An overview of data envelopment analysis application in studies on the socio-economic performance of OECD countries

Rabar, Danijela

doi:10.1080/1331677x.2017.1383178

Cited by 15 publications

(11 citation statements)

References 44 publications

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“…Therefore, the results can be obtained by the simple model that is proposed. There are no firm default frameworks for how to select input and output variables, and they are usually formed in collaboration with economic and mathematical experts, according to the research objective [34]. In line with the aim of this research, the given distance is a key value for DEA and represents the least energy consumption variable.…”

Section: Dea Settingsmentioning

confidence: 99%

Model of Determining the Optimal, Green Transport Route among Alternatives: Data Envelopment Analysis Settings

Vukić

Jugović

Guidi

et al. 2020

JMSE

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Data envelopment analysis (DEA) is a useful method for determining relative efficiency in many types of businesses, including the transport sector. In line with the European Union’s (EU) policy of sustainable development of transport, external costs become the competitiveness factor of the transport route valorization. Presenting specific DEA settings, the paper aims to show and test a developed model for determining the optimal transport route among alternatives towards the same destination where external cost as a socio-ecological factor is included in DEA, along with transport cost (quantitative factor) and transport time (qualitative factor). In order to adhere to the principles of the least possible energy consumption, the given distance that also included in DEA settings represents the shortest route between the starting point and destination, as a unique and constant output variable. Therefore, the optimal direction selected by the DEA stands for the green route. The capabilities of the DEA, set up in this way within the broader model, are demonstrated in the practical case.

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Section: Dea Settingsmentioning

confidence: 99%

Model of Determining the Optimal, Green Transport Route among Alternatives: Data Envelopment Analysis Settings

Vukić

Jugović

Guidi

et al. 2020

JMSE

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“…Collecting different conclusions of the theoretical and empirical literature, Rabar (2017) noted that any of the various DEA approaches could be very indicative of specific issues of interest, but none of them can be determined as the best solution. Nevertheless, they all only offer a background for further surveys that might result in the advancement for the purpose of the investigation of economic efficiency.…”

Section: Literature Reviewmentioning

confidence: 99%

Comparative analysis of the regional efficiency in Serbia: DEA approach

Radonjić¹

2020

Industrija

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The main aim of the paper is to offer a statistical identification of differences in efficiency between Serbian regions. The regional resources covered by the analysis are presented in the form of infrastructure, investment in new fixed assets and employment levels. For the researching purpose, data envelopment method (DEA) is used as a major component in identifying regions that use their resources effectively. This approach of mathematical programming optimization tends to evaluate the efficiency of the analyzed regional spatial aspects. Moreover, studying regional differences and generally spatial efficiency creates a significant basis for mapping key problems of regional development in Serbia and provides important guidelines for the creation and implementation of regional policies.

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“…Other relevant and related research with econometric methodology can be found in the articles mentioned above. An overview of empirical papers with only an economic and social view is given in Rabar (2017).…”

Section: Previous Researchmentioning

confidence: 99%

Re-examining sustainable development in Europe: a data envelopment approach

Škrinjarić

2020

IJESD

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Sustainable development is a widely known concept in public and academic circles and in macroeconomic policy. This study applies data envelopment analysis to 37 European countries for the period 2004-2016 in order to evaluate sustainable development objectively. The model uses gross domestic product per capita as desirable output, CO 2 emissions and Gini Index as undesirable outputs and three input variables: unemployment rate, fixed capital formation and energy consumption. Thus, all three pillars of sustainable development are included in the analysis. This is the first comprehensive analysis of European countries carried out with this methodology. Several model specifications are observed, in order to check for robustness of results. The results indicate that countries which are already highly ranked by existing world indices are ranked similarly in the empirical results of this research. Moreover, the most inefficient countries have shown an increase in sustainable development efficiency score over the observed period.

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An overview of data envelopment analysis application in studies on the socio-economic performance of OECD countries

Cited by 15 publications

References 44 publications

Model of Determining the Optimal, Green Transport Route among Alternatives: Data Envelopment Analysis Settings

Model of Determining the Optimal, Green Transport Route among Alternatives: Data Envelopment Analysis Settings

Comparative analysis of the regional efficiency in Serbia: DEA approach

Re-examining sustainable development in Europe: a data envelopment approach

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