Employee motivation: use of algorithms for its prediction and management

Abstract

INTRODUCTION: The dynamics of organizations have led them to pay special attention to the motivation of workers to ensure good performance. Algorithms offer tools that allow organizational leaders to establish strategies based on the knowledge of the behavioural patterns of the work team.

OBJECTIVES: Evaluate the prediction and management of worker motivation using algorithms.

METHODS: A bibliometric analysis is performed for 2013-2023 with articles from the Scopus database and the VOSviewer program.

RESULTS: Two clusters are derived from the analysis of the Co-occurrence - Author Keywords. The first cluster, identified with red, is related to work environment management and comprises the words Job Satisfaction, Machine Learning and Q-learning. The second cluster identified with green is related to job performance and comprises the words Motivation and Supply Chain Management.

CONCLUSION: The worker performs their activities in a juxtaposition of internal aspects of organizations and external aspects that determine their skills. It is where algorithms play a fundamental role in the links between technological tools and human beings to positively impact worker motivation in different areas, such as training, development, health, well-being and integral development.