Adoption of big data analytics and its impact on organizational performance in higher education mediated by knowledge management

Descripción del Articulo

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 nee...

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Detalles Bibliográficos
Autor: Marchena Sekli, Giulio Franz
Formato: tesis doctoral
Fecha de Publicación:2021
Institución:Pontificia Universidad Católica del Perú
Repositorio:PUCP-Tesis
Lenguaje:inglés
OAI Identifier:oai:tesis.pucp.edu.pe:20.500.12404/21115
Enlace del recurso:http://hdl.handle.net/20.500.12404/21115
Nivel de acceso:acceso abierto
Materia:Educación superior--Instituciones--Gestión de información
Desarrollo organizacional
Big data
Educación superior--Innovación
COVID-19 (Enfermedad)
https://purl.org/pe-repo/ocde/ford#5.02.04
Descripción
Sumario: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.
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