The main purpose of the paper is an expert assessment of the relationship existing between selected indicators carried out using a relatively new tool in economic sciences: Fuzzy Cognitive Maps. The effect of its application is a graphical presentation of the relationship between the factors identified as the key ones. In the paper 23 indicators, describing four selected goals in the Strategy for Sustainable Development, 2030 Agenda were selected. It is assumed that the sustainable development goals should be related but according to the experts opinion this only applies to some indicators. This kind of relationships can be certainly identified in the case of the goals describing social and economic development, but often also economic and environmental development. However, the research results presented in the paper do not always confirm the existence of connections between individual indicators selected for the description of the goals of sustainable development. The paper tries to explain this problem.
The paper deals with an evaluation of the quality of services provided by healthcare organizations. First, an index representing a patient’s health condition is described, then its changes before and after being treated by a given entity are employed as a criterion to assess the operations of this entity. The index of a patient’s health condition is based on the theory of survival analysis, while a model of random effects is used to determine the quality of services based on health value added.
This paper presents a proposition to utilize flexible neural network architecture called Deep Hybrid Collaborative Filtering with Content (DHCF) as a product recommendation engine. Its main goal is to provide better shopping suggestions for customers on the e-commerce platform. The system was tested on 2018 Amazon Reviews Dataset, using repeated cross validation and compared with other approaches: collaborative filtering (CF) and deep collaborative filtering (DCF) in terms of mean squared error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). DCF and DHCF were proved to be significantly better than the CF. DHCF proved to be better than DCF in terms of MAE and MAPE, it also scored the best on separate test data. The significance of the differences was checked by means of a Friedman test, followed by post-hoc comparisons to control p-value. The experiment shows that DHCF can outperform other approaches considered in the study, with more robust scores.
The main aim of this contribution is to outline the role and importance of key performance indicators in the frame of Industry 4.0 implementation. These key performance indicators are presented as a cornerstone for industry 4.0 implementation in organizational practice, since they represent key input for needed data in digitalized organization. In that framework, the contribution first exposes some of the essential characteristics of “Industry 4.0”, followed by the methodology of key performance indicators (KPI). Next, the contribution outlined a proposed methodology for implementing KPIs in frame of Industry 4.0 adoption in organizations. Another section of the paper is dedicatd to the linkage between corporate social responsilbty and KPIs in frame of Industry 4.0. The paper also outlines implications, limitations and further research directions are outlined.
One of the biggest challenges facing the education system in Bosnia and Herzegovina is bridging the gap between the current state of higher education and the demand for research, innovation and a robust STEM (Science, Technology, Engineering, Mathematics) curriculum. Higher education instiutions (HEIs) face poor R&D infrastructure while companies struggle with limited resources and the lack of internal researchers, all of which affect their capabilities to utilize university knowledge and research that will lead to further collaborations and innovations in STEM. Universities are primarily seen as a source of future employees as well as as a source of knowledge and innovation. This study aims to provide an overview and systematic analysis of the current state of scientific and research infrastructure and human resources in public and private universities located in the Sarajevo Canton region. This is done by using primary data collected through semi-structured interviews and a self-reporting comprehensive questionnaire in order to identify areas where further reforms and investments are needed. An analysis of the secondary data sources, such as current strategic documents and the existing assessments of education, was conducted. Consequently, this study offers several practical implications, including policy recommendations in areas such as higher education, research infrastructure and academic excellence, cooperation with the private sector, and IT infrastructure improvements.
This paper adopts a neoclassical framework to study the effect of age composition of the working-age population on labour productivity and its determinants, based on an unbalanced panel of 64 non-oil-producing countries, over the period 1950-2017. Our first contribution comes from testing whether a shock in age structure has the ability to permanently shift labour productivity dynamics. From methodological standpoint, we try to reduce the risk of model mispecification in the existing literature, that has often overlooked the possibility of cross-sectional dependence in the data and heterogeneity in slope coefficients. We also note the importance of time series properties of the data for valid statistical inference. Our results indicate, that ageing of the working-age population depresses labour productivity growth; negative impact of individuals aged between 55 and 64 on total factor productivity growth is only partially offset by its positive impact on human and physical capital accumulation. For sustaining the current level of living standards, adoption of policies, which forestall the negative impact of older workers on innovation process and promote their positive impact on the supply of production factors, is of crucial importance. We do not find evidence, that higher public spending on education in% of GDP has such an effect.
In many countries, collective bargaining coverage is enhanced by government-issued extensions that widen the reach of collective agreements beyond their signatory parties to all firms and workers in the sector. This paper analyzes the causal impact of extensions using a natural experiment in Portugal that resulted in a sharp and unanticipated decline in the extension probability of agreements. Our results, based on a regression discontinuity design, indicate that extensions had a negative impact on employment growth. This effect is concentrated among nonaffiliated firms, which may reflect the limited representativeness of employer associations.
This article analyzes the effects on the West Bank economy of temporary Palestinian employment in Israel, using a new database and a computable general equilibrium model. The results show that Palestinian employment in Israel increases household incomes but distorts the operation of the West Bank labor market and increases domestic wages. Employment in Israel increases the real exchange rate of the West Bank leading to “Dutch disease” effects that inhibit the development of the West Bank economy. A decrease in the number of Palestinian workers in Israel reduces household welfare, and constraints on the West Bank economy restrict domestic absorption of the extra labor. Hence, the Palestinian National Authority may seek more labor exports to Israel. This article contributes to the broader discussion on the effects of migration policies on labor-sending economies by demonstrating the nontrivial benefits from labor migrations, but that these benefits come with costs. This article explores policy options for offsetting those costs.
This paper provides new evidence on the acquisition and persistence of child gender preference among immigrant populations in the United States using Census and American Community Survey data. We first confirm the existing evidence of son preference among immigrant populations from South East Asia that was documented across multiple studies and samples. We then demonstrate several new empirical findings. First, Japanese immigrants exhibit daughter preference. Second, assortative matching between immigrant parents is associated with stronger gender preferences. Third, comparing male and female migrants who marry natives provides suggestive evidence that paternal preferences could be more to blame for son preference than maternal. Fourth, child gender preferences are strongest for migrants who arrive after childhood but do not appear to diminish with the duration of residence in the United States. Finally, while higher-order generations exhibit weaker son preference, there is a high degree of heterogeneity across groups. Most of the second- and higher-order generation immigrants assimilate more rapidly to US norms except Indian immigrant populations, which exhibit strong son preference among higher-order generations.