Business Analytics and Machine Learning for Project Management
The project management process includes the necessity to forecast the effectiveness of each employee’s contribution to the achievement of the targeted result. The transferable utility of each project participant is assessed. The presented study reveals a consolidated approach to the formation of the transferable utility indicator. The proposed model utilizes information from various sources including performance indicators, personnel data and other contextual factors. It is based on the integration of data mining and machine learning techniques and is designed to generate accurate predictive models. The obtained results can be used by top management of companies to make effective managerial decisions in project management and increase the number of financial incentives for those project participants who have shown the highest level of transferable utility.
Authors
- Lyudmila V. Glukhova (ORCID: https://orcid.org/0000-0002-8279-307X)
- S.D. Syrotyuk
- Anton A. Gudkov
- Svetlana A. Gudkova
Institutions
- Togliatti State University (RU)
- Volga Region State University of Service (RU)
Publication Details
- Journal
- Procedia Computer Science
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.procs.2025.09.589
- Citations
- 1
- Primary Topic
- AI and HR Technologies
- Type
- article
- Field-Weighted Citation Impact
- 2.76