Research background: Connected Internet of Robotic Things (IoRT) and cyber-physical process monitoring systems, industrial big data and real-time event analytics, and machine and deep learning algorithms articulate digital twin smart factories in relation to deep learning-assisted smart process planning, Internet of Things (IoT)-based real-time production logistics, and enterprise resource coordination. Robotic cooperative behaviors and 3D assembly operations in collaborative industrial environments require ambient environment monitoring and geospatial simulation tools, computer vision and spatial mapping algorithms, and generative artificial intelligence (AI) planning software. Flexible industrial and cloud computing environments necessitate sensing and actuation capabilities, cognitive data visualization and sensor fusion tools, and image recognition and computer vision technologies so as to lead to tangible business outcomes. Purpose of the article: We show that generative AI and cyber–physical manufacturing systems, fog and edge computing tools, and task scheduling and computer vision algorithms are instrumental in the interactive economics of industrial metaverse. Generative AI-based digital twin industrial metaverse develops on IoRT and production management systems, multi-sensory extended reality and simulation modeling technologies, and machine and deep learning algorithms for big data-driven decision-making and image recognition processes. Virtual simulation modeling and deep reinforcement learning tools, autonomous manufacturing and virtual equipment systems, and deep learning-based object detection and spatial computing technologies can be leveraged in networked immersive environments for industrial big data processing. Methods: Evidence appraisal checklists and citation management software deployed for justifying inclusion or exclusion reasons and data collection and analysis comprise: Abstrackr, Colandr, Covidence, EPPI Reviewer, JBI-SUMARI, Rayyan, RobotReviewer, SR Accelerator, and Systematic Review Toolbox. Findings & value added: Modal actuators and sensors, robot trajectory planning and computational intelligence tools, and generative AI and cyber–physical manufacturing systems enable scalable data computation processes in smart virtual environments. Ambient intelligence and remote big data management tools, cloud-based robotic cooperation and industrial cyber-physical systems, and environment mapping and spatial computing algorithms improve IoT-based real-time production logistics and cooperative multi-agent controls in smart networked factories. Context recognition and data acquisition tools, generative AI and cyber–physical manufacturing systems, and deep and machine learning algorithms shape smart factories in relation to virtual path lines, collision-free motion planning, and coordinated and unpredictable smart manufacturing and robotic perception tasks, increasing economic performance. This collective writing cumulates and debates upon the most recent and relevant literature on cognitive digital twin-based Internet of Robotic Things, multi-sensory extended reality and simulation modeling technologies, and generative AI and cyber–physical manufacturing systems in the immersive industrial metaverse by use of evidence appraisal checklists and citation management software.

Human resources in companies are gaining increasingly more strategic meaning by its ability to influence reaching company goals. The task of a manager is to understand the fact that every employee is different, has different needs, goals, and ambitions, is motivated by something else in every stage of career ladder. The aim of the paper is to define the influence of education in building the employee’s career. The presumption if the level of education has influence on the career motivation factors is verified on the sample of 3,720 respondents. The results of the research have confirmed that the employee’s career is influenced by the level of education significantly. Motivation factors education and personal growth, applying own skills, self-fulfillment, and autonomous decision-making are perceived differently in terms of importance and gender. Therefore, it is recommended the company managers to include into leading of employee’s career also the level of education in the context of gender that influences employee’s needs and interests.

Today´s world is reflected in words such as globalization, economic crisis, market economy and competitiveness. All these influence business entities. An enterprise that does not keep pace with current trends, innovates, seek improvements in quality or assess the effectiveness of its activities, is at risk of stagnating. Similar trends also prevail in logistics enterprises in Slovakia. The aim of this study was to analyse organizational culture in logistics enterprises because it is one of the key factors affecting the quality of the products and the overall competitiveness of an enterprise. Utilizing the Organizational Culture Assessment Instrument (OCAI) we diagnosed the dominant trend within Slovak logistics enterprises. On the whole these enterprises have a hierarchical organizational culture. However, employees are of the opinion that there should be a more familial work environment, typical of a clan organizational culture. Whilst enterprises continue to underestimate this factor, they will miss an important tool to achieve better success rates in a tough competitive environment.

The COVID-19 pandemic has negatively influenced all areas of human life across the world. Economic downturn is evident in almost every country. However, the biggest impact has crisis on micro and small enterprises (MaSEs). As the change of regime and rhythm of work is coming, the important task of employees in management is to retain their subordinates in the state of positive setting and motivation. The aim of the research is to define the impact of pandemic COVID-19 on the level of employee motivation in MaSEs operating in Slovak Republic. The development of employee motivation was investigated in three fields, financial, working and relationship one. A total of 848 respondents were asked in 2017 to 2020 by means of stratified selection. There was a significant decrease of preferences of respondents in all investigated motivation factors. Testing confirmed the existence of statistically significant differences during 2020 in comparison with previous years in investigating the following motivation factors: basic salary, job security, good working team, communication at work and superior's approach. The main contribution of the research is the finding that pandemic COVID-19 has the influence except of other impacts also on the area of employee motivation.

Motivating the employees is considered one of the essential manager’s skills. Knowledge of powerful motivation factors allow managers to motivate employees effectively. It results in motivated employees able to affect a success of enterprises and its competitive advantage. Following the research carried out using 34,000 Slovak employees, the importance of motivation factors relating to finance was defined. Tukey’s HSD test, as a part of the ANOVA analysis, was used for extensive investigation into the most important motivation factors relating to finance. It is supposed that motivation of employees of different gender, age and job position will differ. The suppositions were confirmed by the results achieved in the research showing significant differences between individual employee categories of managers, blue-collar workers and white-collar workers. Taking into consideration the results, managers are suggested to concentrate on motivating the employees as parts and not as a whole because of the differences in the needs of employees in terms of gender, age and mainly job position.