There is no denying that the COVID-19 pandemic resulted in significant stress worldwide and impacted practically every aspect of human activity. The impacts of this deadly virus on education are not seen as gaining much-needed focus from the scientific research community. The majority of educational institutions globally switched to online instruction during the COVID-19 pandemic. However, there were considerable differences in the technical readiness of various nations. In this regard, the study’s attempt to provide a way forward for how the educational sector ought to manage the challenges brought on by COVID-19 issues in support of online educational activities. Since some of the consequences that resulted have an impact on the educational sector, the answers presumably also should have included innovations that would improve scientific research to lessen its effects. Particularly, it appears there is still much that has to be done about the impact of the COVID-19 pandemic on the educational sector. Hence, this perspective review study aims to explore the potential relationship between the COVID-19 pandemic and the educational sector while suggesting a way forward.

The goal of this research is to determine whether hospital financial performance is impacted by particular management accounting techniques, such as departmental revenue budgeting, specific costing, and departmental costing. We analyzed several sets of performance indicators for 146 hospitals whose management accounting adoption status is available. An outlier test was used to determine which data were outliers at the 0.1% significance level, and the results were then eliminated in order to see if any extremely outlier values (hospitals) were present for each indicator. To determine whether there were any noteworthy variations in the average values of the several performance measures, we employed a t-test (two-tailed probability). The results suggest that departmental revenue budgeting and departmental and specific costing improve hospital financial performance.

This research conducts a comparative urban analysis of two coastal cities with analogous tourism models situated in distinct geographical regions: Balneário Camboriú in Brazil and Benidorm in Spain. The study delves into two critical urban phenomena impacting the sustainability of tourist cities, utilising social network data to gather insights into economic and urban activities (Google Places) and spatio-temporal patterns of citizen presence (Twitter). The spatial analysis explores the municipal and, to a more detailed extent, the coastal strip extending 500 m inland from the coastline, spanning the entire length of each city to their municipal boundaries. The analysis uncovers both similarities and differences between the two destinations, offering insights that could inform future development strategies aimed at fostering sustainable urban environments in these well-established coastal tourist areas.

Knowledge transfer, assimilation, transformation and exploitation significantly impact performing business activities, developing innovations and moving forward to new business models such as transferring to a circular economy. However, organizations’ decisions or willingness to transition to a circular economy are very often also influenced by the external environment. The study aims to determine the influence of the external environment on the transfer from a linear to a circular economy while mediating knowledge assimilation. The quantitative research involved 159 Nordic capital companies operating in Estonia and Lithuania. The survey has been performed by means of the CATI method. The analysis has been done also by applying structural equation modelling (SEM). In order to perform mediation analysis, IBM SPSS and a special PROCESS macro have been used. The study showed that knowledge assimilation partially mediates the relationship between the external environment and the transfer to the circular economy. Hence, the external environment’s direct effect is much more significant than the indirect. The added value of the study also consists in extending the concept of circular economy by including some aspects of absorptive capacity and the external environment.

Outsourcing logistics operations is a common trend as businesses prioritize core activities. Establishing a sustainable partnership between businesses and logistics service providers requires a systematic approach. This study is needed to develop a more effective and adaptive framework for logistics service provider selection by integrating diverse criteria and decision-making methodologies, ultimately enhancing the precision and sustainability of procurement processes. This study advocate for leveraging industry-based knowledge in procurement, emphasizing the need to define decision-making elements. The research analyzes nearly 300 logistics procurement projects, using a neural network-based methodology to propose a model that aids businesses in identifying optimal criteria for evaluating logistics service providers based on extensive industry knowledge. The goal of this study is to develop and test a practical model that would support businesses in choosing most suitable criteria for selection of logistics service providers based on cumulative market patterns. The results of this study are as follows. It introduces novel elements by gathering and systematizing unique market data using developed data processing methodology. It innovatively classifies decision-making elements, allocating them into distinct groups for use as features in a neural network. The study further contributes by developing and training a predictive model based on a prepared dataset, addressing pre-defined goals, expectations related to green logistics, and specific requirements in the tendering process for selecting logistics service providers. Study is concluded by summarizing suggestions for future research in area of adopting neural networks for selection of logistics service providers.