RESUMEN

The profound ramifications stemming from a multitude of global events and the ongoing progression of the fourth and fifth industrial revolutions necessitate a broadening of skillsets beyond the mere acquisition of technical and digital proficiencies. The practical, intelligent, responsible, and sustainable utilisation of technologies relies exclusively on human agency. Such employment necessitates a type of cognitive processing that machines find arduous, emphasising the importance of aligning human reasoning with machine intelligence. The significance of digital skills is widely acknowledged within the framework of cultivating suitable sets of employee abilities. Nonetheless, it is imperative to underscore the importance of human skills as they remain irreplaceable by robots. Furthermore, the labour market acknowledges and rewards these skills owing to their capacity to confer flexibility and adaptability, thereby embodying the competing attributes of the future workforce. In light of the prevailing circumstances outlined in Industry 5.0-characterised by an amplified utilisation of technologies and diminished interpersonal interactions resulting from the pervasive impact of the Covid-19 pandemic-this study seeks to provide a theoretical description of the significance of soft skills and their categorisation, while investigating the practical demand for such skills. The dataset used in this study encompasses information pertaining to skill prerequisites extracted from job posts published on a job portal over five years, encompassing 19 000 distinct organisations. The findings of our study revealed that within technologically driven domains, there is a discernible demand for soft skills, such as critical and analytical thinking, problem-solving, communication skills, and creativity with flexibility. Furthermore, our results indicate that individuals must possess balanced proficiency in both soft and digital skills to thrive in a future characterised by technological advancements.

RESUMEN

The need to evaluate suppliers from the perspective of risk analysis by purchasing companies is increasing. Such evaluation of suppliers is conducted primarily by production companies with implemented quality (QMS), environmental (EMS), health and safety management systems (H&SMS), as well as Toyota Production System (TPS). This article aims to examine latent factors for suppliers' evaluation and to describe the intensity of these factors by the implemented management system. The article provides the results of empirical research conducted with the computer-assisted telephone interviewing (CATI) technique in 151 medium and large manufacturing companies operating in Poland. The risk was classified into three main groups to deepen the research process: management system risks, environment risks, and process risks. This allowed for the formulation of some original conclusions. The results showed that companies implementing standardized management systems take the issue of risk analysis and management more seriously than organizations that do not implement such systems. The research also highlighted the differences in the perception of risk caused by implementing various management systems. The study also found that the industry and business profile specificity also affect the risk assessment in cooperation with suppliers.

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RESUMEN

Although there are several articles that have carried out a systematic literature review of the analytical hierarchy process (AHP), many of them work with a limited number of analyzed documents. This article presents a computer-aided systematic literature review of articles related to AHP. The objectives are: (i) to identify AHP usage and research impact in different subject areas; (ii) to identify trends in the popularity of the AHP from the first introduction of the method in 1980 to the present; (iii) to identify the most common topics related to AHP and topic development over time. We process 35,430 documents related to AHP, published between 1980 and 2021, retrieved from the Scopus database. We provide detailed statistics about research interest, research impact in particular subject areas over the analyzed time period. We use Latent Dirichlet Allocation (LDA) using Gibbs sampling to perform topic modeling based on the corpus of abstracts. We identify nine topics related to AHP: Ecology & Ecosystems; Multi-criteria decision-making; Production and performance management; Sustainable development; Computer network, optimization and algorithms; Service quality; Fuzzy logic; Systematic evaluation; Risk assessment. We also present the individual topics trends over time and point out the possible future direction of AHP.

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