Factors Affecting the Efficiency of Teaching Process in Higher Education in the Republic of Serbia during COVID-19 info:eu-repo/semantics/article https://phaidrabg.bg.ac.rs/o:29608 doi:10.3390/su132312935 ISSN: 2071-1050 Sustainability 13(23) Kuleto, Valentin Ilić, Milena P. Popović Šević, Nevenka Ranković, Marko Stojaković, Dušan Dobrilović, Milutin Keywords: distance learning systems (DLS); higher education institutions (HEI); work from home (WFH); human resource management (HRM); COVID-19; principal component analysis (PCA) http://creativecommons.org/licenses/by/4.0/legalcode application/pdf 323591 bytes eng 2021 Abstract: From the moment the Republic of Serbia declared a state of emergency in the summer semester of 2019/2020, higher education institutions (HEIs) used various teaching models from Distance Learning Systems (DLS), online platforms and modern information and communication technologies (ICT), to sending materials via student e-mails and notifications via faculty portals. Using survey research as a method, the paper describes the experiences of teachers and associates at HEIs in Serbia (780 respondents) regarding the efficiency of provided education services. In this article, we used the method of content analysis and participatory observation, as well. We analysed the attitudes of teachers and associates apropos the efficiency of providing educational services through the work from home (WFH) model and distance learning (DL) and other models used in response to COVID-19 epidemiological measures in education. During the WFH setup, we looked for factors that affect educational efficiency. When it comes to the statistical technique, factor analysis was selected. Technology, managerial support, and work–home conflict are all expected to impact process efficiency, so these were the first criteria considered when selecting potential factors. Principal Component Analysis (PCA) was used as the extraction method, and the Varimax rotation method was also used. We discarded all factors with eigenvalues below one. Four factors caught our attention: School management support, Family–work conflict, Home infrastructure, and Technology choice. The results showed that F1 (School management support) is positively correlated to F2 (Family–work conflict) and efficiency and negatively correlated to F3 (Home infrastructure). Conversely, F2 is negatively correlated to F3 and positively correlated to efficiency. The F4 factor shows no significant correlations to other factors