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Efficiency Measurement Using Data Envelopment Analysis (DEA)
1998This chapter is a pivotal chapter in this book. We now begin to explicitly consider the issue of inefficiency. In the previous four chapters we have discussed least squares econometric methods and index number methods, which implicitly assume that all firms are fully efficient.
Tim Coelli +2 more
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Performance Measurement Using Data Envelopment Analysis (DEA)
2014The 1980s brought many challenges to hospitals as they attempted to improve the efficiency of health care delivery through the fixed pricing mechanism of Diagnostic Related Groupings (DRGs). In the 1990s, the federal government extended the fixed pricing mechanism to physicians’ services through Resource-Based Relative Value Scale (RBRVS). Enacted more
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Data Envelopment Analysis (DEA): Algorithms, Computations, and Geometry
2020Data Envelopment Analysis (DEA) has matured but remains vibrant and relevant, in part, because its algorithms, computational experience, and geometry have a broad impact within and beyond the field. Algorithmic, computational, and geometric results in DEA allow us to solve larger problems faster; they also contribute to various other fields including ...
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Nigerian Journal of Science and Environment
The problem associated with data envelopment analysis (DEA) is the lack of discrimination power among efficient decision-making units (DMUs), hence yielding many DMUs to be efficient. The issue is highlighted when the number of DMUs evaluated is significantly less than the number of inputs and outputs used in the evaluation.
Ohoriemu, O.B. +2 more
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The problem associated with data envelopment analysis (DEA) is the lack of discrimination power among efficient decision-making units (DMUs), hence yielding many DMUs to be efficient. The issue is highlighted when the number of DMUs evaluated is significantly less than the number of inputs and outputs used in the evaluation.
Ohoriemu, O.B. +2 more
openaire +2 more sources
Using DEA [data envelopment analysis] in benchmarking
2006Australian banks are currently generating huge profits but are they sustainable? NECMI AVKIRAN suggests that banks will need to scrutinise the performance of their networks to ensure future profits.
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DEA under big data: data enabled analytics and network data envelopment analysis
Annals of Operations Research, 2020Joe Zhu
exaly