Performance evaluation based on multiple attributes with nonparametric frontiers

Performance rating and comparison of a group of entities is frequently based on the values of several attributes. Such evaluations are often complicated by the absence of a natural or obvious way to weight the importance of the individual dimensions of the performance. This paper proposes a framework based on nonparametric frontiers to rate and classify entities described by multiple performance attributes into ‘performers’ and ‘underperformers’. The method is equivalent to Data Envelopment Analysis (DEA) with entities defined only by outputs. In the spirit of DEA, the weights for each attribute are selected to maximize each entity’s performance score. This approach, however, results in a new linear program that is more direct and intuitive than traditional DEA formulations. The model can be easily understood and interpreted by practitioners since it conforms better to the practice of evaluating and comparing performance using standard specifications. We illustrate the model’s use with two examples. The first evaluates the performance of employees. The second is an application in manufacturing where multiple quality attributes are used to assess and compare performance of different manufacturing processes.     

Exploring the Importance of Business Clockspeed as a Moderator for Determinants of Supplier Network Performance*

As the importance of supplier networks becomes increasingly recognized as a vital factor to company performance, researchers and practitioners alike are focusing their attention on this subject. The study's main objective is to test the specific hypotheses that effective use of Information Technology (IT) and the depth of company relationships with suppliers are directly related to Supplier Network (SN) performance, and that industry clockspeed moderates these relationships. A convenience sample of 135 manufacturing organizations was used to empirically test these hypotheses. Our results indicate that clockspeed does moderate the relationship between IT use effectiveness and supplier network performance. The same is true in the case of supplier relations depth, and hence, managers are encouraged to pay attention to the items comprising network performance as a determinant of supplier network performance.     

Reconfiguring the Supply Network Using Current Performance Data

Reconfiguration of the supply chain network from time to time is essential for businesses to retain their competitive edge. This paper presents a methodology for reconfiguration of an existing supply chain network. The methodology is characterized by two decision levels. In the first level, the current network performance is evaluated and efficient practices are identified. In the next level, a model that incorporates efficient practices is developed to reconfigure the network. This integrated methodology allows for decision maker (DM) input throughout the process. The methodology has been implemented and tested in the reconfiguration of an outbound petroleum supply chain network for CountryMark Cooperative, Inc. In this case study, Data Envelopment Analysis (DEA) is used to analyze current operations and an integer programming (IP) model that incorporates efficiency metrics is developed for selection of distribution facilities and allocation of resources to the facilities. Use of this methodology can lead to improved operations and reduced operating expenses.     

企业技术效率的影响分析

 本文以上海市166家大中型企业五年的面板数据为研究对象,设定两种不同的生产函数和两种误差分布,利用随机前沿方法分别进行了技术效率的估计。我们发现不同测算方法的结果差异不大,且对企业的评价具有一致性。结果表明上海市工业企业的技术效率整体水平不高。通过研究影响企业技术效率的外生性因素,发现企业的所有制结构、规模、R&D经费支出与R&D人员投入、资本密集程度和企业的垄断程度等因素都对上海市工业企业的技术效率水平具有显著影响。基于研究结果,我们给出了提高企业技术效率的一些建议。     

统计数据项目、发布渠道与用户质量感知

 通过实施统计用户满意度调查,测量统计用户对于政府统计部门所生产各类统计数据项目的综合质量感知,及其在主要发布渠道的具体质量感知状况。基于调查数据的分析结果表明：各类统计数据项目的综合用户质量感知水平存在较为明显的差异,用户质量感知与其使用频率之间保持了一定的正相关关系;而各类统计项目在不同发布渠道的具体质量表现也不尽相同。据此可以有效确立统计数据质量管理工作的重点环节。     

中国投资者的风险偏好

 投资者如何分配家庭资产,为个体的风险偏好研究提供了重要的信息。本文采用奥尔多投资研究中心《城市投资者行为调查问卷》的调查结果,从投资者对风险资产需求这一角度,详细研究哪些因素会显著影响投资者的风险偏好,以及不同群体投资者风险偏好的异质性问题。研究结果表明：投资者的财富水平、受教育程度、健康状况、收入水平和是否抚养小孩都是影响投资者风险偏好的重要因素。同时,不同群体风险偏好的表现有差异。研究中国投资者风险偏好的异质性,可以为进一步研究投资者的金融资产决策、储蓄行为、财富积累过程以及不同群体对宏观经济政策的反应提供依据。     

基于家庭收入的保障性住房标准研究

 保障性住房是关系国计民生的重大问题,为使保障性住房充分发挥作用,其准入标准的确定尤为重要。目前我国保障性住房准入标准大都以人均收入作为参考指标,本文旨在测算并确立以家庭收入为参考指标的保障性住房准入标准。由于厦门市保障性住房在全国具有示范效应,故以厦门为例考察基于家庭收入的保障性住房准入标准。根据抽样调查的分组数据界定“中低收入组”,通过正态分布与均匀分布的转换,利用格点映射法,找出覆盖面为40%的收入上限值,即为保障性住房的准入标准。基于此标准,结合“按年人均收入限值”这一指标,将家庭组别按人口细分,划分出针对不同家庭规模的参考准入标准。     

大数据的整合分析方法

大数据具有数据来源差异性、高维性及稀疏性等特点,如何挖掘数据集间的异质性和共同性并降维去噪是大数据分析的目标与挑战之一。整合分析（Integrative Analysis）同时分析多个独立数据集,避免因地域、时间等因素造成的样本差异而引起模型不稳定,是研究大数据差异性的有效方法。它的特点是将每个解释变量在所有数据集中的系数视为一组,通过惩罚函数对系数组进行压缩,研究变量间的关联性并实现降维。本文从同构数据整合分析、异构数据整合分析以及考虑网络结构的整合分析三方面梳理了惩罚整合分析方法的原理、算法和研究现状。统计模拟发现,在弱相关、一般相关和强相关三种情形下, Group Bridge、 Group MCP、Composite MCP都表现良好,其中 Group Bridge的假阳数最低且最稳定。最后,将整合分析用于研究具有来源差异性的新农合家庭医疗支出,以及具有超高维、小样本等大数据典型特征的癌症基因数据,得到了一些有意义的结论。     

时变空间权重矩阵面板数据模型稳健LM检验有效性研究

空间权重矩阵是描述个体间空间关系的重要工具,通常基于个体间的地理距离构造不随时间而改变的空间权重矩阵。然而,当个体间的空间关系源自经济/社会/贸易距离或人口流动性/气候等特征时,空间权重矩阵本质上可能将随时间而改变。由此,本研究提出时变空间权重矩阵面板数据模型的稳健LM检验。大量Monte Carlo模拟结果显示：从检验水平和功效角度来看,基于误设的非时变空间权重矩阵的稳健LM检验存在较大偏差,但是基于时变空间权重矩阵的稳健LM检验能够有效地识别面板数据中的空间关系类型。尤其是,在时间较长和个体较多等情况下,时变空间权重矩阵的稳健LM检验功效更高。     

大数据视角下名录库更新维护——基于互联网异源异构数据整合的探讨

统计系统基本单位名录库是统计数据质量的基石,现有数据源在成本、时效性、数据提供者负担方面存在劣势。为此,提出一种互联网大数据整合视角下的名录库更新维护思路：从参与者行为、数据质量角度论证了将异源异构互联网作为名录库更新数据源的优势,讨论了名录库基本信息、属性信息及地理定位信息获取的技术手段,并给出实例应用。