Change Management in the Digital Era: Determinants of Successful Technology Adoption in Large Organizations
Keywords:
Technology adoption, Digital transformation, Change management, Change readiness, Leadership support, Digital competency, Organizational culture, Training effectiveness, Large organizationsAbstract
The rapid acceleration of digital transformation has compelled large organizations to adopt new technologies to enhance operational efficiency, competitiveness, and strategic agility. However, successful technology adoption remains a complex organizational challenge influenced by multiple structural and human factors. This study investigates the determinants of successful technology adoption in large organizations, focusing on five key variables: change readiness, leadership support, digital competency, organizational culture, and training effectiveness. Using a quantitative research design and structural equation modeling (SEM), data were collected from employees across large organizations undergoing digital transformation initiatives. The results reveal that change readiness has the strongest positive effect on technology adoption, followed by leadership support, digital competency, and training effectiveness. Organizational culture, while statistically significant, exhibits a comparatively weaker influence. These findings highlight that technology adoption is not merely a technical process but a multifaceted organizational change effort requiring psychological preparedness, competent leadership, continuous skill development, and a supportive culture. The study contributes to the growing body of digital transformation literature by offering an integrated model of adoption determinants and provides practical insights for leaders seeking to optimize technology implementation strategies. Overall, the research underscores the need for holistic change management approaches to ensure sustainable and effective technology adoption in the digital era.
Downloads
References
AbuAkel, S. A., & Ibrahim, M. (2023). The effect of relative advantage, top management support and IT infrastructure on e-filing adoption. Journal of Risk and Financial Management, 16(6), 295. https://doi.org/10.3390/jrfm16060295
Aguirre‐Urreta, M. I., & Rönkkö, M. (2018). Statistical inference with PLSc using bootstrap confidence intervals. MIS Quarterly, 42(3), 1001–1020. https://doi.org/10.25300/MISQ/2018/13561
Akter, S., Hossain, M. N., Lu, S., & Babu, M. M. (2021). The role of big data analytics in developing resilience in supply chains: A dynamic capability view. International Journal of Production Economics, 234, 108075. https://doi.org/10.1016/j.ijpe.2021.108075
Al-Hajri, A., Abdella, G. M., Al-Yafei, H., Aseel, S., & Hamouda, A. M. (2024). A systematic literature review of the digital transformation in the Arabian Gulf’s oil and gas sector. Sustainability, 16(15), 6601. https://doi.org/10.3390/su16156601
AlHogail, A., & Mirza, A. (2021). Readiness assessment for digital transformation and smart city services adoption. Sustainability, 13(5), 2798. https://doi.org/10.3390/su13052798
Ally, M. (2019). Competency profiles for the digital era. International Journal of Information and Learning Technology, 36(3), 205–213. https://doi.org/10.1108/IJILT-04-2019-0045
Armenakis, A. A., & Harris, S. G. (2009). Reflections: Our journey in organizational change research and practice. Journal of Change Management, 9(2), 127–142.
Atkinson, I., France, L., & Muir, D. (2023). Using survey-based research methods in public sector research: Best practice guidelines. International Journal of Public Administration, 46(4), 334–348. https://doi.org/10.1080/01900692.2022.2036711
Avolio, B. J., & Walumbwa, F. O. (2014). Leadership theory and research in the new millennium: Current theoretical trends and changing perspectives. The Leadership Quarterly, 25(1), 36–62.
Bennett, J., Pitt, M., & Price, S. (2020). Understanding the impact of training on employee performance: A systematic review. Journal of Workplace Learning, 32(2), 93–115. https://doi.org/10.1108/JWL-07-2019-0087
Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). The Guilford Press.
Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). Routledge.
Chuang, S. H. (2020). Co-creating digital transformation: A coevolutionary perspective. Industrial Marketing Management, 88, 170–180. https://doi.org/10.1016/j.indmarman.2020.05.015
Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J., … Upadhyay, N. (2020). Impact of COVID-19 pandemic on information management research and practice. International Journal of Information Management, 55, 102211.
Eisenhardt, K. M., & Martin, J. (2000). Dynamic capabilities: What are they? Strategic Management Journal, 21, 1105–1121.
Etikan, I., & Bala, K. (2017). Sampling and sampling methods. Biostatistics & Biometrics Open Access Journal, 5(6), 00149.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). SAGE Publications.
Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling. SAGE Publications.
Haffke, I., Kalgovas, B., & Benlian, A. (2017). The role of the CIO and the CDO in an organization’s digital transformation. Information Systems Journal, 27(5), 539–576.
Heuermann, M., Gaiser-Bertram, S., & Schallmo, D. (2024). Digital transformation success factors: A systematic literature review and bibliometric analysis. International Journal of Innovation Management, 28(09n10). https://doi.org/10.1142/S1363919624400048
Joshi, A., Kale, S., Chandel, S., & Pal, D. K. (2015). Likert scale: Explored and explained. British Journal of Applied Science & Technology, 7(4), 396–403.
Kane, G. C. (2019). The technology fallacy: How people are the real key to digital transformation. MIT Sloan Management Review.
Kline, R. B. (2023). Principles and practice of structural equation modeling (5th ed.). The Guilford Press.
Kotter, J. P. (2012). Leading change. Harvard Business Review Press.
Kulichyova, A., Kazantsev, N., White, L., & Islam, N. (2025). Digital transformation in large established organisations: Four restructuring dilemmas based on dynamic capabilities. International Journal of Management Reviews. https://doi.org/10.1111/ijmr.12395
Leonardi, P. (2020). COVID-19 and the new technologies of organizing: Digital exhaust, digital footprints, and artificial intelligence in the wake of a pandemic. Journal of Management Studies, 57(8), 1–5.
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539–569.
Schein, E. H., & Schein, P. (2017). Organizational culture and leadership (5th ed.). Wiley.
Susanti, N., Jie, F., & Hill, S. R. (2023). Digital transformation capability and its impact on firm performance. Technological Forecasting and Social Change, 189, 122334.
Taherdoost, H. (2022). Validity and reliability of the research instrument: How to test the validation of a questionnaire/survey. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4120601
van der Kolk, B., van Veen-Dirks, P., ter Bogt, H., & van de Walle, S. (2023). Performance measurement and use of performance information in public organizations: The role of measurement system maturity. Public Administration Review, 83(3), 563–577. https://doi.org/10.1111/puar.13627
Vărzaru, A. A., & Bocean, C. G. (2024). Digital transformation and innovation: The influence of digital technologies on turnover from innovation activities and types of innovation. Systems, 12(9), 359. https://doi.org/10.3390/systems12090359
Vial, G. (2019). Understanding digital transformation: A review and research agenda. The Journal of Strategic Information Systems, 28(2), 118–144.
Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, J. (2021). Business research methods (9th ed.). Cengage Learning




