PERSONNEL MANAGEMENT AUTOMATION: SYSTEMATIC SCIENTIFIC PUBLICATIONS REVIEW

Abstract

Introduction. Automation in the field of HR is one of the ways to increase both the efficiency of the human resource management service and the organization as a whole. Appropriate reviews of the scientific literature are needed to promote awareness and dissemination of the current technological and management practices application. Companies that use modern technologies gain an advantage that determines their higher level of competitiveness compared to organizations that do not pay enough attention to this area. Technological solutions are developing rapidly, and an overview of innovations and existing trends may be of interest to both researchers and practitioners in the field of personnel management. The purpose of this review is to analyze the scientific thought development in the field of personnel management automation over the past 5 years. This article discusses both the possibilities offered by experts in the field of automation through the implementation of specific technological solutions, and methodological approaches in the field of automation of personnel management.

Methodology and methods. The article is a systematic review of scientific publications on the topic of personnel management automation over the past 5 years (since 2019). The OpenAlex platform was used as a database for the analysis. The search date was 23.08.2024, the keywords used were “hr human resources automation”, only scientific articles were included in the analysis perimeter. As a part of the quantitative analysis of the sample, the following items were considered: general characteristics of the sample, productivity of the authors of the articles, an assessment of the use and interrelation of keywords of the sample articles. The bibliometrix package for the R programming language (based on the biblioshiny interface) was used to analyze and present the results. Next, the works were selected for qualitative analysis. Five main thematic areas of publications with the largest number of works were identified. Further, articles were selected out of these works for review based on thematic relevance, content and availability in the Scopus database. The availability of materials selected for analysis varies and is determined by the policy of the publishing journal / publication conditions of a particular article. The PRISMA (2020) recommendations were taken into account when conducting the review.

Results. The initial sample for quantitative analysis included 3727 articles, and 46 papers were selected for qualitative analysis. Basing on the analysis, one may conclude that the number of publications on the topic is growing, while the distribution of publication activity by individual authors does not show significant deviations. The most used keywords are directly related to personnel management and digital technologies. Popular areas of work: Industry 4.0 and digital transformation, analysts in the field of human resource management, approaches in the field of personnel management (usage of key performance indicators, recruiting, personnel development, etc.).

Conclusions. Much attention in the considered works is paid to the potential of using generative language models (like ChatGPT) and the impact of automation of the production process on the HR function work. Subject matter experts see significant potential in improving HR management processes through the use of modern technological solutions. At the same time, the importance of developing existing practices in the field of human resource management and maintaining a focus on the development of human capital of companies is emphasized. Lack of specialized competencies among employees, financial costs when implementing new solutions and the risks of violating ethical standards are difficulties that organizations may possibly face. The development of personnel management practices under the influence of technological changes requires further study. The main limitations of the review include the possible incompleteness of the database used to review the articles, as well as the risks of the author bias in terms of selecting and conducting a qualitative analysis of the articles.