Мониторинг экономики образования. Информационно-аналитический материал
Purpose The purpose of this paper is to provide an understanding of how two types of informal social networks – those related with instrumental purposes of information sharing and those related with expressive purposes of interpersonal trust – impact teachers’ job satisfaction.
Design/methodology/approach This paper utilises social network analysis (SNA) degree and betweenness measures and job satisfaction scales from the Job Diagnostic Survey to collect longitudinal data from employees in one of the vocational schools in Saint Petersburg, Russia via structured interviews. Data on a total of 354 ties were analysed for 40 ego networks in 2018 and 33 ego networks in 2019.
Findings The obtained results partially confirm the positive effect of teachers’ position in instrumental and expressive networks on job satisfaction. More centrally positioned teachers were more satisfied with peers and colleagues. They fell more secure in regards to job security, given the unique and multi-faceted knowledge they possess. Structural diversity of the network, as well as the category of a teacher (core subject or vocational subject), are found to explain the uneven evolvement of network size. The authors argue that the decrease in network size can be treated as a positive externality of changes in an informal network. The variation in teachers' experience seems to explain both job satisfaction and network composition.
Research limitations The paper is based on a case study and its findings are limited to one particular organization. Nonetheless, the proposed SNA application is of potential value for similar organisations in terms of enhancing their capacity to benefit from networks. This study utilizes a structured interview to collect network data and job satisfaction data. However, overt observation or secondary data on written communication (e-mail, reports) may provide additional insights about the sought impact in the context of school.
Practical implications Both teachers and managers benefit from the results of the paper. Educational policymakers and schools' administration can exploit the bird's eye view on an organization that SNA provides. By identifying focal employees and their attitude towards school, one receives an opportunity to prevent structural holes, organizational conflicts and uneven distribution of workload. Novice teachers can nurture their well-being by enhancing personal and instrumental social networks at the start of their career. Experienced teachers benefit from social cooperation as it fosters the exchange of experience and skills, which is vital for job retention.
Originality/value This research extends our understanding of the role of different kinds of social networks in teachers’ job satisfaction. The article provides new insights into the SNA application to vocational schools and developing economies. Authors address teachers’ informal networks both from ego and complete network analyses to provide the holistic, yet detailed view. The use of longitudinal data advances the understanding of how personal and group networks develop over time.
The paper analyzes the results of the systems project Training Workers to Comply with the Requirements of High-Tech Industries Using Dual Education, organized by the Agency for Strategic Initiatives in 13 subjects of the Russian Federation. Dual education implies “dual” institutional consolidation of knowledge obtained in vocational education programs: theory is normally learned at a vocational school, while an apprenticeship is taken within a company, in a real-life working environment. It is shown that the best practices of dual education can be found in the growing sectors. The most successful implementation of the dual model is observed in the regions of Russia that have seen their investment climates improved, their barriers for businesses reduced, and the quality of their public administration increased. Effectiveness of the dual model is largely contingent on the economic motivations of employers investing in a staff training system within the framework of large-scale investment and technology upgrade projects. As employers’ associations are weak, the decisive role in the coordination of efforts between businesses and professional educational institutions is played by regional authorities and governor’s councils, which have virtually grown into substitutes for German chambers of industry and commerce. Nationwide vocational education projects have promoted further development of the dual model due to organizational and financial support from study and career clusters. The best dual education practices should only be spread to regional industries that have the necessary economic and infrastructure premises for companies to invest in such a staff training system.
The article provides an overview of the best practices of the European Union in the field of vocational education and training (VET). The selected projects from vocational educational organizations in Germany, Denmark, Ireland, the Netherlands, Norway, Croatia and some other countries deal with training workers for high-tech sectors of economy, as well as for reintegration of yearly school leavers to education. Particular attention is paid to the mechanisms of public-private partnership in the field of VET, the most effective organizational solutions and models of cooperation among educational organizations, business structures and governmental bodies. The best foreign experience in the field of qualified employees’ training for the post-industrial economy, as well as in the field of social inclusion, can be used for the development of the VET system in the Russian Federation.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.