Journal of Management and Business Education🔗

 
Article

INTELIGENCIA ARTIFICIAL PARA PREDECIR LA LEALTAD A LA UNIVERSIDAD🔗

ARTIFICIAL INTELLIGENCE TO PREDICT LOYALTY TO UNIVERSITY🔗

 
Spanish Full Article Citation
 

Author(s)🔗

Gabriel Cachón Rodríguez , Universidad Rey Juan Carlos, Spain
Raúl Gómez Martínez , Universidad Rey Juan Carlos, Spain
Juan Gabriel Martínez Navalón , Universidad Rey Juan Carlos, Spain
Camilo Prado Roman , Universidad Rey Juan Carlos, Spain

https://doi.org/10.35564/jmbe.2019.0003

Resumen🔗

Debido a la pérdida de competitividad de las instituciones públicas de educación superior esta investigación analiza la identidad visual, la comunicación, el comportamiento, la cultura corporativa y la imagen como predictores de la lealtad en una institución pública de educación superior. Para el análisis de los datos se hace uso del método de redes bayesianas. Los resultados muestran que la inteligencia artificial tiene capacidad predictiva en la lealtad Finalmente la investigación indica una serie de implicaciones para la supervivencia de estas instituciones.

Palabras clave
inteligencia artificial, redes bayesianas, lealtad, universidad

Abstract🔗

Due to the loss of competitiveness of public institutions of higher education this research analyzes the visual identity, communication, behavior, corporate culture and image as predictors of loyalty in a public institution of higher education. For the analysis of the data, the Bayesian network's method is used. The results show that artificial intelligence has a predictive capacity of loyalty. Finally, research indicates a series of implications for the survival of these institutions.

Keywords
artificial intelligence, bayesian networks, loyalty, university

Received
12 February 2019

Accepted
3 April 2019

Copyright
This is an open access article under the CC BY-NC license.

Citation🔗

Cachón Rodríguez, G.; Gómez Martínez, R.; Martínez Navalón, J.G.; & Prado Román, C. (2019). Inteligencia artificial para predecir la lealtad a la universidad. Journal of Management and Business Education, 2(1), 17-27. https://doi.org/10.35564/jmbe.2019.0003

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