Exploring Sustainable Learning Intentions of Employees Using Online Learning Modules of Office Apps Based on User Experience Factors: Using the Adapted UTAUT Model
Source abstract
Abstract
Research on the information module has identified a range of factors in the adoption model that determine their intention to learn sustainably. This research investigates the determinants of employees’ intentions to use an online learning module within an office application, utilizing a modified Unified Theory of Acceptance and Use of Technology (UTAUT) model. Data were collected from 564 employees in different organizations and analyzed using structural equation modeling. The research examines correlations between four key determinants—performance expectancy, effort expectancy, social influence, and facilitating conditions—and eight user experience motivational factors, including career development, business needs, self-management, learning experience, company atmosphere, external pressure, company support, and course quality. The findings indicate that all four UTAUT determinants significantly support employees’ use of the online learning module for continuous learning. Performance expectancy is positively influenced by career development and business needs, effort expectancy by self-management, social influence by external pressure, and facilitating conditions by company support and course quality. The learning experience and company atmosphere showed no significant correlation. The study offers valuable insights for managers, investors, and developers to enhance the adoption of online learning modules, promoting sustainable learning and employee development.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Technology Adoption and User Behaviour · Knowledge Management and Sharing · Digital Marketing and Social Media
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
International Design School for Advanced Studies, Hongik University, Seoul 04068, Republic of Korea
International Design Trend Center, Hongik University, Seoul 04068, Republic of Korea
References (96)
Show source-provided references
1. How to prevent and combat employee burnout and create healthier workplaces during crises and beyond10.1016/j.bushor.2021.02.037 ↗
2. Enhancing employee job satisfaction via e-learning: The mediating role of an organizational learning culture10.1080/10447318.2018.1480694 ↗
3. College students’ use and acceptance of emergency online learning due to COVID-1910.1016/j.ijedro.2020.100011 ↗
4. A review of technology acceptance and adoption models and theories10.1016/j.promfg.2018.03.137 ↗
5. A study on users’ willingness to accept mobility as a service based on UTAUT model10.1016/j.techfore.2020.120066 ↗
6. Technology adoption and use theory review for studying scientists’ continued use of cyber-infrastructure
7. An empirical examination of continuous intention to use m-learning: An integrated model10.1007/s10639-019-10094-2 ↗
8. Wang, S., Chen, S., and Nah, K. (2024). Exploring the Mechanisms Influencing Users’ Willingness to Pay for Green Real Estate Projects in Asia Based on Technology Acceptance Modeling Theory. Buildings, 14.10.3390/buildings14020349 ↗
9. Implications of the coronavirus (COVID-19) outbreak for innovation: Which technologies will improve our lives?10.1016/j.techfore.2020.120451 ↗
10. Understanding information technology acceptance by individual professionals: Toward an integrative view10.1016/j.im.2005.08.006 ↗
11. The yea-paradox: Cognitive bias in technology acceptance surveys10.1016/j.infsof.2023.107253 ↗
12. Virtual Internships and Work-Integrated Learning in Hospitality and Tourism in a Post-COVID-19 World
13. Kant, I., and Schneewind, J.B. (2002). Groundwork for the Metaphysics of Morals, Yale University Press.
14. Mobile learning adoption: A systematic review10.1007/s10639-018-9783-6 ↗
15. The effect of training on work performance and career development: The role of motivation as intervening variable
16. The Effects of Organizational and Individual Career Management on Career Success10.1108/01437729410053617 ↗
17. The impact of career development on employee performance: An empirical study of the public sector in Indonesia
18. A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies10.1287/mnsc.46.2.186.11926 ↗
19. E-learning in business10.1177/1052562903252658 ↗
20. Daily self-management and employee work engagement10.1016/j.jvb.2013.11.002 ↗
21. Self-directed learning in MOOCs: Exploring the relationships among motivation, self-monitoring, and self-management10.1007/s11423-020-09747-8 ↗
22. Web-based instruction: Who is inclined to resist it and why?10.2190/3VQ2-XTRH-08QV-CAEL ↗
23. Self-management as a substitute for leadership: A social learning theory perspective10.2307/257111 ↗
24. The applications of constructivist learning theory and social learning theory on adult continuous development10.1002/pfi.21963 ↗
25. Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction10.1016/j.iheduc.2013.04.001 ↗
26. Integrating learning experiences across tertiary education and practice settings: A socio-personal account10.1016/j.edurev.2014.01.002 ↗
27. Bandura, A. (1986). Social Foundations of Thought and Action, Prentice Hall, Inc.
28. Employee motivation and performance: Do the work environment and the training matter?
29. Lifelong learning and nurses’ continuing professional development, a metasynthesis of the literature10.1186/s12912-021-00579-2 ↗
30. Rogers, E.M., Singhal, A., and Quinlan, M.M. (2014). Diffusion of innovations. An Integrated Approach to Communication Theory and Research, Routledge.
31. External pressure or internal culture? An innovation diffusion theory account of small retail businesses’ social media use10.1016/j.jretconser.2021.102616 ↗
32. Corporate responsibility and employee relations: From external pressure to action10.1177/1059601114560168 ↗
33. Hilton, M.L., and Pellegrino, J.W. (2012). Education for Life and Work: Developing Transferable Knowledge and Skills in the 21st Century, National Academies Press.
34. Employees’ perception of corporate social responsibility (CSR) and its effects on internal outcomes10.1080/02642069.2019.1606906 ↗
35. The impacts of perceived organizational support and psychological empowerment on job performance: The mediating effects of organizational citizenship behavior10.1016/j.ijhm.2011.04.011 ↗
36. Understanding the factors driving m-learning adoption: A literature review10.1108/10650741011073761 ↗
37. Nawrot, I., and Doucet, A. (2014, January 7–11). Building engagement for MOOC students: Introducing support for time management on online learning platforms. Proceedings of the 23rd International Conference on World Wide Web, Seoul, Republic of Korea.10.1145/2567948.2580054 ↗
38. Belief, attitude, intention, and behavior: An introduction to theory and research
39. Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. Action Control: From Cognition to Behavior, Springer.10.1007/978-3-642-69746-3_2 ↗
40. Davis, F.D. (1985). A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. [Ph.D. Thesis, Massachusetts Institute of Technology].
41. Why do people use information technology? A critical review of the technology acceptance model10.1016/S0378-7206(01)00143-4 ↗
42. User acceptance of information technology: Toward a unified view10.2307/30036540 ↗
43. Investigating the determinants and age and gender differences in the acceptance of mobile learning10.1111/j.1467-8535.2007.00809.x ↗
44. The acceptance and use of a virtual learning environment in China10.1016/j.compedu.2006.09.001 ↗
45. A modified UTAUT framework to predict students’ intention to adopt online learning: Moderating role of openness to change10.1108/IJILT-04-2022-0093 ↗
46. An Extended UTAUT Model to Explain Factors Affecting Online Learning System Amidst COVID-19 Pandemic: The Case of a Developing Economy10.3389/frai.2022.768831 ↗
47. Handoko, B.L. (2019, January 15–17). Application of UTAUT theory in higher education online learning. Proceedings of the 2019 10th International Conference on E-Business, Management and Economics, Beijing, China.10.1145/3345035.3345047 ↗
48. Has, M.N. (2016, January 13–15). Examining factors influencing webinar adoption using UTAUT model (Case study at distance learning program, ABC University, Bandung-Indonesia 2016). Proceedings of the 2016 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob), Bandung, Indonesia.
49. Šumak, B., Polancic, G., and Hericko, M. (2010, January 10–16). An empirical study of virtual learning environment adoption using UTAUT. Proceedings of the 2010 Second International Conference on Mobile, Hybrid, and On-Line Learning, Saint Maarten, Netherlands Antilles.10.1109/eLmL.2010.11 ↗
50. Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model10.1007/s10796-017-9774-y ↗
51. Extending the two-stage information systems continuance model: Incorporating UTAUT predictors and the role of context10.1111/j.1365-2575.2011.00373.x ↗
52. Modeling the longitudinality of user acceptance of technology with an evidence-adaptive clinical decision support system10.1016/j.dss.2012.10.049 ↗
53. A study of career needs, career development programs, job satisfaction and the turnover intentions of R&D personnel10.1108/13620430410544364 ↗
54. Assessing and managing employees for embracing change: A multiple-item scale to measure employee readiness for e-business10.1016/j.technovation.2009.05.003 ↗
55. A model for enhancing employees’ lifelong learning intention online10.1016/j.lmot.2021.101733 ↗
56. Factor effecting learner’s satisfaction towards e-learning: A conceptual framework
57. Debriefing experience scale: Development of a tool to evaluate the student learning experience in debriefing10.1016/j.ecns.2011.11.002 ↗
58. Organizational climate and company productivity: The role of employee affect and employee level10.1348/096317904774202144 ↗
59. The measurement of employee well-being: Development and validation of a scale10.1177/0972150919859101 ↗
60. UWIS: An assessment methodology for usability of web-based information systems10.1016/j.jss.2009.06.047 ↗
61. Satisfaction with online learning: A comparative descriptive study
62. Employee training and development, and organisational performance: A study of small-scale manufacturing firms in Nigeria
63. Measuring employee perception of performance management system effectiveness: Conceptualization and scale development10.1108/ER-01-2015-0006 ↗
64. The effect of culture on user acceptance of information technology
65. The psychology of social impact10.1037/0003-066X.36.4.343 ↗
66. Al-Shahrani, H. (2016). Investigating the Determinants of Mobile Learning Acceptance in Higher Education in Saudi Arabia, Northern Illinois University.
67. Technological and structural characteristics, student learning and satisfaction with web-based courses: An exploratory study of two on-line MBA programs10.1177/1350507602333003 ↗
68. The role of self-determination theory in explaining teachers’ motivation to continue to use e-learning technology10.1016/j.compedu.2009.06.001 ↗
69. Online learning experience scale validation and its impact on learners’ satisfaction10.1016/j.procs.2017.08.178 ↗
70. Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M., Danks, N.P., and Ray, S. An introduction to structural equation modeling. Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook, Springer.
71. Structural equation modeling in practice: A review and recommended two-step approach10.1037/0033-2909.103.3.411 ↗
72. Hoyle, R.H. (1995). Structural Equation Modeling: Concepts, Issues, and Applications, Sage.
73. Analyzing data from experimental studies: A latent variable structural equation modeling approach10.1037/0022-0167.45.1.18 ↗
74. Applications of structural equation modeling in social sciences research
75. Development and validation of the Online Learning Self-efficacy Scale (OLSS): A structural equation modeling approach10.1080/08923647.2020.1831357 ↗
76. Online learning performance and satisfaction: Do perceptions and readiness matter?10.1080/01587919.2020.1724768 ↗
77. Course satisfaction and student engagement in online learning amid COVID-19 pandemic: A structural equation model
78. Black, W., and Babin, B.J. (2019). Multivariate data analysis: Its approach, evolution, and impact. The Great Facilitator: Reflections on the Contributions of Joseph F. Hair, Jr. to Marketing and Business Research, Springer International Publishing.10.1007/978-3-030-06031-2_16 ↗
79. Designing an Effective Questionnaire Using Orthogonal Array for Improving Inventory Accuracy at Electricity Warehouse
80. Black, W.C., Babin, B.J., and Anderson, R.E. (2010). Multivariate Data Analysis: A Global Perspective, Pearson.
81. Single-group validity, differential validity, and differential prediction10.1037/0021-9010.63.4.507 ↗
82. A tale of three perspectives: Examining post hoc statistical techniques for detection and correction of common method variance10.1177/1094428109332834 ↗
83. Common method bias: It’s bad, it’s complex, it’s widespread, and it’s not easy to fix10.1146/annurev-orgpsych-110721-040030 ↗
84. Unveiling the Catalysts of Digital Transformation Acceptance: Insights from Employees in Online Distance Learning Higher Education Institutions
85. Salloum, S.A., and Shaalan, K. (2018, January 3–5). Factors affecting students’ acceptance of e-learning system in higher education using UTAUT and structural equation modeling approaches. Proceedings of the International Conference on Advanced Intelligent Systems and Informatics, Cairo, Egypt.10.1007/978-3-319-99010-1_43 ↗
86. Contextual factors influencing the facilitation of others’ learning through everyday work experiences10.1108/13665620710819384 ↗
87. Massive open online courses (MOOCs) as an enabler for competent employees and innovation in industry10.1016/j.compind.2017.05.001 ↗
88. Organizational career growth, affective occupational commitment and turnover intentions10.1016/j.jvb.2012.01.014 ↗
89. A review of employee motivation theories and their implications for employee retention within organizations
90. The impact of social influence on individuals’ adoption of innovation10.1080/10919392.2011.564483 ↗
91. Procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown10.1016/j.paid.2021.110673 ↗
92. The roles of intrinsic motivators and extrinsic motivators in promoting e-learning in the workplace: A case from South Korea10.1016/j.chb.2011.12.015 ↗
93. Knowledge sharing and firm innovation capability: An empirical study10.1108/01437720710755272 ↗
94. Investigating the structural relationships among organisational support, learning flow, learners’ satisfaction and learning transfer in corporate e-learning10.1111/j.1467-8535.2010.01116.x ↗
95. Organisational support for employee learning: An employee perspective10.1108/EJTD-08-2013-0084 ↗
96. Developing and evaluating dialogue games for collaborative e-learning10.1046/j.0266-4909.2001.00215.x ↗