Data Envelopment Analysis Approach and Its Application In Information and Communication Technologies.
Violeta Cvetkoska
Abstract
Violeta Cvetkoska
Abstract
Abstract. Data Envelopment Analysis (DEA) is a relatively new “data oriented ” non-parametric approach for evaluating the performance of complex entities called Decision Making Units (DMUs) which convert multiple inputs into multiple outputs. DEA as a linear programming procedure computes a comparative ratio of outputs to inputs for each DMU, which is reported as the relative efficiency score. In a relatively short period of time DEA has grown into a powerful, quantitative, analytical tool for measuring and evaluating efficiency and has been successfully applied in many contexts worldwide. The reasons why DEA is seeing so much use is that it requires minimal assumptions about how the factors of production relate to each other and assessment by DEA relates to ‘best ’ or ‘efficient ’ rather than average behavior. The purpose of this paper is to describe Data Envelopment Analysis as a new way for organizing and analyzing data and to present the applications of this methodology in information and communication technologies.
OpenAlex reports 12 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Abstract. Data Envelopment Analysis (DEA) is a relatively new “data oriented ” non-parametric approach for evaluating the performance of complex entities called Decision Making Units (DMUs) which convert multiple inputs into multiple outputs. DEA as a linear programming procedure computes a comparative ratio of outputs to inputs for each DMU, which is reported as the relative efficiency score. In a relatively short period of time DEA has grown into a powerful, quantitative, analytical tool for measuring and evaluating efficiency and has been successfully applied in many contexts worldwide. The reasons why DEA is seeing so much use is that it requires minimal assumptions about how the factors of production relate to each other and assessment by DEA relates to ‘best ’ or ‘efficient ’ rather than average behavior. The purpose of this paper is to describe Data Envelopment Analysis as a new way for organizing and analyzing data and to present the applications of this methodology in information and communication technologies.
Key concepts: Data envelopment analysis, Computer science, Efficiency, Linear programming, Production (economics), Parametric statistics, Operations research, Envelopment