On average, approximately 22 thousand tons of new lubrication oil were marketed annually in Serbia in the period 2015–2019. Less than 20% of the waste lubrication oil (WLO) generated was treated, whereas the remainder was mostly uncollected or improperly disposed of. The purpose of this study is to examine different WLO management scenarios that could be implemented in Serbia in the future and to quantify their potential environmental benefits. Different WLO treatment processes (namely the re-refining of used oil for base oil recovery, the use of WLO as a substitute to fossil fuels in cement kilns, and the combustion of WLO in waste incinerators with energy recovery) were evaluated using the life cycle assessment (LCA) and ReCiPe 2016 impact assessment methods. The LCA results obtained indicate that no single WLO treatment process consistently exerts diminished environmental impacts according to all the impact categories considered. From a human health perspective, the incineration of WLO in waste incinerators was found more favourable than the other treatment processes considered, whereas the combustion in cement kilns was the most favourable approach with regard to ecosystem protection. In terms of fossil fuel savings, re-refining technologies performed slightly better than the other processes considered. This can be accounted for by significant amounts of marketable co-products generated in the re-refining process, which can be used as a substitute to fossil-based primary products. Furthermore, a total of four possible WLO management scenarios were developed on the basis of the annual quantities of untreated WLO and a mix of treatment options. The results obtained indicate that up to 22,100 t CO₂ equivalent and 34,300 t oil equivalent could be saved annually in Serbia provided the most favourable WLO management scenario is considered.

The research on Bus Fleet Management (BFM) has undergone significant changes. It is unclear whether these changes are accepted as technological change or as a paradigm shift. Perhaps unintentionally, BFM is still perceived as routing and scheduling by some, and by others as maintenance and replacement strategy. Therefore, the authors conducted a Systematic Literature Review (SLR) to overview the existing concepts and school of thoughts about how stakeholders perceive the BFM. The SLR post-study exposed that BFM should be acknowledged as a multi-realm system rather than a uniform dimension of fulfilling timely service. Nonetheless, the work encapsulates BFM evolution which shows the need for the multi-realm research abstracted as "Bus Fleet Mobility Management" and "Bus Fleet Asset Management". The difficulties of transport agencies and their ability to switch from conventional to Zero-Emission Buses (ZEBs) illustrates why we propose such an agenda, by which the research is validated through needs both in academia and in practice.

As a consequence of the application advanced maintenance practices, the theoretical probability of failures occurring is relatively low. However, observations of low levels of market intelligence and maintenance management have been reported. This comprehensive study investigates the determinants of maintenance practices in companies utilising hydraulic machinery, drawing on empirical evidence from a longitudinal questionnaire-based survey across the West-Balkan countries. This research identifies critical predictors of technical and sustainable maintenance performance metrics by employing the CA-AHC (Correspondence Analysis with Agglomerative Hierarchical Clustering) method combined with non-parametric machine learning models. Key findings highlight the significant roles of the number of maintenance personnel employed; equipment size, determined on the basis of nominal power consumption; machinery age; and maintenance activities associated with fluid cleanliness in influencing hydraulic machine maintenance outcomes. These insights challenge current perceptions and introduce novel considerations with respect to aspects such as equipment size, maintenance skills and activities with the aim of preserving peak performance. However, the study acknowledges the variability resulting from differing operational conditions, and calls for further research for broader validation. As large-scale heterogeneous datasets are becoming mainstream, this research underscores the importance of using multidimensional data analysis techniques to better understand operational outcomes.