The supplier selection process is a strategic decision-making process that influences the company’s sustainability. Lately, the sustainability concept has been highlighted as an organization’s source of success and profitability. Therefore, the selection of a sustainable supplier has become an imperative for organizations and is the focus of this manuscript. Suppliers are key stakeholders in the supply chain, and their proper selection is a key factor in a successful and sustainable supply chain. For this reason, it is crucial to determine how and which methods are mostly used by companies when choosing sustainable suppliers with the aim of examining whether the Data Envelopment Analysis (DEA) contributes to the same. This article is the first to present a comprehensive bibliometric analysis of 87 articles dealing with the application of DEA in the sustainable supplier selection in the period 2010–2022, with the application of the keywords “Data Envelopment Analysis”, “Supplier”, and “Sustainable” in Scopus and Web of Science databases. The main goal of this manuscript is to explore the applications of DEA in a sustainable supplier selection and to provide an analysis and visualization of bibliometric data to reveal the annual trends of published articles in this area, the top contributing journals, the most cited papers, the most contributing authors, citations, affiliations, and countries’ analysis, and an in-depth keyword visualization analysis. The findings of this study provide valuable insights and emphasize the ever-growing trend toward the selection of sustainable partners and suppliers in business using DEA methodology. Notably, this work shows the applicability and efficacy of DEA in specialized areas of supply chain management and should contribute to the construction of an overview of the existing literature on DEA studies regarding the process of selection of sustainable suppliers in supply chain management as well as stimulate the interest in the topic. This article gives an overview of a research field that is actually insufficiently explored through the scientific literature and presents a wide area and guidelines for future work.

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.

This paper investigates the relationship between bank ownership and efficiency before and after the COVID-19 pandemic in a sample of 20 Croatian commercial banks in the period from 2015 to 2020. The interconnection between these variables is examined with the use of a dynamic data envelopment analysis (window DEA) framework. Other goals are to measure the relative efficiency of Croatian banks in the observed period as well as the evolvement of the banking sector as a whole. The findings reveal that domestic banks outperform by little foreign-owned Croatian banks during the COVID-19 crisis year 2020, but, moreover, domestic and small-sized banks have experienced the least negative impact of COVID-19 in 2020. The results regarding the impact of bank size on bank efficiency are inconsistent and require additional study. The used methodology and the findings of this empirical research could be of interest to academic members, bank management and policymakers. The latter should be especially interested in the results and the resilience of domestic and foreign banks to external shocks, in order to re-examine their current bank policies and the national attitude towards attracting foreign capital in the banking sector.

This article focuses on the efficiency of commercial banks in North Macedonia in the period from 2007 to 2020. The main goal is to assess the relative efficiency of the banking sector as a whole, and more importantly, to evaluate and analyse the impact of mergers and acquisition (M&A) transactions on banks’ efficiency. For this reason, the leading nonparametric methodology Data Envelopment Analysis (DEA) has been employed, i.e., the window DEA model with two input and two output variables on a sample of 13 commercial banks. Based on balanced panel data from the banking sector of North Macedonia, the obtained results show a constant fall of efficiency of the whole banking sector, from 83.33% in 2007 to 70.06% in 2011 and 66.36% in 2020. The results of the M&A transactions case study analysis show that, in general, M&A transactions decrease banks' efficiency, i.e., they do not result in an efficiency increase. The contribution of the study is that it comprises the first study analysing the effects of banks' M&A on bank efficiency in the region of South-Eastern Europe with the application of DEA and thus, it provides valuable information for investors, bank management, M&A analysts, academic members and regulatory bodies.

The overarching objective of this paper is to survey, identify and present the most relevant papers that have applied the leading non-parametric methodology (namely, the Data Envelopment Analysis, hereafter DEA) in the research field of multimedia. A...

Purpose – this paper aims to analyse the business efficiency of the Alibaba platform at the beginning and during the COVID-19 crisis. Methodology/Design - The research is based on the official financial reports of the platform as well as on the reports of other specialized agencies that monitor the platform industry. The study focuses on an analysis of the financial indicators of the business. It compares the financial indicators with an analysis of the data on the trend of the user community on the platform. The results - the study's findings did not find a major impact of the COVID-19 pandemic on the overall business results of the Alibaba platform. The survey results confirmed changes in operating profit and net profit trends as a result of changes in the structure of operating revenues. Conclusion - Total revenues are growing at a slower pace as a result of the changes in business policy and changes in revenue structures than as a result of the impact of the COVID-19 pandemic.