In this paper we apply data envelopment analysis (DEA) to evaluate the performance of hedge fund classifications. The purpose of alternative investment strategies such as hedge funds is to offer absolute returns, so using passive benchmarks to measure their performance could be ineffective. With the increasing number of hedge funds available, institutional investors, pension funds, and high net...

Data Envelopment Analysis models are based on linear programming problems (LPP) to determine the efficiency of Decision-Making Units (DMUs). This process can be computationally intense, as a LPP has to be run for each unit. Besides, a typical DEA LPP has a large number of redundant constraints concerning the inefficient DMUs. That results in degenerate LPPs and in some cases multiple efficient ...

Airport efficiency is an area of increasing interest to academics, policy makers and practitioners. This has resulted in a body of literature applying various econometric techniques to compare efficiency between different samples of airports. This paper uses the multi-criteria decision making method Analytic Hierarchy Process (AHP) to incorporate the weightings of input and output variables int...

In this paper, a Network DEA approach to assess the efficiency of NBA teams is proposed and compared with a black-box (i.e. single-process) DEA approach. Both approaches use a Slack-Based Measure of efficiency (SBM) to evaluate the potential reduction of inputs consumed (team budget) and outputs produced (games won by the team). The study considers the distribution of the budget between first-t...

In today’s economy and society, performance analyses in the services industries attract more and more attention. The traditional data envelopment analysis (DEA) approach requires a consistent operating environment. However, in reality, there is a need to evaluate the units belonging to different environment. This reality challenges the traditional methods of applying DEA theory to real-world ca...

In this paper, Data Envelopment Analysis (DEA) and super efficient DEA (SE-DEA) are employed to measure the efficiency of Chinese commercial banks. Incorporating Tobit regression analysis, the determinants of banking efficiency are investigated based on Panel data. Overall, the DEA results show relatively low average efficiency levels and state-owned banks are more inefficient than that of join...

Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs vs. multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. After pointing out needs for inclusion of them in DEA models, we propose a slacks-based network DEA model that can deal with intermediate products. Using this model we can ...

Data Envelopment Analysis (DEA) provides means for piecewise linear approximation of production functions. To improve the fit to the data we propose to improve the flexibility of the frontier by extending DEA towards a more general piecewise quadratic approximation, called Quadratic Data Envelopment Analysis (QDEA). In contrast to the linear approximation, the quadratic approximation allows for...

Denitrifying enzyme activity (DEA) in artificially established denitrification activity zones was, on average, 3.5-fold greater than in bulk soil. Denitrifier biomass was between 1 and 4 orders of magnitude greater in activity zones. Denitrifier specific activity was lower in activity zones and more similar to specific activity values reported for pure cultures of denitrifying bacteria added to...

We address the problem of the statistical analysis of a time series generated by complex dynamics with the diffusion entropy analysis (DEA) [N. Scafetta, P. Hamilton, and P. Grigolini, Fractals 9, 193 (2001)]. This method is based on the evaluation of the Shannon entropy of the diffusion process generated by the time series imagined as a physical source of fluctuations, rather than on the measu...