Identification of Characteristics of Employee’s Individual Human Capital with Data on Self-Reports of Professional Skills and Personal Characteristics

Author:

Stoliarova ValerieORCID,Tulupyeva TatianaORCID,Abramov MaximORCID,Salakhova ValentinaORCID

Abstract

In the field of recruitment and human resources management, the problem arises of automatization of the assessment process of the characteristics of human capital, taking into account, among other things, the personality characteristics of the employee. The article is devoted to the problem of identification of such characteristics that have the greatest contribution to some indicators of the effectiveness of an employee of an organization with self-reported data on professional skills and answers to questions–statements about various psychological aspects of personality. The general structure of the survey tools based on self-reports of employees is proposed, as well as the formalization of the proposed methods of data analysis. The cluster analysis was used for the identification of groups with similar professional skills. Special psychometric scales based on the questions–statements are selected and analyzed via the item response theory approach, giving the estimates of the latent variable, that reflects personal characteristics. At the final stage of the study, the relationship between the estimated factors (identified clusters and estimated latent variables) and the indicator of employee effectiveness was assessed. As such indicator, the fact of a managerial position was used. The proposed approach is a structure of a pilot study that allows to identify the characteristics of human capital (professional skills and personality traits) that have the greatest contribution to the performance indicators of an employee or organization, and is aimed at reducing labor costs at subsequent stages of a more detailed and targeted study. The possibilities of the proposed approach are demonstrated with data collected among state civil servants in Russia. The fact of having a managerial position is used as an indicator of effectiveness.

Publisher

SPIIRAS

Subject

Artificial Intelligence,Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Computer Networks and Communications,Information Systems

Reference44 articles.

1. Dastile X., Celik T., Potsane M. Statistical and machine learning models in credit scoring: A systematic literature survey // Applied Soft Computing. 2020. vol. 91. pp. 106263.

2. Djeundje V.B., Crook J., Calabrese R., Hamid M. Enhancing credit scoring with alternative data // Expert Systems with Applications. 2021. vol. 163. pp. 113766.

3. Абрамов М.В., Тулупьева Т.В., Тулупьев А.Л. Социоинженерные атаки: социальные сети и оценки защищенности пользователей. СПб.: ГУАП, 2018. 266 с.

4. Олисеенко В.Д., Абрамов М.В., Тулупьев А.Л., Иванов К.А. Прототип программного комплекса для анализа аккаунтов пользователей социальных сетей: веб-фреймворк Django // Программные продукты и системы. 2022. Т. 35. № 1. С. 45–53. doi: 10.15827/0236-235X.137.

5. Khlobystova A., Korepanova A., Maksimov A., Tulupyeva T. An Approach to Quantification of Relationship Types between Users Based on the Frequency of Combinations of Non-numeric Evaluations // Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). Advances in Intelligent Systems and Computing. 2020. vol. 1156. pp. 206—213.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3