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...

Coastal salt marshes are a buffer between the uplands and adjacent coastal waters in New England (USA). With increasing N loads from developed watersheds, salt marshes could play an important role in the water quality maintenance of coastal waters. In this study we examined seasonal relationships between denitrification enzyme activity (DEA) in salt marshes of Narragansett Bay, Rhode Island, an...

This paper proposes the macro model and micro model for the efficiency evaluation of data warehouses (DWH), and introduces Fuzzy Data Envelopment Analysis (FDEA) and Data Envelopment Analysis (DEA) to comprehensively assess DWH efficiency. FDEA can determine the efficiencies of data warehouses with multiple input / output variables, and also resolve the problem that standard DEA cannot handle w...

UT HO R CO PY Two-stage network DEA: when intermediate measures can be treated as outputs from the second stage Sonia Aviles-Sacoto, Wade D Cook*, Raha Imanirad and Joe Zhu Doctoral Program in Engineering Sciences, ITESM-Monterrey, Mexico; Schulich School of Buisness, York University, Toronto, Canada M3J1P3; Doctoral Program, Harvard Business School, Soldiers Field, Boston, MA 02163; and Intern...

Data Envelopment Analysis (DEA) is a powerful performance measurement in economic sector and operations research to assess the relative efficiency for each decision making unit (DMU). In general, there are two assumptions in DEA. Firstly, the DEA assumes that all DMUs are homogenous in their environments and secondly, the DEA is a deterministic approach which refers to not allow to noise or err...

Supplier selection is a multi-Criteria problem. This study proposes a hybrid model for supporting the suppliers’ selection and ranking. This research is a two-stage model designed to fully rank the suppliers where each supplier has multiple Inputs and Outputs. First, the supplier evaluation problem is formulated by Data Envelopment Analysis (DEA), since the regarded decision deals with uncertai...

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...

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...

Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). Recently DEA has been extended to examine the efficiency of two-stage processes, where all the outputs from the first stage are intermediate measures that make up the inputs to the second stage. The resulting two-stage DEA model provides not only an overall efficiency score for the ent...

Data envelopment analysis is computationally intensive. The standard approach requires the solution of as many LPs as there are points in the data domain, each with as many columns. This number is frequently in the thousands and multi-period DEA amplifies the problem. Enhancements that reduce the size of the LPs are possible and a new scheme consisting of partitioning the domain offers more tim...