This study investigates the impact of selected macroeconomic, demographic, institutional and educational determinants on youth unemployment rates in Europe, with special attention to effects of Active Labour Market Policies on unemployment dynamics. Dynamic panel data estimates have been done with the Generalised Method of Moments on data from 27 E.U. Members States plus Norway (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014). The results indicate significant impact of the main macroeconomic variables on youth unemployment rates, total unemployment rates and shares of young people (15-24 y.o.) neither employed nor in education or training. Other variables show various levels of significance, including variables which describe labour market policies (L.M.P.s). In all estimations, public expenditure in L.M.P.s as a percentage of gross domestic product has statistically significant impact on unemployment rates, with positive coefficients. However, opposite effects have been estimated when using the number of participants in L.M.P.s and public expenditure in L.M.P.s per unemployed person, which suggests that L.M.P.s better target the general unemployed population than the vulnerable group of the unemployed youth.

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Purpose: Employees and their work during non-work time are affected bytechnology development, societal changes and other factors that havean inherent impact on the employees’ attitude towards work during nonworktime. The purpose of this article is to provide an overview of the upto-date research on employees performing work during non-work time.Design/Methodology/Approach: The main methodological approachused in the article is a systematic literature review of 18 scientific articlesfound in citation databases in WOS, Scopus, etc. The collected literatureis relevant as it encompasses both quantitative and qualitative analysesto gather insights on performing work during non-work time.Findings: The results imply that work during non-work time is a growingphenomenon among employees and public employees are no exception.Regarding the socio-demographic groups affected, findings indicatethat work during non-work time is particularly common for employees inmanagerial positions and for professionals in education, health and policeservices, as well as for employees engaged in remote work. They alsoconfirm that employees work during non-work time at different times ofthe day, at weekends, and during their annual and sick leave.Practical Implications: The article is especially relevant for public employeesdue to increased use of information and communication technology.As such, they are also exposed to intensifying work-related expectationsand requests/pressures for flexible work arrangements.Originality/Value: The originality of the topic is reflected in the underrepresentationof scientific research on the performance of work duringnon-work time among public employees.    

Industries create specific business settings that exert a backward influence on industry prospects. In this paper, the manner in which two industries -the construction industry and the food and beverage processing industry -have behaved during a crisis period is examined and compared. First, the performance indicators available from statistic sources are compared; then, the panel data of the two subsamples of the largest Croatian firms in terms of capital and employment related to construction and food processing in the period 2005-2014 are subjected to comparison. The provided data demonstrate that the five largest business firms in the two industries have a tendency to employ different business behaviors specific to the industry they are part of. The basic idea behind this research was that industry characteristics are created by individual business firms through their adjusting their behavior, i.e. strategies, organizational design and operation models to perceived industry settings. So, in the longer time period, depending on resource availability at the firm level and the market opportunities in the industry, a dominant pattern of the business model will evolve. The research showed differences in the rate of the activity and business demography during the observed period. There is also evidence of different business models being employed in construction and food processing. However, at this stage of our research, we have not been able to establish a relationship between the business model employed and the firm´s or industry performance.

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