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Article
Publication date: 7 September 2023

Şerife Uğuz Arsu and Esra Sipahi Döngül

This study aims to identify articles examining human-robot interaction and the effects of robotic systems on employment.

Abstract

Purpose

This study aims to identify articles examining human-robot interaction and the effects of robotic systems on employment.

Design/methodology/approach

In this research, electronic searches were performed for articles published between 2000 and 2022 in Emerald, Springer, PubMed, Science Direct, Wiley and Google Scholar. In the searches of robotic systems with keywords such as “motivation, job satisfaction, job loss, performance, job giving,” 5 quantitative and 5 qualitative studies were included in the systematic review. The selected research was conducted using the Johanna Briggs Analytical Cross-Sectional Studies Checklist from the Joanna Briggs Institute (JBI) critical evaluation lists and the JBI Critical Appraisal Checklist for Qualitative Research, depending on their type. The included studies are mostly on employee-robot collaboration.

Findings

Although the majority of the articles examined in this study are included in keywords or titles, it is determined that there is a gap in descriptive quantitative studies in the literature on the effects of employee-robot collaboration, robotic systems and robotic systems on variables such as motivation, job satisfaction, job loss, performance and employment, although they do not mention a framework that directly investigates human-robot interaction and the effects of robotic systems on employment.

Research limitations/implications

There are several limitations in this study. One of them is that, although the databases are comprehensively scanned, only studies published in English between 2000 and 2022 are included in the systematic review. Another limitation is the heterogeneity between studies.

Practical implications

As a result of the authors’ findings, the practical effects of the research are reflected as follows: It serves as a guide for future studies to fill the gap in the field, especially for academics and researchers working in the field of social sciences on robotic systems and intelligent automations. In addition to the qualitative studies on this subject, there is a need for the use of robotic systems in the field of human resources and management and quantitative studies with more sample sizes, especially at the corporate (firms) and individual (employees) level. Considering that the number of studies on this subject is very insufficient, this research is important in terms of shedding light on future studies.

Originality/value

The authors believe that the impact of robotic systems on employment is one of the few conceptual articles that systematically examines 6 dimensions (job satisfaction, performance, job loss, employment, motivation, employment).

Details

Journal of Organizational Change Management, vol. 36 no. 7
Type: Research Article
ISSN: 0953-4814

Keywords

Expert briefing
Publication date: 20 September 2024

Criminal violence has been rising in Chiapas in recent years, and the impact of increased security deployments has been dampened by shifting criminal dynamics. Armed groups have a…

Details

DOI: 10.1108/OXAN-DB289780

ISSN: 2633-304X

Keywords

Geographic
Topical
Article
Publication date: 21 May 2024

Jose Leao and Marcele Fontana

This study aims to develop a talent selection model for learning organizations capable of connecting two groups, candidates in a talent hiring process and managers of the hiring…

Abstract

Purpose

This study aims to develop a talent selection model for learning organizations capable of connecting two groups, candidates in a talent hiring process and managers of the hiring company, in a reliable process, promoting organizational learning and increasing employee satisfaction.

Design/methodology/approach

This paper integrates egalitarian principles, an artificial intelligence mechanism founded on stable matching algorithms, and evaluating critical soft skills to enhance recruitment practices within learning organizations. The authors conduct a numerical real-world application in Python to showcase the model’s effectiveness. Five candidates were evaluated for five job positions. Moreover, 26 soft skills were analyzed by the five company leaders, relating them to the requirements of each job position and by all candidates, as a self-assessment process.

Findings

The model promoted egalitarian talent management because it motivates the candidates to choose the preferred position in a company, and the employers hire the best candidate. It is satisfactory for all participants in a company’s hiring process if the parties intend to be fair and egalitarian. The benefits of the process can be considered isolated (parties’ satisfaction) or a part of a company’s effort to stimulate an egalitarian culture in organizational values.

Practical implications

The information generated by the model is used to refine its selection process and improve its understanding of the job requirements and candidate profiles of the company. The model supports this idea, using the concepts of indifference, stability, egalitarianism and the soft skills required and identified to be more effective and learn about themselves.

Social implications

This paper discusses an egalitarian point of view in the recruitment process. It is satisfactory for all participants in a company’s hiring process if the parties intend to be fair and egalitarian. The process’s benefits can be considered part of a company’s effort to stimulate an egalitarian culture in organizational values.

Originality/value

This paper brings an excellent future perspective and points to the company’s development of talent retention. The model simultaneously solves the evolution of talent management processes through new technologies and soft skills emerging in the postpandemic scenario.

Details

The Learning Organization, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-6474

Keywords

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