This article presents a bibliometric analysis of scientific publications investigating technological megatrends at the societal level, through the parallel analysis of 549 documents from Scopus and 291 documents in Web of Science (WoS) using the VOSviewer software and the Excel component of the MS Office 365 package. The main purpose of this study was to obtain an overview of the evolution of the research on the subject of technological megatrends from the perspective of interest, domains, geographical areas, sources, authors and cocitation networks, research clusters of countries, and cluster-related concepts. The results showed that publications on technological megatrends started in 1982, but from a scientific point of view they started in 1983 (Scopus) and 1984 (WoS), and that they display an increasing trend after 2010. Technological Forecasting and Social Change, Nature, SAE Technical Papers, VDI Berichte, Harvard Business Review, Advances in Intelligent Systems and Computing, and Sustainability represent the most important sources, and Gibbs, Kraemer, Dedrick, Kim, Chmiela, Sauceda, Müller, Tkatchenko, Pratt, Sarmiento, Montes, Ogilvie, Marcus, Perez, Brownson, D. Mourtzis, M. Doukas, and Bernidaki are the most notorious researchers in the field. At the societal level, technological megatrends are closely related to foresight, globalization, industry 4.0, the internet of things, digitalization, technology, artificial intelligence, innovation, the future, and sustainability. This study is original and useful for researchers in the context of the lack of similar studies on this subject.

In this paper, we want to examine how unemployment impacts social life, and, by using datasets from six European countries, we analyze the effect of unemployment on two of the main aspects of social life: social exclusion and life satisfaction. First, we predict unemployment rates using the Auto Regressive Integrated Moving Average (ARIMA) model and the results are further used in a linear regression model alongside social exclusion and life satisfaction data, thus obtaining the hybrid model. With the help of the point prediction method, we use the hybrid model to predict new values for the two aspects of social life for the upcoming three years and we analyze the results obtained in order to better understand their interconnection. The results suggest that unemployment has particularly adverse effects on the subjective perception of life satisfaction, furthermore increasing the social exclusion percentage.

This paper aims to identify to what extent artificial intelligence (AI) is biologically limited and to launch a debate on the issue of overcoming these limitations. To achieve our goal, we utilized a qualitative research methodology framework, providing an in-depth analysis of AI limitations formulated by prominent scholars within this field of specialization. We found that the biological boundary imposes a double limitation on AI, both from a gnoseological perspective and from a technological perspective. This twofold limitation of AI underpins the idea that as long as the biological cannot be understood, formalized, and imitated, we will not be able to develop technologies that mimic it. By adopting an original approach, our research paper focused on mapping out the twofold limitation of the biological with reference to the success of AI. Special attention was paid to the motivational analysis of this limitation in terms of human existence, the opportunity and utility to create artificial intelligences as superior to the human-like condition. We have opened the door for future debates on the need to decode cellular communication by understanding and developing a natural language of the living cell (N2LC). Based on the present research, we proposed that within the current technological context, biological computers (biocomputing) could represent a so-called invisible hand outstretched by biological systems towards AI.

In this article, we address a variant of the vehicle routing problem which occurs in real-life applications, called the clustered vehicle routing problem. The clustered vehicle routing problem (CluVRP) looks for an optimal collection of routes, with respect to cost minimization, for a fleet of vehicles, fulfilling all customers’ requirements which have a particular structure being divided into clusters, the capacity constraints of the vehicles and with the additional constraint that all the customers belonging to the same cluster must be visited consecutively before leaving the cluster. We propose a novel approach for solving the problem using a decomposition-based method which splits the CluVRP into two easier subproblems. The results of the computational experiments on three sets of benchmark instances from the literature show that our approach is competitive in comparison with the known solution approaches published to date.

Although risks are present in any organisation and the importance of their study is obvious, the authors find that risk analysis is an area still in its infancy, as reflected in the small number of existing publications on this topic. Human resources tend to understand risk in an elementary way. The ability of human resources to perceive risk is the ability and competence to identify a potential threat that does not always appear. Aim: The aim of the this chapter was to provide additional knowledge on human resource competencies, in order to avoid the emergence and spread of risks at the organisational and cyber level. Methodology: The authors used the quantitative–comparative analysis, by presenting all the details regarding the competencies of the human resource in order to manage the risks at organisational and cybernetic level. Findings: The findings of this chapter show that the compulsory competencies of the human resource influence both the general competencies and the special competencies: information technology and communications, security ethics and economic ones. These, in turn, can improve or diminish cyber security competencies by almost 50%. Originality of the Study: This study is highlighted by results obtained from the analysis of the capacity of human resources, to integrate theoretical knowledge and practical competencies on the perception of cyber risk. Of particular importance for this research are the analysis of data and the interpretation of results on human resources competencies. In this sense, throughout the chapter are assessed the skills of human resources, necessary for the management of cyber risks at the organisational level. In terms of future research implications, it could be important research to identify a method of assessing the competencies acquired by human resources applied from the perspective of cyber risk.