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Copyright of Verimlilik Dergisi is the property of Verimlilik Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Reduction of poverty or social exclusion belongs to the priorities of the EU countries defined in the Europe 2020 Strategy. This priority was defined as being interrelated with the priorities focused on employment and education. Numbers of people living in poverty varied between the EU countries, which also varied in the progress towards achieving their national targets concerning poverty reduction. The aim of the paper was to assess the EU countries with respect to the prevalence of poverty and its determinants in the context of the priorities of the Europe 2020 Strategy. Two methods were used to meet the aim of the paper – the correlation analysis and the Data Envelopment Analysis (DEA), including also the Malmquist Index. Results of the DEA revealed that all EU countries were not assessed as being fully efficient. A number of efficient countries first declined between the years 2008-2010, then it started to increase and reached the maximum value in 2017. Between the years 2010-2014, 11 countries improved their productivity, but between the years 2017-2019, improvement was identified only for five countries. Results of correlation analysis confirmed the importance of policies focused on households’ incomes and employment for the successful reduction of poverty. [ABSTRACT FROM AUTHOR]

The emergence of sports tourism has compelled sports managers to rethink the management and improvement of sports facilities. Through service quality analysis, sports managers can identify the strengths and weaknesses of their activities for possible advancement. Hence, this study aims to develop a decision support model based on integrating online reviews and data envelopment analysis to measure the degree of tourist satisfaction and provide benchmarking goals for service improvement. The proposed model employs text mining techniques to discover service quality attributes from text reviews. According to the discovered service quality attributes, we conduct sentiment analysis to reveal the sentiment polarities of the text reviews. Then, we refine the polarities and ratings of online reviews into linguistic distribution assessments. Furthermore, we develop a linguistic distribution output-oriented non-discretionary bestpoint slack-based measure (BP-SBM) to compute the degree of tourist satisfaction and benchmarking goals. The linguistic distribution output-oriented non-discretionary BP-SBM can handle both positive and negative data values, thus overcoming the flaws of the traditional model. Meanwhile, the proposed decision support model investigates how the service-quality attributes interact to provide improvement pathways for an underperforming stadium based on association rule mining. We test the applicability of the proposed decision support model on some Elite stadia in Europe. [ABSTRACT FROM AUTHOR]

Greenhouse gas emissions, acidification, and the dispersion of particles are negative side effects of railways that have received notable attention in Europe but are seldom considered in performance evaluations. The objective of this work was to assess the efficiency of European railways involved in the commitment signed by the international railway association (UIC) and The community of European railway and infrastructure companies (CER), considering the action of 14 rail companies to reduce negative externalities. Data envelopment analysis was applied under the framework of a slacks-based measure and the technique for order of preference by similarity to ideal solution to account for undesirable outputs and ensure unique rankings. Three different measures were considered: two ordinary energy efficiency models, with and without environmental restrictions, which are input–output ratios, and the eco-efficiency, which is an economic performance-to-environmental impacts ratio. The first two models were found to be similar to each other but different to the eco-efficiency, as a high ordinary efficiency ranking generally is not equivalent to high eco-efficiency. The results indicate that the average performance of the firms is low, but with a considerable temporal growth which is driven by environmental factors. Several policy-making implications are addressed to assist railway efficiency improvements and avoid anomalies in environmental performance evaluations. This data envelopment analysis application is the first to incorporate several air pollutants in railway efficiency assessment. Time-series evolution of the efficiency scores for railway companies involved in the UIC-CER commitment during 2011–2019. [ABSTRACT FROM AUTHOR]

Copyright of Polish Journal of Economics / Gospodarka Narodowa is the property of SGH Warsaw School of Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The most important goals included in the Europe 2020 Strategy are climate/energy targets, which determine not only the achievement of its other goals but also climate neutrality by 2050. This article aims to assess the efficiency of implementing the climate/energy targets of the Europe 2020 Strategy and to analyse changes over time, taking into consideration the structural diversity between the old (EU 15) and new EU members (EU 13) in the period of 2014–2018. The assessment of changes in the efficiency of climate/energy targets over time adds value to the evaluation methods used to date in this area. This was done using data envelopment analysis (DEA) and the Malmquist index. Earlier works usually specified only the level of target achievement, mostly jointly in relation to all of the goals of the Europe 2020 Strategy. The efficiency of their implementation at the macroeconomic level has not been studied. Furthermore, the added value of this paper consists in obtaining additional information concerning the internal structure and character of the studied efficiency of old and new member states. Changes in the efficiency level have been analysed with regard to the key climate/energy indicators used to monitor the Europe 2020 Strategy. Based on the results, the EU countries were divided into six groups with similar levels of efficiency in achieving energy and climate objectives and ranked using the DEA–Malmquist index according to changes in their level over time. This makes it possible not only to assess the performance of countries but also to formulate recommendations for decision-makers. [ABSTRACT FROM AUTHOR]