Efficiency and its determinants in the Algerian banks: network data envelopment analysis and partial least squares regression

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Adel Achi
Keyword(s):  
Data Envelopment Analysis ◽  
Banking System ◽  
Foreign Banks ◽  
Network Data ◽  
Data Envelopment ◽  
Pls Regression ◽  
Content Type ◽  
Explanatory Factors ◽  
Overall Efficiency ◽  
Domestic Banks

PurposeThe purpose of this paper is to evaluate the efficiency of Algerian banks and examine the effects of explanatory factors on their performance.Design/methodology/approachIn this paper, a methodology of two-stage network data envelopment analysis (DEA) is used to explore the efficiency of a sample of 13 Algerian banks during the 2013–2017 period. In the first stage, the network DEA is used to assess the overall and stages efficiencies. In the second stage, the partial least squares (PLS) regression is conducted to determine the potential effects of explanatory factors on stages efficiency.FindingsThe main empirical results indicate that Algerian banks need an efficiency improvement in both stages. The overall efficiency of the Algerian banking system improves over the study period. The deposit producing efficiency is positively affected by bank size and bank age. The revenue earning efficiency is negatively associated with bank size and bank age. The domestic banks are more efficient than foreign banks in the deposit producing stage and the foreign banks are more efficient than domestic banks in the revenue earning stage.Practical implicationsThe results might be used as guidelines for both managers and policymakers in order to improve banks and banking system performance.Originality/valueTo the best of our knowledge, this study is the first that uses the DEA in investigating the efficiency of Algerian banks by dividing the overall efficiency into deposit producing and revenue earning efficiencies. Unlike most studies that have usually used OLS regression, Tobit regression and bootstrapped truncated regression, this study is the first in the bank efficiency literature that uses PLS regression to investigate the potential effect of explanatory variables on deposit producing and revenue earning efficiencies.

scholarly journals Has the Efficiency of China’s Healthcare System Improved after Healthcare Reform? A Network Data Envelopment Analysis and Tobit Regression Approach

2019 ◽  
Vol 16 (23) ◽  
pp. 4847 ◽  
Author(s):  
Guangwen Gong ◽  
Yingchun Chen ◽  
Hongxia Gao ◽  
Dai Su ◽  
Jingjing Chang
Keyword(s):  
Data Envelopment Analysis ◽  
Healthcare System ◽  
Health Expenditure ◽  
Healthcare Reform ◽  
Healthcare Systems ◽  
Network Data ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Network Data Envelopment Analysis ◽  
Overall Efficiency

Background: A healthcare system refers to a typical network production system. Network data envelopment analysis (DEA) show an advantage than traditional DEA in measure the efficiency of healthcare systems. This paper utilized network data envelopment analysis to evaluate the overall and two substage efficiencies of China’s healthcare system in each of its province after the implementation of the healthcare reform. Tobit regression was performed to analyze the factors that affect the overall efficiency of healthcare systems in the provinces of China. Methods: Network DEA were obtained on MaxDEA 7.0 software, and the results of Tobit regression analysis were obtained on StataSE 15 software. The data for this study were acquired from the China health statistics yearbook (2009–2018) and official websites of databases of Chinese national bureau. Results: Tobit regression reveals that regions and government health expenditure effect the efficiency of the healthcare system in a positive way: the number of high education enrollment per 100,000 inhabitants, the number of public hospital, and social health expenditure effect the efficiency of healthcare system were negative. Conclusion: Some provincial overall efficiency has fluctuating increased, while other provincial has fluctuating decreased, and the average overall efficiency scores were fluctuations increase.

scholarly journals The Sustainability Performance of Chinese Banks: A New Network Data Envelopment Analysis Approach and Panel Regression

2019 ◽  
Vol 11 (6) ◽  
pp. 1622 ◽  
Author(s):  
Yantuan Yu ◽  
Jianhuan Huang ◽  
Yanmin Shao
Keyword(s):  
Data Envelopment Analysis ◽  
Scale Effects ◽  
Estimation Method ◽  
Dynamic Network ◽  
Generalized Least Squares ◽  
Foreign Banks ◽  
Network Data ◽  
Significant Heterogeneity ◽  
Data Envelopment ◽  
Network Data Envelopment Analysis

This paper develops a new network data envelopment analysis (DEA) model that simultaneously integrates the non-convex metafrontier and undesirable outputs and which is super efficient at performing dynamic network slacks-based measures. The model is employed to discuss the efficiency of 36 commercial banks in China during the years 2010–2014. The efficiency of these banks shows significant heterogeneity and the efficiency of most foreign banks has much room for improvement. Regarding both the non-convex metafrontier and the group frontier, state-owned banks perform the best, followed by joint-stock banks, with foreign banks performing the worst; the same is true for the technology gap ratios. The empirical results produced by the feasible generalized least squares estimation method indicate that liquidity and scale effects exert positive impacts on bank efficiency. An alternative estimation method confirmed that the conclusions were robust.

Forecasting sustainability of supply chains in the circular economy context: a dynamic network data envelopment analysis and artificial neural network approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hadi Shabanpour ◽  
Saeed Yousefi ◽  
Reza Farzipoor Saen
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Data Envelopment Analysis ◽  
Supply Chains ◽  
Circular Economy ◽  
Real Life ◽  
Network Data ◽  
Data Envelopment ◽  
Content Type ◽  
First Time

PurposeThe objective of this research is to put forward a novel closed-loop circular economy (CE) approach to forecast the sustainability of supply chains (SCs). We provide a practical and real-world CE framework to improve and fill the current knowledge gap in evaluating sustainability of SCs. Besides, we aim to propose a real-life managerial forecasting approach to alert the decision-makers on the future unsustainability of SCs.Design/methodology/approachIt is needed to develop an integrated mathematical model to deal with the complexity of sustainability and CE criteria. To address this necessity, for the first time, network data envelopment analysis (NDEA) is incorporated into the dynamic data envelopment analysis (DEA) and artificial neural network (ANN). In general, methodologically, the paper uses a novel hybrid decision-making approach based on a combination of dynamic and network DEA and ANN models to evaluate sustainability of supply chains using environmental, social, and economic criteria based on real life data and experiences of knowledge-based companies so that the study has a good adaptation with the scope of the journal.FindingsA practical CE evaluation framework is proposed by incorporating recyclable undesirable outputs into the models and developing a new hybrid “dynamic NDEA” and “ANN” model. Using ANN, the sustainability trend of supply chains for future periods is forecasted, and the benchmarks are proposed. We deal with the undesirable recycling outputs, inputs, desirable outputs and carry-overs simultaneously.Originality/valueWe propose a novel hybrid dynamic NDEA and ANN approach for forecasting the sustainability of SCs. To do so, for the first time, we incorporate a practical CE concept into the NDEA. Applying the hybrid framework provides us a new ranking approach based on the sustainability trend of SCs, so that we can forecast unsustainable supply chains and recommend preventive solutions (benchmarks) to avoid future losses. A practicable case study is given to demonstrate the real-life applications of the proposed method.

A data envelopment analysis approach by partial impacts between inputs and desirable-undesirable outputs for sustainable supplier selection problem

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Nemati ◽  
Reza Farzipoor Saen ◽  
Reza Kazemi Matin
Keyword(s):  
Data Envelopment Analysis ◽  
Supplier Selection ◽  
Selection Problem ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Content Type ◽  
Dea Model ◽  
Sustainable Supplier Selection ◽  
Overall Efficiency ◽  
Supplier Selection Problem

PurposeThe objective of this paper is to propose a new data envelopment analysis (DEA) model for assessing sustainability of suppliers with partial impacts between inputs, desirable outputs and undesirable outputs.Design/methodology/approachThis paper examines partial impacts of inputs on desirable and undesirable outputs and applies weak disposability assumption to propose a novel DEA model to determine the sustainability of suppliers.FindingsThis paper shows the type of resource sharing in DEA models and takes into account sustainable development and sustainability assessment concepts for sustainable supplier selection problem and develops a DEA model for selecting the most sustainable suppliers with partial sharing of resources. To select the most sustainable suppliers, this model helps managers to consider aggregate efficiency, overall efficiency and bundle efficiency. The paper introduces the supplier which is efficient at all levels as the most sustainable supplier.Originality/valueFor the first time, this paper suggests a new DEA model by partial impact between inputs and good outputs/bad outputs for selecting sustainable supplier and deals with the situations in which each supplier has several subunits. The new model calculates aggregate efficiency, overall efficiency and subunit efficiency of supplier. paper introduces the supplier which is efficient in all levels including aggregate efficiency, overall efficiency and subunit efficiency as the best supplier.

Evaluation of the components of intelligence and greenness in Iranian ports based on network data envelopment analysis (DEA) approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Esmaeil Sadri ◽  
Fatemeh Harsej ◽  
Mostafa Hajiaghaei-Keshteli ◽  
Jafar Siyahbalaii
Keyword(s):  
Performance Evaluation ◽  
Data Envelopment Analysis ◽  
The Other ◽  
Network Data ◽  
Data Envelopment ◽  
Maritime Transport ◽  
Content Type ◽  
Other Hand ◽  
Green Port ◽  
Smart Ports

Purpose Creating green ports, while observing international and international standards and maritime conventions and regulations and moving toward smart ports, can increase the speed of goods transfer, enable the tracking of ships and goods, increase the transparency of statistics, increase the quality and capacity of ports and reduce costs. Hence, the purpose of this study the development and evaluation of ports play a key role in their commercial success. Development policies can be formulated for these ports by properly evaluating their performance indicators. On the other hand, traditional methods of performance evaluation cannot provide a good multidimensional evaluation of the status of ports. Design/methodology/approach More than 90% of the world’s heavy transit today is carried out by the sea. With this volume of freight, transit accidents are inevitable for ships passing through oceans, seas, waterways, rivers, ports and mooring at docks. Besides, gases from ships’ fuels at sea, especially in ports, oil spills due to maritime incidents, the negligence of the ship’s crew, the use of port equipment, dirty fuel of diesel power substations, etc., have increased greenhouse gases, polluted the environment and endangered human lives. Findings A new approach has been introduced in the field of port performance evaluation based on the components of greenness and intelligence. This approach performs evaluations in two stages and a network. In this study, the performance of 11 Iranian ports was evaluated based on the network data envelopment analysis approach in 2 stages of greenness and intelligence during 4 years. The results indicated that only 5% of the ports meet the standards of intelligence and greenness. Originality/value On the other hand, as shown in the above studies, the issue of green ports is directly related to the development of animal and plant ecosystems in the seas and the environment around ports. The presence of pollution in the ports has caused the animal and plant habitats around the ports to face a complete pollution crisis or to be completely destroyed. Therefore, the development of green port concepts in third world countries will help prevent environmental pollution of the seas. Therefore, it is necessary for ports to review their strategic maritime transport model and use the development of green port indicators in their implementation processes. Therefore, the strategic development of green ports is created to create and benefit from the components of intelligence, and as mentioned in previous research, intelligence and greenness are in line and the lack of development of one of the concepts causes defects in others. According to reports provided in Iran’s maritime transport systems, most accidents have led to environmental disasters during the absence of intelligent equipment. The use of smart technologies prevents all environmental damage and the development of port services. On the other hand, in evaluating the published articles in the field of development of green and smart ports, so far, the components of intelligence and greenness have not been evaluated and analyzed in a practical and operational way in ports and only the influencing the development of agents on each other has been done (Chen, 2019). Therefore, evaluating the efficiency of ports based on green components and intelligence causes ports to fundamentally review their executive infrastructure and take an active part in the global green development plan.

Evaluating after-sales service units by developing inverse network data envelopment analysis model

2019 ◽  
Vol 27 (2) ◽  
pp. 695-707 ◽  
Author(s):  
Reza Farzipoor Saen ◽  
Seyed Shahrooz Seyedi Hosseini Nia
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Efficiency Score ◽  
Data Envelopment Analysis Model ◽  
Network Data ◽  
Data Envelopment ◽  
Analysis Model ◽  
Content Type ◽  
Network Data Envelopment Analysis ◽  
Decision Making Unit

Purpose The purpose of this paper is to develop an inverse network data envelopment analysis (INDEA) model to solve resource allocation problems. Design/methodology/approach The authors estimate inputs’ variations based on outputs so that the efficiencies of decision-making unit under evaluation (DMUo) and other decision-making units (DMUs) are constant. Findings The new INDEA model is developed to allocate resources such that inputs are not increased while efficiency scores of all DMUs remain constant. Furthermore, the authors obtain new combinations of inputs and outputs, together with a growth in efficiency score of DMUo such that efficiency scores of other DMUs are not changed. A case study is provided. Originality/value This paper proposes INDEA model to estimate inputs (outputs) without changing efficiency scores of DMUs.

An application of network data envelopment analysis with fuzzy data for the performance evaluation in cargo sector

2018 ◽  
Vol 31 (4) ◽  
pp. 492-509 ◽  
Author(s):  
Berna Simsek ◽  
Fatih Tüysüz
Keyword(s):  
Performance Evaluation ◽  
Data Envelopment Analysis ◽  
Performance Measurement ◽  
Real Life ◽  
Process Efficiency ◽  
Network Data ◽  
Data Envelopment ◽  
Fuzzy Data ◽  
Content Type ◽  
Network Data Envelopment Analysis

Purpose The purpose of this paper is to present a methodology which enables to measure and analyze the performance of sub-process and overall system of a cargo company. Design/methodology/approach Network data envelopment analysis method with fuzzy data is used for performance measurement which considers the sub-process efficiency simultaneously together with the overall efficiency and also the uncertainty included in input–output data. Findings A real-life application of the proposed model is presented for Turkey. The application results show the efficiency scores of ten branches according to each sub-process and also the overall system. Although the obtained results are case specific, the application results indicate that the inefficient branches can achieve efficiency either by decreasing circulation ratio input for human resources sub-process or by increasing closed complaint output or by decreasing open complaint output for customer relationship management sub-process. Originality/value The study presented provides insights into the performance measurement applications in cargo sector. The methodology presented provides the flexibility of removing or adding some new sub-processes and also decision-making units which enables the approach to be used for other performance evaluation problems.

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