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Nowadays, we live in the fourth industrial revolution (the so-called digital revolution), which is fundamentally reshaping industry and business as well as the economy and civil society. Within the research activities of the National Laboratory for Social Innovation project, a research plan has been drawn up taking into account the quadruple helix model. The aim of this research is to map the social impacts of digitalisation based on the perspective of Hungarian experts. The research aims to map the social impact of digitalisation, whether the perception of the impact of digitalisation on society depends on the individual perceptions of the experts involved in the research (age, education) or organisational (sector of the organisation represented). The research seeks to answer the following research questions: Q1. How can the social impact of digitalisation be described? Q2. Do individual (age, education) or organisational (sector of the organisation represented) characteristics influence the experts' opinion? Q3. Are there any significant relationships between experts' responses to questions on the social impact of digitalisation and, if so, how strong are they? The data analysed are the results of a qualitative and quantitative, empirical survey carried out in 2021 with experts from academia, government, business and civil society. The former was conducted in the form of focus group interviews with invited experts (n=9) and the latter, in the form of an online questionnaire survey (n=78) using descriptive statistics and relationship analysis methods (Cramer's V and Kendall's Tau). The results show that the majority of experts consider the social impact of digitalisation to be rather positive, highlighting for example more efficient problem solving. It can be shown that the development of digitalisation requires a well thought-out but not over-regulated framework. As the transfer of knowledge improves, the opportunities for those who use digital technologies increase, but so does awareness of its harmful effects. The results can guide digital policy makers in identifying key areas for intervention. [ABSTRACT FROM AUTHOR]

Global competitiveness emphasizes that nations with digitally literate and adaptable populations are likely to be more competitive in the global economy. In the contemporary global landscape, technology plays a pivotal role in economic growth, innovation, and competitiveness. Nations that prioritize the development of digital skills and foster a growth mindset among their populations are better positioned to thrive in the digital age. Moreover as technology continues to evolve, there is a need to understand how individuals integrate and adapt to new digital tools. Another significant aspect is that higher educational institutions can play a crucial role to ensure that graduates are well-prepared to meet the complex requirements of the new digital world. The aim of the research is to explore university students' digital intelligence (DQ) levels from the view of growth mindset. More specifically, understanding how the mindset of students contributes to their openness related to developing the different levels of DQ. The research applied Q-methodology, that allows to capture the diverse perspectives of students, providing a nuanced understanding of their openness to DQ maturity. Different individuals have distinct views on how it relates to a growth mindset, and the strategies they believe are effective for developing digital skills. Findings from this research offer implications for educational policies and curriculum development, ensuring that educational institutions are preparing students for the challenges and opportunities presented by the digital landscape. Moreover it allows educators to tailor teaching methods and curriculum design to enhance students' digital literacy and adaptability. It provides insights into the psychological and behavioral aspects of learning in a digital context. From a theoretical aspect the study contributes to understanding the cognitive processes involved in students' decision-making and attitudes towards different levels of DQ, considering the phenomenon of growth mindset. [ABSTRACT FROM AUTHOR]

In our digital age, the effects of digital transformation, the scope and speed of current changes, and the emergence of digital technologies have led to a radical transformation of workplaces, resulting in a reduction of demand for employees carrying out routine, manual tasks, while evokes a need for digitally-skilled employees emphasising the importance of digital and soft skills for business growth. Organisations need to equip their employees with different types of skills to achieve organisational goals in order to benefit from investments in digital technologies. While practitioners and academics are increasingly focusing on the importance of the human factor of digital transformation processes, there is limited knowledge about the impacts of digital transformation on the digital skills of the employee and how organisations can guide employees through the digital transformation journey, yet. This study provides an important insight into a specific country's context, which has not been sufficiently examined. This paper aims 1) to investigate how the digital transformation has changed the demand for human workforce (Q1a) and the challenge in the lack of digital skills (Q1b) and 2) to examine the importance of soft skills as an impact of digital transformation (Q2). The target group of the research is the managers and white collar workers of Hungarian manufacturing companies. The data collection was in spring 2021. Descriptive statistics and relationship analyses (Cramer's V and Kendall's Tau) were used to analyse the collected data (n=489). The research investigates an important social-digital phenomena determining how digital transformation arises significant demands on digital and soft skills. Results indicate that digital and soft skills such as critical thinking, complex problem solving, adaptability, resilience and creativity are essential to successfully exploit the digital transformation. The result can add value and stimulate new research on digital and soft skills and provide a useful benchmark for other countries. [ABSTRACT FROM AUTHOR]

One of the defining trends of our time is the rapid development and spread of artificial intelligence (AI) and machine learning. With the recent boom in digital innovation, AI is getting a bigger emphasis, brings new opportunities to tackle many issues within organizations and raises new challenges about its usage and limits. It is expected that more and more "smart" interconnected machines capable of situational awareness and independent decision-making will emerge. Large-scale projects are being launched all over the world including Hungary, for developing and applying automation and AI-based business solutions. AI and expert systems were already used in the fifties and later in the seventies and eighties, but results did not bring any breakthrough success. Thanks to technological development the situation has changed and many seemingly unsolvable problems (e.g. machine interpretation, facial recognition, diagnosis and prognosis of certain rare diseases) are progressing well. Beside "human" knowledge, "machine" and common "human-machine" knowledge play an increasing role, in addition to "human" creativity "machine" creativity gains ground. In the field of Knowledge Management (KM), both theoretically and practically important issues arise like how the development of technology affects KM or how AI can contribute to the organization of knowledge, and how it can facilitate and extend the future of knowledge workers. The research is intended to map the future of KM and knowledge workers in the light of the emergence of knowledge generated by emerging technologies. The research is carried out via qualitative methodology by conducting interviews that result in organizational case studies with respondents from various organizations operating in Hungary. Just as effective adaptation of KM and today's technological achievements play an essential role in the survival of companies, it can be a significant advantage if the knowledge created during application of emerging technologies is managed in some way. [ABSTRACT FROM AUTHOR]

Internet, social media, digital transformation, Internet of Things (IoT), smart technologies, artificial intelligence (AI) are increasingly part of people’s lives. Some of these have made our interaction with machines more effective and information more natural and more powerful. Others have helped companies tap into consumers' relationships, behaviors and innermost thoughts in powerful and often disturbing ways. In addition, automation and robotics provide the muscle for Industry 4.0. Beside the several positive aspects of using these new technologies the challenge is to reliably collect data concerning human knowledge, competences, attitudes and emotions towards the demands of Industry 4.0 as well as the possible intentions attributed to it. Companies are now facing the challenge of integrating AI and robots into their workforce by encouraging employees to work with their “robotic teammates”. Only a few studies have examined attitudes towards these new technologies or dealt with the assumptions in service providers, factories and manufacturing contexts. The current research identifies essential features and characteristics that have the potential to increase the acceptance of these networked cyber-physical systems and reduce prejudices. The study summarizes the first part of a major research project that aims to reveal the attitude and perception of company leaders towards digital transformation and Industry 4.0. The research is based on qualitative interviews with Hungarian company leaders. The main findings show that there is a great amount of uncertainty towards the upcoming changes in the world of work and a bit of anxiety as well, but as the change unfolds, the companies get more and more confident and willing to apply the new technologies. [ABSTRACT FROM AUTHOR]

Artificial Intelligence and Robotics, Industry 4.0 and Digitalization, Machine Learning and Big Data are defining nowadays' trends worldwide, moreover Artificial Intelligence has become the biggest buzzword these days. It has the potential to completely reshape tomorrow's workplace, but the main question is how. Business always wants to derive insights from information in order to make better, real time, fact- based decisions: there is a demand for depth of knowledge that drives the growth of big data tools. Organizations need to start managing knowledge through different sources, and integrating its usefulness via a range of technologies. In 1966 Polanyi argued that human knowledge and capability relied on skills and rulesets that are often beneath conscious appreciation (transmitted to the people via culture, tradition, evolution, etc.). The thesis of the book was summarized as "We can know more than we can tell". Many of the tasks people perform rely on tacit, intuitive knowledge that is difficult to codify and automate (Polanyi's paradox). In recent decades, focusing on understanding, capturing, sharing and applying tacit knowledge has been the focus of either national or international research. In the current state of technological development, machines become capable to learn and manage tacit knowledge. Beyond "human" knowledge, "machine" knowledge will play an increasing role. In the area of Knowledge Management, questions of both theoretical and practical relevance are emerging: Does this Polanyi's paradox interpret as an obstacle throughout technological improvement? What affects could Artificial Intelligence have on Knowledge management? How could Artificial Intelligence be accompanied with Knowledge Management facilitating and enhancing the future of knowledge workers? How could we apply and manage knowledge created by these new technologies? What are the differences between human and machine knowledge? The aim of the paper is to explore the theoretical and the practical background and limitations of Artificial Intelligence and Knowledge Management with particular emphasis on the role of human-machine tacit knowledge. [ABSTRACT FROM AUTHOR]

The interpretation of 'lean production' has been slowly shifting from technical to socio-technical aspects since its appearance. This is well illustrated by the growing number of expressions associated with lean like 'lean management' and 'lean thinking'. Seeking more advanced and at the same time more successful ways of lean implementation, researchers and practitioners discovered that carefully adding human, behavioural, management, leadership and many other soft elements in the lean melting-pot, will most likely improve application results. Still, despite all the efforts made, the sociotechnical definition of lean is still blurry, researcher-dependent and mostly not confirmed by evidence. This study introduces a unified, cultural definition of lean integrating the culture model of Schein and the lean model from Modig and Åhlström. It shows that lean could be interpreted in different abstraction levels, as basic underlying assumptions, espoused values, methods and tools, giving an interrelated definition for each. The study also presents the findings of an empirical quantitative questionnaire research verifying the 'lean culture' definition and identifying correlations between 'lean culture', corporate competitiveness and corporate characteristics, based on information from 193 participating Hungarian medium and large sized industrial companies. The data show that the underlying assumptions of lean culture named Objective waste elimination, System level rationalization and Vision is improvement are significantly correlated with the components of corporate competitiveness. The findings draw attention to the soft, cultural side of lean production implementation and give practical advice on methods how to shape and control the cultural aspects of the implementation process to improve the chances of success. [ABSTRACT FROM AUTHOR]

In the era of knowledge economy, knowledge is increasingly seen as the most important strategic asset. A significant part of the knowledge possessed by an organization is within the knowledge workers. Thus, it is important to understand what encourages and what holds back individuals from sharing knowledge. Employees' willingness to share knowledge can be influenced by individual factors like people behaviours, motives and characteristics. Emotional intelligence can be one of the individual factors that can play an important role in forming their knowledge sharing endeavours. The paper aims to reveal the relationship between emotional intelligence and knowledge sharing of employees of Hungarian organizations. More specifically the relationship between the factors of emotional intelligence such as Well-being, Selfcontrol, Sociability and Emotionality with the factors of knowledge sharing Altruism, Reciprocity, Reputation, Loss of Knowledge and Organizational reward have been investigated. Furthermore the study sheds light on the role of individual characteristics such as gender, generation, qualification and tenure considering size of the organization. The research has been carried out among more than 200 Hungarian employees from different industries. Significant positive relationship can be identified between employees' emotional intelligence and knowledge sharing behaviour. Well-being, Emotionality, Selfcontrol and Sociability as emotional intelligence factors show relation to Altruism, Loss of knowledge and Reputation. Among individual factors, differences can be identified regarding generation and position, while gender and education do not seem to play a significant role in this relationship. Regarding organizational characteristics, differences can be detected according to the size of the organization. The outcome of the research can help companies, managers and HR specialists to learn how to trigger knowledge sharing behaviour according to gender and position while taking the size of the organisation into consideration. The paper reviews the results of the empirical study and concludes with a discussion of a potential new research direction and practical implications. [ABSTRACT FROM AUTHOR]