OECD. (2024). OECD economic surveys: Indonesia 2024. OECD Publishing. https://doi.org/10.1787/de87555a-en
Prologis. (2023). Future proofing the global supply chain: How AI, automation and other technologies are impacting efficiency (Key takeaways). Prologis.
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In C. Homburg, M. Klarmann, & A. Vomberg (Eds.), Handbook of market research (pp. 587–632). Springer. https://doi.org/10.1007/978-3-319-57413-4_15
Schmid, A. M., Recker, J., & vom Brocke, J. (2017). The socio-technical dimension of inertia in digital transformations. Proceedings of the 50th Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2017.583
Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill-building approach (7th ed., Ed.). Wiley.
Seppänen, S., Ukko, J., & Saunila, M. (2025). Understanding determinants of digital transformation and digitizing management functions in incumbent SMEs. Digital Business, 5(1), 100106. https://doi.org/10.1016/j.digbus.2025.100106
Sudaryanto, M. R., Hendrawan, M. A., & Andrian, T. (2023). The effect of technology readiness, digital competence, perceived usefulness, and ease of use on accounting students artificial intelligence technology adoption. E3S Web of Conferences, 388, 04055. https://doi.org/10.1051/e3sconf/202338804055
Tahar, A., Riyadh, H. A., Sofyani, H., & Purnomo, W. E. (2020). Perceived ease of use, perceived usefulness, perceived security and intention to use e-filing: The role of technology readiness. Journal of Asian Finance, Economics and Business, 7(9), 537–547. https://doi.org/10.13106/jafeb.2020.vol7.no9.537
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Vink, L. S., & Walzl, B. (2025). Redefining human performance in complex socio-technical systems: Human performance as key-performance indicator. Transportation Research Procedia, 31–39. https://doi.org/10.1016/j.trpro.2025.05.004
Virmani, N., Kumar, P., Karuppiah, K., & Jagtap, S. (2025). Adopting net-zero supply chains: Integrated model of TOE and TAM in emerging economy context. Sustainable Futures, 10, 101188. https://doi.org/10.1016/j.sftr.2025.101188
Xames, M. D., & Topcu, T. G. (2025). Digital engineering transformation as a sociotechnical challenge: Categorization of barriers and their mapping to DoD’s policy goals. arXiv. https://arxiv.org/abs/2509.15461
Xiong, Q., Yang, J., Zhang, X., Deng, Y., Gui, Y., & Guo, X. (2025). The influence of digital transformation on the total factor productivity of enterprises: The intermediate role of human-machine cooperation. Journal of Innovation & Knowledge, 10(4), 100736. https://doi.org/10.1016/j.jik.2025.100736
Copyright (c) 2026 Daniel Eka Putra, Rizqi Fathur Rahman , Sara Marsha Eunicque , Darjat Sudrajat

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.




