A NEW MALMQUIST PRODUCTIVITY INDEX BASED ON SEMI-DISCRETIONARY VARIABLES WITH AN APPLICATION TO COMMERCIAL BANKS OF CHINA

2011 ◽  
Vol 10 (04) ◽  
pp. 713-730 ◽  
Author(s):  
GONG-BING BI ◽  
JING-JING DING ◽  
YAN LUO ◽  
LIANG LIANG
Keyword(s):  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Mixed Integer ◽  
Productivity Change ◽  
Data Envelopment ◽  
Bank Of China ◽  
Proposed Model ◽  
Efficiency Increase ◽  
Integer Linear Model ◽  
Changes Over Time

The Malmquist productivity index studies productivity change, that is, the technical progress or regress together with the efficiency changes over time. In a nonparametric framework, the index can be estimated by data envelopment analysis (DEA). In this paper, first all inputs are divided into three groups, namely, discretionary variables, nondiscretionary variables, and semi-discretionary variables, and then a mixed integer linear model is proposed to deal with semi-discretionary variables. The proposed models consider not only the properties of semi-discretionary inputs, but also the relationship between them and other inputs. By introducing such a relationship and the preferences of decision-makers (DMs), the models aid DMs in generating efficiency scores and finding proper benchmarking points. Finally, the Malmquist productivity index combining the proposed model is computed and illustrated by an empirical application to the evaluation of 17 branches of Bank of China in Anhui Province. The results show a slight decrease in productivity during the year 2007/2008, and the productivity change positively during 2008/2009 due largely to efficiency increase.

scholarly journals Measuring the Productivity of Energy Consumption of Major Industries in China: A DEA-Based Method

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Xishuang Han ◽  
Xiaolong Xue ◽  
Jiaoju Ge ◽  
Hengqin Wu ◽  
Chang Su
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Policy Makers ◽  
Time Periods ◽  
Decision Making Units

Data envelopment analysis can be applied to measure the productivity of multiple input and output decision-making units. In addition, the data envelopment analysis-based Malmquist productivity index can be used as a tool for measuring the productivity change during different time periods. In this paper, we use an input-oriented model to measure the energy consumption productivity change from 1999 to 2008 of fourteen industry sectors in China as decision-making units. The results show that there are only four sectors that experienced effective energy consumption throughout the whole reference period. It also shows that these sectors always lie on the efficiency frontier of energy consumption as benchmarks. The other ten sectors experienced inefficiency in some two-year time periods and the productivity changes were not steady. The data envelopment analysis-based Malmquist productivity index provides a good way to measure the energy consumption and can give China's policy makers the information to promote their strategy of sustainable development.

scholarly journals Eco-Efficiency Assessment for Some European Countries Using Slacks-Based Measure Data Envelopment Analysis

2020 ◽  
Vol 10 (5) ◽  
pp. 1760 ◽  
Author(s):  
Chia-Nan Wang ◽  
Hsien-Pin Hsu ◽  
Yen-Hui Wang ◽  
Tri-Tung Nguyen
Keyword(s):  
Data Envelopment Analysis ◽  
Poor Performance ◽  
European Countries ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Measure Data ◽  
Productivity Change ◽  
Data Envelopment ◽  
Efficiency Assessment ◽  
Energy Inputs

One problem raised by the lack of energy efficiency is the generation of more greenhouse gases (GHGs) that can cause air pollution and climate change. Ecological efficiency (eco-efficiency) means the efficiency of resources used. A poor performance from this efficiency can then be detected for further improvement. In this research, we conduct an assessment on the eco-efficiency for some European countries as they consume a large part of global energy annually. A total of 17 European countries were selected as decision making units (DMUs) and assessed by the Slacks-based measure (SBM) Data Envelopment Analysis (DEA) model. Indices including Catch-Up, Frontier-Shift, and Malmquist Productivity Index (MPI) have been used to evaluate eco-efficiency, as well as efficiency change, technological change, and productivity change, over 2013–2017. In the model, energy consumption and share of renewable energy are used as energy inputs, and labor productivity and gross capital formation are used as economy inputs. On the other hand, GDP is used as a desired output, and CO2 emissions is used as one undesired output. The experimental results show that the 17 countries as a whole lacked eco-efficiency in 2013–2017, implying more efforts are required to improve their eco-efficiency.

scholarly journals A DEA Resampling Past-Present-Future Comparative Analysis of the Food and Beverage Industry: The Case Study on Thailand vs. Vietnam

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1140 ◽  
Author(s):  
Chia-Nan Wang ◽  
Minh Nhat Nguyen ◽  
Anh Luyen Le ◽  
Hector Tibo
Keyword(s):  
National Income ◽  
Value Added ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Beverage Industry ◽  
Food And Beverage Industry ◽  
Food And Beverage ◽  
Research Findings

The food and beverage industry plays a significant role in the economic development of developing and emerging countries in Asia through an immense contribution to the national income, employment, value-added inducement, and foreign exchange earnings. Among the developing countries in Asia, Thailand and Vietnam have recently experienced a significant growth in the industry due to their many advantages. However, the nascent stage of this industry was found to be lacking sustainable competitiveness in both countries. Therefore, this study aims to evaluate and forecast the performance efficiency of the food and beverage industry in Thailand and Vietnam to understand how efficient the food and beverage industry to these countries is and formulate suggestions to improve their productivity in accordance with the research findings. To achieve the research objectives, the resampling method in the data envelopment analysis is applied to measure and forecast the efficiency of 20 Vietnamese companies and 20 Thailand firms over the period of 2016 to 2023. The Malmquist productivity index is deployed to calculate the efficiency change over observed periods. The results reveal that Vietnam is found to have a higher efficiency than Thailand due to the outstanding performance of one company but have performed quite poorly due to low scores in technical and productivity change. The findings of this research can give useful information and practical suggestions to improve performance for inefficient companies as well as enhance competitiveness of the efficient companies trying to operate and reach global markets.

Global Malmquist Productivity Index based on preference common-weights

Filomat ◽  
2016 ◽  
Vol 30 (10) ◽  
pp. 2653-2661 ◽  
Author(s):  
Salman Abbasian-Naghneh
Keyword(s):  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Programming Technique ◽  
Common Weights ◽  
Common Basis ◽  
Dea Models ◽  
Efficiency And Productivity ◽  
Linear Programming Technique

Data Envelopment Analysis is a linear programming technique for assessing the efficiency and productivity of decision making units (DMUs). Over the last decade, DEA has gained considerable attention as a managerial tool for measuring performance. The flexibility in selecting the weights in standard DEA models deters the comparison among DMUs on a common base. Moreover, these weights are unsuitable to measure the preferences of a decision maker (DM). For dealing with these two difficulties simultaneously; we use preference common weights. This paper uses preference common weights for time-series evaluations to calculate the global Malmquist productivity index (MPI) so that the productivity of changes of all DMUs have a common basis for comparison, and DM?s preference information is incorporated in calculating global MPI. The Malmquist Productivity Index (MPI) suggests a convenient way of measuring the productivity change of a given unit between two consequent time periods.

scholarly journals A Novel Improved Data Envelopment Analysis Model Based on SBM and FDH Models

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Mirpouya Mirmozaffari ◽  
Gohar Azeem ◽  
Azam Boskabadi ◽  
Ali Aranizadeh ◽  
Aditya Vaishnav ◽  
...  
Keyword(s):  
Data Envelopment Analysis ◽  
High Performance ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Free Disposal Hull ◽  
Free Disposal ◽  
Proposed Model

During the past decade, applying nonparametric operation research problems such as Data Envelopment Analysis(DEA) has received significant consideration among researchers. In this paper, a new DEA-based SBM-FDH model is introduced. Finally, productivity evaluation for banking systems in Malmquist Productivity Index (MPI) based on the proposed model has been compared with Slack Based Measurement (SBM) and Free Disposal Hull (FDH). The obtained results confirm the high performance of the proposed model in comparison to the other models used in this paper.                                                                                                                                                                                                                                                                                                                           

scholarly journals EVALUATING THE EFFICIENCY PROGRESS WITH TECHNOLOGY IN A SPANISH HOTEL CHAIN

2015 ◽  
Vol 55 (5) ◽  
pp. 551-562 ◽  
Author(s):  
Maria del Rosario González-Rodriguez ◽  
Rosario Martín-Samper ◽  
Antonio Carlos Giuliani
Keyword(s):  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Organizational Changes ◽  
Technological Efficiency ◽  
Total Productivity ◽  
Hotel Chain ◽  
Recession Period

ABSTRACTThis paper analyzes the changes in the total factor productivity index of a Spanish hotel chain in the period from 2007 to 2010 with the purpose of identifying efficiency patterns for the chain in a period of financial crisis. The data envelopment analysis (DEA) Malmquist productivity index was used to estimate productivity change in 38 hotels of the AC chain. Results reveal AC hotels' efficiency trends and, therefore, their competitiveness in the recession period; they also show the changes experienced in these hotels' total productivity and its components: technological and efficiency changes. Positive efficiency changes were due to positive technical efficiency rather than technological efficiency. The recession period certainly influenced the performance of AC Hotels, which focused on organizational changes rather than investing in technology.

scholarly journals EFFICIENCY AND PRODUCTIVITY CHANGE ACROSS THE ECONOMIC SECTORS IN LITHUANIA (2000–2010): THE DEA–MULTIMOORA APPROACH

2014 ◽  
Vol 19 (Supplement_1) ◽  
pp. S191-S213 ◽  
Author(s):  
Tomas Baležentis ◽  
Algimantas Misiūnas ◽  
Alvydas Baležentis
Keyword(s):  
Value Added ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Economic Sectors ◽  
Services Sector ◽  
Intermediate Consumption ◽  
The Impact ◽  
Efficiency And Productivity

Reasonable strategic management requires the complex assessment of the regulated area. This study, thus, presents a multi-criteria framework for frontier assessment of efficiency and productivity across the Lithuanian economic sectors throughout 2000–2010. The data envelopment analysis was employed to estimate efficiency in terms of an output indicator (value added) and input indicators (intermediate consumption, capital consumption, and remunerations). Furthermore, the decomposition of the Malmquist productivity index enabled to describe the impact of frontier shifts and catch-up effect on the overall change in efficiency. The multi-criteria decision making method MULTIMOORA aggregated different indicators of efficiency and productivity and thus resulted in the ranking of the economic sectors. The analysis suggests that services sector was the most efficient one, whereas manufacturing was second best. Certain branches of manufacturing, namely pharmaceutical, wood, food, and furniture industry, were rather efficient.

scholarly journals ANALISIS TINGKAT EFISIENSI SEKTOR PARIWISATA DI JAWA TENGAH TAHUN 2017 DAN 2019

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Yennie Glorya Panjaitan ◽  
Edy Yusuf Agung Gunanto
Keyword(s):  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change

Sektor pariwisata sebagai salah satu sektor yang diandalkan bagi penerimaan daerah maka pemerintah Provinsi Jawa Tengah dituntut untuk dapat menggali dan mengelola potensi wisata yang dimiliki. Penelitian ini bertujuan untuk menganilisis tingkat efisiensi dan produktivitas pada sektor pariwisata di Jawa Tengah antara tahun 2017 dan 2019 dengan sampel 35 Kabupaten/Kota. Analisis dilakukan dengan menggunakan konsep efisiensi yang didasarkan pada teori produksi, pengukuran nilai efisiensi dan produktivitas diperoleh menggunakan metode analisis Data Envelopment Analysis (DEA) dan Malmquist Productivity Index (MPI). Asumsi yang digunakan adalah variable return to scale (VRTS) dan model orientasi output (output oriented). Dengan variable input objek wisata, restoran dan rumah makan, biro perjalanan wisata dan jumlah hotel bintang serta melati. Variabel output dalam penelitian ini adalah wisatawan dan pendapatan sektor pariwisata. Hasil akhir penelitian menunjukkan bahwa terdapat 16 Kabupaten/Kota (45,8%) di tahun 2017, 18 Kabupaten/Kota (51,4%) di tahun 2019 yang mencapai efisiensi teknis penuh. Total Factor productivity change mengindikasikan bahwa 22 Kabupaten/Kota (62,8%) mendekati frontier baik pada frontier produksi maupun frontier efisiensi dan dari scale efficiency change mengindikasikan bahwa terdapat 17 Kabupaten/Kota (48,57%) mengalami perbaikan efisiensi teknis selama periode 2017 ke 2019.

scholarly journals Bank Branch Closure Assessment Using DEA

JEJAK ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 134-145
Author(s):  
Renata Parsaulian ◽  
Dony Abdul Chalid
Keyword(s):  
Efficiency Score ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Bank Branch ◽  
The One ◽  
Branch Office ◽  
Efficiency And Productivity

The downward trend in the number of commercial bank offices is driven by the bank's efforts to shift banking transactions from physical branch to digital channels in order to improve efficiency. In prioritizing the branch closure, bank needs to define the appropriate method used in the analysis. This case study is intended to identify the parameter to determine the prioritization of bank branch office closure. This study uses a non-parametric approach of Data Envelopment Analysis (DEA) to examine the efficiency and productivity change of branch offices at one of the large bank in Indonesia. The one-stage DEA was used to generate the relative efficiency score, and the input-oriented Variable Return to Scale (VRS) assumption is adopted in data analysis based on the production approach. The Malmquist Productivity Index was also adopted to measure the total factor productivity change. The DEA result shows that a number of closed branches in 2019 and 2020 were actually considered efficient, with increasing productivity, compared to many other inefficient branches. The efficiency and productivity score can be further used by the bank’s management to evaluate the upcoming branch closure as well as the overall branches efficiency.

Postcrisis REIT performance using financial ratios: A DEA approach

2020 ◽  
pp. 135481662096266
Author(s):  
Apostolos Ampountolas
Keyword(s):  
Financial Ratios ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Moderate Degree ◽  
Efficiency Change ◽  
Real Estate Investment ◽  
Operational Strategies ◽  
Performance Determinants

This study examines the performance of public lodging real estate investment trusts (REITs) following the financial crisis period from 2013 to 2017. We employed data envelopment analysis, a nonparametric technique based on linear programming, to measure performance. Determinants of efficiency were assessed by a set of financial ratios predicting each REIT’s efficiency against its peers. Consequently, a Malmquist productivity index (MPI) evaluated the efficiency change in several periods. The empirical results revealed that the REITs generally performed well despite the moderate degree of volatility in the financial ratios. Results showed a wide variation in performance consistency, with a limited number of REITs—that is, 5 out of 20—consistently performing well during the study period. Additionally, the MPI indicated a decline in efficiency, while the productivity change showed a mixture of reflections. The decomposition components of the productivity index and efficiency changes are also provided. This study sheds light on understanding inefficient REITs and provides some guidance on the critical indicators that would help such REITs restructure their operational strategies to improve efficiency.

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