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This bibliometric mapping study aimed to provide comprehensive insights into the global research landscape of cybernetics. Utilizing the biblioshiny function in R Studio, we conducted an analysis spanning 1958 to 2023, sourcing data from Scopus. This research focuses on key terms such as cybernetics, cybernetics systems, complex adaptive systems, viable system models (VSM), agent-based modeling, feedback loops and complexity systems.

The analysis leveraged R Studio’s biblioshiny function to perform bibliometric mapping. Keyword searches were conducted within titles, abstracts and keywords, targeting terms central to cybernetics. The timespan, 1958–2023, provides a comprehensive overview of the evolution of cybernetics-related literature. The data were extracted from Scopus to ensure a robust and widely recognized source.

The results revealed a rich and interconnected global research network in cybernetics. The word cloud analysis highlights prominent terms such as “agent-based modeling,” “complex adaptive systems,” “feedback loop,” “viable system model” and “cybernetics.” Notably, the journal Kybernetes has emerged as a focal point, with significant citations, solidifying its position as a key source within the cybernetics research domain. The bibliometric map provides visual clarity regarding the relationships between various concepts and their evolution over time.

This study contributes original insights by employing advanced bibliometric techniques in R Studio to map the cybernetics research landscape. The comprehensive analysis sheds light on the evolution of key concepts and the global collaborative networks shaping cybernetics research. The identification of influential sources, such as Kybernetes, adds value to researchers seeking to navigate and contribute to the dynamic field of cybernetics. Furthermore, this study highlights that cybernetics not only provides a useful framework for understanding and managing major economic shocks but also offers perspectives for understanding phenomena in various fields such as economics, medicine, environmental sciences and climate change.

Following the COVID-19 pandemic, the issues related to job insecurity became even more prominent than before. This paper sets out to identify the determinants of job insecurity in the context of the COVID-19 pandemic among Romanian workers, a topic than was scarcely addressed in previous studies.

Based on a representative sample at the national level (N = 744), the authors performed a multilinear regression analysis that pinpoints the factors predicting job insecurity.

This study findings indicate that high-skilled workers employed on permanent arrangements, having higher workloads, who had received organizational support, and managed to harmonize work demands with family responsibilities experience the lowest levels of job insecurity. In this study, teleworking does not influence the level of job insecurity. Gender (being male), working in the public sector and approving the political management of the COVID-19 pandemic also count in securing the feelings employees have about their job.

Besides filling a geographical gap in the literature, another innovative contribution of the paper is the emphasis on the importance for the employees of how public authorities manage the public health crisis. Also, this study explores the workload as a factor of job insecurity which was unaddressed previously. Implications for research and practice are emphasized.