A Method for Evaluating Human Resource Value at the Task Level: Integrating Hard and Soft Skills in Intelligent Decision Systems
ABSTRACT The article proposes a method for assessing the value of human resources at the level of an individual production or project task, based on integrating hard and soft skills indicators into a single intellectual system to support management decisions. Unlike traditional approaches based on static personnel parameters, the developed model combines elements of multicriteria analysis, fuzzy logic theory and weighting coefficients for quantitative assessment of personnel competencies in conditions of uncertainty. The Human Resource Value Index is proposed to determine an employee's integral value for a specific task, taking into account the requirements of the work process and the dynamics of changes in employee characteristics. Experimental modelling has been conducted, confirming the methodology's ability to differentiate personnel decisions based on the priority of hard and soft skills, as well as to respond appropriately to changes in input data. The results of the work demonstrate the feasibility of using the model in digital HR analytics platforms and DSS for adaptive personnel management in project‐oriented structures, particularly in maritime logistics. The scientific novelty lies in the development of a formalized mechanism for measuring employee value in real time, ensuring greater accuracy and objectivity in personnel decisions within complex socio‐technical systems.
Authors
- Діана ВОРОХОБІНА (ORCID: https://orcid.org/0000-0002-7414-4133)
- Олег Анатолійович Онищенко (ORCID: https://orcid.org/0000-0002-3766-3188)
- Олександра Кравченко (ORCID: https://orcid.org/0000-0002-3085-7449)
- O. Melnyk
- Sergiy Kuznichenko
- Svitlana Onyshchenko
- Aditya Rio Prabowo
- Ivana Golub Medvešek
Institutions
- Sebelas Maret University (ID)
- National University Odesa Law Academy (UA)
- Yaroslav Mudryi National Law University (UA)
- Odessa National Maritime University (UA)
- University of Split (HR)
Publication Details
- Journal
- Systems Research and Behavioral Science
- Published
- 2026-03-07
- DOI
- https://doi.org/10.1002/sres.70043
- Primary Topic
- AI and HR Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00