IEEE Access (Jan 2019)

Big Data Adoption and Knowledge Management Sharing: An Empirical Investigation on Their Adoption and Sustainability as a Purpose of Education

  • Waleed Mugahed Al-Rahmi,
  • Noraffandy Yahaya,
  • Ahmed A. Aldraiweesh,
  • Uthman Alturki,
  • Mahdi Alamri,
  • Muhammad Sukri Bin Saud,
  • Yusri Bin Kamin,
  • Abdulmajeed A. Aljeraiwi,
  • Omar Abdulrahman Alhamed

DOI
https://doi.org/10.1109/ACCESS.2019.2906668
Journal volume & issue
Vol. 7
pp. 47245 – 47258

Abstract

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The aim of this paper to develop a model to measure sustainability for education and incorporate the literature big data adoption and knowledge management sharing in the educational environment. This paper hypothesizes that perceived usefulness, perceived ease of use, perceived risk, and behavioral intention to use big data should influence adoption of big data, while age diversity, cultural diversity, and motivators should impact knowledge management sharing. Therefore, knowledge management sharing influences behavior intention to use technologies and big data adoption would be positively associated with sustainability for education. This paper employed a version of TAM and motivation theory as the research framework and adopted quantitative data collection and analysis methods by surveying 214 university students who were chosen through stratified random sampling. Student's responses were sorted into the 11 study constructs and analyzed to explain their implication of sustainability on education. The data were then quantitatively analyzed using structural equation modeling (SEM). The results showed that perceived usefulness, perceived ease of use, perceived risk, and behavioral intention to use big data were significant determinants of big data adoption, while age diversity, cultural diversity, and motivators were significant determinants of knowledge management sharing. The knowledge management sharing, behavior intention to use technologies, and big data adoption succeeded in explaining 66.7% of sustainability on education. The findings and implications of this paper are provided.

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