scholarly journals Progress and Regress of Time Dependent Data and Application in Bank Branch

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
F. Hosseinzadeh Lotfi ◽  
Z. Taeb ◽  
S. Abbasbandy
Keyword(s):  
Decision Making ◽  
Commercial Bank ◽  
Spline Function ◽  
Time Dependent ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Dependent Data ◽  
Bank Branch ◽  
Decision Making Unit ◽  
Cubic Spline Function

To evaluate each decision making unit having time dependent inputs and outputs data, a new method has been developed and reported here. This method uses the Malmquist productivity index, and is a very simple function based on Cubic Spline function to determine the progress and regress of that unit. To show the capability of this developed method, the data of 9 branches of a commercial bank has been used, evaluated, and reported.

scholarly journals A STUDY FOR SUSTAINABLE DEVELOPMENT IN OPTOELECTRONICS INDUSTRY USING MULTIPLE CRITERIA DECISION MAKING METHODS

2015 ◽  
Vol 23 (2) ◽  
pp. 221-242 ◽  
Author(s):  
Chun-Chu LIU ◽  
An-Chin CHENG ◽  
Shih-Hui CHEN
Keyword(s):  
Decision Making ◽  
Sustainable Development ◽  
Multiple Criteria Decision Making ◽  
Operational Efficiency ◽  
Multiple Criteria ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Decision Making Unit ◽  
The Future ◽  
Constant Returns To Scale

This study assessed the operational efficiency of the optoelectronics industry in the Southern Taiwan Science Park (STSP) between 2007 and 2011 by using multiple criteria decision making methods (data envelopment analysis, Malmquist productivity index and Bootstrap). The data analysis showed that during the study period, meaning that the operational efficiency gap among manufacturers in STSP is widening. Among these manufacturers, eight manufacturers exhibited constant returns to scale, which was more than a half of the overall decision making unit (DMU), indicating that the operational scale of these manufacturers was nearing the optimal scale. Based on Malmquist productivity index (MPI) analysis, the factors that affect the operational efficiencies of optoelectronics manufacturers’ were as follow: operational cost, the number of employees, and the amount of fixed assets. The development should be focused on increasing technological efficiency and technological change in the future. Finally, based on Bootstrap, the results showed that the focus should be on the production technology while improving productive efficiency to ensure sustainable development of the entire domestic optoelectronics industry in the future.

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.

Application of Malmquist Productivity Index in Integrated Units of Power Plant

2017 ◽  
pp. 83-137
Author(s):  
Elahe Shariatmadari Serkani ◽  
Seyed Esmaeil Najafi ◽  
Arash Nejadi
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Precise Data ◽  
Time Period ◽  
Decision Making Unit ◽  
Time Periods ◽  
Value Of Money

The Malmquist Productivity Index (MPI) evaluates the productivity change of a Decision Making Unit (DMU) between two time periods. DEA considers performance analysis at a given point of time. Classic Malmquist Productivity Index shows regress and progress of a DMU in different periods with efficiency and technology variations without considering the present value of money. In this chapter Application of Malmquist productivity index in integrated units of power plant is discussed. Four units of one of the power plants are assessed & the data of its five successive years are supplied. Also application of Malmquist productivity index (precise data) in Safa Rolling and pipe plants for the time period of 2007 – 2012 is studied.

scholarly journals Application of Multi-Criteria Decision-Making Model and GM (1,1) Theory for Evaluating Efficiency of FDI on Economic Growth: A Case Study in Developing Countries

2019 ◽  
Vol 11 (8) ◽  
pp. 2389 ◽  
Author(s):  
Wang ◽  
Le
Keyword(s):  
Economic Growth ◽  
Decision Making ◽  
Developing Countries ◽  
Economic Development ◽  
Exchange Rate ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Sustainable Economic Development ◽  
Sustainable Economic Growth

Foreign direct investment (FDI) and corporate social responsibility (CSR) spending are one of the major factors in improving sustainable economic development of a country. Therefore, this study focuses on the multi criteria application of FDI and sustainability factors (CSR spending) in various developing countries to explore its impact and decision making for sustainable economic growth. The study uses a case study methodology whereby FDI, exchange rate, and CSR expenditure data from 20 countries were used to assess the efficiency in sustainable economic growth. Data were collected from the World Bank for 20 Asian and African developing countries during 2012–2017 and analyzed using GM (1,1), mean absolute percentage error (MAPE), Malmquist productivity index (MPI)-data envelopment analysis (DEA), and the slacks-based measure of efficiency (SBM) model. Correlation analysis is used to find the relationship for FDI, CSR, exchange rate, gross domestic product (GDP), and GDP per capita (GDPPC). The results of the Malmquist productivity index and the frontier effect clearly highlight that a few countries have witnessed a great improvement in terms of productivity and technological progression. Therefore, the decision makers must adopt the model of those countries with respect to sustainable development of the nation. This study helps developing nations as well as researchers to benchmark efficient countries and follow their strategies to develop a new one for utilizing FDI and CSR spending in sustainable economic development. The study also helps policy makers in multi criterion application of FDI and CSR for decision making in economic development.

scholarly journals MEASURING EFFICIENCY CHANGE IN TIME APPLYING MALMQUIST PRODUCTIVITY INDEX: A CASE OF DISTRIBUTION CENTRES IN SERBIA

2021 ◽  
Vol 19 (3) ◽  
pp. 499
Author(s):  
Milan Andrejić ◽  
Milorad Kilibarda ◽  
Vukašin Pajić
Keyword(s):  
Decision Making ◽  
Environmental Changes ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Decision Making Process ◽  
Distribution Centers ◽  
Efficiency Change ◽  
Selection Of Variables ◽  
Measuring Efficiency ◽  
The Impact

In the last decade, more and more attention has been paid to the efficiency of logistics systems not only in the literature but also in practice. The reason is the huge savings that can be achieved. In a very dynamic market with environmental changes distribution centers have to realize their activities and processes in an efficient way. Distribution centers connect producers with other participants in the supply chain, including end-users. The main objective of this paper is to develop a DEA model for measuring distribution centers’ efficiency change in time. The paper investigates the impact of input and output variables selection on the resulting efficiency in the context of measuring the change in efficiency over time. The selection of variables on the one hand is a basic step in applying the DEA method. On the other hand, the number of basic and derived indicators that are monitored in real systems is increasing, while the percentage of those used in the decision-making process is decreasing (less than 20%). The developed model was tested on the example of a retail chain operating in Serbia. The main factors changing the efficiency have been identified, as well as the corresponding corrective actions. For measuring efficiency change in time Malmquist productivity index is used. The developed approach could help managers in the decision-making process and also represents a good basis for further research.

scholarly journals Global malmquist index for measuring the economic productivity changes

2020 ◽  
Vol 53 (7-8) ◽  
pp. 1278-1285
Author(s):  
Esmaeil Mombini ◽  
Mohsen Rostamy-Malkhalifeh ◽  
Mansor Saraj ◽  
Mohsen Zahraei ◽  
Reza Tayebi Khorami
Keyword(s):  
Decision Making ◽  
Malmquist Index ◽  
Productivity Index ◽  
Programming Models ◽  
Data Envelopment ◽  
Decision Unit ◽  
Economic Productivity ◽  
Use Of Resources ◽  
Decision Making Unit ◽  
Decision Making Units

Data envelopment analysis is a nonparametric method for measuring of the performance of decision-making units—which do not need to have or compute a firm’s production function, which is often difficult to calculate. For any manager, the progress or setback of the thing they manage is important because it makes planning and adoption of future policies for the organization or decision-making unit more rational and scientific. Different methods have been used to calculate the improvements and regressions using Malmquist Index. In this article, we evaluate the units under review in terms of economic efficiency, and the units in terms of spending, production, revenue and profit over several periods, and the rate of improvement or regression of each of these units. Considering the minimal use of resources and consuming less money, generating more revenue, and maximizing profits, the improvement or retreat of the recipient’s decision unit in terms of cost, revenue, and profit was examined by presenting a method based on solving linear programming models using the productivity index is Malmquist and Malmquist Global. Finally, by designing and solving a numerical example, we emphasize and test the applicability of the material presented in this article.

scholarly journals Discovering the Arrow of Time in Machine Learning

2021 ◽  
Author(s):  
J. Kasmire ◽  
Anran Zhao
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Anomaly Detection ◽  
Explicit Instruction ◽  
Time Dependent ◽  
Dependent Data ◽  
Temporal Context ◽  
Arrow Of Time ◽  
Twitter Data ◽  
Classification Tasks

Machine learning (ML) is increasingly useful as data grows in volume and accessibility as it can perform tasks (e.g. categorisation, decision making, anomaly detection, etc.) through experience and without explicit instruction, even when the data are too vast, complex, highly variable, full of errors to be analysed in other ways , . Thus, ML is great for natural language, images, or other complex and messy data available in large and growing volumes. Selecting a ML algorithm depends on many factors as algorithms vary in supervision needed, tolerable error levels, and ability to account for order or temporal context, among many other things. Importantly, ML methods for explicitly ordered or time-dependent data struggle with errors or data asymmetry. Most data are at least implicitly ordered, potentially allowing a hidden `arrow of time’ to affect non-temporal ML performance. This research explores the interaction of ML and implicit order by training two ML algorithms on Twitter data before performing automatic classification tasks under conditions that balance volume and complexity of data. Results show that performance was affected, suggesting that researchers should carefully consider time when selecting appropriate ML algorithms, even when time is only implicitly included.

scholarly journals Revenue Malmquist productivity index and application in bank branch

2006 ◽  
pp. 1233-1247 ◽  
Author(s):  
M. Navanbakhsh ◽  
G. R. Jahanshahloo ◽  
F. Hosseinzadeh Lotfi ◽  
Z. Taeb
Keyword(s):  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Bank Branch

scholarly journals A Comparative Evaluation of Public Road Transportation Systems in India Using Multicriteria Decision-Making Techniques

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Anand Kumar ◽  
Gurmeet Singh ◽  
Omkarprasad S. Vaidya
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Transportation Systems ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Solution Technique ◽  
Road Transportation ◽  
Multicriteria Decision ◽  
Functional Head ◽  
Public Road

In this paper, we evaluate the performance of major public road transport organizations in India. The contribution of the paper lies in integrating four multicriteria decision-making (MCDM) techniques to assess the relative performance of public road transportation systems on twenty-three criteria across two consecutive years. The paper classifies the criteria into functional heads and establishes the relative importance of heads using the analytical hierarchical process (AHP). The efficiency scores of each organization referred to as a decision-making unit (DMU) were computed for the classified heads using the Data Envelopment Analysis (DEA) approach. The multicriteria optimization and compromise solution technique “VlseKriterijumska Optimizacija I Kompromisno Resenje” (VIKOR) was used to assign a final rank to each of the DMUs using computed efficiency scores and established weights. Finally, we analyzed the performance of the DMUs across the two consecutive years using the Malmquist Productivity Index (MPI). Our key findings are as follows: First, the performance of all DMUs has improved in the second year with respect to the first year; second, significant improvement is observed in the “expenses” functional head which carries a substantial weight among the functional heads; third, barring few DMUs, the performance of the majority of DMUs has worsened in the “accident” functional head; fourth, while few DMUs have been consistently very good performers in both the years, there are also few DMUs which have consistently performed poorly in both the years. The inferences drawn from the study can be leveraged for future policy formulations by the state government and local municipal corporations and for sharing best practices among the DMUs.

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.

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