INTENTION TO ADOPT INNOVATION CULTURE AMONG EMPLOYEES IN ONLINE DISTANCE LEARNING HIGHER EDUCATION INSTITUTIONS
Abstract
The objective of the study is to evaluate both direct and indirect relationships among organizational culture, attitude, intention, and adoption of the innovation culture in Malaysian ODL higher education institutions. The findings of this study are crucial for ODL institutions to maximize employee performance by adopting an innovation culture for their survival and sustainability. The research framework includes two independent variables: organizational culture and attitude, intention as a mediator, and adoption as a dependent variable. Primary data was collected through the survey questionnaire and distributed via e-mail. The study utilized non-probability purposive sampling. This study analyzed 316 questionnaires, representing an 86.5% response rate. The results support the proposed hypotheses, confirming the significant influence of organizational culture and attitude on intention. The findings show that attitude and intention significantly influence adoption. However, organizational culture does not significantly influence adoption. The intention was a critical mediator between independent and dependent variables. This study’s model demonstrates high prediction relevance based on statistical analysis with PLS prediction and a validated predictability test (CVPAT). Only one direct relationship hypothesis was rejected, while the four direct and two indirect relationship hypotheses were supported. Overall, this study provides valuable insights into maximizing the adoption of an innovation culture in ODL higher education institutions.
Keywords
Attitude, intention, adoption, innovation culture, organizational culture, open distance learning
Supporting Institution
OPEN UNIVERSITY MALAYSIA
References
- Ayvaz, M. Y., Akyol, Y. E., & Demiral, M. (2019). Innovation in nursing and innovative attitudes of nurses. International Journal of Health Administration and Education Congress (Sanitas Magisterium), 5(2), 52-59.
- Chin, W., Cheah, J., Liu, Y., Ting, H., Lim, X., & Cham, T. H. (2020). Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research. Industrial Management & Data Systems, 120(12), 2161-2209. https://doi:10.1108/imds-10-2019-0529
- Fuad, D. R., Musa, K., & Hashim, Z. (2022). Innovation culture in education: A systematic review of the literature. Management in Education, 36(3), 135-149. https://doi:10.1177/0892020620959760
- Ghasemy, M., Teeroovengadum, V., Becker, J., & Ringle, C. M. (2020). This fast car can move faster: A review of PLS-SEM application in higher education research. Higher Education, 80(6), 1121-1152. https://doi:10.1007/s10734-020-00534-1
- Hair, J.F., Hult, G.T.M., Ringle, C.M., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE Publications.