Towards a better understanding of the Organizational Characteristics that affect Acceptance of Big Data Platforms for Academic Teaching - Adnan Aldholay; Osama Isaac; Abdullah Nabeel Jalal; Farah Akmar Anor; Ahmed M. Mutahar (Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 2021)
In today's era of information, data has been growing at an exponential rate to become big data, and it needs platforms to allow users to govern, access, deliver, analyze, and use these huge databases. Academics in higher education need to utilize these platforms in teaching to enrich and empower the educational experience of their students of these institutions. The purpose of the current study is to investigate the impact of organizational characteristics on the acceptance of big data platforms for academic teaching among higher education institutes in Malaysia. 143 respondents participated to examine the effect of organizational characteristics (Management Drive, Bandwagon Pressure, and Training) on the acceptance of big data platforms for academic teaching. Besides, examining the moderating role of task technology fit. The results illustrate that management drive, bandwagon pressure has a significant impact on the acceptance, with an insignificant impact of training on the acceptance. However, task technology fit has not moderated any of the proposed relationships. This study would give insight for the higher education institutes managements to improve their academics acceptance of the big data platforms in teaching and therefore drive them to use the aforementioned platforms.