Mutual fund performance evaluation using data envelopment analysis with new risk measures

The data envelopment analysis (DEA) technique has been found very useful for evaluating the mutual fund performance. This applied study extends previous results in two ways: to properly reflect the pervasive skewness and leptokurtosis in return distributions of actively managed funds, new risk measures value-at-risk (VaR) and conditional value-at-risk (CVaR) are introduced into inputs of the existing DEA models; to fairly evaluate the relative performance of the same fund during different time periods, we creatively treat the same fund during different periods as different decision making units. Except for confirming current empirical conclusions, detailed empirical analyses using data of the Chinese mutual fund market show that, VaR and CVaR, especially their combinations with traditional risk measures, are very helpful for comprehensively describing return distribution properties and fund characteristics such as the asset allocation structure, which, in turn, can better evaluate the overall performance of mutual funds. Treating the same fund during different time periods as different funds can not only show the specific performance variation, but reveal the reasons for that variation.

Dual-role factors in data envelopment analysis

This paper presents a methodology for dealing with performance evaluation settings where factors can simultaneously play both input and output roles. Model structures are developed for classifying Decision-Making Units (DMUs) into three groups according to whether such a factor is behaving like an output, an input, or is in equilibrium, neither wanting to lose or gain any of the factors. We connect these ideas to those involving increasing, decreasing and constant returns to scale. Examples of factors that play this dual-role are: trainees in organizations, such as nurses, medical students, and doctoral students; awards to scholars or university departments; certain revenue—generating transactions in banks, and so on. We apply the model to the analysis of a set of university departments. In some settings, a dual-role factor may be one that can be reallocated, such as would be the case when DMUs are managed by a central authority. We develop the appropriate model structures to permit such a reallocation. We present two such structures, with the first involving reallocation from an existing allocation, and the second, a zero-base allocation.     

Combining balanced scorecard with data envelopment analysis to conduct performance diagnosis for Taiwanese LED manufacturers

Light emitting diode (LED) is a popular component to replace the traditional lighting source or advertising sign display. In 2014, high-brightness LED has a strong growth in backlight display, mobile appliances, automotive devices and outdoor illumination. However, emerging technologies in compound materials, epitaxying, packaging and new entrants result in a scale-based economy and intensively competitive environment. Inspired by the concept of business analytics, this paper proposes a novel framework to conduct corporate diagnosis for Taiwanese LED manufacturers: (1) balanced scorecard is fused with data envelopment analysis to address the impact of operational efficiency on performance outcomes, (2) financial and non-financial indicators are incorporated into the process of performance measurement, (3) the intricate causalities between key performance indicators (KPIs) and multiple outcomes (i.e. earnings per share and return on equity) are captured and (4) managerial insights are provided to indicate adaptive adjustment on significant KPIs. More importantly, a data-set comprising representative Taiwanese LED companies spanned from 2010 to 2014 is used to justify the validity of the proposed framework.     

Application of data envelopment analysis for cell performance evaluation and process improvement in cellular manufacturing

This paper proposes a methodology for cell performance evaluation and improvement which considers multiple cell inputs and outputs. A specific technique in data envelopment analysis called 'window analysis', which captures the cell efficiency changes over time, is modified and utilized in the methodology. The evaluation is performed by considering the local part families (manufactured in single cells) and the infrequent parts (manufactured in multiple cells) processed by a cell. A major contribution of this research is in proposing a new 'modified window analysis' technique for cell performance evaluation, and in demonstrating its effectiveness over the 'traditional window analysis'. Another contribution is in using the cross efficiency matrix to identify periods of best cell operating practices which aid management in cell process improvement.     

Output deterioration with input reduction in data envelopment analysis

In most practical applications of Data Envelopment Analysis (DEA), it is recognized that there is a gap between the theoretical maximum reduction in inputs, e.g., 1 -θ, versus what is actually achievable. In this paper we examine this phenomenon in the context of productivity measurement of highway maintenance crews. Here, maintenance supervisors and geotechnical engineers estimate the maximum achievable reduction in resources without impacting the outputs from the process. Furthermore, they put bounds on the extent of output erosion that can result from input reduction beyond this maximum level. We present a modified version of the standard Banker, Charnes and Cooper (BCC) DEA model that explicitly addresses this erosion phenomenon. The resulting projections provide maintenance managers with a measure of the impact on system performance under excessive resource reduction, and aid in setting guidelines for maintenance budgeting at the patrol level.     

基于数据包络分析方法的数据中心能效评价

数据中心面临能源消耗量急剧上升的问题,需要研究绿色节能的能效评价方法。首先探讨数据包络分析方法在数据中心能效评价中可行性、应用方式与建模方法,进一步提出基于数据包络分析的数据中心能效评价方法,并通过对该分析方法的应用,获得不同数据中心能效结果。研究结果表明:数据包络分析方法可克服目前数据中心机房通常采用单一指标参数的局限性,不用对输入元素权重进行主观分析,可推广到其他多因素的性能测试与评价方法中。     

Supplier selection using analytic network process and data envelopment analysis

The present study intends to present a supplier selection method, which also considers green indicators due to environmental protection issues, by using an analysis network process (ANP) as well as data envelopment analysis (DEA). ANP which is able to consider the interdependency between criteria releases the constraint of DEA that the users cannot set up criteria weight preferences. The model evaluation results for high-tech industry show that the proposed method can provide not only reasonable outcomes with a smaller number of decision making units, but can also provide more consistent results.     

Robust design for multiple dynamic quality characteristics using data envelopment analysis

The Taguchi method is extensively adopted in various industries to continuously improve product design in response to customer requirements. The dynamic system of the Taguchi method is frequently implemented to design products with flexible applications. However, Taguchi's dynamic system can be employed only for individual quality characteristic, and the relationship between the quality characteristic and the signal factor is assumed to be linear. Because of these restrictions, Taguchi's dynamic system is ineffective for multiple quality characteristics or when the quality characteristic has a nonlinear relationship with the signal factor. This study describes a novel procedure for optimizing a dynamic system based on data envelopment analysis. The proposed procedure overcomes the limitations of Taguchi's dynamic system. Two cases are analyzed to demonstrate the effectiveness of the proposed procedure. The results show that the proposed procedure can enhance multiple dynamic quality characteristics. Copyright © 2008 John Wiley & Sons, Ltd.     

Inter-country R&;D efficiency analysis: An application of data envelopment analysis

This study examines the relative efficiency of the R&D process across a group of 22 developed and developing countries using Data Envelopment Analysis (DEA). The R&D technical efficiency is examined using a model with patents granted to residents as an output and gross domestic expenditure on R&D and the number of researchers as inputs. Under CRS (Constant Returns to Scale), Japan, the Republic of Korea and China are found to be efficient, whereas under the VRS (Variable Returns to Scale) framework, Japan, the Republic of Korea, China, India, Slovenia and Hungary are found to be efficient. The emergence of some of the developing nations on the efficiency frontier indicates that these nations can also serve as benchmarks for their efficient use of R&D resources. The inefficiency in the R&D resource usage highlighted by this study indicates the underlying potential that can be tapped for the development and growth of nations.     

Assessing sustainability of Islamic countries via data envelopment analysis (DEA)

Clean Technologies and Environmental Policy - Given international regulations, countries try to improve their sustainability. The objective of this paper is to assess the sustainability of Islamic...     

Benchmarking the darrieus wind turbine configurations through review and data envelopment analysis

Clean Technologies and Environmental Policy - The global demand for small and medium-scale wind energy production necessitates the development of vertical axis wind turbines for centralized and...     

Benchmarking road safety: Lessons to learn from a data envelopment analysis

Road safety performance indicators (SPI) have recently been proposed as a useful instrument in comparing countries on the performance of different risk aspects of their road safety system. In this respect, SPIs should be actionable, i.e. they should provide clear directions for policymakers about what action is needed and which priorities should be set in order to improve a country’s road safety level in the most efficient way. This paper aims at contributing to this issue by proposing a computational model based on data envelopment analysis (DEA). Based on the model output, the good and bad aspects of road safety are identified for each country. Moreover, targets and priorities for policy actions can be set. As our data set contains 21 European countries for which a separate, best possible model is constructed, a number of country-specific policy actions can be recommended. Conclusions are drawn regarding the following performance indicators: alcohol and drugs, speed, protective systems, vehicle, infrastructure and trauma management. For each country that performs relatively poor, a particular country will be assigned as a useful benchmark.     

Consistent and robust ranking in imprecise data envelopment analysis under perturbations of random subsets of data

Data envelopment analysis (DEA) is a non-parametric method for measuring the relative efficiency of a set of decision making units using multiple precise inputs to produce multiple precise outputs. Several extensions to DEA have been made for the case of imprecise data, as well as to improve the robustness of the assessment for these cases. Prevailing robust DEA (RDEA) models are based on mirrored interval DEA models, including two distinct production possibility sets (PPS). However, this approach renders the distance measures incommensurate and violates the standard assumptions for the interpretation of distance measures as efficiency scores. We propose a modified RDEA (MRDEA) model with a unified PPS to overcome the present problem in RDEA. Based on a flexible formulation for the number of variables perturbed, MRDEA calculates the empirical distribution for the interval efficiency for the case of a random number of variables affected. The MRDEA approach also decreases the computational complexity of the RDEA model, as well as significantly increases the discriminatory power of the model without additional information requirements. The properties of the method are demonstrated for four different numerical instances.     

Road safety risk evaluation and target setting using data envelopment analysis and its extensions

Currently, comparison between countries in terms of their road safety performance is widely conducted in order to better understand one's own safety situation and to learn from those best-performing countries by indicating practical targets and formulating action programmes. In this respect, crash data such as the number of road fatalities and casualties are mostly investigated. However, the absolute numbers are not directly comparable between countries. Therefore, the concept of risk, which is defined as the ratio of road safety outcomes and some measure of exposure (e.g., the population size, the number of registered vehicles, or distance travelled), is often used in the context of benchmarking. Nevertheless, these risk indicators are not consistent in most cases. In other words, countries may have different evaluation results or ranking positions using different exposure information. In this study, data envelopment analysis (DEA) as a performance measurement technique is investigated to provide an overall perspective on a country's road safety situation, and further assess whether the road safety outcomes registered in a country correspond to the numbers that can be expected based on the level of exposure. In doing so, three model extensions are considered, which are the DEA based road safety model (DEA-RS), the cross-efficiency method, and the categorical DEA model. Using the measures of exposure to risk as the model's input and the number of road fatalities as output, an overall road safety efficiency score is computed for the 27 European Union (EU) countries based on the DEA-RS model, and the ranking of countries in accordance with their cross-efficiency scores is evaluated. Furthermore, after applying clustering analysis to group countries with inherent similarity in their practices, the categorical DEA-RS model is adopted to identify best-performing and underperforming countries in each cluster, as well as the reference sets or benchmarks for those underperforming ones. More importantly, the extent to which each reference set could be learned from is specified, and practical yet challenging targets are given for each underperforming country, which enables policymakers to recognize the gap with those best-performing countries and further develop their own road safety policy.     

Value-at-risk and data envelopment analysis: comments on Wu and Olson (2010)

In this note, we identify three major errors contained in Wu and Olson [Wu, D.D. and Olson, D., 2010. Enterprise risk management: a DEA VaR approach in vendor selection. International Journal of Production Research, 48 (16), 4919–4932]. It is shown that the ‘DEA VaR’ model named by the authors is not truly a Value-at-risk (VaR) minimisation problem. It is also pointed out that the authors confused two concepts of stochastic efficiency. Finally, it is revealed that the linearisation technique proposed by the authors is questionable under some conditions and a correction is suggested.     

Performance ranking of Asian lead frame firms: a slack-based method in data envelopment analysis

With the quick growth of economics, the semiconductor foundry in the Asian area produces a large amount of derived demand for the lead frame. To deal with the quickly changing competitive environment in high technology innovation, better performing firms can constantly capture a competitive advantage. A survey is conducted to obtain the operating data of Asian lead frame firms and a slack analysis in data envelopment analysis (DEA) is applied to identify the benchmarks of the Asian lead frame industry according to their management performance. This study is carried out through literature review and experts’ opinions to conclude assessing factors. This can aid the scholars in their performance evaluation of the related industries. We also interview the CEOs of benchmark firms to attain the outstanding strengths and strategies. In addition, this study investigates the differences among firms in proposing possible improvement strategies for inefficient firms.     

标准控制探索

我们厂在进行ＩＳＯ９０００族系列标准认证过程中,碰到了一个棘手的问题：如何做到对技术标准进行一对一的控制？我们厂的产品林林总总有近百余种。其种类之杂,牵涉行业之广,复杂程度之大堪称一绝。标准使用范围计有ＧＢ、ＪＢ、ＣＢ、ＧＪＢ、ＭＴ、ＹＢ、ＪＴ、ＪＧ...     

Combining reference point based composite indicators with data envelopment analysis: application to the assessment of universities

In our knowledge society, where universities are key players, the assessment of higher education institutions should meet the new demands of the present complex environment. This calls for the use of techniques that are able to manage this complexity. In this paper, we propose a novel combination of methodologies, jointly using a multi-criteria reference point scheme and the data envelopment analysis (DEA) for the assessment of universities. This combination allows us to take into account all the aspects regarded as relevant to assess university performance, and use them as outputs in the efficiency analysis. Our findings highlight the convenience to assess the university performance by using both compensatory and non-compensatory schemes. This way, the information provided allows to detect the actions needed to improve the performances of the universities, rather than just giving an overall performance measure. Furthermore, combining the use of composite indicators with the DEA analysis provides a more complete picture of the institutions assessed, allowing universities to check their efficiency and to detect their weaknesses and strengths accordingly. The approach is illustrated using data of 47 Spanish public universities for the academic year, 2016–2017.

     

连续爆炸冲击下负泊松比超材料防护结构性能研究

连续爆炸冲击现象在重大爆炸事故中经常出现,这对防护结构的性能提出更高要求。该研究对负泊松比超材料防护结构在连续爆炸冲击作用下的抗爆性能开展研究。首先,探讨了连续爆炸载荷的特点及作用方式。其次,采用数值仿真方法分析了海洋平台的负泊松比超材料防爆墙和负泊松比超材料双层横舱壁在连续爆炸冲击下的变形模式和应变分布,揭示了连续爆炸冲击下该类超材料结构的二次变形规律和毁伤机理。研究发现,內爆和外爆连续冲击载荷的作用方式并不相同,负泊松比超材料结构在连续外部及内部爆炸冲击时分别出现了局部坍塌挤压吸能、结构密实化整体弯曲等两种不同变形模式。研究结果可为防护结构连续抗爆设计提供参考。