Application of Data Envelopment Analysis (DEA) in Information and Communication Technologies

Abstract

The consistent improvements and fast-growing trend of information and communication technology (ICT) have impacted all areas of society and the economy. In 2020, with the sudden pandemic of COVID-19, businesses worldwide faced great challenges and had to transform and become digital-native enterprises by using data analytics, digital business platforms and personalized customer approaches. In such a digital era, innovation, entrepreneurial dynamism and ICT are the key ingredients for business' success and sustainability. Furthermore, it has become very clear that the influence of the ICT industry on economic growth is immense. Therefore, it should not come as a surprise that the interest in research of the ICT industry is great. Data Envelopment Analysis (DEA) is the leading non-parametric mathematical technique for assessing performance and measuring efficiency of complex entities called Decision-Making-Units (DMUs), by conversion of multiple input variables to multiple output variables. DEA has experienced rapid growth in use in many areas ever since its introduction by Charnes, Cooper and Rhodes in 1978. The purpose of this paper is to present and describe Data Envelopment Analysis as the leading mathematical programming technique for data analysis and to provide an extensive literature review, to identify the studies implementing the DEA methodology in Information and Communication Technologies (ICT) and to present its findings. Furthermore, this study's goal is to inspire and encourage researchers to employ this methodology in the fields of ICT and to give guidance for future research in this area.