scholarly journals Strategic Container Ports Competitiveness Analysis in West Africa Using Data Envelopment Analysis (DEA) Model

2019 ◽  
Vol 07 (02) ◽  
pp. 680-692
Author(s):  
Bomboma Kalgora
Keyword(s):  
Data Envelopment Analysis ◽  
West Africa ◽  
Data Envelopment ◽  
Dea Model ◽  
Container Ports ◽  
Using Data

scholarly journals Measuring West-Africa Ports Efficiency Using Data Envelopment Analysis

2019 ◽  
Vol 09 (03) ◽  
pp. 287-308 ◽  
Author(s):  
Bomboma Kalgora ◽  
Sidoine Yao Goli ◽  
Bomboma Damigou ◽  
Hamadou Tahirou Abdoulkarim ◽  
Kwame Kwadu Amponsem
Keyword(s):  
Data Envelopment Analysis ◽  
West Africa ◽  
Data Envelopment ◽  
Using Data

scholarly journals Data envelopment analysis with fuzzy complex numbers; with an empirical case on power plants of Iran

2020 ◽  
Author(s):  
Mahmood Esfandiari ◽  
Saber Saati
Keyword(s):  
Data Envelopment Analysis ◽  
Power Plants ◽  
Complex Numbers ◽  
Complex Data ◽  
Data Envelopment ◽  
Steam Power ◽  
Dea Model ◽  
Steam Power Plants ◽  
Using Data ◽  
Α Level

Using Data Envelopment Analysis (DEA) in complex environment is an idea that has recently presented for measuring the relative efficiencies of a set of Decision Making Units (DMUs) with complex inputs and outputs. The values of the input and output data in real-world problems appear sometimes as fuzzy complex number. For dealing with these types of data in DEA, we need to design a new model. This paper proposes a DEA model with triangular fuzzy complex numbers and solve it by using the concept of the data size and the α-level approach. This method transforms DEA model with fuzzy complex data to a linear programing problem with crisp data. In the following, a ranking model is also developed using the above approach to rank the efficient DMUs. The proposed method is presented for the first time by the authors and there is no similar method. Finally, we present a case study in the generators of the steam power plants to demonstrate the applicability of the proposed methods in the power industry.

scholarly journals Measurement of Ministry/Institution Budget Performance Efficiency Using Data Envelopment Analysis (DEA)

2020 ◽  
Vol 2 (1) ◽  
pp. 43
Author(s):  
Shiddiq Ardhi Irawan
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Performance Achievement ◽  
Dea Model ◽  
Constant Return ◽  
Crs Model ◽  
The Government ◽  
Using Data ◽  
Measurement And Evaluation ◽  
Model Approach

Efficiency is one of the tools used by the Government to measure the success of an activity. Based on PMK Number 214/ PMK.02/2017 it is regulated regarding the measurement and Evaluation of Budget Performance for the implementation of Work Plans and Ministries/Institutions Budgets. To measure budget performance achievement based on aspects of implementation 4 (four) variables i.e. budget absorption, output achievements, efficiency, and consistency of budget absorption towards planning, are used. This study aims to measure the efficiency level of Ministries/Institutions budget performance using Data Envelopment Analysis (DEA). However, the variables used are not only based on measurement aspects of implementation according to PMK Number 214/PMK.02/2017 but also the number of satker (satuan Kerja). The approach used in the DEA model is Constant Return to Scale (CRS) model and Variable Return to Scale (VRS) model. This study uses the DEA model approach by comparing the results of the CRS model with VRS model. Based on DEA results, the number of Ministries/Institutions that have efficient scores is less than the number of Ministries/Institutions with inefficient scores. In addition, based on the value of slacks in each Ministries/Institutions, the variables that need to be improved are the coordination among satkers in when they are recording their performance achievements in the SMART application. Other variables that also require improvements are the ministry/agency’s willingness to revise their Disbursement Plan (RPD) after each budget revision and the speed at which they spend their budget once DIPA is stipulated.

Evaluating the efficiency of Mediterranean container ports using data envelopment analysis

2021 ◽  
pp. 178359172110478
Author(s):  
Gianfranco Fancello ◽  
Patrizia Serra ◽  
Valentina Aramu ◽  
Daniel Mark Vitiello
Keyword(s):  
Data Envelopment Analysis ◽  
Success Factors ◽  
Management Strategies ◽  
The Arctic ◽  
Data Envelopment ◽  
Port Throughput ◽  
Container Ports ◽  
Market Needs ◽  
Production Output ◽  
Using Data

Mediterranean container ports are constantly requested to face new market challenges after years of decline of their traffic in favour of a stronger leadership of Northern range ports, also favoured by the consolidation of the Arctic Route and the Belt and Road Initiative. To regain competitiveness, Mediterranean ports must undertake a path of operational, managerial and infrastructural strengthening. This study applies Data Envelopment Analysis (DEA) to 35 Mediterranean container ports in order to identify the potential key success factors on which to intervene to improve their competitiveness potential and response to the new market needs. The application uses the port throughput as output, and three inputs: yard area, number of quay cranes and distance of the port from the Suez–Gibraltar axis. The latter has been inserted in the study to evaluate whether it can affect port efficiency. Both input- and output-oriented approaches are used in order to investigate the port competitiveness through the production function (input-oriented), and the port commercial competitiveness based on the output and feasibility of its production (output-oriented). Results can provide insights for the implementation of future policies and management strategies aimed to strengthen the Mediterranean port context.

Strategic resource management model and data envelopment analysis for benchmarking of Indian retailers

2016 ◽  
Vol 23 (2) ◽  
pp. 286-312 ◽  
Author(s):  
Aradhana Gandhi ◽  
Ravi Shankar
Keyword(s):  
Data Envelopment Analysis ◽  
Resource Management ◽  
Data Envelopment ◽  
Planning Tool ◽  
Content Type ◽  
Dea Model ◽  
Strategic Resource ◽  
Using Data ◽  
Practical Implications ◽  
Better Than

Purpose – The purpose of this paper is to use strategic resource management (SRM) model and data envelopment analysis (DEA) for benchmarking Indian retailers. The study ascertains, how a retailer can benchmark its performance at company level, global level, store level and finally at merchandise category level using diverse strategies for inventory, space and people. Design/methodology/approach – The paper aims to use SRM model, for evaluating and comparing the performance of two generalized retailers Shoppers Stop and Trent. These two generalized retailers are benchmarked with another best-in-class retailer, Wal-Mart using the SRM model. The benchmarking exercise brings out improvement directions for the Indian retailers. In the next part of the study, economic efficiencies of 11 generalized retailers are ascertained using DEA model. Finally, a study is conducted to understand, how SRM model can be used as a planning tool for deciding alternative inventory, space and people strategies at store level as well as at merchandise category level. Findings – Based on the data for the year 2011-2012, Trent’s performance is comparatively better than Shoppers Stop. The paper offers suggestion to improve its performance. Next, it was found that the performance of Wal-Mart is superior to the two Indian retailers. The study offers direction to the two retailers to devise appropriate strategies to improve their performance. The study further ascertains the relative efficiencies of 11 generalized retailers in the country. Finally, an illustration of how a retailer can use the SRM model as a tool for planning alternative strategy for inventory, space and people in a particular merchandise category is offered using data from a retail firm. The study has used “Jeans” and “Toys” as two categories to demonstrate this concept. Practical implications – The examples considered in this paper can be used by practicing retailers to plan and benchmark their performance. Originality/value – The study proposes a method, by which retailers can examine ways to plan and improve their operations and profitability by using the SRM and DEA model. The study is therefore relevant to practicing retailers as well as academicians.

scholarly journals Measuring efficiency of federally qualified health centers : a multi model approach using data envelopment analysis (DEA) and latent class analysis (LCA)

2021 ◽  
Author(s):  
◽  
Rohith Madhi Reddy
Keyword(s):  
Health Care ◽  
Data Envelopment Analysis ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Health Centers ◽  
Data Envelopment ◽  
Class Analysis ◽  
Federally Qualified Health Centers ◽  
Dea Model ◽  
Using Data

There are 1300 federally qualified health centers (FQHCs) in the United States providing the health care to underserved and uninsured population. These FQHCs serve the patients irrespective of their ability to pay. Using the resources effectively, these FQHCs can provide better health care. In this study of prenatal care, we measure the efficiencies of the FQHCs using data envelopment analysis (DEA). As in service industry, where quality is of at most importance, we used two different DEA approaches considering quality called the Two model DEA approach by (Shimshak, D., and Lenard, M.L.,2007) and Quality adjusted DEA approach by (Sherman, H.D., and Zhu, J, 2006). Efficient frontiers are determined by using these DEA approaches. There are differences that exists across FQHCs due to various factors to include demographic characteristics of patients visited the FQHCs, operational characteristics of health centers. Latent class analysis is performed before performing the DEA to classify the FQHCs into different classes based on the regional and population measures. Four different models namely aggregated Shimshak and Lenard and aggregated Sherman and Zhu models (DEA model is run on the whole sample), partitioned S and L and partitioned S and Z models (DEA model is run individually by class) have been used to determine the efficiencies of the FQHCs. Using the S and L approach, it is found that the FQHCs that formed the efficient frontier is of smaller FQHCs whereas the S and Z approach has a mix of small and large FQHCs. Based on the results determined, more insights are provided on the FQHCs and the models used in the analysis.

Data Envelopment Analysis (DEA) in the Psychological Sciences

2019 ◽  
Author(s):  
Jeffrey A. Shero ◽  
Sara Ann Hart
Keyword(s):  
Data Envelopment Analysis ◽  
Aggressive Behavior ◽  
Personality Traits ◽  
Educational Administration ◽  
Latent Variable ◽  
Organizational Management ◽  
Data Envelopment ◽  
Targeted Interventions ◽  
Component Skills ◽  
Using Data

Using methods like linear regression or latent variable models, researchers are often interested in maximizing explained variance and identifying the importance of specific variables within their models. These models are useful for understanding general ideas and trends, but often give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method with roots in organizational management that make such insights possible. Unlike models mentioned above, DEA does not explain variance. Instead, it explains how efficiently an individual utilizes their inputs to produce outputs, and identifies which input is not being utilized optimally. This paper provides readers with a brief history and past usages of DEA from organizational management, public health, and educational administration fields, while also describing the underlying math and processes behind said model. This paper then extends the usage of this method into the psychology field using two separate studies. First, using data from the Project KIDS dataset, DEA is demonstrated using a simple view of reading framework identifying individual efficiency levels in using reading-based skills to achieve reading comprehension, determining which skills are being underutilized, and classifying and comparing new subsets of readers. Three new subsets of readers were identified using this method, with direct implications leading to more targeted interventions. Second, DEA was used to measure individuals’ efficiency in regulating aggressive behavior given specific personality traits or related skills. This study found that despite comparable levels of component skills and personality traits, significant differences were found in efficiency to regulate aggressive behavior on the basis of gender and feelings of provocation.

Sign in / Sign up

Export Citation Format

Share Document