scholarly journals Developing a Novel Integrated Generalised Data Envelopment Analysis (DEA) to Evaluate Hospitals Providing Stroke Care Services

2021 ◽  
Vol 8 (12) ◽  
pp. 207
Author(s):  
Mirpouya Mirmozaffari ◽  
Elham Shadkam ◽  
Seyed Mohammad Khalili ◽  
Maziar Yazdani
Keyword(s):  
Data Envelopment Analysis ◽  
Stroke Care ◽  
Medical Emergency ◽  
Data Envelopment ◽  
Step Method ◽  
Efficient Approach ◽  
Care Services ◽  
Novel Approach ◽  
The Us ◽  
Approach Method

Stroke is the biggest cause of adult disability and the third biggest cause of death in the US. Stroke is a medical emergency, and the treatment given in the early hours is important in shaping the patient’s long-term recovery and prognosis. Despite the fact that substantial attention has been dedicated to this complex and difficult issue in healthcare, novel strategies such as operation research-based approaches have hardly been used to deal with the difficult challenges associated with stroke. This study proposes a novel approach with data envelopment analysis (DEA) and multi-objective linear programming (MOLP) in hospitals that provide stroke care services to select the most efficient approach, which will be a new experiment in literature perception. DEA and MOLP are widely used for performance evaluation and efficiency measurement. Despite their similarities and common concepts, the two disciplines have evolved separately. The generalised DEA (GDEA) cannot incorporate the preferences of decision-makers (DMs) preferences and historical efficiency data. In contrast, MOLP can incorporate the DM’s preferences into the decision-making process. We transform the GDEA model into MOLP through the max-ordering approach to (i) solve the problem interactively; (ii) use the step method (STEM) and consider DM’s preferences; (iii) eliminate the need for predetermined preference information; and (iv) apply the most preferred solution (MPS) to identify the most efficient approach. A case study of hospitals that provide stroke care services is taken as an example to illustrate the potential application of the proposed approach method.

scholarly journals Fuzzy data envelopment analysis in the presence of undesirable outputs with ideal points

2020 ◽  
Author(s):  
Ali Ebrahimnejad ◽  
Naser Amani
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
New Approach ◽  
Novel Approach ◽  
Fuzzy Data Envelopment Analysis ◽  
Relative Closeness ◽  
Fuzzy Ideal ◽  
Ideal Points ◽  
Fuzzy Dea

Abstract Data envelopment analysis (DEA) is a prominent technique for evaluating relative efficiency of a set of entities called decision making units (DMUs) with homogeneous structures. In order to implement a comprehensive assessment, undesirable factors should be included in the efficiency analysis. The present study endeavors to propose a novel approach for solving DEA model in the presence of undesirable outputs in which all input/output data are represented by triangular fuzzy numbers. To this end, two virtual fuzzy DMUs called fuzzy ideal DMU (FIDMU) and fuzzy anti-ideal DMU (FADMU) are introduced into proposed fuzzy DEA framework. Then, a lexicographic approach is used to find the best and the worst fuzzy efficiencies of FIDMU and FADMU, respectively. Moreover, the resulting fuzzy efficiencies are used to measure the best and worst fuzzy relative efficiencies of DMUs to construct a fuzzy relative closeness index. To address the overall assessment, a new approach is proposed for ranking fuzzy relative closeness indexes based on which the DMUs are ranked. The developed framework greatly reduces the complexity of computation compared with commonly used existing methods in the literature. To validate the proposed methodology and proposed ranking method, a numerical example is illustrated and compared the results with an existing approach.

scholarly journals A longitudinal Perspective on Efficiency of Airlines in Europe and the U.S

2021 ◽  
Vol 4 (2) ◽  
pp. 11-24
Author(s):  
Minh-Anh Nguyen Thi
Keyword(s):  
Data Envelopment Analysis ◽  
Marketing Strategies ◽  
Early Age ◽  
Employee Productivity ◽  
Data Envelopment ◽  
Publicly Traded ◽  
Dynamic Data ◽  
The Us ◽  
Dynamic Data Envelopment Analysis ◽  
The U.S

The aviation industries in Europe and the US have been well-established since a very early age and have attracted great attention from both industry practitioners and academics. To derive a different perspective on the efficiency levels of airlines operating in the two matured markets, we adopted dynamic data envelopment analysis (DEA). Using the data of the period 2014 – 2016 of 7 European airlines and 9 US airlines that are publicly traded, the study offers an overall picture of airlines' efficiency in the two regions. Notably, the resource flow between the consecutive periods is incorporated into the measure to yield a longitudinal perspective on airlines' efficiency. The study reveals the two major findings. First, most publicly traded airlines in Europe and the US are efficient, except for Hawaiian airline headquartered in the US. Second, Hawaiian airline's inefficiency is majorly contributed by the overuse of the number of employees, consumed fuel, and the deficit of revenue seat-miles in 2014 and 2015. To improve the efficiency level, Hawaiian airlines could consider increasing employee productivity, using more fuel-efficient aircraft, and implementing new marketing strategies to boost sales.

scholarly journals The Impact of Firm Financial Efficiency on Executive Compensation of United States Apparel Stores Industry: An Application of Panel Data Envelopment Analysis

2018 ◽  
Vol 11 (6) ◽  
pp. 165
Author(s):  
Herman Sahni ◽  
Christian Nsiah
Keyword(s):  
Data Envelopment Analysis ◽  
Executive Compensation ◽  
Pay For Performance ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Financial Efficiency ◽  
Performance Framework ◽  
The Us ◽  
Ceo Pay ◽  
The Impact

This study examines the effect of firm financial efficiency on executive compensation with an emphasis on the US apparel industry. We find that both annual efficiency levels and cumulative efficiency changes obtained from the Data Envelopment Analysis (DEA) are positively associated with CEO pay. The effect is stronger for technological changes and changes in scale efficiency. Our results seem to support the pay-for-efficiency paradigm, a stricter version of the pay-for-performance framework under the efficient contracting explanation for CEO pay.

scholarly journals A Mathematical Programming Approach to Brand Efficiency of Smartphones in the US Market

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Shiu-Wan Hung ◽  
Han-Chung Chou ◽  
Wen-Min Lu ◽  
Shi-Xiao Wang
Keyword(s):  
United States ◽  
Data Envelopment Analysis ◽  
Mathematical Programming ◽  
Growth Period ◽  
The United States ◽  
Programming Approach ◽  
Data Envelopment ◽  
Significant Difference ◽  
The Us ◽  
Mathematical Programming Approach

This study applied mathematical programming approach to investigate the brand efficiency of smartphone brands by collecting data of 2013–2015 from Consumer Report. The brand efficiency was completed by employing the slack-based measure in data envelopment analysis. The degree of inefficiency of each brand was evaluated, and each brand’s metatechnology ratio was calculated using the metafrontier concept. The results revealed that the sampled smartphone brands reach the highest average brand efficiency in 2013, where Apple exhibited the highest brand efficiency among the sampled brands. The high brand efficiency in 2013 was attributed to the small number of product types at beginning of the growth period of smartphones. Finally, this study examined the efficiency of smartphone brands among four major telecommunications operators in the United States. It was found that Apple demonstrated the highest efficiency with all four operators, while no significant difference was noted among operators and smartphone brands.

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