Titlebook: Advances in Efficiency and Productivity II; Juan Aparicio,C. A. Knox Lovell,Joe Zhu Book 2020 Springer Nature Switzerland AG 2020 Producti

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Alireza Heidari,Mohammadali Ghorbanie setting is one where all DMUs use the same inputs, produce the same outputs, experience the same operating conditions, and generally operate in similar environments. In many applications, however, it can occur that the DMUs fall into different groups or categories, where the efficiency scores for

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Springer Proceedings in Complexityouped based on Lauwers’ (Ecological Economics 68:1605–1614, 2009) seminal three-group classification and extended to a fourth group of recent models grounded on the estimation of several sub-technologies depending on the type of the outputs. With this fourth group of models, we provide a new complet

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D. Pikulins,S. Tjukovs,J. Eidakscy results of their disaggregated decision-making units (DMUs) microdata. The most common approach for calculating average efficiency is to use a set of inputs and outputs from a representative sample of DMUs, typically schools or high schools, in order to characterize the performance of the populat

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https://doi.org/10.1007/978-1-4757-4740-9data of US firms from 2004 to 2015. The chapter uses a dynamic data envelopment analysis (DEA) model to measure productivity change and its technical, technical-inefficiency, and scale-inefficiency change components. A bootstrap regression model relates CSR and its dimensions of social, environmenta

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Encoding Images by Simple Transformations, use to analyse relevant fields such as environmental efficiency. In this context, slacks-based measure (SBM) models offer a remarkable alternative, largely due to their ability to deal with undesirable outputs. Additionally, super-efficiency evaluation in DEA is a useful complementary analysis for