
handle: 10419/279861
Generation Z (Gen Z) is the young generation born between the mid-1990s and 2010s. They are now entering the market and starting their first jobs. Therefore, managers must shape the company workplace environment to encourage young employees to work efficiently and connect their future with the company. Only then will both managers and employees share mutual satisfaction from collaboration and aim at the common target, which should be the prosperity of the company. This book presents research results and techniques for analysing the working expectations and needs of Gen Z. The analyses were made in various countries in Europe: The Czech Republic, Latvia, Poland, and Portugal. The book contains chapters that present the analysis results and technical chapters that outline modern methods of analysis of management data, including tutorial chapters on machine learning, which currently makes a strong appearance in research in various disciplines. This volume will be of interest to researchers, academics, practitioners, and students in the fields of management studies, research methods, and human resource management.
Machine Learning, ddc:320, engagement at workplace, hygge, generation Z, work-life balance, Python
Machine Learning, ddc:320, engagement at workplace, hygge, generation Z, work-life balance, Python
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 11 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
