Reconciling internal and external performance in a holistic approach: a Bayesian network model in higher education

University education is crucial for cultural and economic growth. Thus, the academic mission recognizes the achievement of both institutional and social objectives, and research provides the basis for the systematic creation of knowledge and the development of human capital. Universities attempt to manage a global system with a holistic vision based on data and facts and oriented to the continuous improvement of its effectiveness and efficiency. The goal is achieved by implementing a monitoring system based both on internal and external performances. As a consequence, it is necessary to consider both students perspective regarding needs, expectations, level of satisfaction and loyalty and internal key performance indicators. This paper proposes the use of Bayesian networks for jointly monitoring internal and external performance of a Master’s programme of an Italian University in a holistic approach. A Bayesian network is estimated using a learning algorithm able to analyze the association structure among mixed ordinal and nominal variables. Various scenarios are evaluated thanks to efficient computational algorithms of Bayesian networks.