Purpose: The purpose of this paper is to identify the factors which determine the level of public employees' job satisfaction and as result help to have effective and efficient management system in the public sector, in developing countries such as Turkey.Design/methodology/approach: Based on theoretical considerations, a model was proposed linking the employee satisfaction and loyalty (ESL) constructs. The paper exhibits the findings of a satisfaction and loyalty survey of employment factors within the Turkish public sector. The survey was conducted in 2009 and covered 220 employees within the Istanbul Branch of a Social Security Institution in Turkey. A model was developed by including effecting factors of employee satisfaction, their relations and effects of employee satisfaction on employee loyalty. Partial least squares structural equation model was employed to test the model in the public insurance sector in Turkey.Findings: Data analysis reveals that there is a strong relationship between ESL in a branch of a public sector Social Security Institution in Turkey. Training and personal development was found the most effecting factor of customer satisfaction. The study also finds a positive relationship between working conditions and satisfaction.Originality/value: The paper reveals the relationship between the employee satisfaction and affecting factors in the public sector in Turkey. These factors are developed only incidentally in the public sector in Turkey. Human resource management (HRM) applications such as measuring employee satisfaction, performance development are widely used in private sector. Specifically, in developing countries such as Turkey, these applications are rarely used in the public sector. Therefore, the paper advocates the use of HRM applications in the public sector in a developing country.

Scalability is a key feature of reconfigurable manufacturing systems (RMS). It enables fast and cost-effective adaptation of their structure to sudden changes in product demand. In principle, it allows to adjust a system's production capacity to match the existing orders. However, scalability can also act as a "safety buffer" to ensure a required minimum level of productivity, even when there is a decline in the reliability of the machines that are part of the machine tool subsystem of a manufacturing system. In this article, we analysed selected functional structures of an RMS under design to see whether they could be expanded should the reliability of machine tools decrease making it impossible to achieve a defined level of productivity. We also investigated the impact of the expansion of the system on its reliability. To identify bottlenecks in the manufacturing process, we ran computer simulations in which the course of the manufacturing process was modelled and simulated for 2-, 3-, 4- and 5-stage RMS structures using Tecnomatix Plant Simulation software.

Social networks have become popular among researchers and scientists. Specialized platforms for researchers offer many metrics and indicators which are used to evaluate various scientists and assess the strength of their impact. In this article the authors perform systematic comparison between the main university level ResearchGate (RG) metrics: total RG Score, number of publications, number of affiliated profiles and ARWU. A tool for acquiring the RG metrics of research units and a framework for calculating alternative university ranks was implemented and tested. As a point of reference the ranking system of the Academic Ranking of World Universities (ARWU, 2019) was used. The authors used a web scraping technique to acquire data. Data analysis was based on Spearman's rho and multiple linear regression (MLR). Ten additional ranks were developed and compared with the benchmark ranking. The k-means clustering method was used to identify the groups of ARWU universities. The research results show that the metrics provided by specialized social networks can be used for the assessment of universities, however, an in-depth evaluation requires a more advanced procedure and indicators to measure many areas of scholarly activity like research, integration, application, teaching, and co-creation. Clustering method showed also that the distance between the ARWU universities measured in values of RG metrics are bigger for the top of the ranking. The university authorities should encourage researchers to use specialized social networks, and train them how to do it, to promote not only their own achievements, but also to increase the impact and recognition of their respective research units. At the end of the article some limitations of the method used and some practical recommendations for the university authorities were formulated.

The concept of Industry 4.0 is becoming more and more popular all over the world. The implementation of its assumptions in business practice changes the way companies operate. The enormous innovative potential of the Industry 4.0 concept and the intensive use of processes based on the implementation of advanced technologies in its assumptions have an impact on various industries in each country. The article attempts to analyze the critical factors for the implementation of Industry 4.0 in Kazakhstan. Primary and secondary data sources were used for this purpose. The majority of existing government initiatives and reports do not reflect the actual situation. Additionally, these materials do not always represent the experiences or positions of all the parties involved. Opinions of companies and organizations implementing Industry 4.0 solutions remain unexplored. The primary goal of the paper is to fill the cognitive gap by analyzing stakeholder responses and identifying the actual level of their awareness of the development of Industry 4.0. An additional intention of the authors was to empirically establish barriers that companies face while implementing the most desirable technologies, as well as to establish other critical factors, taking into account the specificity of the country under study. The results of the research can be used by policymakers, scientists and other stakeholders to develop forecasts and strategic plans, as well as to develop and conduct further research on the implementation processes of Industry 4.0 in Kazakhstan.