scholarly journals Multivariate Data Envelopment Analysis to Measure Airline Efficiency in European Airspace: A Network-Based Approach

2019 ◽  
Vol 9 (24) ◽  
pp. 5312 ◽  
Author(s):  
Ramon Hermoso ◽  
M. Pilar Latorre ◽  
Margarita Martinez-Nuñez
Keyword(s):  
Social Media ◽  
Data Envelopment Analysis ◽  
Network Analysis ◽  
Multivariate Data ◽  
Business Management ◽  
User Engagement ◽  
Data Envelopment ◽  
Input Output ◽  
Comprehensive Understanding ◽  
Network Analysis Metrics

In this paper, data envelopment analysis (DEA) is applied to exhaustively examine the efficiency of the main airline companies in the European airspace by using novel input/output parameters: business management factors, network analysis metrics, as well as social media estimators. Furthermore, we also use network analysis to provide a better differentiation among efficiency values. Results indicate that user engagement, as well as the analysis of the position within the airspace-from an operative perspective, influence the efficiency of the airline companies, allowing a more comprehensive understanding of its functioning.

scholarly journals A full investigation of the directional congestion in data envelopment analysis

2019 ◽  
Author(s):  
somayeh khezri ◽  
Akram Dehnokhalaji ◽  
Farhad Hosseinzadeh Lotfi
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Input Output ◽  
Input And Output ◽  
Dea Models ◽  
Systems Of Inequalities ◽  
Full Investigation ◽  
Decision Making Units ◽  
Inputs And Outputs

One of interesting subjects in Data Envelopment Analysis (DEA) is estimation of congestion of Decision Making Units (DMUs). Congestion is evidenced when decreases (increases) in some inputs re- sult in increases (decreases) in some outputs without worsening (im- proving) any other input/output. Most of the existing methods for measuring the congestion of DMUs utilize the traditional de nition of congestion and assume that inputs and outputs change with the same proportion. Therefore, the important question that arises is whether congestion will occur or not if the decision maker (DM) increases or de- creases the inputs dis-proportionally. This means that, the traditional de nition of congestion in DEA may be unable to measure the con- gestion of units with multiple inputs and outputs. This paper focuses on the directional congestion and proposes methods for recognizing the directional congestion using DEA models. To do this, we consider two di erent scenarios: (i) just the input direction is available. (ii) none of the input and output directions are available. For each scenario, we propose a method consists in systems of inequalities or linear pro- gramming problems for estimation of the directional congestion. The validity of the proposed methods are demonstrated utilizing two nu- merical examples.

scholarly journals Efficiency of Two-Stage Technological Innovation in High Patent-Intensive Industries That Considers Time Lag: Research Based on the SBM-NDEA Model

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Junzhong Zou ◽  
Wei Chen ◽  
Nan Peng ◽  
Xuan Wei
Keyword(s):  
Data Envelopment Analysis ◽  
Panel Data ◽  
Technological Innovation ◽  
Time Lag ◽  
Innovation Process ◽  
Indicator System ◽  
Data Envelopment ◽  
Input Output ◽  
Two Stages ◽  
Output Indicator

Considering time lag and accumulation of inputs and outputs, this paper adopts the superefficiency data envelopment analysis (DEA) model to study the technological innovation efficiency of high patent-intensive industries using panel data from 2007 to 2017. Given the characteristics and the actual circumstances of the industries, the innovation process is divided into two stages, and an input-output indicator system is established. The results show that the overall innovation efficiency level of high patent-intensive industries in China is increasing. However, the R&D achievements in technology are not quickly applied or sufficiently transformed.

scholarly journals Strategies For Manufacturing Servitization Of Korean SMEs: By Using Data Envelopment Analysis

2016 ◽  
Vol 32 (2) ◽  
pp. 635 ◽  
Author(s):  
Seung Yin Ha ◽  
Gun Hee Lee ◽  
Bum Seok Kim
Keyword(s):  
Data Envelopment Analysis ◽  
Production Process ◽  
Product Differentiation ◽  
Mass Production ◽  
Business Processes ◽  
Business Management ◽  
Data Envelopment ◽  
Sales Channel ◽  
Customized Production ◽  
Using Data

This study examines the efficiency of Korean manufacturing SMEs through data envelopment analysis. We divide business processes into support activities (e.g., business management and product planning) and primary activities (e.g., production and sales and after-sales services) to measure the efficiency of each process by product module. Moreover, we verify the effect of manufacturing servitization by comparing between the efficiency of servitized and non-servitized firms. The result shows that support activities are generally more efficient than primary activities and that standardized mass production with option (module 2) and totally customized production (module 4) is more efficient than either standardized mass production without option (module 1) or customized assembly after standardized production (module 3). The results suggest that, as SMEs are small, they have an advantage in support activities but also lack production and sales channel infrastructure. Moreover, modules 2 and 4 are relatively efficient because they can increase their product values via product differentiation. In addition, servitized firms are more efficient than non-servitized firms in almost every process and module, implying that servitization in manufacturing is an effective way to improve product value. Finally, module 1 and the production process are relatively inefficient, while servitized firms have higher efficiency scores than do non servitized firms. Likewise, module 3 and sales and after-sales services are relatively inefficient, while servitized firms have higher efficiency scores than do non servitized firms. There results imply that servitization can be used by Korean manufacturing SMEs to develop efficiently and effectively.

Social Media Metrics in an Academic Setup

2017 ◽  
pp. 116-130
Author(s):  
Tasleem Arif ◽  
Rashid Ali
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Present Status ◽  
The Internet ◽  
Collaboration Networks ◽  
Different Types ◽  
Network Metrics ◽  
Network Analysis Metrics

Social media is perhaps responsible for largest share of traffic on the Internet. It is one of the largest online activities with people from all over the globe making its use for some sort of activity. The behaviour of these networks, important actors and groups and the way individual actors influence an idea or activity on these networks, etc. can be measured using social network analysis metrics. These metrics can be as simple as number of likes on Facebook or number of views on YouTube or as complex as clustering co-efficient which determines future collaborations on the basis of present status of the network. This chapter explores and discusses various social network metrics which can be used to analyse and explain important questions related to different types of networks. It also tries to explain the basic mathematics behind the working of these metrics. The use of these metrics for analysis of collaboration networks in an academic setup has been explored and results presented. A new metric called “Average Degree of Collaboration” has been defined to quantify collaborations within institutions.

The Comprehensive Efficiency Evaluation of Electrical Power System of China Based on Data Envelopment Analysis

2013 ◽  
Vol 860-863 ◽  
pp. 1881-1885 ◽  
Author(s):  
Wang Cheng Long ◽  
Xiao Wang ◽  
Dong Peng ◽  
Qiao Wang
Keyword(s):  
Data Envelopment Analysis ◽  
Power System ◽  
Electrical Power ◽  
Scientific Development ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Input Output ◽  
Analysis Model ◽  
Electrical Power System ◽  
Output Efficiency

With the power system of China continuous expanding recently, the electric power generation, transmission and supply capacity increased dramatically. In order to improve economic operational efficiency and realize scientific development, the Input-Output efficiency between the input of the power system facilities and the output of the power supply becomes a critical issue that government, business and academia have to face up to. In this paper, we used the DEA (Data Envelopment Analysis) model and tested the Input-Output efficiency of power system development and study the trend of important development segment. The relative efficiency of power system is closely related to the electricity management system and economic situation, the elements of reduce the efficiency were been found out by analyzing the DEA results. And a series of suggestions were proposed to increase the comprehensive efficiency.

scholarly journals Dimension-Specific Efficiency Measurement Using Data Envelopment Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Hongjun Zhang ◽  
Youliang Zhang ◽  
Rui Zhang
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
The Other ◽  
Data Envelopment ◽  
Input Output ◽  
Single Dimension ◽  
Measuring Efficiency ◽  
Using Data ◽  
The City ◽  
Decision Making Units

Data envelopment analysis (DEA) is a powerful tool for evaluating and improving the performance of a set of decision-making units (DMUs). Empirically, there are usually many DMUs exhibiting “efficient” status in multi-input multioutput situations. However, it is not appropriate to assert that all efficient DMUs have equivalent performances. Actually, a DMU can be evaluated to be efficient as long as it performs best in a single dimension. This paper argues that an efficient DMU of a particular input-output proportion has its own specialty and may also perform poorly in some dimensions. Two DEA-based approaches are proposed to measure the dimension-specific efficiency of DMUs. One is measuring efficiency in multiplier-form by further processing the original multiplier DEA model. The other is calculating efficiency in envelopment-form by comparing with an ideal DMU. The proposed approaches are applied to 26 supermarkets in the city of Nanjing, China, which have provided new insights on efficiency for the managers.

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