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Recent Developments in Data Envelopment Analysis and its Applications
Abstract
Proceedings of the 12th International Conference on Data Envelopment Analysis, DEA2014, April 2014, Kuala Lumpur, Malaysia
Citation: Emrouznejad, A., R. Banker R., S. M. Doraisamy and B. Arabi (2014), Recent Developments in Data Envelopment Analysis and its Applications: Proceedings of the 12th International Conference of DEA, April 2014, Kuala Lumpur, Malaysia, ISBN: 978 1 85449 487 0
... In order to apply KAM, the value of epsilon is introduced as 10 -8 [10]. Indeed, data are quite large and the small values of epsilon makes a very small and negligible thickness in the frontier. ...
... Column 4 ofTable 3 illustrates the best technically efficient scores of DMUs with 10 -8 -degree of freedom (DF). There are only 3 efficient DMUs with 10 -8 -DF, such as A02, A07 and A09when δ = 10 -9 [3, 10]. A02 is the best customer service centres of telecommunication company followed by A09 and A07.Columns 4-5 illustrates the rank and reference sets for each DMU. ...
This paper investigates the relative efficiency of customer service centres for a telecommunication company in Malaysia using Data Envelopment Analysis (DEA). Thirteen customer service centres located across Klang Valley area are selected as Decision Making Units (DMUs) with four input factors such as cost of manpower, materials, premise rental and goods sold and three output factors such as revenue from service commission, retails sales and amount of bill collection. A recent robust DEA model, Kourosh and Arash Model (KAM) is applied to discriminate between DMUs appropriately. There are 9 technically efficient DMUs which 3 of them are efficient with 10^(-8)-Degree of Freedom (DF) and others were inefficient with 10^(-8)-DF. Simulations are performed with Microsoft Excel Solver 2013.
... DEA is a widely used tool by academics and practitioners to assess the performance of firms [19][20][21][22][23][24][25]. DEA is a comparison approach based on linear mathematical programming, in which units use multiple inputs to produce multiple outputs, resulting in a single measure of overall performance [26]. ...
Nuclear technology has started in Malaysia since the establishment of the Malaysian Nuclear Agency (Nuclear Malaysia) in 1972. The agency was established to promote the peaceful application of nuclear science and technology for national development. Nuklear Malaysia also plays important role in providing research, development, commercialisation, and innovation (RDCI) in line with national interests, including industry, medicine and healthcare, food and agriculture, natural resources, energy, and nuclear safety and security. This paper aims to examine the performance and the growth of nuclear technology R&D in Nuklear Malaysia from 2011-2021 using the data envelopment analysis (DEA) and Malmquist index (MI) analysis. The study uses two inputs, namely RDC & Development budget (RM Million) and Operating budget (RM Million), and three outputs, namely revenue (RM Million), no. of R&D products and no. of publications. The result shows that the performance of nuclear technology R&D in Nuklear Malaysia is 96.70 per cent from 2011-2021. The study shows that nuclear R&D growth decreased by 8.3 per cent for the entire study period. The technological changes decreased at 8.3 per cent, while the efficiency changes remain. The study also found that nuclear technology R&D growth index in Nuklear Malaysia is mainly affected by technological changes due to policy changes compare to the resources provided since efficiency changes remain. The findings of the study help management and officials of Nuklear Malaysia to realign the institution's direction to ensure the nuclear technology RDCI contribute to the socio-economic development of the country.
... This study employs DEA and MI analysis to evaluate the relative effectiveness of nuclear technology R&D activities and the development of nuclear science and technology in Nuklear Malaysia from 2011 to 2021. DEA is a common instrument used by academics and professionals to evaluate the performance of businesses [13][14][15][16][17][18][19]. DEA is a single-measure comparison approach of total performance produced by units using many inputs to produce numerous outputs which are based on linear mathematical programming [20]. ...
Nuclear science and technology for peaceful uses successfully progressed in various areas such as industry, medicine and healthcare, food and agriculture, natural resources, energy, and nuclear safety and security, through research and development and innovation (RDI). Realizing the importance of RDI in nuclear technology as the driving force in addressing societal challenges, most countries, including Malaysia, are developing new policies to promote R&D and innovation in nuclear technology. This paper assesses the impact of the policy on the performance of R&D and innovation in nuclear technology in Malaysia from 2011-2021 using the data envelopment analysis (DEA) and Malmquist index (MI) analysis. The study used two inputs, namely RDC & Development budget (RM Million) and Operating budget (RM Million), and three outputs, namely revenue (RM Million), no. of R&D products and no. of publications. The result shows that the performance of R&D and innovation in nuclear technology is 96.70 per cent from 2011-2021. The study shows that the growth of R&D and innovation in nuclear technology decreased by 8.3 per cent for the entire study period. The technological changes decreased at 8.3 per cent, while the efficiency changes remain. The study also found that nuclear technology growth is mainly affected by technological changes due to policy changes compare to the resources provided since efficiency changes remain.
... Data envelopment analysis (DEA) is a method that has been gaining popularity from scholars for performance measurement activities as an alternative to other econometric approaches, for example, ratio analysis and regression. [1][2][3][4][5][6] DEA has been utilized to determine the performance efficiency of decision-making unit (DMU) peers with several inputs and outputs. 7 In general, each DMU performs a similar function of a system model by transforming multiple input indicators to multiple output indicators. ...
This article provides a systematic analysis of renewable energy performance using data envelopment analysis (DEA) to understand the diverging paths of renewable energy development for countries. In this review, 72 quantitative studies were identified using a multi-stage selection process. The review found that the DEA method can be used as an appropriate tool for performance evaluation of renewable energy studies' research. The DEA method can be applied critically for decision making, especially for policymakers in the renewable energy sector. The review also demonstrated that the DEA method, either traditional or advanced, can be comprehensively used to evaluate the performance of renewable energy studies depending on the objective of the research, as well as the complexity and accuracy of data issues. This review revealed that the selection of input and output factors used in DEA is sufficient enough to evaluate renewable energy performance. This review contributed to the current energy literature and filled in the gap with the addition of new knowledge on assessing renewable energy research studies intensively using a formal systematic literature review process. The review revealed that the development of DEA methodologies and applications in renewable energy should be expanded in the future. The results obtained from this review are both beneficial and inspirational for further research regarding the DEA application in renewable energy and provide valuable input for policymakers in decision-making processes.
... The finding of this study (H3) is consistent with the studies conducted by [10, 24, 25] that size was negatively related with relative efficiency. Similarly, in [14, 26, 27] also found that the sequence of M&A and size were the significant variables that effect TE (negative relationship). In summary, the coefficients computed for the two samples are similar whereby the sequence of acquisitions and size are negatively influenced TE while M&A intensity is insignificant and also negatively influences TE. ...
Traditionally, acquiring companies have an expectation of synergy in the coming years as a result of M&As.
Instead of using traditional financial ratios from accounting statements such as return on assets in terms of
measuring performance, this study intends to provide a broad view of the effects of M&As and asset utilisation
on technical efficiency. In light of the foregoing, this study was done by taking into account the consequences of
multiple M&As undertaken by the telecommunication companies in the Asean region using year-by-year
projections. The study employed the Data Envelopment Analysis (DEA) approach which calculates the technical
efficiency using the total asset of companies during the period between 2000-2011. Subsequently, regression
analysis was employed to examine the factors that influenced the efficiency of the companies. The empirical
findings indicate that there exists a significant relationship, of negative value, between sequence of M&A and
TE. The findings also indicated that the relationship between size and TE are significant and negative. This paper
also discussed the importance of having a merger control under Competition Law and suggested that there is a
need for improvement of merger control regulations to sustain the relative efficiency of companies.
... Hence, the primary aim of this study is to measure the eco-efficiency trend of power plants for an eight-year period of the Iranian power industry restructuring from 2003, when the power market, as one the most effective modules of restructuring, started. DEA (Data Envelopment Analysis) is one of the well-recognized approach using for measuring efficiency and productivity of DMUs (Decisions Making Units) [22]. DEA has widely been adopted by many researchers to evaluate energy efficiencies [37,41,46,47,57,62] . ...
One of the main objectives in restructuring power industry is enhancing the efficiency of power facilities. However, power generation industry, which plays a key role in the power industry, has a noticeable share in emission amongst all other emission-generating sectors. In this study, we have developed some new Data Envelopment Analysis models to find efficient power plants based on less fuel consumption, combusting less polluting fuel types, and incorporating emission factors in order to measure the ecological efficiency trend. We then applied these models to measuring eco-efficiency during an eight-year period of power industry restructuring in Iran. Results reveal that there has been a significant improvement in eco-efficiency, cost efficiency and allocative efficiency of the power plants during the restructuring period. It is also shown that despite the hydro power plants look eco-efficient; the combined cycle ones have been more allocative-efficient than the other power generation technologies used in Iran.
... ≠ 0, = 1,2, … , }, respectively, where is a nonnegative real number [23][24]. The value of is considered as a very small positive real number in order to have a negligible thickness in the frontier. ...
The study investigates the relative efficiency of 20 investment programs in agriculture sector studied by Martic et al. (1996). The agriculture bank management is facing the tremendous problem of deciding under the constraints of limited funds and wish to maximize the economic return, which the firms to be selected for their investment portfolio. A recent model in Data Envelopment Analysis (DEA), called Kourosh and Arash Model (KAM) is applied in order to find the most efficient investment program. Although, there were 9 technically efficient investment programs by Constant Returns to Scale (CRS) technology, 10^(-6)-KAM suggests that there are only 2 efficient ones with 10^(-6) degree of freedom (DF) in the frontier. Moreover, number of technically efficient investment programs was 14 while Variable Returns to Scale (VRS) is applied. However, 10^(-6)-KAM shows there were only 4 efficient ones with 10^(-6)-DF in the frontier.
... Input2: Cost of operating in a month (RM) Input3: Time in travelling (minutes) Input4: Tuition fee per student (RM) Output1: Number of Teachers Output2: Area of kindergarten (square feet) A kindergarten which has less values of selected inputs and high values of selected outputs is suggested to the parent for enrolling their child. As can be seen the components of epsilon vector are completely negligible according to minimums of each factor [11]. Moreover, the value of í µí»¿ is introduced as í µí¼/10, that is, í µí»¿ = 10 -7, to suggest the best selection among 12 available kindergartens. ...
Sending children to kindergarten at the early age can be considered as very important responsibilities for parent nowadays. In this study, it is supposed that a parent wants to get decision which kindergarten from 12 kindergartens of Selangor, Malaysia, should be selected to enroll their child. For each kindergarten 6 factors are selected inclusive 4 inputs such as expected number of students, cost of operating in a month, time in travelling and tuition fee per student, and 2 outputs such as number of teachers and area of school. The study shows how a recent robust Data Envelopment Analysis (DEA) model, Kourosh and Arash Model (KAM) is applied to rank all kindergartens significantly, and suggests the best selection to the parent. Microsoft Excel Solver 2013 is used to solve KAM and represent its outcomes.
This paper proposes the use of a metafrontier efficiency analysis approach to estimate residential property values. The objective is to mitigate inefficiencies in these valuations, thereby enhancing tax revenue and fairness in tax burdens. Property features (such as acreage, living area, number of bedrooms, number of bathrooms, age, and pool presence) along with contextual variables (such as county and median household income) are utilized to estimate just market value. Observations can be grouped based on some of these variables, allowing a metafrontier analysis to be conducted. This analysis not only assesses efficiency scores but also identifies technology gaps for each group. Furthermore, the proposed approach can be employed to estimate the value of any property based on its characteristics. To illustrate the proposed approach, we utilize data on over 30,000 properties in Orange and Seminole Counties in central Florida. Additionally, we present the results of a robust regression approach for comparison purposes. While our approach can serve as a valuable tool across various sectors, its primary aim is to promote best practices in governance regarding land use and real estate valuation. This includes balancing multiple objectives such as tax revenue, economic growth, environmental sustainability, and social considerations.
There has been an ever-growing concern to measure efficiency of decision-making units (DMUs). Regression and Stochastic frontier analysis have been the popular methods of measuring the same. Data Envelopment Analysis (DEA) is one of the latest additions to the bracket of these techniques. DEA is essentially an op-timization algorithm, which develops efficiency scores for all DMUs on a scale of zero to 100%, with units receiving 100% efficiency score being called efficient. Further a simple modification in the DEA model also accounts for scaling efficiencies especially for large sized DMUs. In this study, technical efficiency measure-ment of State Road Transport Undertakings (STUs) was done using the data on a sample of 44 Indian state road transport undertakings. Using a variable return to scale model, efficiency scores were developed for all the state road transport undertakings. The study has revealed that only eight out of 44 STUs were scale efficient. One of the interesting findings of the study is that STUs operating as companies were relatively more technically efficient than others.
Background: In this study, the effects of different protein and energy levels in mixed feed on growth performance and reproduction
characteristics of heifers were investigated.
Method: The material of the study consisted of 36 Holstein Friesian (black pied) breed cattle at the age of 6 months and average live
body weight of 156.65 kg and the experiment was continued for 8 months. During the experiment, four different feeds containing 16%
CP - 2500 kcal / kg ME for the 1st group, 16% CP - 2700 kcal / kg ME for the 2nd group, 18% CP - 2500 kcal / kg ME for the 3rd group,
18% HP - 2700 kcal / kg ME for the 4th group were given at 1.5% of the live weight of heifers. (Where CP and ME stand for Crude
Protein and Metabolizable Energy, respectively). As roughage, an equal amount of straw and alfalfa hay mixture was given.
Result: As a result of this study, the effects of the different protein levels on live body weight and body measurements (body length-
BL, withers height-WH, hip height-HH, hip width-HW, body depth-BD, chest girth-CG) were not found significant (P> 0.05). Similarly,
the effects of different energy levels on body weight and body measurements (P> 0.05) and protein X energy interaction in terms of
live body weight and size were also not found significant (P> 0.05). Regarding the reproductive properties, the differences between
the groups in terms of the effect of different protein and energy levels on the first estrus age were found statistically significant
(P <0.05). As a result of the analysis made in terms of heifers age during the first insemination, the difference was found to be
statistically significant (P <0.05). The effect of different protein and energy levels on the conception rate in the first insemination was
found significant (P <0.05). As a result, it was concluded that affordable mixed feed combinations can be used within the limits of
mixed feed combinations containing 2500-2700 kcal / kg ME and 16-18% CP, which were given in the investigation; however, low
energy-high protein combinations would give more positive results considering their effects on the reproductive performances and
conception rates at first insemination.
The balanced dose of fertilizer used for any crop to get the desirable yield is very much and is dependent upon different factors like soil type, soil texture, soil structure, organic matter and especially soil moisture availability is the main and crucial factor in predicting optimum use of fertilizers. The areas w irrigation practices are available and the moisture level differences are minimum, there the prediction of fertilizer is simple and depends upon soil type, availability of different nutrients and organic matter in the soil which helps to estimate nutrient deficiencies to be supplemented by different fertilizers with optimum dose. Commendable job has been done by scientists of University of Agriculture, Faisalabad to design a model to predict fertilizer doses for all districts of Punjab for different cropping pattern with the help of some basic soil fertility status (organic matter, available phosphorus) assuming no water shortage during crop growth period. Rainfed/barani tract comprises 3.10 million hectare (mha) out of total 11.83 mha under cul practices are not present and the crop production is entirely dependent upon uncertain and uneven distribution of rainfall which makes the agriculture risky and the farmers are reluctant to incur ex especially fertilizers, so one cannot rely only on basic soil fertility status. The fertilizer doses vary according to moisture available at the specific site besides other factors and one cannot use only soil type and nutrien fertilizer dose prediction to get maximum and desired yields. In order to address this issue work done by different scientists is reviewed to establish the relationship or role of soil water contents in fertilizer use efficiency in rainfed areas to design a future study to predict different fertilizer doses under different prevailing soil water contents to achieve desired yield targets.
Data envelopment analysis is used to compare private for-profit colleges to publicly owned colleges in terms of their operating efficiency and productivity. Academic year 2005-09 panel data is used for two-year institutions in the U.S. Results indicate that for-profit efficiency exceeded that of public colleges. Malmquist index results show that colleges in both sectors increased managerial and scale efficiencies, but that both were hindered by technological regress to the extent that overall productivity declined. 2007-08 created efficiency declines across the board, but for-profits managed large technological gains that produced the only annual productivity improvement for either sector. The results are important for better understanding the increasing privatization of higher education through the entry of for-profit institutions and for understanding the inter-sector differential effects and responses to the global financial crisis.
For any processing plant there will be deleterious elements or minerals which affect production or quality, and a strategy to predict their occurrence and mitigate their impact is required. An early objective of the Olympic Dam geometallurgy program was prediction of the acid consumption and gelling behaviour of the ore, which affects leach recovery, throughput and circuit availability. The geometallurgical test program measured the response of a wide range of ore types, and then relationships between mineralogy, metallurgy and chemistry were developed. Thus the drivers of acid consumption and triggers for gelling events could be described in ways that were meaningful to plant operations. To enable optimisation of the mine planning and ore blending processes, the parameters driving metallurgical response must be translated to the block model. Data support is critical in populating a block model. Assay information is easily obtained, but mineralogical and metallurgical information is more expensive and time consuming to collect. Hence population of a block model with mineralogical and metallurgical values using a conventional geostatistical approach is not always possible. An alternative approach employed at Olympic Dam was the development of a suite of assay-to mineral algorithms. These algorithms were calibrated using all available mineralogical information, and this enabled the calculation of mineral abundances for more than 1.5 million assayed samples. Estimation of the minerals in the block model, and the generation of acid consumption values for each block could subsequently occur. The use of back-calculated mineralogy from assays as part of process model generation is an innovative tool which can be used for mine planning and optimisation and to ensure the plant does not receive any unwelcome surprises. Ultimately, one purpose of geometallurgy is to predict potential processing issues and their drivers so that these can be mitigated. A strategy to achieve this is outlined hereafter.
The paper provides a new approach to modeling bank efficiency. Unlike previous bank efficiency studies, the present paper employs the data envelopment analysis (DEA) method on quarterly data to construct the efficiency frontiers. The Malaysian banking sector is used for a case study. The results show that the Malaysian banking sector has exhibited the mean technical efficiency of 97.3%, suggesting the minimal input waste of 2.7%. The empirical findings suggest that the pure technical efficiency outweighs the scale efficiency in determining the Malaysian banking sector’s technical efficiency. The results imply that, although the Malaysian banking sector has been efficient in managerial terms, it has been operating at a non-optimal scale of operations.p
Professor Sten Malmquist constructed the Malmquist quantity index and in doing so developed a distance function defined on a consumption space. This function is the consumer analog to the Shephard input distance function of producers and is used in ratio form to define the quantity index. This volume contains new contributions based on Malmquist's work nearly 50 years ago and provides modern perspectives on the value of this research.