Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds

Development and application of the data envelopment analysis (DEA) method, have been the subject of numerous reviews. In this paper, we consider the papers that apply DEA methods specifically to financial services, or which use financial services data to experiment with a newly introduced DEA model. We examine 620 papers published in journals indexed in the Web of Science database, from 1985 to April 2016. We analyse the sample applying citations network analysis. This paper investigates the DEA method and its applications in financial services. We analyse the diffusion of DEA in three sub-samples: (1) banking groups, (2) money market funds, and (3) insurance groups by identifying the main paths, that is, the main flows of the ideas underlying each area of research. This allows us to highlight the main approaches, models and efficiency types used in each research areas. No unique methodological preference emerges within these areas. Innovations in the DEA methodologies (network models, slacks based models, directional distance models and Nash bargaining game) clearly dominate recent research. For each subsample, we describe the geographical distribution of these studies, and provide some basic statistics related to the most active journals and scholars

The potential of energy efficiency measures in micro and small scale businesses in Kumasi-Ghana

In industry, energy efficiency reduces operating cost and emissions to the environment whiles enhancing energy security. In order to ensure the sustainability of micro and small scale businesses in a developing country such as Ghana, measures that can ensure energy efficiency are therefore essential for these businesses to have a productive and economical operation that will ensure their sustainability. In this study, the potential of energy efficiency measures for micro and small scale businesses have been examined by performing industrial energy systems analysis on some selected micro and small scale businesses in Kumasi-Ghana through a practical study and administering of questionnaire about their energy consumption. Legislative instruments that are linked with energy use in Ghana were looked into. Some possible energy efficiency measures that could be adopted by these businesses have been analyzed. In this study it is established that energy supply to these businesses is not reliable and it is continuously becoming expensive. In addition, other findings were that value could be added to the processes of these businesses if they incorporate energy efficiency measures in their operations. The main driving force that will encourage these businesses to incorporate energy efficiency measures in their operation is the energy prices increase; therefore, their interest is the measures that could reduce their energy cost rather than the positive impacts that will come to the environment. In doing this renewable energy has the greatest potential in ensuring energy efficiency to these businesses. Finally, it is established that there are no specific legislations on energy use that will bring negative effects to these businesses and this could create enabling environment for private investors of energy efficiency

DEA based on strongly efficient and inefficient frontiers and its application on port efficiency measurement

10.1007/s00291-011-0263-2OR Spectrum344943-96

Some models and measures for evaluating performances with DEA: past accomplishments and future prospects

Efficiency, Effectiveness, Social Indicators, Engineering-science, Welfare economics, Distance measures,

Selective measures in data envelopment analysis

Data envelopment analysis (DEA) is a data based mathematical approach, which handles large numbers of variables, constraints, and data. Hence, data play an important and critical role in DEA. Given a set of decision making units (DMUs) and identified inputs and outputs (performance measures), DEA evaluates each DMU in comparison with all DMUs. According to some statistical and empirical rules, a balance between the number of DMUs and the number of performance measures should exist. However, in some situations the number of performance measures is relatively large in comparison with the number of DMUs. These cases lead us to choose some inputs and outputs in a way that produces acceptable results. We refer to these selected inputs and outputs as selective measures. This paper presents an approach toward a large number of inputs and outputs. Individual DMU and aggregate models are recommended and expanded separately for developing the idea of selective measures. The practical aspect of the new approach is illustrated by two real data set applications.Web of Science226164262