In the world of work, the political transition created a difficult situation in Hungary which has become even less favourable in the 2010s. Employees are exposed to numerous infringements. The case study presented at previous MEB conferences and continued herein illustrates the vulnerability of employees. The case study provides an excellent opportunity for the presentation of the special Hungarian labour law (the conclusion of an employment relationship, payment of wages, performance of work, trial period, termination, corporate dismissal, etc.) and for summarising the lessons learned. In addition to the court judgement involving heavy expenditure, it can also be concluded that successful corporate work can only be achieved by respected and skilled employees, and the loyalty of employees is the key source of results. This, in turn, can only be achieved if the representatives of the owners and the management of the company pay great attention, as a subsystem, to the lawful employment and motivation of employees.
Marie Pavláková Docekalová, Alena Kocmanová and Jirí Kolenák
Effective corporate governance is a key element in achieving long-term success for any company. The codes of conduct that corporate governance adopts directly determine the sustainability of business activities. With this in mind, this paper aims to demonstrate the results of research that identifies a set of key indicators of corporate governance performance. The presented research is quantitative. In order to identify key performance indicators, factor analysis was employed. It was found that corporate governance performance is influenced by two factors. For the first factor, the relationship between corporate governance and stakeholders is measured by key indicators: percentage of women within CG, contributions to political parties, politicians and related institutions and number of complaints received from stakeholders. The second factor, strategy & compliance, is generated from the following: percentage of strategic objectives met and total number of sanctions for breaching the law. This research aims to assist both academic and corporate practitioners who want to improve corporate governance performance and, through the use of key performance indicators, support the transparency and sustainability of their business.
The corporate governance quality has always been a decision criterion for investments, many recent studies trying to define metrics in order to help investors in their decision process. In this paper we investigate whether the clustering of companies’ information concerning their corporate governance politics and financial information could be mapped with the help of clustering. Our approach is to build clusters using machine learning techniques, based on corporate governance and financial variables from a number of 1400 listed companies. We evaluate the obtained clusters by matching them with the classes of two well-known indicators (Tobin’s Q and Altman Z-score), used to estimate the companies’ performance. We obtain partial matches of the benchmark variables and we compare the performances of the used algorithms.