This paper presents an innovative use case of virtual reality (VR) for career development and exploration, within the context of the CareProfSys recommendation system for professions. The recommender users receive recommendations not only in textual format but as WebVR gamified scenarios as well, having thus the possibility to try activities specific to the suggested professions and decide whether they are suitable for them or not. This paper describes, from a functional and technical point of view, scenarios for six different jobs: computer network specialists, civil engineers, web and multimedia developers, chemical engineers, project managers, and university professors. Extended experiments were performed, using an internal protocol, with 47 students enrolled in engineering studies. The results of the experiments were measured with the aid of four instruments: two questionnaires, one unstructured interview, and the VR simulation performance recording module. Positive results were obtained: the users admitted that such a tool was useful when choosing one’s career and that it was entertaining. Most of the students considered the VR scenarios as learning or testing experiences, too. Thus, we claim that a VR form of providing job recommendations is more appealing to young people and brings value to career development initiatives.

Professionalization of work represents the process of transforming an occupation into a profession with a high degree of integrity and competence, requiring the existence of professional qualification frameworks, standards, and nomenclatures to describe the necessary skills, abilities, and education for an individual to have a fruitful career. The current study provides details on professions from the engineering domain that are modeled using a prototype ontology tailored to the context of Industry 4.0 in the Romanian landscape. Our ontology represents the foundations for providing personalized recommendations to find suitable professions in the Romanian job market while illustrating the importance of AI tools to support career development.

We propose an empirical analysis of the clustering phenomenon in the Eastern part of Romania as a relevant example to support the idea that the question of clusters in lagging regions, usually with economic structures dominated by mid-tech and low-tech industries, could become an interesting niche for cluster-devoted research in forthcoming years. The specific features in two lagging Romanian regions have been investigated by means of geographic information systems, followed by an interview-based qualitative inquiry. The findings indicate that, despite its great potential, the clustering process has not yet reached an upper-level stage; it is still in a ‘start-up’ phase with a series of ‘economic agglomerations’ that could be mostly considered of a static-cluster type. Subsequent reflections on support policies suggest that local production systems of industrial-district type are an appropriate organisational form for cluster development in the two analysed regions, with a special emphasis on ‘soft’ measures that are able to strengthen the local networks and to ensure cluster identity.

A risk evaluation model for IT projects using fuzzy inference is proposed. The knowledge base for fuzzy processes is built using a causal and cognitive map of risks. This map was specially developed for IT projects and takes into account the typical lifecycle and the risk taxonomy created by the Software Engineering Institute. The model was used to compute the technological risk of an e-testing project. This project was positioned on the middle level of the risk map, implying that the probability of encountering technological difficulties depends on the number of technologies used and their market maturity. A software system for validating the model was also developed.