Using N-D method to solve multi-response problem in Taguchi

Using Taguchi method to achieve a robust experimental design in the study of product quality is an important issue. The Taguchi method is to seek the best factors/levels combination with lowest societal cost solution to achieve customers requirements. However, the Taguchi method can only be used to optimize the single-response problem; it cannot be used to optimize the multi-response problem. This paper submits an optimal procedure, N-D method (Artificial Neural Network and Data Envelopment Analysis), by using artificial neural networks (ANNs) and data envelopment analysis (DEA) to achieve the optimization of multi-response problem. Two case studies in Su and Tong (1997) and Tong and Su (1997) are resolved by the proposed N-D method. The result deriving from the proposed N-D method indicates that it offers an efficient and feasible solution in the multi-response problems.This revised version was published in June 2005 with corrected page numbers.     

基于群决策考虑属性效用一致性的DEA他评交叉效率公共权重排序法

针对数据包络分析(DEA)交叉效率方法大多是面向结果采用平均方式集结交叉效率,没有考虑评价过程中属性效用数据及其变动的特性,导致大量决策信息丢失、相对效率评价值与被评价决策单元的指标值关联性不够等问题,以交叉效率评价过程为导向,引入群决策理论,研究属性偏好及其属性效用变化特征,运用熵权法分析属性效用稳定性,发现评价中存...     

VCSTalk：基于DEA的开源软件开发人员效率评价工具*

介绍了VCSTalk的具体设计和实现架构,并展示了它用于评价若干开源软件项目中的开发人员效率的一个具体实例.     

考虑数据不确定性的鲁棒交叉效率DEA方法及其应用

数据包络分析(DEA)是一种评价决策单元相对效率的数学规划模型,在管理决策领域得到了广泛应用.传统交叉DEA方法高度依赖于真实且准确的数据.当数据存在不确定性时,确定性假设下得到的DEA模型解可能会失去可行性,从而使得效率评价结果不可靠.针对这一问题,首先,基于鲁棒优化方法,提出一种鲁棒交叉效率DEA模型,其中为了避免多重最优解造成的交叉效率值不唯一问题,进一步建立二级目标模型来选择一组可接受的最优解;然后,引入鲁棒价格的概念来分析决策单元应对数据不确定性的能力,并在此基础上探讨仁慈型和对抗型两种交叉策略的选择问题;最后,基于15个OECD国家的可再生能源数据,验证所构建方法的可行性和有效性.     

电子通路与公司绩效关联性之研究

The stimulus of advances in Information Technology (IT), particularly the Internet, has forced firms to explore new organizational forms and deliver service innovation. Emerging Internet-based electronic distribution channels, i.e., Internet channels, might be another forms of services innovation for firms to face the market dynamics. However, empirical studies fail to provide direct evidence of whether Internet channels enhance business performance[1]. In order to fill in the literature gap, this empirical study attempts to investigate performance implications of Internet channels in Taiwan by means of applying data envelopment analysis (DEA). Results show that operating efficiency of financial services firms following the Internet channels announcement is increased. This work therefore concludes that Internet channels have positive influence on business performance.     

Improved data envelopment analysis models for evaluating interval efficiencies of decision-making units

In a recent article, Wang et al. [Wang, N. S., Yi, R. H., & Wang, W. (2008). Evaluating the performances of decision-making units based on interval efficiencies. Journal of Computational and Applied Mathematics, 216, 328–343] proposed a pair of interval data envelopment analysis (DEA) models for measuring the overall performances of decision-making units (DMUs) with crisp data. In this paper, we demonstrate that interval DEA models face problems in determining the efficiency interval for each DMU when there are zero values for every input. To remedy this drawback, we propose a pair of improved interval DEA models which make it possible to perform a DEA analysis using the concepts of the best and the worst relative efficiencies. Two numerical examples will be examined using the improved interval DEA models. One of the examples is a real-world application about 42 educational departments in one of the branches of the Islamic Azad University in Iran that shows the advantages and applicability of the improved approach in real-life situations.     

Cross efficiency evaluation method based on weight-balanced data envelopment analysis model

In this paper, the cross efficiency evaluation method, regarded as a DEA extension tool, is firstly reviewed for its utilization in identifying the Decision Making Unit (DMU) with the best practice and ranking the DMUs by their respective cross-efficiency scores. However, we then point out that the main drawback of the method lies in non-uniqueness of cross-efficiency scores resulted from the presence of alternate optima in traditional DEA models, obviously making it become less effective. Aiming at the research gap, a weight-balanced DEA model is proposed to lessen large differences in weighted data (weighted inputs and weighted outputs) and to effectively reduce the number of zero weights for inputs and outputs. Finally, we use two examples of the literature to illustrate the performance of this approach and discuss some issues of interest regarding the choosing of weights in cross-efficiency evaluations.     

A computational study of DEA with massive data sets

Data envelopment analysis (DEA) is computationally intensive. This work answers conclusively questions about computational performance and scale limits of the standard LP-based procedures currently used. Examples of DEA problems with up to 15K entities are documented and it is not hard to imagine problem size increasing as new more sophisticated applications are found for DEA. This work reports on a comprehensive computational study involving DEA problems with up to 100K DMUs. We explore the impact of different LP algorithms including interior point methods as well as accelerators such as advanced basis starts and DEA specific enhancements such as “restricted basis entry” (RBE). Our results demonstrate that solution times behave close to quadratically and that massive problems can be solved efficiently. We propose ideas for extending DEA into a data mining tool.     

基于SPEM扩展元模型的PSP实施方法*

提出了一种支持PSP过程的SPEM扩展元模型P-SPEM,并给出了基于P-SPEM的PSP实施过程及支持该过程的原型工具.其中使用PROBE方法帮助个体进行项目计划和估算,用DEA分析方法综合评价工程师的过程性能,有效地指导工程师实施PSP.     

基于共享回馈DEA模型的中国省际 高技术产业创新效率研究

数据包络分析(data envelopment analysis, DEA)已被证明是测度高技术产业创新绩效的好方法,但现有文献忽略了现实中企业会将创新带来的经济效益回馈至两个子阶段进行再研发和生产,从而保证持续创新.基于此,结合高技术产业创新过程的特征,将其分为技术研发和商业转化两个子阶段,提出考虑共享回馈DEA模型的两阶段效率测度模型,不仅拓展了数据包络分析方法,也促进了创新绩效管理研究.实证结果表明:中国高技术产业整体效率良好,仍有提升空间,但省际发展不均衡,各省内部不同阶段效率也存在明显的差异,实行有针对性的管理是提升绩效的有效措施.     

Measuring energy efficiency performance of China’s transport sector: A data envelopment analysis approach

This study presents an application of data envelopment analysis (DEA) approach with considering undesirable outputs, and not only examines the energy efficiency performance of China’s transport sector from 2003 to 2009, but also maximizes energy-saving potential of transport sector of China’s 30 administrative regions. Environmental DEA technology is adopted, which treats undesirable measures by distinguishing between weak and strong disposability. The output directional distance function is used, which explicitly expands desirable outputs and simultaneously reduces undesirable outputs. From the empirical results, the lowest number of efficient regions was recorded in 2007 or 2008, which eventually slightly recovered. Similarly, the overall average energy efficiency reached the lowest record in 2007 or 2008. These results are consistent with the policy guidance in the 11th Five-Year Plan (2006–2010) period that a series of new policies in the transport sector are implemented to reverse the trend of energy intensity increase. The Eastern area generally performed better than the Central area and Western area. The Central area was better than the Western area, except in some critical years such as in 2008, the financial crisis significantly affected port turnover. The total potential energy saving from 2003 to 2009 was 35.72 Mtce, the total potential energy saving was approximately 2.75% of the total transport energy use.     

Measuring entrepreneurship: Expert-based vs. data-based methodologies

The concept of entrepreneurial orientation (EO) has become essential in research into the degree of entrepreneurial behavior at firm level. It is relevant to managers to be able to assess explicitly the level of entrepreneurship of a firm. Incubators, venture capitalists, corporate venturing units, angel investors, investment banks and governments need solid measures that go beyond expert intuition to assess the entrepreneurial nature of firms before they invest in them. Researchers have examined EO and consider innovativeness, risk taking, and proactiveness are important dimensions of this concept. Although the concept is seen as a multidimensional construct, there has been a great deal of debate among scholars on how to analyse it. The traditional statistical methodology has a number of drawbacks. In this article, we extend the debate and assess the construct of EO using four different methodologies: the traditional statistical methodology, a fuzzy-logic methodology, a DEA-like methodology and a naïve methodology. As an expert-based methodology, fuzzy logic compensates some of the limitations of the statistical methodology. Drawing on a sample of 59 start-ups in a self-administered questionnaire, we measure innovativeness, risk taking and proactiveness and subsequently compare the resulting EO scores using the four methodologies. We found several differences, the most prominent of which are discussed in greater detail. The EO score from a naïve methodology yields a value that lies between the other results, while the entrepreneurial score from a fuzzy logic methodology is most different from the other results.     

Fuzzy data envelopment analysis and its application to location problems

In this paper, fuzzy DEA (data envelopment analysis) models are proposed for evaluating the efficiencies of objects with fuzzy input and output data. The obtained efficiencies are also fuzzy numbers that reflect the inherent ambiguity in evaluation problems under uncertainty. An aggregation model for integrating fuzzy attribute values is provided in order to rank objects objectively. Using the proposed method, a case study involving a restaurant location problem is analyzed in detail. Rent of establishment, traffic amount, level of security, consumer consumption level and competition level are identified as the primary factors in determining an ideal location for a Japanese-style rotisserie restaurant. Based on field investigation, the uncertain information on primary factors is represented by fuzzy numbers. Using the fuzzy aggregation model, the best location of restaurant is determined. The case study shows that fuzzy DEA models can be quite useful for solving business problems under uncertainty.     

Measuring the relative performance for leading fabless firms by using data envelopment analysis

IC Design (fabless) is critical for the global semi-conductor industry. The total revenue of all global fabless firms in 2003 was about US$20 billion, with the top 30 firms earning accounting for 96% of the market share. To examine the leaders in the field, this research analyzes the relative performances of those top 30 fabless firms. Fabless firms are often evaluated based on subjective judgments, and an overall scheme to measure the performance involving objective, multi-input and multi-output criteria is yet to be established. There is also a need for identifying and determining suggestions of how specific firms could improve their performance. Data Envelopment Analysis (DEA) method has been employed in this paper to satisfy the above needs. Using the input and output data of 2003, this study used the DEA method to build a model to evaluate the performance of those global top 30 fabless firms. The current research used four efficiency models: CCR, A&P, BCC, and Cross-Efficiency. To offer a comparison of efficiencies and associated discussions, an analysis of the Scale-Return is provided. Finally, the performance of various fabless firms in 2003 is analyzed. According to the CCR and A&P models, the results showed that the top ten Decision Management Units (DMUs) achieved better operation performance among the 30 leading global fabless firms.