(Pontificia Universidad Católica del Perú, 2021-12-10) Marchena Sekli, Giulio Franz; De la Vega Hernández, Iván Manuel
Due to SARS-CoV-2 pandemic, higher education institutions are challenged to continue
providing quality teaching, consulting, and research production through virtual education
environments. In this context, a large volume of data is being generated, and technologies
such as big data analytics are needed to create opportunities for open innovation by obtaining
valuable knowledge. The purpose of this paper was to investigate the factors that influence the
adoption of big data analytics, as well as to evaluate the relationship it has with performance
and knowledge management, taking into consideration that this technology is in its initial
stages and that previous research has provided varied results depending on the sector in focus.
To address these challenges, a theoretical framework was developed to empirically test the
relationship of these variables. A total of 265 members of universities in Latin America were
surveyed and structural equation modeling was used for hypothesis testing. The findings
identified compatibility, an adequate organizational data environment, and external support as
factors required to adopt big data analytics and their positive relationship is tested with
knowledge management processes and organizational performance. This study provides
practical guidance for decision-makers involved in or in charge of defining the
implementation strategy of big data analytics in higher education institutions.
