Low-energy electron-impact hydrogen loss due to dissociative electron attachment (DEA) to the uracil and thymine molecules in a water cluster environment is investigated theoretically. Only the A(')-resonance contribution, describing the near-threshold behavior of DEA, is incorporated. Calculations are based on the nonlocal complex potential theory and the multiple scattering theory, and are pe...

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Conventional data envelopment analysis (DEA) assists decision makers in distinguishing between efficient and inefficient decisionmaking units (DMUs) in a homogeneous group. However, DEA does not provide more information about the efficient DMUs. This research proposes a methodology to determine one common set of weights for the performance indices of only DEA efficient DMUs. Then, these DMUs ar...

Selection of international market (IM) is a critical decision and needs to be made with considerable attention and deliberation. In some situations however, some criteria have the nature of both cost and profit. Likewise, in data envelopment analysis (DEA) some criteria play both input (cost) and output (profit) roles, simultaneously. In the DEA literature such criteria are called dual-role fac...

Aggregation of corporate social performance (CSP) metrics poses a major challenge to researchers and practitioners. This study provides a critical evaluation of current aggregation approaches and proposes a new methodology based on Data Envelopment Analysis (DEA) to compute a CSP index. DEA is independent of subjective weight specifications and provides an efficiency index to benchmark the CSP ...

Data quality is critical to a successful data envelopment analysis (DEA) study. Outlier detection not only identifies suspicious data points and thus prevents the drawing of erroneous conclusions, but also can lead to the discovery of unexpected knowledge. This study develops a unified model to identify outliers in DEA studies by examining how they effect on the boundaries of a data set. The pr...

(2011). " Formative evaluation of electricity distribution utilities using Data Envelopment Analysis ". Abstract — The use of Data Envelopment Analysis (DEA) in the electricity distribution sector has been prolific in the number of papers published in research journals. However, while numerous studies have been documented, they have mostly been summative. Their aim has been predominantly descri...

Data envelopment analysis (DEA) is a representative method to estimate efficient frontiers and derive efficiency. However, in a situation with weight restrictions on individual input–output pairs, its suitability has been questioned. Therefore, the main purpose of this paper is to develop a mathematical method, which we call the input-oriented ratio-based comparative efficiency model, DEA-R-I, ...

DEA models treat the DMU as a “black box.” Inputs enter and outputs exit, with no consideration of the intervening steps. Consequently, it is di(cult, if not impossible, to provide individual DMU managers with speci;c information regarding the sources of ine(ciency within their DMUs. We show how to use DEA to look inside the DMU, allowing greater insight as to the sources of organizational ine(...

Although data envelopment analysis (DEA) has been extensively used to assess the performance of mutual funds (MF), most of the approaches overestimate the risk associated to the endogenous benchmark portfolio. This is because in the conventional DEA technology the risk of the target portfolio is computed as a linear combination of the risk of the assessed MF. This neglects the important effects...