Traditionally, ports have been regarded as hubs responsible for the reception of ships and passengers, but nowadays they have a much wider economic function, being clusters of various activities directly or indirectly linked to maritime transportation and seaborne trade, among which container traffic is the most important segment. The Port of Rijeka as the largest Croatian cargo port, positioned in the North Adriatic Sea, has exceptional but not fully exploited opportunities for further economic development of importance not just for the port and the city but for the Republic of Croatia as well. In addition, its geostrategic position makes it an important international port for Central and South Eastern European countries. The aim of this paper is to investigate and identify the current position of the Port of Rijeka (hereinafter Rijeka) in relation to the container business and, using Benchmarking as the research method, to analyse the established five main factors that have to be taken into consideration where its efficiency is compared to the statistically proven “best container port” in the region – the Port of Koper (hereinafter Koper). The results show significant competitive advantages of the Port of Koper almost in any of the analysed factors. Therefore, recommendations are given for further actions and improvement according to the natural advantages that Rijeka has to utilize in order to enhance its competitiveness and overall performance.

Public health services, as a preventive aspect of health care, are essential for the sustainability of the entire health care system. However, the context of public health services, which focus is primarily on prevention, is not a common setting when measuring the efficiency within nonparametric evidence-based approach. The aim of this study is to measure the efficiency of the financial performance of organizational units of the public health institute in Croatia, the Health Ecology Department in particular, during the period 2016-2018 using data envelopment analysis. Among the many reasons behind choosing this nonparametric method is the fact that it identifies the sources of inefficiency and specifies the directions and magnitudes of improvements required. Two input-oriented models-CCR under constant and BCC under variable returns-to-scale assumptionare employed for evaluating three types of efficiencytechnical, pure technical and scale efficiency. Two hypotheses are examined and empirically confirmed: first, that there is significant between-unit variability in financial performance, and second, that investments are the major source of inefficiency among the observed indicators. The results have additionally revealed that the mentioned differences are less pronounced in the case of pure technical efficiency, implying that the overall inefficiency of the Health Ecology Department units can be generally attributed to scale efficiency. Besides, only three out of twelve department units are considered efficient. The implications of the research results are aimed at further research and testing the efficiency of the entire network of public health institutes, as well as to provide policy makers with new insights when considering different modes of organizing and delivering public health services.

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Background: The main function of public health services is to improve people’s health and therefore, efficiency and effectiveness are constantly a subject of various world-wide research works. Today, in the era of digitalization, when numerous data are created and built, it is much easier to develop and implement a measurement system. It is possible to quickly use a wide variety of accurate and reliable data, aiming to create different measures that will help in the assessment and the decision-making process. For a long time, public health services have been facing a problem of finding an appropriate solution for measuring efficiency and effectiveness. Objective: The aim of this research is to find an appropriate analytical-predictive model for measuring efficiency and effectiveness of public health institutes. Public health is oriented to monitoring, analysis, and evaluation of the health of a population i.e., prevention activities. It is a complex and interdependent process of different realisation of services, programmes, and activities the results of which are sometimes visible only after a long period of time. Therefore, the results of their activities should be evaluated using an appropriate performance measurement system. Methods: The adjusted Balanced Scorecard (BSC) combined with the non-parametric Data Envelopment Analysis (DEA) technique is used to help identify the possibilities for improving the efficiency and effectiveness of public health service activities. Results: The result of this study is the proposed Analytical-Predictive Model (APE) that uses Balanced Scorecard combined with Data Envelopment Analysis to measure relative and technical efficiency as well as long-term effectiveness. The model used DEA as a benchmark for targets set in each perspective within the BSC. Using the BSC model, we selected the goals and common indicators for all DMUs, and using DEA, we identified relative efficiency of the DMUs. Efficient DMUs are considered a benchmark and used as targets for measuring effectiveness. Conclusion: This research has confirmed the appropriateness of the combination of BSC and DEA methods for measuring efficiency and effectiveness of public health institutions. To be able to measure and predict the long-term effectiveness of the activities and programmes, we had to combine the realised outputs and the set outcomes. The implementation of the APE model in the institutes of public health will contribute to the improvement of analysis, forecast, and optimisation of all their activities. The model is applicable to other public health institutions.

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