A 3-in-1 framework for human resources' selection and positioning based on machine learning tools. (24th December 2021) - Pampouktsi, Panagiota; Kermanidis, Katia-Lida; Avlonitis, Markos
Administration is aiming to control the performance of human resources in order to achieve its best possible exploitation and through it resources economy that is an important issue for all organisations. Innovations about human resource evaluation systems, is a success factor of all administrative changes. Management of human resources is based on proper selection and positioning of the staffs that add value to an organisation. Artificial intelligence is the new ally for managers, but it is not wide-spread in the public sector. In this study, we collected and assessed personnel's data in a public organisation and by using various classification algorithms, specific models were built according to job description and employees' qualifications. Our scope is the development of an innovative framework, using machine learning techniques for meritocratic personnel selection for recruitment and simultaneously, positioning either horizontally in the departments or vertically in leadership positions, unifying three procedures in one.