scholarly journals A DEA Analysis Using Quality And Advertising As Determinants Of Strategic Group Membership In The Automobile Industry

2010 ◽  
Vol 14 (4) ◽  
Author(s):  
Eric C. Jackson
Keyword(s):  
Data Envelopment Analysis ◽  
Automobile Industry ◽  
Rank Test ◽  
Data Envelopment ◽  
Market Segment ◽  
Strategic Group ◽  
Time Period ◽  
The Family ◽  
Dea Analysis ◽  
The Individual

This manuscript considers sales within an automotive strategic group.  Sales within the “Family Car” segment are examined. The efficient uses of inputs relative to the sales generated as determined by Data Envelopment Analysis are compared. The relative efficiencies are used to identify strategic groups within the market segment and to suggest how resources may be utilized more efficiently.  Data Envelopment Analysis, (DEA), is used to compare three inputs and one output for several automobile manufacturers competing for sales in the same market segment.  The three inputs used are two aggregate measures of quality and one measure of the dollar volume spent on advertising by the firms. The output measure used is the volume of sales each year over a five-year period. A Kruskal and Wallis rank test is performed to confirm that the data is comparable over the five year time period. Specifically, comparisons are made to establish that no significant changes in quality or advertising expenditures have occurred during the study period. Once it has been established that no significant changes occurred during the study period for the input and output measures for the individual automotive models. Next, firms are compared using the DEA efficiencies and are grouped according to these efficiencies.  The efficiency measurements indicate that there are two distinct clusters of companies formed within the market segment.  The most efficient cluster is composed of five firms. The least efficient cluster is composed of five firms. An intermediate cluster of two firms exists that is neither extremely efficient nor extremely inefficient in it’s utilization of resources but may be more closely aligned with the efficient firms than with the inefficient group. This stratification into groups within the market segment by efficiency suggests that practitioners might be able to adjust their utilization of resources to compete in a different strategic group. It also suggests that success within a strategic group may be impacted by how firms utilize strategic levers within their control.

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 Efficiency Institution Baitul Maal Tamwill in The Westdistrict Bandung

2020 ◽  
Vol 1 (1) ◽  
pp. 18-24
Author(s):  
Annisa Nur Hakim ◽  
A Jajang W Mahri ◽  
Aas Nurasyiah
Keyword(s):  
Data Envelopment Analysis ◽  
Research Method ◽  
Secondary Data ◽  
Data Envelopment ◽  
Analysis Technique ◽  
Dea Analysis ◽  
Input Variables ◽  
Operational Activities ◽  
A Company ◽  
Descriptive Method

Abstract.     Baitul Maal Wat Tamwil has experienced development in recent years. However, based on BMT performance data in West Bandung regency is less optimal. It is known that there are one efficient BMTs in West Bandung Regency and three BMTs that are inefficient. The cause of BMT's less optimal performance is inefficiency in operational activities. This study aims to determine the level of efficiency of BMT in West Bandung 2011-2017 period and find out the causes of inefficiency. This study uses secondary data from four BMTs in West Bandung District which are sampled. The research method used is descriptive method with Data Envelopment Analysis (DEA) analysis technique which is to measure the level of efficiency of a company. Input variables used are operating expenses, total assets, and TPF. Furthermore, the output variables used are SHU, income, and financing. Based on the results of research conducted, the conditions of the BMT in West Bandung Regency have not been perfectly efficient. There are three BMTs that have experienced inefficiencies including BMT Dana Ukhuwah, BMT Mustama, and BMT Rabbani. Keywords.          Efficiency, Baitul Maal Wat Tamwil, Data Envelopment Analysis

scholarly journals Effects of aspiration-induced adaptation and migration on the evolution of cooperation

2014 ◽  
Vol 25 (07) ◽  
pp. 1450025 ◽  
Author(s):  
Yu Peng ◽  
Xu-Wen Wang ◽  
Qian Lu ◽  
Qing-Ke Zeng ◽  
Bing-Hong Wang
Keyword(s):  
Data Envelopment Analysis ◽  
Prospect Theory ◽  
Evolution Of Cooperation ◽  
Square Lattice ◽  
Data Envelopment ◽  
Aspiration Level ◽  
Aspiration Levels ◽  
Emergence Of Cooperation ◽  
And Migration ◽  
The Individual

In the light of the prospect theory (PT), we study the prisoner's dilemma game (PDG) on square lattice by integrating the deterministic and Data envelopment analysis (DEA) efficient rule into adaptive rules: the individual will change evolutionary rule and migrate if its payoff is lower than their aspiration levels. Whether the individual choose to change the evolutionary rule and migrate is determined by the relation between its payoff and aspiration level. The results show that the cooperation frequency can hold unchange with the increasing of temptation to defect. The individual chooses to adopt DEA efficient rule and to migrate that can induce the emergence of cooperation as the payoff is lower than its aspiration.

scholarly journals TOTAL FACTOR OF PRODUCTIVITY AND ITS COMPONENTS: EVIDENCE FROM CEMENT - AND ENERGY SECTORS OF PAKISTAN

2018 ◽  
Vol 9 (1) ◽  
pp. 55 ◽  
Author(s):  
Razzi Abbas Jafri ◽  
Shahbaz Khan ◽  
Muhammad Haroon Shah ◽  
Nida Baig
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Change ◽  
Annual Reports ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Financial Firms ◽  
Tfp Growth ◽  
Time Period ◽  
Dea Method

This study employs “Data Envelopment Analysis (DEA)” method to calculate the “Total Factor Productivity (TFP)” growth and its components of 19 non-financial firms from Cement and Energy sectors of Pakistan listed on ISE-100 Index during the time period 20052011. The research focuses on to identify the factors like, technical change and technical efficiency change tends to influence the TFP of cement -and energy sectors of Pakistan. We use hand collected data from the annual reports of these non-financial firms included in our sample. Results show that cement sector has an overall positive TFP growth of 9.7%, and energy sector has an overall TFP growth of 1.5% during the study period. The study may assist us to recognize the extent to which these components can affect the TFP of a sector, and will further help us to explore new ways to boost up the productivity of these sectors which in turn may be beneficial to move country towards a sustainable path.

scholarly journals Analisis Efisiensi Asuransi Umum Syariah di Indonesia Tahun 2013-2015: Aplikasi Metode Data Envelopment Analysis (DEA)

2017 ◽  
Vol 4 (9) ◽  
pp. 757
Author(s):  
Yulia Wahyu Ningsih ◽  
Noven Suprayogi
Keyword(s):  
Data Envelopment Analysis ◽  
Insurance Companies ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Insurance Company ◽  
Average Value ◽  
General Insurance ◽  
Decision Making Unit ◽  
Dea Analysis ◽  
Input Variables

This study aims to analyze the efficiency of sharia general insurance companies in Indonesia. The input variables used are total assets, expenses, and payment of claims, while the output variable is the income and tabarru’ funds. The method were used to measure the level of efficiency is the Data Envelopment Analysis (DEA) with the assumption of Variable Return to Scale (VRS) with input and output orientation. The samples are 12 sharia general insurance companies during 2013-2015. The results of the study indicate that the average result of DEA analysis for the entire DMU (Decision Making Unit) has not been efficient. The average value of economic efficiency (CRS) by 0.978, technically efficiency (VRS) for 0.925, and scale efficiency for 0.945. Source of inefficiency sharia insurance company is the scale of operations and management of input to output is not optimal.

Data envelopment analysis methods in sustainable agricultural development research

2021 ◽  
pp. 179-205
Author(s):  
Katarzyna Smędzik-Ambroży ◽  
Agnieszka Sapa
Keyword(s):  
Sustainable Development ◽  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Economies Of Scale ◽  
Scale Effects ◽  
Three Dimensions ◽  
Data Envelopment ◽  
Farm Accountancy Data Network ◽  
Business Entities ◽  
The Individual

Sustainable development of business entities can be analysed in terms of three dimensions, i.e., economic, social and environmental ones. The economic dimension of sustainable development can be assessed, inter alia, by entities’ technical efficiency defined as the relation of outputs to inputs. One of the methods that is used to assess the technical efficiency of business entities compared to other entities is the Data Envelopment Analysis (DEA) method. The aim of the chapter is to determine the relative technical efficiency of representative agricultural farms from the individual European Union countries in 2018. Moreover, the scale efficiency indexes and the area of scale effects (increasing or decreasing) of the analysed farms were also determined. In the study the data from the Farm Accountancy Data Network (FADN) for 2018 were applied. In order to achieve the assumed research goals, the input-oriented DEA model was used, and the technical efficiency indexes of farms were estimated with the assumption of constant return to scale (CRS) and variable return to scale (VRS). This allowed, among others, for indicating the countries with farms achieving the highest technical efficiency (Belgium, Spain, Italy, Malta and Netherlands assuming CRS, and Belgium, Spain, Italy, Malta and Netherlands, Greece, Ireland, Romania and Slovenia assuming VRS), the lowest technical efficiency (the Czech Republic and Slovakia) within surveyed group of farms. All relatively inefficient farms (except Slovakia) functioned in the area of increasing economies of scale.

Measuring operational efficiency of isolation hospitals during COVID-19 pandemic using data envelopment analysis: a case of Egypt

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahmoud Abdelrahman Kamel ◽  
Mohamed El-Sayed Mousa
Keyword(s):  
Data Envelopment Analysis ◽  
Design Methodology ◽  
Operational Efficiency ◽  
Data Envelopment ◽  
Allocation Of Resources ◽  
Tobit Regression ◽  
Health Crisis ◽  
Content Type ◽  
Dea Analysis ◽  
Using Data

PurposeThis study used Data Envelopment Analysis (DEA) to measure and evaluate the operational efficiency of 26 isolation hospitals in Egypt during the COVID-19 pandemic, as well as identifying the most important inputs affecting their efficiency.Design/methodology/approachTo measure the operational efficiency of isolation hospitals, this paper combined three interrelated methodologies including DEA, sensitivity analysis and Tobit regression, as well as three inputs (number of physicians, number of nurses and number of beds) and three outputs (number of infections, number of recoveries and number of deaths). Available data were analyzed through R v.4.0.1 software to achieve the study purpose.FindingsBased on DEA analysis, out of 26 isolation hospitals, only 4 were found efficient according to CCR model and 12 out of 26 hospitals achieved efficiency under the BCC model, Tobit regression results confirmed that the number of nurses and the number of beds are common factors impacted the operational efficiency of isolation hospitals, while the number of physicians had no significant effect on efficiency.Research limitations/implicationsThe limits of this study related to measuring the operational efficiency of isolation hospitals in Egypt considering the available data for the period from February to August 2020. DEA analysis can also be an important benchmarking tool for measuring the operational efficiency of isolation hospitals, for identifying their ability to utilize and allocate their resources in an optimal manner (Demand vs Capacity Dilemma), which in turn, encountering this pandemic and protect citizens' health.Originality/valueDespite the intensity of studies that dealt with measuring hospital efficiency, this study to the best of our knowledge is one of the first attempts to measure the efficiency of hospitals in Egypt in times of health' crisis, especially, during the COVID-19 pandemic, to identify the best allocation of resources to achieve the highest level of efficiency during this pandemic.

Data Envelopment Analysis and Cross-Efficiency Evaluation in the Management of Sports Teams: The Assessment of Game Performance of Players in the Spanish Handball League

2013 ◽  
Vol 27 (3) ◽  
pp. 217-229 ◽  
Author(s):  
Óscar Gutiérrez ◽  
José L. Ruiz
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Sports Teams ◽  
Premier League ◽  
Support Tools ◽  
Sports Team ◽  
Overall Performance ◽  
The Individual ◽  
Game Performance

Data Envelopment Analysis (DEA) and cross-efficiency evaluation are shown as support tools for sports team management in the context of a study of assessment of the individual game performance of handball players of the Spanish premier league. A sample of 66 players that play as backs in their teams is evaluated from the perspective of their offensive game. DEA yields a measure of the overall performance of the game of the players, and allows to identifying relative strengths and weaknesses by means of a benchmarking analysis. The cross-efficiency evaluation has provided a peer-appraisal of the players with the different patterns of game that the 10 players rated as efficient have used in the DEA assessments, and has made it possible to derive a full ranking of players.

Managerial ability and real earnings management in family firms

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Adhitya Agri Putra ◽  
Nanda Fito Mela ◽  
Ferdy Putra
Keyword(s):  
Data Envelopment Analysis ◽  
Earnings Management ◽  
Family Firms ◽  
Random Effect ◽  
Real Earnings Management ◽  
Data Envelopment ◽  
Managerial Ability ◽  
Information Distortion ◽  
Content Type ◽  
The Family

Purpose This study aims to examine the effect of managerial ability on real earnings management (hereafter REM) in family firms. Design/methodology/approach The sample consists of 864 firms-years listed in the Indonesian Stock Exchange. REM is measured by abnormal activities. Managerial ability is measured by data envelopment analysis. Data analysis uses random-effect regression analysis. Findings Family firms reduce the possibility of higher ability managers to engage in REM. Compare to non-family firms, higher ability managers in family firms are more likely to engage in REM to improve future earnings. Research limitations/implications This research only uses efficiency score data envelopment analysis to measure managerial ability while the managerial ability is, by nature, multi-dimensional and unobservable. This research also does not find the role of professional Chief Executive Officer (hereafter CEO) in the family firms in REM behavior because does not consider the professional CEO motivation (e.g. compensation structure). Practical implications This research is expected to help family firms formulate managers' selection based on managerial ability. This research also is expected to help investors and creditors to put their funds in the family firms with higher ability managers that reduce earnings information distortion. Originality/value To the best of the author’s knowledge, this research is the first research that examines the managerial ability on REM in Indonesian family firms. This research also contributes to fil the findings gap in managerial ability and REM.

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