scholarly journals Benchmarking with network dea in a fuzzy environment

2019 ◽  
Vol 53 (2) ◽  
pp. 687-703 ◽  
Author(s):  
Adel Hatami-Marbini
Keyword(s):  
Classification Scheme ◽  
Data Envelopment ◽  
Network Dea ◽  
Performance Benchmarking ◽  
Fuzzy Environment ◽  
Dea Models ◽  
Banking Education ◽  
Business Engineering ◽  
Fuzzy Network

Benchmarking is a powerful and thriving tool to enhance the performance and profitabilities of organizations in business engineering. Though performance benchmarking has been practically and theoretically developed in distinct fields such as banking, education, health, and so on, benchmarking of supply chains with multiple echelons that include certain characteristics such as intermediate measure differs from other practices. In spite of incremental benchmarking activities in practice, there is the dearth of a unified and effective guideline for benchmarking in organizations. Amongst the benchmarking tools, data envelopment analysis (DEA) as a non-parametric technique has been widely used to measure the relative efficiency of firms. However, the conventional DEA models that are bearing out precise input and output data turn out to be incapable of dealing with uncertainty, particularly when the gathered data encompasses natural language expressions and human judgements. In this paper, we present an imprecise network benchmarking for the purpose of reflecting the human judgments with the fuzzy values rather than precise numbers. In doing so, we propose the fuzzy network DEA models to compute the overall system scale and technical efficiency of those organizations whose internal structure is known. A classification scheme is presented based upon their fuzzy efficiencies with the aim of classifying the organizations. We finally provide a case study of the airport and travel sector to elucidate the details of the proposed method in this study.

Measuring Performance of a Three-Stage Network Structure Using Data Envelopment Analysis and Nash Bargaining Game: A Supply Chain Application

2018 ◽  
Vol 17 (05) ◽  
pp. 1429-1467 ◽  
Author(s):  
Mohammad Amirkhan ◽  
Hosein Didehkhani ◽  
Kaveh Khalili-Damghani ◽  
Ashkan Hafezalkotob
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Nash Bargaining ◽  
Data Envelopment ◽  
Second Stage ◽  
Proposed Model ◽  
Nash Bargaining Game ◽  
Dea Models ◽  
Overall Efficiency

The issue of efficiency analysis of network and multi-stage systems, as one of the most interesting fields in data envelopment analysis (DEA), has attracted much attention in recent years. A pure serial three-stage (PSTS) process is a specific kind of network in which all the outputs of the first stage are used as the only inputs in the second stage and in addition, all the outputs of the second stage are applied as the only inputs in the third stage. In this paper, a new three-stage DEA model is developed using the concept of three-player Nash bargaining game for PSTS processes. In this model, all of the stages cooperate together to improve the overall efficiency of main decision-making unit (DMU). In contrast to the centralized DEA models, the proposed model of this study provides a unique and fair decomposition of the overall efficiency among all three stages and eliminates probable confusion of centralized models for decomposing the overall efficiency score. Some theoretical aspects of proposed model, including convexity and compactness of feasible region, are discussed. Since the proposed bargaining model is a nonlinear mathematical programming, a heuristic linearization approach is also provided. A numerical example and a real-life case study in supply chain are provided to check the efficacy and applicability of the proposed model. The results of proposed model on both numerical example and real case study are compared with those of existing centralized DEA models in the literature. The comparison reveals the efficacy and suitability of proposed model while the pitfalls of centralized DEA model are also resolved. A comprehensive sensitivity analysis is also conducted on the breakdown point associated with each stage.

scholarly journals Dealing with Interval DEA Based on Error Propagation and Entropy: A Case Study of Energy Efficiency of Regions in China Considering Environmental Factors

2015 ◽  
Vol 3 (6) ◽  
pp. 538-548 ◽  
Author(s):  
Jianping Fan ◽  
Weizhen Yue ◽  
Meiqin Wu
Keyword(s):  
Energy Efficiency ◽  
Environmental Factors ◽  
Error Propagation ◽  
Interval Data ◽  
Data Envelopment ◽  
Exact Data ◽  
Dea Models ◽  
Traditional Approaches ◽  
Decision Making Units

AbstractThe conventional data envelopment analysis (DEA) measures the relative efficiency of decision making units (DMUs) consuming multiple inputs to produce multiple outputs under the assumption that all the data are exact. In the real world, however, it is possible to obtain interval data rather than exact data because of various limitations, such as statistical errors and incomplete information, et al. To overcome those limitations, researchers have proposed kinds of approaches dealing with interval DEA, which either use traditional DEA models by transforming interval data into exact data or get an efficiency interval by using the bound of interval data. In contrast to the traditional approaches above, the paper deals with interval DEA by combining traditional DEA models with error propagation and entropy, uses idea of the modified cross efficiency to get the ultimate cross efficiency of DMUs in the form of error distribution and ranks DMUs using the calculated ultimate cross efficiency by directional distance index. At last we illustrate the feasibility and effectiveness of the proposed method by applying it to measure energy efficiency of regions in China considering environmental factors.

PORTFOLIO PERFORMANCE BENCHMARKING WITH DATA ENVELOPMENT ANALYSIS

2013 ◽  
Vol 30 (05) ◽  
pp. 1350011 ◽  
Author(s):  
PHILIP Y. L. WONG ◽  
STEPHEN C. H. LEUNG ◽  
JOHN D. GILLEARD
Keyword(s):  
Data Envelopment Analysis ◽  
Facility Management ◽  
Future Research ◽  
Portfolio Performance ◽  
Analysis Tool ◽  
Data Envelopment ◽  
Performance Improvements ◽  
Hard Data ◽  
Performance Benchmarking

This paper proposes data envelopment analysis (DEA) as a suitable data analysis tool to overcome facility management (FM) benchmarking difficulties: FM performance benchmarking analysis is often unsophisticated, relying heavily on simple statistical representation, linking hard cost data with soft customer satisfaction data is often problematic. A case study is presented to show that DEA can provide FM personnel with an objective view on performance improvements. An objective of the case study is to investigate the relative efficiency of nine facilities with the same goals and to determine the most efficient facility. The case is limited to nine buildings in FM on four inputs and nine output criteria. The paper concludes by demonstrating that DEA-generated improvement targets can be applied when formulating FM outsourcing policies, strategies and improvements. Facility manager can apply DEA-generated improvement targets in formulating FM outsourcing policies, specifications development, FM strategy and planning. FM benchmarking with DEA can enhance continuous improvement in service efficiency and cost saving. This will help reduce utility cost as well as pollution. This paper fills the gap in the research of FM benchmarking by applying DEA which studies both soft and hard data simultaneously. It also contributes to a future research of a trade-off sensitivity test between FM cost, services performance and reliability.

scholarly journals Uniformization of frontiers in non-radial ZSG-DEA models: an application to airport revenues

2010 ◽  
Vol 30 (1) ◽  
pp. 175-193 ◽  
Author(s):  
Aline Bandeira de Mello Fonseca ◽  
João Carlos Correia Baptista Soares de Mello ◽  
Eliane Gonçalves Gomes ◽  
Lidia Angulo Meza
Keyword(s):  
Data Envelopment Analysis ◽  
Theoretical Approach ◽  
Approximate Algorithm ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Dea Models ◽  
Weights Restrictions ◽  
Zero Sum

We propose in this paper an extension to the Zero Sum Gains Data Envelopment Analysis model (ZSG-DEA). The proposed approach takes into account, simultaneously, non-radial projections and cone-ratio weights restrictions. We developed an iterative approximate algorithm to solve this model, as in the case study it is oriented only to the constant sum output. The theoretical approach is applied to the concession of discounts and surcharges problem, in terms of airport fees.

International performance benchmarking in winemaking

2017 ◽  
Vol 24 (1) ◽  
pp. 24-33 ◽  
Author(s):  
Anatoliy G. Goncharuk ◽  
Natalia Lazareva
Keyword(s):  
Wine Industry ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Content Type ◽  
International Performance ◽  
Performance Benchmarking ◽  
Capital Productivity ◽  
Product Service ◽  
Study Results ◽  
Dea Models

Purpose The purpose of this paper is to study winemaking efficiency with the help of international performance benchmarking and to finding ways for its improvement. Design/methodology/approach In this research, three models of data envelopment analysis (DEA) and other tools of international performance benchmarking are used to analyse the efficiency of wine companies. Return to scale (RTS) and scale efficiency, labour and capital productivity and some other indicators are examined. The research is based on a sample of 36 wine companies from 15 countries. Findings International benchmarking expands performance improvement for domestic companies. The most efficient wine companies are originated from Germany, USA and New Zeeland. Scale inefficiency and increasing RTS for most of the wine companies was identified. Only three wine companies have decreasing RTS (those from UK, Australia and France). To increase relative efficiency, these companies need to reduce the output and sales as their costs are growing faster than the revenues. A huge potential for cost reduction and efficiency growth within Ukrainian wine companies was revealed. Research limitations/implications The research is limited to a single industry. This is explained by the requirement of technology (product, service) homogeneity while using DEA tools. Practical implications Study results include the data and recommendations to develop winemaking. These results can be used by wine companies’ management, present and potential investors and proprietors, regulative public authority, e.g. to improve efficiency in winemaking. Originality/value This is the first paper that adapts various DEA models to measure efficiency in the wine industry of Ukraine and the tools of international performance benchmarking for wine companies around the world.

scholarly journals A Review of Data Envelopment Analysis in Airline Efficiency: State of the Art and Prospects

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Qiang Cui ◽  
Li-Ting Yu
Keyword(s):  
Data Envelopment Analysis ◽  
Rapid Development ◽  
Aviation Industry ◽  
Future Research ◽  
Data Envelopment ◽  
Social Concern ◽  
Network Dea ◽  
Advantages And Disadvantages ◽  
Dea Models ◽  
Future Research Directions

The rapid development of the aviation industry has brought about the deterioration of the climate, which makes airline efficiency become a hot issue of social concern. As an important nonparametric method, Data Envelopment Analysis (DEA), has been widely applied in efficiency evaluation. This paper examines 130 papers published in the period of 1993–2020 to summarize the literature involving the special application of DEA models in airline efficiency. The paper begins with an overall review of the existing literature, and then the radial DEA, nonradial DEA, network DEA, dynamic DEA, and DEA models with undesirable outputs applied in airline efficiency are introduced. The main advantages and disadvantages of the above models are summarized, and the drivers of airline efficiency are analyzed. Finally, the literature review ends up with future research directions and conclusions.

A NEW RANKING APPROACH WITH A MODIFIED CROSS EVALUATION MATRIX

2013 ◽  
Vol 30 (04) ◽  
pp. 1350008 ◽  
Author(s):  
BYUNG HO JEONG ◽  
CHANG-SOO OK
Keyword(s):  
Rank Order ◽  
Distance Measures ◽  
Data Envelopment ◽  
Ranking Methods ◽  
Ranking Problem ◽  
Dea Models ◽  
The Difference ◽  
Ranking Problems ◽  
Evaluation Matrix

Cross evaluation matrix was suggested to resolve a ranking problem in the data envelopment analysis (DEA) context. The cross evaluation matrix is composed of simple efficiency and cross-efficiency (CE) values of decision making units (DMUs). However, simple efficiency cannot discriminate efficient DMUs because of the nature of basic DEA models. To make complete use of the efficiency information of DMUs, a modified cross evaluation matrix is proposed. The modified matrix consists of super-efficiency (SE) values for diagonal elements and CE values for nondiagonal elements. As the efficiency values are not limited to "1" in SE approach, the proposed matrix can explain the difference of efficiency of efficient DMUs. The proposed matrix can be more accurate than the original cross evaluation matrix. Consequently, the rank order of DMUs generated by the suggested matrix reflects differences in relative efficiency of DMUs. A numerical example is given to show the superiority of the proposed approach. This is done by comparing with other available ranking methods in the DEA context. Several distance measures are utilized to compare rank consistency of the ranking methods. Finally, a case study is presented to explain how our approach is applied to real ranking problems.

A novel fuzzy network SBM model for data envelopment analysis: A case study in Iran regional power companies

Energy ◽  
2016 ◽  
Vol 112 ◽  
pp. 686-697 ◽  
Author(s):  
H. Ebrahimzadeh Shermeh ◽  
S.E. Najafi ◽  
M.H. Alavidoost
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Regional Power ◽  
Sbm Model ◽  
Fuzzy Network

scholarly journals Fuzzy Ranking Network DEA with General Structure

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2222
Author(s):  
Plácido Moreno ◽  
Sebastián Lozano
Keyword(s):  
General Structure ◽  
Efficiency Score ◽  
Linear Program ◽  
Data Envelopment ◽  
Network Dea ◽  
Fuzzy Ranking ◽  
Overall Efficiency ◽  
Highly Correlated ◽  
Fuzzy Network ◽  
General Networks

This paper extends two fuzzy ranking data envelopment analysis (DEA) approaches to the case of general networks of processes. The first approach provides an efficiency score for each possibility level which requires solving one linear program for each possibility level. The second approach is even simpler and provides an overall efficiency score solving just one linear program. The proposed approaches are tested on two datasets from the literature and compared with other fuzzy network DEA approaches. The results show that the two methods provide very highly correlated efficiency estimates which are also consistent with those of other fuzzy network DEA approaches.

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