scholarly journals Performance Management of Public Transportation by the Network Data Envelopment Analysis (DEA) Model

2020 ◽  
Vol 25 (2) ◽  
pp. 45-58
Author(s):  
Babak Farhang Moghaddam ◽  
Zahra Saedi ◽  
◽  
Keyword(s):  
Data Envelopment Analysis ◽  
Performance Management ◽  
Public Transportation ◽  
Network Data ◽  
Data Envelopment ◽  
Dea Model ◽  
Network Data Envelopment Analysis

scholarly journals Sustainability Evaluation of Product Packaging System with a Three-Stage Network Data Envelopment Analysis Methodology

2019 ◽  
Vol 9 (2) ◽  
pp. 246 ◽  
Author(s):  
Yong Xie ◽  
Yafang Gao ◽  
Shihao Zhang ◽  
Hailong Bai ◽  
Zhenghao Liu
Keyword(s):  
Life Cycle ◽  
Data Envelopment Analysis ◽  
Empirical Test ◽  
Environmentally Friendly ◽  
Network Data ◽  
Data Envelopment ◽  
Packaging System ◽  
Product Packaging ◽  
Dea Model ◽  
Network Data Envelopment Analysis

This study presents a method that is based on the three-stage network Data Envelopment Analysis (DEA) to evaluate the sustainability of packaging systems for a product. This method facilitates the selection of better product packaging alternatives from an environmentally friendly point of view and it comprises the following four steps: (i) the definition of packaging sustainability indicator (PSI) based on environmental efficiency and impact indicator of three-stage in packaging life cycle, (ii) modeling a three-stage Network DEA model for a packaging system, (iii) computing PSI based on the DEA model, and (iv) result analysis. An empirical test has been progressed to prove the feasibility of the proposed method by selecting the three types of milk packaging systems. The results indicated that the PSI value of PrePack is the maximum and the Tetra Pak minimum. According to these results, the study provides an environmentally friendly evaluation method for product packaging systems, which is more intuitive than Life Cycle Assessment (LCA).

Conventional versus Islamic bank efficiency: A dynamic network data-envelopment-analysis approach

2020 ◽  
pp. 1-13
Author(s):  
Md Abul Kalam Azad ◽  
Muzalwana Binti Abdul Talib ◽  
Kwek Kian Teng ◽  
Paolo Saona
Keyword(s):  
Data Envelopment Analysis ◽  
Dynamic Network ◽  
Policy Implications ◽  
Network Data ◽  
Data Envelopment ◽  
Islamic Banks ◽  
Network Dea ◽  
Dea Model ◽  
Network Data Envelopment Analysis ◽  
Conventional Banks

This study compares the efficiency of conventional and Islamic banks in Malaysia by engaging in a dynamic three-step (production, intermediation, and profitability) network data envelopment analysis (DEA). The inputs and outputs for the DEA model are selected based on the CAMELS rating. The major contributions of this study are threefold. First, this study investigates the efficiency of Malaysian banks using a novel dynamic network DEA model. Second, the Malaysian banking industry is found to be efficient in creating earning assets rather than in creating loans or profit. The results reveal that only a few banks in Malaysia have been efficient in converting deposits and equities into profit. Third, Islamic banks, in general, have been performing efficiently in the production and profitability approaches. Conventional banks, in contrast, are found to have been efficient in the intermediation approach. Policy implications are derived from the main conclusions.

scholarly journals MEASURING EFFICIENCY OF A UNIVERSITY FACULTY USING A HIERARCHICAL NETWORK DATA ENVELOPMENT ANALYSIS MODEL

2018 ◽  
Author(s):  
Rosmaini Kashim ◽  
Maznah Mat Kasim ◽  
Rosshairy Abd Rahman
Keyword(s):  
Data Envelopment Analysis ◽  
Measurement Model ◽  
Data Envelopment Analysis Model ◽  
Network Data ◽  
University Faculty ◽  
Data Envelopment ◽  
Analysis Model ◽  
Dea Model ◽  
Network Data Envelopment Analysis ◽  
The Impact

An efficiency measurement model of a university faculty is proposed with additional new sub-functions that produce new output variables, based on the network Data Envelopment Analysis (DEA) model for systems with a hierarchical structure.For production systems composed of hierarchical processes, the system efficiency is well represented as the aggregated performance of the components involved in the system. It is identified that the conventional DEA model ignores internal process activities in a university. Therefore, an improved DEA model based on a network structure that accounts for more activities in a university is proposed to measure its overall efficiency. The impact of major functions of a university are taken into account to represent the output variables in assessing the efficiency. Currently, collaboration activities have been given more attention, so, this variable is suggested as a new output for the hierarchical production system. In order to show the practicality of the model, a hypothetical set of data of 14 faculties has been used as a numerical example. The results show that none of the faculties is relatively efficient since its functions were found to be inefficient. The proposed model enables to help the management of university faculties to identify weaknesses of each function and thus to plan for suitable actions on improving the overall performance of the university.  

scholarly journals Recommending investment opportunities given congestion by adaptive network data envelopment analysis model: Assessing sustainability of supply chains

2019 ◽  
Author(s):  
Hossein Hajaji ◽  
Sara Yousefi ◽  
Reza Farzipoor Saen ◽  
Amir Hassanzadeh
Keyword(s):  
Data Envelopment Analysis ◽  
Supply Chains ◽  
Data Envelopment Analysis Model ◽  
Network Data ◽  
Data Envelopment ◽  
Analysis Model ◽  
Adaptive Network ◽  
Dea Model ◽  
Network Data Envelopment Analysis ◽  
Desirable And Undesirable Outputs

Nowadays, forward-thinking companies move beyond conventional structures of organizations and consider all parties of the supply chain. The objective of this paper is to present an adaptive network data envelopment analysis (DEA) model to evaluate overall and divisional efficiency of sustainable supply chains in the presence of desirable and undesirable outputs. Our adaptive network DEA model can assess overall and divisional efficiency of supply chains given managerial and natural disposability. Also, it suggests new investment opportunity given congestion type. A case study is presented.

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