高校行政人员的绩效考核及其优化

绩效考核是现代化管理的有效手段。目前针对高校行政人员的绩效考核亟待改进。做好高校行政人员绩效考核应遵循四项原则,即差异化原则、公开透明原则、定性与定量相结合原则和以服务对象期望为导向的原则。应从岗位目标制定、完善领导机制、激励奖惩机制以及有效沟通等方面优化措施,以期提升高校行政人员绩效考核的客观公正性和科学有效性。     

A scoping review of knowledge syntheses in the field of evaluation across four decades of practice

This scoping review of 62 knowledge syntheses published in evaluation-focused journals between 1979 and May 2018 provides a portrait of synthesis practices and their evolution in the mainstream of the field of evaluation. Concerns surrounding the production of knowledge syntheses to answer policy questions are not new in the field of evaluation. However, during this last decade, knowledge synthesis methods have expanded as a means to go beyond the limits and constraints of singular evaluations. This scoping review reveals and discusses two key issues with regards to the expansion of knowledge synthesis practices within the field of evaluation: the diversity—and muddling— of methodological practices and synthesis designs, and the frequent omission of quality appraisals.     

Quality_Family Deployment: A New Perspective in Determining Priority Importance for Improving Work Performance in Organization

Determining priority importance is a matter of concerns among the organization to improve their performance. One of the important aspects that should be considered by the organization is management of human resources, comprising of members who have their own family life. In this paper, we deliver a new perspective for organization to provide priority importance for their members with respect to family matters in order to inculcate the sense of belonging in the organization. To be effective in considering family matters in the organizational policy making, closer look of family characteristics are required. The idea of translating several family characteristics as quality variables and applying the quality function deployment (QFD) method to these variables could present a new way of improving the decision making in the organization by considering the process of decision in the family. Quality function deployment for family (QFDF) produces a friendly interpretation of a highly complex and intangible matters around family life; thus, making the assessment of a family easier. QFD is applied on the data gathered from a questionnaire survey based on 1,213 families in West Malaysia, Malaysia. Twelve variables are identified as voice of family, where seven of them are found to have the highest priority of importance. These variables could also be translated into quality variables in the context of organization, the strategy of improvement for the family could be interpreted as strategy for improvement in the organization. Furthermore, the results of this study provide suggestion to improve actions for managing human resource. In the discussion, three most high ranked variables from both perspectives of family and organization are considered.     

中国铁路信息化项目效益评价方法研究——以竞争力为导向的BAF法

本文以竞争力理论为指导,借鉴企业信息化测评指标体系设计的方法,从战略地位、系统应用水平、经济效益、社会效益和信息资源效益五方面考察我国铁路信息化项目效益,建立相应的评价指标体系,综合"BSC AHP FUZZY"提出铁路信息化项目效益评价的BAF法,给出有关评价步骤.     

Sexual Orientation in State Hate Crime Laws: Exploring Social Construction and Criminal Law

Several studies have described and analyzed the development and diffusion of hate crime laws in the United States, but none specifically examined state-level differences in protected categories. Forty-five of the 50 states have a hate crime statute, but only 30 of those include sexual orientation. In this study the social construction framework is applied to the hate crime policy domain in order to determine whether or not variations in the social and political status of gays and lesbians are associated with the inclusion of sexual orientation in state hate crime laws. Content analysis of daily newspapers in six states revealed that a positive social construction is associated with groups seeking hate crime law protections, and that political influence may also be a key factor.     

基于样本集的区间数灰靶分类决策模型及应用

基于灰靶思想的不确定背景分类决策问题分析,本文提出了区间数灰靶分类决策模型。该模型将灰靶决策拓展到决策信息为区间数的情况,提出了区间数的靶心距测度方法;根据靶心距提出了灰靶分类决策中的靶心分类临界值设置方法;以决策对象的靶心距与临界值之间的偏差总量最小为目标,建立了指标权重和分类临界值的确定模型;依据求解的权重与分类临界值对决策对象集进行分类评价。算例分析验证了该模型的有效性和可行性,可以很好地解决决策对象众多、分类数不确定等特性的多属性分类决策问题。     

Program Evaluation and Causal Inference With High‐Dimensional Data

In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment effects including local average (LATE) and local quantile treatment effects (LQTE) in data‐rich environments. We can handle very many control variables, endogenous receipt of treatment, heterogeneous treatment effects, and function‐valued outcomes. Our framework covers the special case of exogenous receipt of treatment, either conditional on controls or unconditionally as in randomized control trials. In the latter case, our approach produces efficient estimators and honest bands for (functional) average treatment effects (ATE) and quantile treatment effects (QTE). To make informative inference possible, we assume that key reduced‐form predictive relationships are approximately sparse. This assumption allows the use of regularization and selection methods to estimate those relations, and we provide methods for post‐regularization and post‐selection inference that are uniformly valid (honest) across a wide range of models. We show that a key ingredient enabling honest inference is the use of orthogonal or doubly robust moment conditions in estimating certain reduced‐form functional parameters. We illustrate the use of the proposed methods with an application to estimating the effect of 401(k) eligibility and participation on accumulated assets. The results on program evaluation are obtained as a consequence of more general results on honest inference in a general moment‐condition framework, which arises from structural equation models in econometrics. Here, too, the crucial ingredient is the use of orthogonal moment conditions, which can be constructed from the initial moment conditions. We provide results on honest inference for (function‐valued) parameters within this general framework where any high‐quality, machine learning methods (e.g., boosted trees, deep neural networks, random forest, and their aggregated and hybrid versions) can be used to learn the nonparametric/high‐dimensional components of the model. These include a number of supporting auxiliary results that are of major independent interest: namely, we (1) prove uniform validity of a multiplier bootstrap, (2) offer a uniformly valid functional delta method, and (3) provide results for sparsity‐based estimation of regression functions for function‐valued outcomes.     

供应链绩效评价指标体系与评价方法研究

供应链管理(SCM)与现行企业模式有较大区别,其绩效评价指标体系的建立与评价方法也就有其特殊性,目前这方面的研究还略显不足。本文在综合分析现有的SCM评价指标体系的基础上,初步建立了一套适合我国SCM绩效评价的指标体系。同时,给出了SCM绩效评价的多级动态模糊综合评价方法。     

企业年金积累期的最优动态资产配置策略

替代率是评价企业年金基金投资效果的重要指标之一.本文构建了与替代率挂钩的目标基金,建立了基于目标的企业年金基金最优资产配置模型,利用随机动态规划方法获得了年金基金最优投资策略的解析解,并通过蒙特卡洛模拟技术对所得结果进行数值模拟,考察了不同市场环境及不同群体的最优配置策略和最优策略对可控制参数的敏感性.结果表明:模型中参数对年金基金的最优配置策略各有不同影响,不同群体和不同金融市场中的最优策略也有差异,但总体而言最优资产配置策略具有高风险资产权重随着时间推移而降低的动态特征.     

基于多目标加权灰靶决策模型的节能服务公司选择研究

用能方对节能服务公司（Energy Service Company,ESCO）的选择关系到合同能源管理（Energy Performance Contracting,EPC）能否顺利实施。从用能方的角度,采用灰色系统理论中的多目标加权灰靶决策模型,对存在多决策目标的ESCO选择问题进行研究。通过层次分析法确定ESCO的11个决策目标的决策权数,根据综合效果测度值的比较,最终实现最优对策的选择。本文为用能方的ESCO选择问题提供了一种新的思路。