scholarly journals Malmquist Index with Time Series to Data Envelopment Analysis

2018 ◽  
Author(s):  
Jhon Jairo Vargas Sánchez
Keyword(s):  
Time Series ◽  
Data Envelopment Analysis ◽  
Malmquist Index ◽  
Data Envelopment

scholarly journals Long-Term Economic Sustainability of Humanitarian Logistics—A Multi-Level and Time-Series Data Envelopment Analysis

2021 ◽  
Vol 18 (5) ◽  
pp. 2219
Author(s):  
Matthias Klumpp ◽  
Dominic Loske
Keyword(s):  
Data Envelopment Analysis ◽  
Time Series Data ◽  
Malmquist Index ◽  
Developed Countries ◽  
Efficiency Analysis ◽  
Humanitarian Logistics ◽  
Series Data ◽  
Data Envelopment ◽  
Least Developed Countries ◽  
Window Analysis

Although resources are scarce and outputs incorporate the potential to save human lives, efficiency measurement endeavors with data envelopment analysis (DEA) methods are not yet commonplace in the research and practice of non-government organizations (NGO) and states involved in humanitarian logistics. We present a boot-strapped DEA window analysis and Malmquist index application as a methodological state of the art for a multi-input and multi-output efficiency analysis and discuss specific adaptions to typical core challenges in humanitarian logistics. A characteristic feature of humanitarian operations is the fact that a multitude of organizations are involved on at least two levels, national and supra-national, as well as in two sectors, private NGO and government agencies. This is modeled and implemented in an international empirical analysis: First, a comprehensive dataset from the 34 least developed countries in Africa from 2002 to 2015 is applied for the first time in such a DEA Malmquist index efficiency analysis setting regarding the national state actor level. Second, an analysis of different sections in a Rohingya refugee camp in Bangladesh is analyzed based on a bootstrapped DEA with window analysis application for 2017, 2018, and 2019 quarter data regarding the private NGO level of operations in humanitarian logistics.

scholarly journals KOMPARASI EFISIENSI & PRODUKTIVITAS PERUSAHAAN ASURANSI JIWA KONVENSIONAL DAN SYARIAH DI INDONESIA PADA TAHUN 2014 – 2017, DENGAN PENDEKATAN DEA & INDEKS MALMQUIST

2020 ◽  
Vol 6 (9) ◽  
pp. 1877
Author(s):  
Oky Suryoaji ◽  
Eko Fajar Cahyono
Keyword(s):  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Malmquist Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Constant Return

Tujuan penelitian ini adalah untuk mengetahui tingkat efisiensi dan produktivitas perusahaan asuransi jiwa antara konvensional dan syariah (baik Unit Usaha Syariah maupun Full Fledge) periode 2014 – 2017. Penelitian ini menggunakan pendekatan kuantitatif dengan metode non parametrik DEA (Data Envelopment Analysis) yang dilandaskan dengan asumsi CRS (Constant Return to Scale) dan VRS (Variable Return to Scale) dan Indeks Malmquist asumsi TFPC (Total Factor Productivity Change) dengan diolah menggunakan aplikasi DEAP Versi 2.1. Variabel yang digunakan meliputi Total Aset, Beban, Klaim, Premi/Dana Tabrru’, dan Pendapatan. Subjek yang digunakan dalam penelitian ini sebanyak 29 perusahaan asuransi jiwa syariah yang terdiri 10 perusahaan asuransi jiwa syariah dan 19 perusahaan asuransi jiwa konvensional. Hasil penelitian menunjukkan bahwa rata-rata perusahaan asuransi jiwa konvensional dan syariah belum mencapai efisien (CRS) dan rata-rata TFPC perusahaan asuransi jiwa konvensional sudah mencapai produktivitas sementara syariah belum mencapai produktivitas.Keywords:Asuransi Jiwa Syariah, Efisiensi, Produktivitas, Data Envelopment Analysis (DEA), Constant Return to Scale (CRS), Variable Return to Scale (VRS), Malmquist Index (MI), Total Factor Productivity Change (TFPC)

scholarly journals ASSESSMENT OF CONTINENT-WISE ENERGY EFFICIENCY BASED ON CO2 EMISSIONS: A SLACK-BASED DEA APPROACH

2021 ◽  
pp. 17-31
Author(s):  
Mohd Afjal ◽  
Kavya C S
Keyword(s):  
Energy Efficiency ◽  
Data Envelopment Analysis ◽  
Co2 Emissions ◽  
Malmquist Index ◽  
Efficiency Score ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Dea Approach

This study uses the Data Envelopment Analysis (DEA) slack-based model (SBM) and Malmquist Productivity Index (MPI) to evaluate energy efficiency based on CO2 emissions in 42 countries belonging to 6 continents. First, the data envelopment analysis was employed to calculate the efficiency scores for the countries individually and continent basis and then Malmquist index was used to examine the improvement. The study period chosen was 2011-2020. The results of this study showed that on the basis of continents there has been fluctuations in energy efficiency except for Australia, with an efficiency score of equal to one throughout the study period. Additionally, from the results of Malmquist Productivity Index it was found that the 42 countries showed no significant energy enhancement during the period of 2011-2020. KEYWORDS: Energy Efficiency, CO2 emissions, Continents, Data Envelopment Analysis, Malmquist Productivity Index

Data Envelopment Analysis and Malmquist Index Application: Efficiency of Primary Health Care in Morocco and Covid-19

2021 ◽  
Vol 12 (5) ◽  
pp. 971-983
Author(s):  
Youssef Er Rays, Et. al.
Keyword(s):  
Health Care ◽  
Primary Health Care ◽  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Malmquist Index ◽  
Policy Implications ◽  
Data Envelopment ◽  
Primary Health ◽  
Parametric Data ◽  
Strategic Role

The Primary Health Care in Morocco plays a very strategic role in the prevention against various diseases, in particular the current pandemic COVID 19. The efficiency of these centers has a direct impact on the reduction of this pandemic. First, this is why will try to research the literature review about the technical efficiency of primary health care. In the second step, the non-parametric: Data Envelopment Analysis method will be used to apply the empiric phase during the period 2012-2015, to estimate the relative technical efficiency, this method will be calculated by using two models: the theory of the return to scale constant with a middle equal to 0.437 and the theory of the variable return to scale with an average of 0.537. It’s necessary to combine the DEA approach with the Malmquist index to evaluate the factors of production. Finally, to compare the results of the proposed method which are generally very poor, and discuss his policy implications for health care.

scholarly journals Total Productivity Change of Health Centers in Greece in 2016-2018: A Malmquist Index Data Envelopment Analysis Application for the Primary Health System of Greece.

2021 ◽  
Author(s):  
Anastasios Trakakis ◽  
Miltiadis Nektarios ◽  
Styliani Tziaferi ◽  
Panagiotis Prezerakos
Keyword(s):  
Health Care ◽  
Primary Health Care ◽  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Malmquist Index ◽  
Health Centers ◽  
Productivity Change ◽  
Data Envelopment ◽  
Primary Health ◽  
Total Productivity

Abstract Background: This paper attempts to evaluate Primary Health Care System by evaluating Health Centers in Greece.Methods: Malmquist Index Data Envelopment Analysis is applied to study the total productivity of 155 Heath Centers in Greece during 2016-2018. The Data were collected from the Ministry of Health and were submitted into quality tests to ensure validity and avoid bias.Results: This paper measures the productivity of each of the 155 Health Centers in Greece and how it shifted during 2016-2018. In addition, the overall productivity change of the 155 Health Centers over time is calculated and analyzed into a change due to technical efficiency and a change due to technological efficiency. The analysis of the means values showed a decrease of 0,9% in the overall productivity factor from the year 2016 to the year 2017 and a decrease of 5,2% from the year 2017 to the year 2018. The overall decrease in the productivity of the 155 health Centers was 3,1%. From 2016 to 2018, 59 Health centers changed their productivity mainly due to technological change, 91 mainly due to technical efficiency change, while one Health Center showed regression to its total productivity due to equal regression of its technical efficiency and technology.Conclusions: The method used is non-parametric Data Envelopment Analysis along with Malmquist Index, so as to include panel data in the analysis. Meaningful results were extracted by indicating the number of Health Centers that their productivity improved, regressed or remained constant through the period 2016-2018. This paper may contribute to improve Health Centers’ efficiency and productivity. Furthermore, valuable results can be extracted, for the National Health Care System in order to match available resources depending on each Health Center’s needs, as well as for manager planners and stakeholders in Primary Health Care.JEL Classification: C14, C32, C52, I10

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