The rapid evolution of the Indian Information Technology (IT) sector necessitates a strategic transition from traditional training to technology-mediated learning ecosystems. This study examines the structural factors influencing the acceptance of digital training interventions and their ultimate impact on employee satisfaction. Drawing upon the Technology Acceptance Model (TAM), Innovation Diffusion Theory (IDT), and Organizational Support Theory (OST), proposed an integrative framework linking management/IT support and individual technology adoption to employee sentiment. Scale validation and hypothesis testing were conducted using a cross-sectional sample from an IT organization in Gurugram, India. Principal Component Analysis (PCA) and multiple linear regression demonstrate that both Technology Adoption and Management/IT Support significantly predict multifaceted Employee Satisfaction. These findings establish a reliable instrument foundation for full-scale corporate learning research and demonstrate that individual behavioral readiness remains a crucial driver of T&D success alongside organizational backing.
Jain, P. & Jain, C. (2026). Navigating the Digital Shift: The Interplay of Organizational Support, Individual Behaviour, and Technology-Driven Training on Employee Satisfaction in the Indian IT Sector. Journal of Modern Management & Entrepreneurship, 16(03), 124–128. https://doi.org/10.62823/JMME/16.03.9401
1.Alshaabani, A., Naz, F., Magda, R., & Rudnák, I. (2021). Impact of perceived organizational support on OCB in the time of COVID-19 pandemic in Hungary: Employee engagement and affective commitment as mediators. Sustainability, 13(14), Article 7800. https://doi.org/10.3390/su13147800
2.Bakker, A. B., & Demerouti, E. (2007). The Job Demands-Resources model: State of the art. Journal of Managerial Psychology, 22(3), 309–328. https://doi.org/10.1108/02683940710733115
3.Cropanzano, R., Dasborough, M. T., & Weiss, H. M. (2017). Affective events and the development of leader-member exchange. Academy of Management Review, 42(2), 233–258. https://doi.org/10.5465/amr.2014.0384
4.Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
5.Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475–487. https://doi.org/10.1006/imms.1993.1022
6.Eedara, V. S., & Korrapati, R. B. (2017). A review of research on the factors affecting job satisfaction in Information Technology (IT) companies. International Journal of Engineering and Management Research, 7(1), 232–234.
7.Eisenberger, R., Huntington, R., Hutchison, S., & Sowa, D. (1986). Perceived organizational support. Journal of Applied Psychology, 71(3), 500–507. https://doi.org/10.1037/0021-9010.71.3.500
8.Green, S. B. (1991). How many subjects does it take to do a regression analysis. Multivariate Behavioral Research, 26(3), 499–510. https://doi.org/10.1207/s15327906mbr2603_7
9.Harikumar, P., & Porkodi, S. (2026). Digital transformation in corporate training: Evaluating the link between technology acceptance and workforce retention in IT service firms. International Journal of Learning and Human Capital Development, 14(1), 45–62.
10.KPMG. (2023). Addressing the tech talent deficit: Reskilling strategies for the Indian IT industry. KPMG Thought Leadership Series.
11.Marler, J. H., Liang, X., & Dulebohn, J. H. (2006). Training and effective technology use: The mediating role of user beliefs. Journal of Applied Social Psychology, 36(3), 721–743. https://doi.org/10.1111/j.0021-9029.2006.00025.x
12.NASSCOM. (2023). Strategic review 2023: Priming the technology industry for the next decade. National Association of Software and Service Companies.
13.Paliwal, M., & Meshram, M. (2021). Job satisfaction among IT employees: A review of literature. Journal of Science & Technology, 6(Spl 1), 494–501.
14.Parent-Rocheleau, X., & Parker, S. K. (2022). Algorithms as work designers: How algorithmic management impacts work design and employee well-being. Human Resource Management Review, 32(3), Article 100838. https://doi.org/10.1016/j.hrmr.2021.100838
15.Riketta, M. (2002). Attitudinal organizational commitment and job performance: A meta-analysis. Journal of Organizational Behavior, 23(3), 257–266. https://doi.org/10.1002/job.141
16.Rogers, E. M. (1995). Diffusion of innovations (4th ed.). The Free Press.
17.Salah-Eddine, E. A. (2025). Digital competence, autonomy, and collaboration: Determinants of employees' affective commitment. Revue ISG, 12(2), 114–132.
18.Sharma, A., & Sharma, R. (2022). Emerging trends in technology-mediated learning: A systematic review of Indian corporate training frameworks. Asian Journal of Business and Management Studies, 10(2), 112–129.
19.Solís, P., Lago-Urbano, R., & Real Castelao, S. (2023). Factors that impact the relationship between perceived organizational support and technostress in teachers. Behavioral Sciences, 13(5), Article 364. https://doi.org/10.3390/bs13050364
20.Sung, S. Y., & Choi, J. N. (2013). Do organizations spend wisely on employees? Effects of training and development investment on firm performance. Journal of Organizational Behavior, 34(8), 1086–1112. https://doi.org/10.1002/job.1837
21.Upadhyaya, P., & Vrinda. (2021). Impact of technostress on workplace productivity and job satisfaction: An empirical assessment. Journal of Enterprise Information Management, 34(4), 1198–1221. https://doi.org/10.1108/JEIM-05-2020-0182
22.Xu, G. (2025). Does digitalization benefit employees? A systematic meta-analysis of the digital technology–employee nexus in the workplace. Systems, 13(6), Article 409.
23.Xu, L., Xue, Y., & Zhao, Y. (2023). How organizational support shapes digital learning engagement and workplace performance. Frontiers in Psychology, 14, Article 1089234. https://doi.org/10.3389/fpsyg.2023.1089234
- Xu, Y., Chen, Z., & Liu, W. (2025). Organizational support, work engagement, and turnover intention in modern technology enterprises. Journal of Managerial Psychology, 40(1), 88–104. https://doi.org/10.1108/JMP-02-2024-0112.