Data envelopment analysis

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Data envelopment analysis topic overview

The analysis highlights History, Products, Art and Measurement as prominent areas in the source structure around Data envelopment analysis.

Related topics: 26
Source areas: 5
Connected nodes: 31
Extracted relationships: 7
Related term clusters: 17
Bridge connections: 31

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Description · 9 topics

History · 9 topics

Overview · 5 topics

Techniques · 2 topics

Extensions · 1 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

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Data envelopment analysis

5Non-parametric statistics · Operations research · Economics

8Abraham Charnes · William W. Cooper · Edwardo Rhodes

13Empirically · Productive efficiency · Production (economics)

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

For the semantics nerds

You can skip this section if you’re here for content ideas and keyword inspiration.

Advanced semantic analysis

How Data envelopment analysis connects Entity context

See recurring relationship patterns around Data envelopment analysis before inspecting the individual extracted relationships.

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

data efficiency analysis doi envelopment 10 dea cooper inputs journal displaystyle research production charnes outputs 2022 dmus used s2cid productivity

Data envelopment analysis relationships Subject–Predicate–Object triples

TTTA extracted 7 structured relationships around Data envelopment analysis. Examples in this analysis include input → instance of → They range from adapting implicit model assumptions. The table shows each extracted connection, where it came from and its confidence.

Subject	Predicate	Object	Confidence	Src
input	instance of	They range from adapting implicit model assumptions	0.80	text
output orientation	instance of	They range from adapting implicit model assumptions	0.80	text
distinguishing technical	instance of	They range from adapting implicit model assumptions	0.80	text
allocative efficiency	instance of	They range from adapting implicit model assumptions	0.80	text
adding limited disposability of inputs/outputs or varying returns-to-scale to techniques that utilize DEA results	instance of	They range from adapting implicit model assumptions	0.80	text
extend them for more sophisticated analyses	instance of	They range from adapting implicit model assumptions	0.80	text
such as stochastic DEA or cross-efficiency analysis	instance of	They range from adapting implicit model assumptions	0.80	text

Related concept clusters Related term clusters

The concept neighborhoods around Data envelopment analysis bring nearby vocabulary together. In this analysis, examples include Envelopment, Analysis and Data. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

Data envelopment analysis
- Envelopment
- Analysis
- Data
- Models
- Using
- Applications
- Wager
- Charnes
- Measurement
- William
- Production
- Cooper
data envelopment analysis
- Envelopment
- Analysis
- Data
- Models
- Using
- Applications
- Wager
- Charnes
- William
- Measurement
- Cooper
- Production
data
- Envelopment
- Analysis
- Models
- Using
- Applications
- Wager
- Charnes
- Measurement
- William
- Production
- Cooper
- Efficiency
stochastic frontier analysis
- Envelopment
- Data
- Production
- Number
- Used
- Models
- Applications
- Rhodes
- Wager
- Charnes
- Using
- William
productive efficiency
- Inputs
- Measurement
- Outputs
- Displaystyle
- Rhodes
- Cross-efficiency
- Weights
- Charnes
- Productivity
- Using
- Dmus
- Cooper
efficiency ratios
- Inputs
- Measurement
- Outputs
- Displaystyle
- Rhodes
- Cross-efficiency
- Weights
- Charnes
- Productivity
- Using
- Dmus
- Cooper
allocative efficiency
- Inputs
- Measurement
- Outputs
- Displaystyle
- Rhodes
- Cross-efficiency
- Weights
- Charnes
- Productivity
- Using
- Dmus
- Cooper
efficiency
- Inputs
- Measurement
- Outputs
- Displaystyle
- Rhodes
- Cross-efficiency
- Weights
- Charnes
- Productivity
- Using
- Dmus
- Cooper

Connections between topic areas Semantic bridges

For Data envelopment analysis, one of the stronger structural bridges in this analysis connects Data envelopment analysis with Description. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3

Data envelopment analysis — Description · splits 22 ⟂ 10

Data envelopment analysis — History · splits 22 ⟂ 10

Data envelopment analysis — Overview · splits 26 ⟂ 6

Data envelopment analysis — Techniques · splits 29 ⟂ 3

Map overview Semantic statistics

Nodes32

Edges31

Triples7

Avg. degree1.94

Density0.0625

Components1

Source & methodology

TTTA analyzes the structure around Data envelopment analysis to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Products, Art & Measurement, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — Data envelopment analysis · EN edition · Analysis: TopicsToTalkAbout

Data envelopment analysis: History, Products, Art & Measurement

Data envelopment analysis topic overview

What this topic covers Research coverage

Key facts & relationships

Start with your topic. Discover where to go next.

Questions to explore

Explore all related topics Closing gaps

Overview

Description

History

Techniques

Extensions

For the semantics nerds

Advanced semantic analysis

How Data envelopment analysis connects Entity context

Important terminology

Important terminology

Data envelopment analysis relationships Subject–Predicate–Object triples

Related concept clusters Related term clusters

Connections between topic areas Semantic bridges

Map overview Semantic statistics

Data envelopment analysis

Source & methodology