Exploring the Price Efficiency within Automotive Markets - An Application of Data Envelopment Analysis

2009 ◽  
Vol 51 (3) ◽  
pp. 1-18
Author(s):  
Pingjun Jiang
Keyword(s):  
Data Envelopment Analysis ◽  
Lower Price ◽  
Price Reduction ◽  
Quality Information ◽  
Data Envelopment ◽  
Data Set ◽  
Price Efficiency ◽  
Car Model ◽  
Car Market ◽  
Parametric Data

Using a non-parametric data envelopment analysis (DEA) approach, this paper compares the price of each car model in a segment of the personal car market with the best possible price in view of the technology available given its particular combination of characteristics. In this approach, a car model is defined as price efficient if it offers customers the highest value per dollar spent for that set of characteristics. Likewise, a car model is inefficient if there is some other car model with a lower price having equivalent or higher quality, whereby a measure of the price efficiency is determined by the price reduction needed to make a car model efficient. The data set covers 141 different year 2002 car models. The vehicles that are listed by Edmunds.com as consumers’ most wanted are compared with those at the top of our efficiency list. It is found that the majority of cars at the top of the list are also listed as most wanted by Edmunds.com. Evidently, consumers who usually make decisions based on price and quality information will naturally employ a heuristic such as ‘buy car models at the top of price efficiency list’ if this list is made available to them.

Forecast of the efficiency confidence interval of decision-making units in data envelopment analysis

2020 ◽  
Vol 33 (02) ◽  
pp. 431-445
Author(s):  
Azarnoosh Kafi ◽  
Behrouz Daneshian ◽  
Mohsen Rostamy-Malkhalifeh ◽  
Mohsen Rostamy-Malkhalifeh
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Confidence Interval ◽  
Data Envelopment ◽  
Data Set ◽  
Interval Model ◽  
Time Period ◽  
Proposed Model ◽  
The Future ◽  
Decision Making Units

Data Envelopment Analysis (DEA) is a well-known method for calculating the efficiency of Decision-Making Units (DMUs) based on their inputs and outputs. When the data is known and in the form of an interval in a given time period, this method can calculate the efficiency interval. Unfortunately, DEA is not capable of forecasting and estimating the efficiency confidence interval of the units in the future. This article, proposes a efficiency forecasting algorithm along with 95% confidence interval to generate interval data set for the next time period. What’s more, the manager’s opinion inserts and plays its role in the proposed forecasting model. Equipped with forecasted data set and with respect to data set from previous periods, the efficiency for the future period can be forecasted. This is done by proposing a proposed model and solving it by the confidence interval method. The proposed method is then implemented on the data of an automotive industry and, it is compared with the Monte Carlo simulation methods and the interval model. Using the results, it is shown that the proposed method works better to forecast the efficiency confidence interval. Finally, the efficiency and confidence interval of 95% is calculated for the upcoming period using the proposed model.

scholarly journals Ten years of research on parametric data envelopment analysis

2013 ◽  
Vol 33 (1) ◽  
pp. 89-104 ◽  
Author(s):  
Armando Zeferino Milioni ◽  
Luciene Bianca Alves
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Parametric Data

scholarly journals The Efficiency of Non-Bank Financial Intermediaries: Empirical Evidence from Malaysia

2008 ◽  
Author(s):  
Fadzlan Sufian
Keyword(s):  
Risk Factors ◽  
Data Envelopment Analysis ◽  
Empirical Evidence ◽  
Financial Institutions ◽  
Economies Of Scale ◽  
Financial Intermediaries ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Parametric Data ◽  
Dea Method

This paper investigates the performance of Malaysian non-bank financial institutions during the period of 2000-2004. Several efficiency estimates of individual NBFIs are evaluated using the non-parametric Data Envelopment Analysis (DEA) method. The findings suggest that during the period of study, scale inefficiency outweighs pure technical inefficiency in the Malaysian NBFI sector. We find that the merchant banks have exhibited a higher, technical efficiency compared to their peers. The empirical findings suggest that scale efficiency tends to be more sensitive to the exclusion of risk factors, implying that potential economies of scale may be overestimated when risk factors are excluded.  

An application of data envelopment analysis for Korean banks with negative data

2017 ◽  
Vol 24 (4) ◽  
pp. 1052-1064 ◽  
Author(s):  
Yong Joo Lee ◽  
Seong-Jong Joo ◽  
Hong Gyun Park
Keyword(s):  
Data Envelopment Analysis ◽  
Data Sets ◽  
Data Envelopment ◽  
Negative Data ◽  
Ownership Type ◽  
Data Set ◽  
Translation Invariant ◽  
Content Type ◽  
Dea Models ◽  
Regional Banks

Purpose The purpose of this paper is to measure the comparative efficiency of 18 Korean commercial banks under the presence of negative observations and examine performance differences among them by grouping them according to their market conditions. Design/methodology/approach The authors employ two data envelopment analysis (DEA) models such as a Banker, Charnes, and Cooper (BCC) model and a modified slacks-based measure of efficiency (MSBM) model, which can handle negative data. The BCC model is proven to be translation invariant for inputs or outputs depending on output or input orientation. Meanwhile, the MSBM model is unit invariant in addition to translation invariant. The authors compare results from both models and choose one for interpreting results. Findings Most Korean banks recovered from the worst performance in 2011 and showed similar performance in recent years. Among three groups such as national banks, regional banks, and special banks, the most special banks demonstrated superb performance across models and years. Especially, the performance difference between the special banks and the regional banks was statistically significant. The authors concluded that the high performance of the special banks was due to their nationwide market access and ownership type. Practical implications This study demonstrates how to analyze and measure the efficiency of entities when variables contain negative observations using a data set for Korean banks. The authors have tried two major DEA models that are able to handle negative data and proposed a practical direction for future studies. Originality/value Although there are research papers for measuring the performance of banks in Korea, all of the papers in the topic have studied efficiency or productivity using positive data sets. However, variables such as net incomes and growth rates frequently include negative observations in bank data sets. This is the first paper to investigate the efficiency of bank operations in the presence of negative data in Korea.

scholarly journals Implementation of Data Envelopment analysis (DEA) in measuring the efficiency zakat fund management

2019 ◽  
Vol 1 (1) ◽  
pp. 50-57
Author(s):  
Tsalis Syaifuddin
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Fund Management ◽  
Improve Performance ◽  
Output Variable ◽  
Travel Costs ◽  
Parametric Data ◽  
Dea Method ◽  
Input Variables ◽  
Output Variance

This study aims to determine the efficiency level of management of zakat funds at the National Zakat Amil Agency (BAZNAS). The author uses the quantitative non-parametric Data Envelopment Analysis (DEA) method. Total assets, promotion, and documentation costs, and official travel costs as input variables. Whereas the output variance consists of receiving zakat funds and distributing zakat funds. The results showed that BAZNAS experienced efficiency in 2012-2014 and 2017 with a score of 100%. Inefficiencies occurred in 2015 at 79.16% and in 2016 amounted to 98.72%. In 2015-2016, all input variables experienced inefficiency, while the output variable was the only inefficient distribution of zakat funds. In overcoming, inefficiencies can be adjusted between the target and actual quantities specified in the DEA calculation. The author recommends that BAZNAS pay attention to the causes of inefficiency so that it can improve performance better.

scholarly journals Modifying the convexity condition in Data Envelopment Analysis (DEA)

2020 ◽  
Vol 33 (02) ◽  
pp. 454-467
Author(s):  
Roghyeh Malekii Vishkaeii ◽  
Behrouz Daneshian ◽  
Farhad Hosseinzadeh Lotfi
Keyword(s):  
Data Envelopment Analysis ◽  
Real Data ◽  
Data Envelopment ◽  
Convexity Condition ◽  
Discrimination Power ◽  
Data Set ◽  
Step Procedure ◽  
Proposed Model ◽  
Dea Models ◽  
Production Possibility Set

Conventional Data Envelopment Analysis (DEA) models are based on a production possibility set (PPS) that satisfies various postulates. Extension or modification of these axioms leads to different DEA models. In this paper, our focus concentrates on the convexity axiom, leaving the other axioms unmodified. Modifying or extending the convexity condition can lead to a different PPS. This adaptation is followed by a two-step procedure to evaluate the efficiency of a unit based on the resulting PPS. The proposed frontier is located between two standard, well-known DEA frontiers. The model presented can differentiate between units more finely than the standard variable return to scale (VRS) model. In order to illustrate the strengths of the proposed model, a real data set describing Iranian banks was employed. The results show that this alternative model outperforms the standard VRS model and increases the discrimination power of (VRS) models.

scholarly journals Analysis of the Efficiency of Spanish Soccer League Players (2009/10) Using the Metafrontier Approach

2020 ◽  
Vol 30 (2) ◽  
pp. 565
Author(s):  
Rafael Caballero Fernández ◽  
Trinidad Gómez Núñez ◽  
Ramón Sala Garrido
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Data Set

This paper analyses the efficiency of players in the Spanish Soccer League for the 2009/2010 season using a metafrontier version of data envelopment analysis (DEA) methodology. It is possible to apply a metafrontier approach if separate frontiers can be identified for different groups in the data set. In our case, we divide the sample of players into three groups, according to the playing position within a team, because different positions define different behaviours (technologies). These behaviours are compared against each other and globally.

scholarly journals EFFICIENT COMPARISON OF THE TOP 10 LARGEST COMMERCIAL BANKS IN INDONESIA: DEA (DATA ENVELOPMENT ANALYSIS)

2021 ◽  
Vol 11 (3) ◽  
pp. 427
Author(s):  
Ari Christianti
Keyword(s):  
Data Envelopment Analysis ◽  
Commercial Banks ◽  
Banking Industry ◽  
Maximum Efficiency ◽  
Data Envelopment ◽  
Labor Costs ◽  
Banking Efficiency ◽  
Parametric Data ◽  
Fixed Assets ◽  
Using Data

Banking efficiency is very important in supporting the success of macro policies specifically, maintaining the sustainability of development that affects economic growth and social welfare. This study discusses the efficiency of commercial banks for the 2015-2019 period using data from the 10 largest commercial banks in Indonesia. The methodology used is non-parametric, Data Envelopment Analysis, to analyze technical efficiency. The results showed that 7 banks had a maximum efficiency level consistently during the study period and there were still 3 banks that did not reach the maximum efficiency but during certain periods or periods. Based on the results of the DEA, inefficient banks in a certain period can achieve maximum efficiency by reducing inputs such as labor costs, net fixed assets, and the number of deposits. This might be attributed that the competition in the banking industry and because not all inputs could be controlled by management, some large banks cannot maintain their level of efficiency consistently.

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