Tesis y Trabajos de Investigación PUCP

URI permanente para esta comunidadhttp://54.81.141.168/handle/123456789/6

El Repositorio Digital de Tesis y Trabajos de Investigación PUCP aporta al Repositorio Institucional con todos sus registros, organizados por grado: Doctorado, Maestría, Licenciatura y Bachillerato. Se actualiza permanentemente con las nuevas tesis y trabajos de investigación sustentados y autorizados, así como también con los que que fueron sustentados años atrás.
Ingresa a su web: Repositorio Digital de Tesis y Trabajos de Investigación PUCP

Explorar

Filtros

20211

Ajustes

Autorsearch.filters.applied.operator.equals: search.filters.author.Marchena Sekli, Giulio FranzTemasearch.filters.applied.operator.equals: search.filters.subject.Desarrollo organizacional

Resultados de búsqueda

Mostrando 1 - 1 de 1
  • No hay miniatura disponible
    ÍtemTexto completo enlazado
    Adoption of big data analytics and its impact on organizational performance in higher education mediated by knowledge management
    (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.