Health system efficiency in OECD countries: dynamic network DEA approach

Background In recent years, measuring and evaluating the efficiency of health systems has been explored in the context of seeking resources to ensure the sustainability of 'countries' health and social systems and addressing various crises in the health sector. The study aims to quantify and compare the efficiency of OECD health systems in 2000, 2008, and 2016. The contribution to research in the field of efficiency in the healthcare system can be seen in the application of Dynamic Network Data Envelopment Analysis (DNDEA), which help us to analyse not only the overall efficiency of the healthcare system but analyse the overall efficiency as the result of the efficiencies of individual interconnected areas (public and medical care area). By applying the DNDEA model, we can realise the analysis not only within one year, but we can find out if the measures and improvements taken in the healthcare sector have a positive impact on its efficiency in a later period (eight-year interval). Methods The analysis focuses on assessing the efficiency of the health systems of OECD countries over three periods: 2000, 2008, and 2016. Data for this study were derived from the existing OECD database, which provides aggregated data on OECD countries on a comparable basis. In this way, it was possible to compare different countries whose national health statistics may have their characteristics. The input-oriented Dynamic Network Data Envelopment Analysis model was used for data processing. The efficiency of OECD health systems has been analysed and evaluated comprehensively and also separately in two divisions: public health sub-division and medical care sub-division. The analysis combines the application of conventional and unconventional methods of measuring efficiency in the health sector. Results The results for the public health sub-division, medical care sub-division and overall health system for OECD countries under the assumption of constant returns to scale indicate that the average overall efficiency was 0.8801 in 2000, 0.8807 in 2008 and 0.8472 in 2016. The results of the input-oriented model with the assumption of constant returns to scale point to the overall average efficiency of health systems at the level of 0.8693 during the period. According to the Malmquist Index results, the OECD countries improved the efficiency over the years, with performance improvements of 19% in the public health division and 8% in the medical care division. Conclusions The results of the study are beneficial for health policymakers to assess and compare health systems in countries and to develop strategic national and regional health plans. Similarly, the result will support the development of international benchmarks in this area. The issue of health efficiency is an intriguing one that could be usefully explored in further research. A greater focus on combining non-parametric and parametric models could produce interesting findings for further research. The consistency in the publication and updating of the data on health statistics would help us establish a greater degree of accuracy.Internal Grant Agency of FaME Tomas Bata University in Zlin [RO/2020/05]Univerzita Tomáše Bati ve Zlíně: RO/2020/05; European Regional Development Fund, ERD

Concept of SME Business Model for Industry 4.0 Environment

Ongoing technological development pushes industry towards the so called fourth industrial revolution. Considering new technology as a determinant of future business environment, we find it necessary to examine how platforms such as Industry 4.0 will change enterprises organization and business models. Designed model should serve as guidance for new and also already existing enterprises for implementing of Industry 4.0 required attributes especially in early stage. Main emphasis is given on software and cloud solutions that will become necessary despite the fact that in recent industrial SMEs they do not play significant role. Such transformation will raise crucial questions about funding new technologies