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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 is to investigate the factors that influence the adoption of big data analytics and 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 is developed to empirically test the relationship of these variables; 265 members of universities in Latin America were surveyed, and structural equation modeling is used. The findings identify 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.
Sekli et al. (Tue,) studied this question.