Assessment of the productive efficiency of large wind farms in the United States: An application of two-stage data envelopment analysis

2017 ◽  
Vol 153 ◽  
pp. 188-214 ◽  
Author(s):  
Ümit Sağlam
Keyword(s):  
United States ◽  
Data Envelopment Analysis ◽  
Wind Farms ◽  
The United States ◽  
Productive Efficiency ◽  
Data Envelopment ◽  
Two Stage ◽  
Large Wind

scholarly journals Benchmarking the operational efficiency of major U.S. trucking firms using data envelopment analysis

2003 ◽  
Vol 14 (2) ◽  
pp. 22-34 ◽  
Author(s):  
Hokey Min ◽  
Seong Jong Joo
Keyword(s):  
United States ◽  
Data Envelopment Analysis ◽  
Best Practices ◽  
Continuous Improvement ◽  
The United States ◽  
Operational Efficiency ◽  
Data Envelopment ◽  
Logistics Industry ◽  
Non Profit ◽  
Using Data

In an era of downsizing and financial cutbacks, the operational efficiency of trucking firms dictates their competitiveness and survival. In an effort to help trucking firms develop a winning formula in the fiercely competitive logistics industry, this research aims to develop a meaningful set of benchmarks that will set the tone for best practices. In particular, a data envelopment analysis (DEA) is described. DEA has proven to be useful for measuring the operational efficiency of various profit or non-profit organizations. Using the examples of major trucking businesses in the United States, the usefulness of data envelopment analysis for the continuous improvement of trucking services is illustrated.

Characteristics of Health Maintenance Organizations and Their Influence on Efficiency

2000 ◽  
Vol 13 (1) ◽  
pp. 40-56 ◽  
Author(s):  
D. A. Draper ◽  
I. Solti ◽  
Y. A. Ozcan
Keyword(s):  
United States ◽  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
The United States ◽  
Health Maintenance Organizations ◽  
Data Envelopment ◽  
Health Maintenance ◽  
Operational Characteristics ◽  
Medicare Programme ◽  
Programme Participation

This study examines the efficiency of Health Maintenance Organizations (HMOs) based on a sample of 249 HMOs operating in the United States in 1995. Data Envelopment Analysis (DEA) was used to calculate the level of technical efficiency for each HMO included in the sample. Further descriptive analyses were conducted examining various structural and operational characteristics of HMOs and their impact on efficiency. Federal qualification status, Medicare programme participation, combined Medicare and Medicaid programmes participation, chain affiliation and size were found to be significant influences on HMO efficiency.

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