Developing a new super-efficiency DEA model in the presence of both zero data and stochastic data: a case study in the Iranian airline industry

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Tavassoli ◽  
Amirali Fathi ◽  
Reza Farzipoor Saen
Keyword(s):  
Airline Industry ◽  
Returns To Scale ◽  
Content Type ◽  
Super Efficiency ◽  
Dea Model ◽  
Proposed Model ◽  
Stochastic Dea ◽  
Stochastic Data ◽  
Constant Returns To Scale

PurposeThe purpose of this study is to propose a novel super-efficiency DEA model to appraise the relative efficiency of DMUs with zero data and stochastic data. Our model can work with both variable returns to scale (VRS) and constant returns to scale (CRS).Design/methodology/approachThis study proposes a new stochastic super-efficiency DEA (SSDEA) model to assess the performance of airlines with stochastic and zero inputs and outputs.FindingsThis paper proposes a new analysis and contribution to the knowledge of efficiency assessment with stochastic super-efficiency DEA model by (1) using input saving and output surplus index for efficient DMUs to get the optimal solution; (2) obtaining efficiency scores from the proposed model that are equivalent to original stochastic super-efficiency model when feasible solutions exist. A case study is given to illustrate the applicability of our proposed model. Also, poor performance reasons are identified to improve the performance of inefficient airlines.Originality/valueFor the first time, a new SSDEA model for ranking DMUs is proposed. The introduced model produces a feasible solution when dealing with zero input or output. This paper applies the input saving and output surplus concept to rectify the infeasibility problem in the stochastic DEA model.

Estimating the efficiency of Greek banking system during the last decade of world economic crisis

2018 ◽  
Vol 25 (6) ◽  
pp. 1762-1794 ◽  
Author(s):  
Zois Sompolos ◽  
Maria Mavri
Keyword(s):  
Economic Crisis ◽  
Banking Sector ◽  
Returns To Scale ◽  
Banking System ◽  
Operational Efficiency ◽  
Operating Efficiency ◽  
Content Type ◽  
Dea Model ◽  
The Impact ◽  
Constant Returns To Scale

Purpose The purpose of this paper is to examine the efficiency of the four largest Greek banking organizations for the period 2004–2014, including both a period of strong economic growth and a period of economic crisis and recession, which is still plaguing the Greek economy and more specifically the Greek banking sector. Design/methodology/approach The study incorporates the application of financial ratio analysis and the data envelopment analysis (DEA) in order to calculate the technical efficiency of Greek financial institutions. More specifically, a two-stage output-oriented DEA model is developed in order to estimate the global efficiency of banks. The banking function is considered as consisting of two stages in series, a service/operational efficiency and a profitability efficiency. In both output-oriented models, methods of constant returns to scale and variable returns to scale were applied. Findings The results show that in terms of operational efficiency, banks started from a low rate of return in 2004, which improved until 2008, which marked the peak of operational efficiency. By 2010, the operating efficiency varied with downward trend until 2012–2013. In terms of profitability efficiency, the image is clearer, since the impact the financial crisis had on bank’s profit efficiency led, by 2012, to a plunge in the average efficiency by 30–40 percent. Originality/value A multi-stage DEA process, input oriented, was used in order to estimate changes in the performance and efficiency of banking system. The period 2004–2014 has not been examined until recently and all previous studies used the output-oriented DEA model.

Fuzzy stochastic Data Envelopment Analysis with application to NATO enlargement problem

2019 ◽  
Vol 53 (2) ◽  
pp. 705-721 ◽  
Author(s):  
Ali Ebrahimnejad ◽  
Seyed Hadi Nasseri ◽  
Omid Gholami
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Threshold Values ◽  
Discrimination Power ◽  
Dea Model ◽  
Nato Enlargement ◽  
Proposed Model ◽  
Stochastic Dea ◽  
Dea Models ◽  
Stochastic Data

Data Envelopment Analysis (DEA) is a widely used technique for measuring the relative efficiencies of Decision Making Units (DMUs) with multiple deterministic inputs and multiple outputs. However, in real-world problems, the observed values of the input and output data are often vague or random. Indeed, Decision Makers (DMs) may encounter a hybrid uncertain environment where fuzziness and randomness coexist in a problem. Hence, we formulate a new DEA model to deal with fuzzy stochastic DEA models. The contributions of the present study are fivefold: (1) We formulate a deterministic linear model according to the probability–possibility approach for solving input-oriented fuzzy stochastic DEA model, (2) In contrast to the existing approach, which is infeasible for some threshold values; the proposed approach is feasible for all threshold values, (3) We apply the cross-efficiency technique to increase the discrimination power of the proposed fuzzy stochastic DEA model and to rank the efficient DMUs, (4) We solve two numerical examples to illustrate the proposed approach and to describe the effects of threshold values on the efficiency results, and (5) We present a pilot study for the NATO enlargement problem to demonstrate the applicability of the proposed model.

A cross evaluation-based measure of super efficiency in DEA with interval data

Kybernetes ◽  
2016 ◽  
Vol 45 (4) ◽  
pp. 666-679 ◽  
Author(s):  
Qian Yu ◽  
Fujun Hou
Keyword(s):  
Data Envelopment Analysis ◽  
Practical Method ◽  
Interval Data ◽  
Data Envelopment ◽  
Imprecise Data ◽  
Content Type ◽  
Super Efficiency ◽  
Dea Model ◽  
Model Based ◽  
Proposed Model

Purpose – The traditional data envelopment analysis (DEA) model as a non-parametric technique can measure the relative efficiencies of a decision-making units (DMUs) set with exact values of inputs and outputs, but it cannot handle the imprecise data. The purpose of this paper is to establish a super efficiency interval data envelopment analysis (IDEA) model, an IDEA model based on cross-evaluation and a cross evaluation-based measure of super efficiency IDEA model. And the authors apply the proposed approach to data on the 29 public secondary schools in Greece, and further demonstrate the feasibility of the proposed approach. Design/methodology/approach – In this paper, based on the IDEA model, the authors propose an improved version of establishing a super efficiency IDEA model, an IDEA model based on cross-evaluation, and then present a cross evaluation-based measure of super efficiency IDEA model by combining the super efficiency method with cross-evaluation. The proposed model cannot only discriminate the performance of efficient DMUs from inefficient ones, but also can distinguish between the efficient DMUs. By using the proposed approach, the overall performance of all DMUs with interval data can be fully ranked. Findings – A numerical example is presented to illustrate the application of the proposed methodology. The result shows that the proposed approach is an effective and practical method to measure the efficiency of the DMUs with imprecise data. Practical implications – The proposed model can avoid the fact that the original DEA model can only distinguish the performance of efficient DMUs from inefficient ones, but cannot discriminate between the efficient DMUs. Originality/value – This paper introduces the effective method to obtain the complete rank of all DMUs with interval data.

Selecting Six Sigma project: a comparative study of DEA and LDA techniques

2018 ◽  
Vol 9 (4) ◽  
pp. 506-522 ◽  
Author(s):  
A. Hadi-Vencheh ◽  
A. Yousefi
Keyword(s):  
Six Sigma ◽  
Selection Process ◽  
Project Selection ◽  
Decision Quality ◽  
Data Envelopment ◽  
Content Type ◽  
Dea Model ◽  
Risk Of Failure ◽  
Proposed Model

Purpose Nowadays, most of the organizations have focused through the world on Six Sigma to reduce the costs, improve the productivity and enhance concerned individuals’ satisfaction, especially customers’ satisfaction. Annually, these organizations define and execute thousands of Six Sigma projects which involve a great deal of investments. But are all of these projects successful and do the organizations benefit from the above advantages? The purpose of this study is to proposing a methodology to to answer this question that: How can we reduce the risk of failure in Six Sigma projects? The first step to reduce the risk of failure in Six Sigma projects is selecting optimal ones which have the most profits and the least expected risks. Design/methodology/approach First, the effective criteria are recognized and defined in selecting Six Sigma projects. Then, a new data envelopment analysis (DEA) model is proposed for project selection process. A real example is resolved by the presented model. Finally, the authors use linear discriminate analysis (LDA) to examine the validity of obtained results from the proposed model. Findings The results show that the proposed model is a suitable tool for selecting Six Sigma Projects. The findings demonstrate that the selected projects by suggested integrated DEA model are those confirmed by LDA. Originality/value The paper, using a real case study, provides a mathematical model to enhance decision quality in Six Sigma project selection. Applying the specific DEA model is remarkable itself, which joined to a pioneering procedure to use LDA to validity evaluation of the results.

scholarly journals How to evaluate sustainability of supply chains? A dynamic network DEA approach

2017 ◽  
Vol 117 (9) ◽  
pp. 1866-1889 ◽  
Author(s):  
Vahid Shokri Kahi ◽  
Saeed Yousefi ◽  
Hadi Shabanpour ◽  
Reza Farzipoor Saen
Keyword(s):  
Big Data ◽  
Supply Chains ◽  
Real World ◽  
Performance Optimization ◽  
Network Dynamic ◽  
Network Dea ◽  
Content Type ◽  
Dea Model ◽  
Proposed Model ◽  
First Time

Purpose The purpose of this paper is to develop a novel network and dynamic data envelopment analysis (DEA) model for evaluating sustainability of supply chains. In the proposed model, all links can be considered in calculation of efficiency score. Design/methodology/approach A dynamic DEA model to evaluate sustainable supply chains in which networks have series structure is proposed. Nature of free links is defined and subsequently applied in calculating relative efficiency of supply chains. An additive network DEA model is developed to evaluate sustainability of supply chains in several periods. A case study demonstrates applicability of proposed approach. Findings This paper assists managers to identify inefficient supply chains and take proper remedial actions for performance optimization. Besides, overall efficiency scores of supply chains have less fluctuation. By utilizing the proposed model and determining dual-role factors, managers can plan their supply chains properly and more accurately. Research limitations/implications In real world, managers face with big data. Therefore, we need to develop an approach to deal with big data. Practical implications The proposed model offers useful managerial implications along with means for managers to monitor and measure efficiency of their production processes. The proposed model can be applied in real world problems in which decision makers are faced with multi-stage processes such as supply chains, production systems, etc. Originality/value For the first time, the authors present additive model of network-dynamic DEA. For the first time, the authors outline the links in a way that carry-overs of networks are connected in different periods and not in different stages.

A bi-level mathematical model for logistic management considering the evolutionary game with environmental feedbacks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Peiman Ghasemi ◽  
Fariba Goodarzian ◽  
Angappa Gunasekaran ◽  
Ajith Abraham
Keyword(s):  
Mathematical Model ◽  
Lagrangian Relaxation ◽  
Evolutionary Games ◽  
Relaxation Method ◽  
Objective Functions ◽  
Content Type ◽  
Medical Centers ◽  
Location Routing ◽  
Proposed Model

PurposeThis paper proposed a bi-level mathematical model for location, routing and allocation of medical centers to distribution depots during the COVID-19 pandemic outbreak. The developed model has two players including interdictor (COVID-19) and fortifier (government). Accordingly, the aim of the first player (COVID-19) is to maximize system costs and causing further damage to the system. The goal of the second player (government) is to minimize the costs of location, routing and allocation due to budget limitations.Design/methodology/approachThe approach of evolutionary games with environmental feedbacks was used to develop the proposed model. Moreover, the game continues until the desired demand is satisfied. The Lagrangian relaxation method was applied to solve the proposed model.FindingsEmpirical results illustrate that with increasing demand, the values of the objective functions of the interdictor and fortifier models have increased. Also, with the raising fixed cost of the established depot, the values of the objective functions of the interdictor and fortifier models have raised. In this regard, the number of established depots in the second scenario (COVID-19 wave) is more than the first scenario (normal COVID-19 conditions).Research limitations/implicationsThe results of the current research can be useful for hospitals, governments, Disaster Relief Organization, Red Crescent, the Ministry of Health, etc. One of the limitations of the research is the lack of access to accurate information about transportation costs. Moreover, in this study, only the information of drivers and experts about transportation costs has been considered. In order to implement the presented solution approach for the real case study, high RAM and CPU hardware facilities and software facilities are required, which are the limitations of the proposed paper.Originality/valueThe main contributions of the current research are considering evolutionary games with environmental feedbacks during the COVID-19 pandemic outbreak and location, routing and allocation of the medical centers to the distribution depots during the COVID-19 outbreak. A real case study is illustrated, where the Lagrangian relaxation method is employed to solve the problem.

An M/M/C/K queueing system in an inventory routing problem considering congestion and response time for post-disaster humanitarian relief: a case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahdieh Masoumi ◽  
Amir Aghsami ◽  
Mohammad Alipour-Vaezi ◽  
Fariborz Jolai ◽  
Behdad Esmailifar
Keyword(s):  
Sensitivity Analyses ◽  
Inventory Routing ◽  
Humanitarian Relief ◽  
Exact Methods ◽  
Routing Problem ◽  
Content Type ◽  
Inventory Routing Problem ◽  
The People ◽  
Proposed Model

PurposeDue to the randomness and unpredictability of many disasters, it is essential to be prepared to face difficult conditions after a disaster to reduce human casualties and meet the needs of the people. After the disaster, one of the most essential measures is to deliver relief supplies to those affected by the disaster. Therefore, this paper aims to assign demand points to the warehouses as well as routing their related relief vehicles after a disaster considering convergence in the border warehouses.Design/methodology/approachThis research proposes a multi-objective, multi-commodity and multi-period queueing-inventory-routing problem in which a queuing system has been applied to reduce the congestion in the borders of the affected zones. To show the validity of the proposed model, a small-size problem has been solved using exact methods. Moreover, to deal with the complexity of the problem, a metaheuristic algorithm has been utilized to solve the large dimensions of the problem. Finally, various sensitivity analyses have been performed to determine the effects of different parameters on the optimal response.FindingsAccording to the results, the proposed model can optimize the objective functions simultaneously, in which decision-makers can determine their priority according to the condition by using the sensitivity analysis results.Originality/valueThe focus of the research is on delivering relief items to the affected people on time and at the lowest cost, in addition to preventing long queues at the entrances to the affected areas.

A multi-attribute approach to select the best method for repairing river bridge columns

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mitra Salmaninezhad ◽  
S. Mahmood Jazayeri Moghaddas
Keyword(s):  
Evaluation Criteria ◽  
Bridge Columns ◽  
Pier Scour ◽  
Content Type ◽  
Accuracy And Precision ◽  
Proposed Model ◽  
Research Findings ◽  
Multi Attribute Decision Making ◽  
Weighing Method

PurposePier scour is one of the main causes of damage to the columns of the river bridges. It is essential to select the best method among various repair methods based on different evaluation indices. However, there is no procedure for ranking these repair methods based on their attributes. The present study seeks to set an approach for this ranking.Design/methodology/approachIn this paper, a multi-attribute decision-making (MADM) model is presented for ranking the repair techniques, in which alternatives are examined using the most important evaluation criteria. In addition, a combination of entropy and eigenvector methods has been proposed for weighting these attributes. A case study is then used to demonstrate the applicability and the validity of the method.FindingsThe execution of the model using two multi-criteria methods yielded similar results, which confirms its accuracy and precision. Moreover, the research findings showed the consistency of the objective and subjective weighting methods and the conformity of the weights obtained for the attributes from the combination of these methods to the nature of the problem.Originality/valueThe selection of the proper method for repairing the bridge columns plays an essential role in success of the bridge restoration. The proposed model introduces an approach for ranking repair methods and selecting the best one that has not been presented so far. Also, the weighing method for attributes is an innovative method for ranking restoration methods that has been proven in a case study.

A novel product recommendation model consolidating price, trust and online reviews

Kybernetes ◽  
2019 ◽  
Vol 48 (6) ◽  
pp. 1355-1372 ◽  
Author(s):  
Ying Huang ◽  
Nu-nu Wang ◽  
Hongyu Zhang ◽  
Jianqiang Wang
Keyword(s):  
Search Engines ◽  
Distance Measure ◽  
Fuzzy Theory ◽  
Online Reviews ◽  
Purchasing Decisions ◽  
Neutrosophic Sets ◽  
Content Type ◽  
Product Recommendation ◽  
Proposed Model

Purpose The purpose of this paper is to propose a model for product recommendation to improve the accuracy of recommendation based on the current search engines used in e-commerce platforms like Tmall.com. Design/methodology/approach First, the proposed model comprehensively considers price, trust and online reviews, which all represent critical factors in consumers’ purchasing decisions. Second, the model introduces the quantization methods for these criteria incorporating fuzzy theory. Third, the model uses a distance measure between two single valued neutrosophic sets based on the prioritized average operator to consolidate the influences of positive, neutral and negative comments. Finally, the model uses multi-criteria decision-making methods to integrate the influences of price, trust and online reviews on purchasing decisions to generate recommendations. Findings To demonstrate the feasibility and efficiency of the proposed model, a case study is conducted based on Tmall.com. The results of case study indicate that the recommendations of our model perform better than those of current search engines of Tmall.com. The proposed model can significantly improve the accuracy of product recommendations based on search engines. Originality/value The product recommendation method can meet the critical challenge from the search engines on e-commerce platforms. In addition, the proposed method could be used in practice to develop a new application for e-commerce platforms.

scholarly journals Loyalty programs: the vital safety feature for airlines to survive COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Manuel E. Pascual ◽  
Lisa Nicole Cain
Keyword(s):  
Airline Industry ◽  
Loyalty Programs ◽  
Current Response ◽  
Long Term Effects ◽  
Loyalty Program ◽  
Case Study Methodology ◽  
Content Type ◽  
Hospitality And Tourism ◽  
American Airlines

PurposeThe airline industry has been severely impacted by COVID-19 due to widespread travel restrictions. Its current response is crucial to ensure continued operations after the global pandemic is resolved. One resource the airlines are leveraging is loyalty programs. This study aims to examine the viability of leveraging loyalty programs in times of crisis.Design/methodology/approachThis study employs a case study methodology to examine how one company, American Airlines, has used its loyalty program to survive a pandemic and alleviate the financial costs associated with limited and restricted travel.FindingsAmerican Airlines' AAdvantage loyalty program structure may be used as a benchmark to understand how airlines can anchor their loyalty base to reinvigorate travel interest and use these programs as safeguards in critical instances that may arise in the future.Research limitations/implicationsThe case was bound by the fact that the pandemic was still a threat during the time of analysis. The findings of this case study go beyond the airline industry and may inform other hospitality and tourism organizations on the benefits of loyalty programs in times of financial distress.Originality/valueThis is the first known case study examining the strengths and opportunities of the structure of the American Airlines' AAdvantage program as a means for surviving in a time of crisis. Moreover, understanding how to mitigate the long-term effects of crises may help to inform future short-term strategies of airlines and other hospitality and tourism organizations for navigating unexpected shocks to their ecosystem.

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