%0 Conference Proceedings
%T A Conceptual Framework of Intelligent Management Control System for Higher Education
%+ Wroclaw University of Economics and Business
%+ Université de Reims Champagne-Ardenne (URCA)
%+ Wroclaw University of Science and Technology
%A Dudycz, Helena
%A Hernes, Marcin
%A Kes, Zdzislaw
%A Mercier-Laurent, Eunika
%A Nita, Bartłomiej
%A Nowosielski, Krzysztof
%A Oleksyk, Piotr
%A Owoc, Mieczysław, L.
%A Palak, Rafał
%A Pondel, Maciej
%A Wojtkiewicz, Krystian
%< avec comité de lecture
%@ 978-3-030-80846-4
%( IFIP Advances in Information and Communication Technology
%B 8th IFIP International Workshop on Artificial Intelligence for Knowledge Management (AI4KM)
%C Yokohama, Japan
%Y Eunika Mercier-Laurent
%Y M. Özgür Kayalica
%Y Mieczyslaw Lech Owoc
%I Springer International Publishing
%3 Artificial Intelligence for Knowledge Management
%V AICT-614
%P 35-47
%8 2021-01-07
%D 2021
%R 10.1007/978-3-030-80847-1_3
%K Management control system;Intelligent systems;Artificial intelligence;Higher education;Cognitive technologies
%Z Computer Science [cs]Conference papers
%X The utilization of management control systems in university management poses a considerable challenge because university’s strategic goals are not identical to those applied in profit-oriented management. A university’s management control system should take into account the processing of management information for management purposes, allowing for the relationships between different groups of stakeholders. The specificity of the university operation assumes conducting long-term scientific research and educational programmes. Therefore, the controlling approach to university management should considerat long-term performance measurement as well as management in key areas such as research, provision of education to students, and interaction with the tertiary institution’s socio-economic environment. This paper aims to develop a conceptual framework of the Intelligent Management Control System for Higher Education (IMCSHE) based on cognitive agents. The main findings are related to developing the assumption, model, and technological basis including the artificial intelligence method.
%G English
%Z TC 12
%Z WG 12.6
%2 https://inria.hal.science/hal-04041355/document
%2 https://inria.hal.science/hal-04041355/file/518231_1_En_3_Chapter.pdf
%L hal-04041355
%U https://inria.hal.science/hal-04041355
%~ URCA
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-WG12-6
%~ IFIP-TC12
%~ IFIP-AI4KM
%~ IFIP-AICT-614