IT能力对制造企业服务创新绩效的作用路径研究

构建服务型制造模式下IT能力、服务创新绩效、组织学习及服务化战略的理论分析框架,采用结构方程模型对理论假设进行实证分析,研究发现:IT能力正向影响制造企业服务创新绩效;组织学习在IT能力与服务创新绩效的关系中发挥着部分中介作用;服务化战略在IT能力与组织学习以及与服务创新绩效的关系中发挥着调节作用。本研究对于制造企业采用合适的服务化战略和提高制造企业的服务创新绩效有所裨益。     

全面培养现代远程开放教育中学生的自主学习能力

开放教育的学习组织形式和学习方法是开放教育试点教学模式改革的重要因素之一,开放教育学习的兴起为学习者提供了新的学习方式,在新的条件下采用何种教与学的组织形式来开展教学是摆在我们面前急需回答的问题。远程开放教育的性质决定了其学习模式的特点,远程开放教育的教学过     

开放大学教育体制下文字教材网络化管理与服务

一、开放大学要搞教材发行网络化管理 在国家开放大学成立后,教学的对象和教育理念都有了改变,开放大学是以现代信息技术为支撑,学历教育与非学历教育并举,实施远程开放教育的新型高等学校.开放大学着力于推进信息技术与教育教学深度融合,完善以学习者为中心、基于网络自主学习、远程支持服务与面授相结合的教学方式,创建友好的数字化学习环境;加快推进优质教育资源共建共享,着力扩大优质资源种类、总量和覆盖面,为各类人群特别是基层学习者提供更多更好的教育服务.文字教材作为学生学习的主要材料,它的发行与管理直接影响到开放大学整体的教学质量和教学声誉,因此搞好教材管理工作成为资源建设的主要部分.根据自治区开放大学特点,教材发行管理建设方面必须脱离开过去的传统发行模式,结合地域特点采取一种新的模式,更好更快地为学生服务.     

非参数统计在汉语国际推广中的应用——智能ABC汉字提取模式分析

文本采用非参数统计的方法,对汉文化圈学习者和非汉文化圈学习者自体书写汉字的需求差别,以及非汉文化圈学习者电脑提取模式和自体书写模式测试成绩的差别进行检验分析,并将两项检验结果引入《基于智能ABC平台的汉字提取教学模式》课题的研究,为研究的准确性和可靠性提供保证,从而确定该研究在汉语国际推广汉字教学中的应用价值。     

基于网络资源利用的课程教学设计方案研究

统计学专业课程的基于网络资源利用教学设计分三个层面:首先是课程教学设计,它是由诸多的单元教学设计及课程总体规划构成:其次是单元教学设计,它是由课堂教学与单元在课程中的地位组成;最基层最基本的是课堂教学设计。本文重点对课程教学和单元教学进行了详细设计,课堂教学设计则在教学过程中根据学生学习状况随时调整,及时修订。一、统计学专业课程教学设计方案(一)课程学习目标设计课程教学总体学习目标是培养学生在网络纠;境下,基于问题的自主与合作相结合的研究性学习能力。这就涉及到学生掌握知识的质量,以及利用这些知识在经济与管理…     

基于胜任力的管理辅导效能实验研究

研究通过在国内一家知名企业实施的纵向现场追踪实验发现：中国情景下适应性绩效是个多维结构，包括“组织与文化适应性”、“创造性地解决问题？等五个因素。而且，基于胜任力的辅导模式能更有效地提高被辅导人的适应性绩效水平。这个结果包括两层意思：其一，同未能得到辅导支持的成员相比，被辅导人具有更高的适应性绩效水平；其二，接受“胜任力辅导模式”者比接受”传统辅导模式”者具有更高的适应性绩效水平。另外，统计结果还表明，职位因素在辅导行为对适应性绩效的贡献上并未有显著影响。     

学校远程教育教学模式的改革探讨

远程教育与其他教育一样,其目的是培养面向基层、面向操作和管理;面向业务第一线的应用型、实践性高级专门人才。在教学过程中,如何保证远程教育的质量、达到人才培养目标,是摆在我们每个教师面前的重要课题。多年来,我们在边研究、边实践、边产出、边完善的原则指导下,在教学工作实践中,逐渐形成了以人才培养模式改革和发展为契机,以加强课程教学方式改革与学生自主学习过程管理为工作核心内容,探索远程教育的教学模式和管理模式。为培养社会建设     

内向型创新、国际化与创新绩效的关系研究

知识获取过程中的投机性学习是影响创新绩效的关键因素之一,但却被以往研究所忽略.本文以开放式创新为视角,结合组织学习、国际化理论,阐述了企业投机性学习影响创新绩效的机制;选取高新技术企业,运用普通线性回归与泊松回归检验了理论假设.研究发现,内向型创新模式,包括从国外、国内引进技术都能够提高创新绩效,但是国际化程度负向调节上述关系,投机性学习对内向型与创新绩效之间的关系也起着负向调节作用.本文研究结论有利于开放式创新能力及中国企业国际竞争力的提高.     

基金业绩分析——基于有向学习网络的研究

本文使用LASSO算法构建了基于基金持股数据的基金间动态学习网络,将基金研究中传统的无向网络扩展为有向网络,并检验了正向学习与反向学习两种不同的学习模式(信息利用方式) 对基金业绩的影响,进而探讨了其背后的经济含义。实证结果表明:当基金作为被学习者(信息被观测方)时,被正向学习会显著提高其业绩,被反向学习会显著降低其业绩;当基金作为主动学习者(信息观测方)时,无论是正向学习还是反向学习均不会对其业绩造成显著影响;对基金学习动机的分析表明,基金参与学习是为了提升相对自己上期的业绩、防止业绩倒退,且反向学习相对更加有效。本文分析了信 息传递方向、信息利用方式对基金业绩的影响,为如何将统计学习方法应用于金融问题的分析提供了一个新的视角。     

企业绩效管理的研究与实践

一、绩效与绩效管理绩效就是个体或群体的工作成绩和效果。绩效管理是为了达到企业目标,对企业资源进行规划、组织和使用,并实现顾客期望的过程。绩效管理的实质是一个循环往复的过程,每个过程都包括绩效计划、绩效促进、绩效评估和绩效激励四个阶段。绩效管理的终极目标是实现企业的战略目标。     

Triple-goal estimates in two-stage hierarchical models

The beauty of the Bayesian approach is its ability to structure complicated models, inferential goals and analyses. To take full advantage of it, methods should be linked to an inferential goal via a loss function. For example, in the two-stage, compound sampling model the posterior means are optimal under squared error loss. However, they can perform poorly in estimating the histogram of the parameters or in ranking them. 'Triple-goal' estimates are motivated by the desire to have a set of estimates that produce good ranks, a good parameter histogram and good co-ordinate-specific estimates. No set of estimates can simultaneously optimize these three goals and we seek a set that strikes an effective trade-off. We evaluate and compare three candidate approaches: the posterior means, the constrained Bayes estimates of Louis and Ghosh, and a new approach that optimizes estimation of the histogram and the ranks. Mathematical and simulation-based analyses support the superiority of the new approach and document its excellent performance for the three inferential goals.     

Bivariate negative binomial regression model with excess zeros and right censoring: an application to Indonesian data

We propose a bivariate hurdle negative binomial (BHNB) regression model with right censoring to model correlated bivariate count data with excess zeros and few extreme observations. The parameters of the BHNB regression model are obtained using maximum likelihood with conjugate gradient optimization. The proposed model is applied to actual survey data where the bivariate outcome is number of days missed from primary activities and number of days spent in bed due to illness during the 4-week period preceding the inquiry date. We compared the right censored BHNB model to the right censored bivariate negative binomial (BNB) model. A simulation study is conducted to discuss some properties of the BHNB model. Our proposed model demonstrated superior performance in goodness-of-fit of estimated frequencies.KEYWORDS: Zero inflation, over-dispersion, parameter estimation, model selection, right censoring     

A computationally fast alternative to cross-validation in penalized Gaussian graphical models

We study the problem of selecting a regularization parameter in penalized Gaussian graphical models. When the goal is to obtain a model with good predictive power, cross-validation is the gold standard. We present a new estimator of Kullback–Leibler loss in Gaussian Graphical models which provides a computationally fast alternative to cross-validation. The estimator is obtained by approximating leave-one-out-cross-validation. Our approach is demonstrated on simulated data sets for various types of graphs. The proposed formula exhibits superior performance, especially in the typical small sample size scenario, compared to other available alternatives to cross-validation, such as Akaike's information criterion and Generalized approximate cross-validation. We also show that the estimator can be used to improve the performance of the Bayesian information criterion when the sample size is small.     

基于目标导向的银行理财产品最优费率研究

建立基于银行目标导向的理财产品费率模型,通过对不同目标下银行行为的讨论,得出理财产品费率调整的一个分析框架。研究发现：存在使银行的经济效益和社会效益综合提升程度最大的最优理财产品费率;最优费率不是固定值,而是一个动态概念;单纯考虑经济效益时,银行将调高理财产品费率;银行调高理财产品费率,将提升自身综合目标的实现程度;银行调低理财产品费率,并不改变银行的综合目标。     

The Mean Squared Error of the Generalized Ridge Regression Estimator and the Orientation of β

Newhouse and Oman (1971) identified the orientations with respect to the eigenvectors of X'X of the true coefficient vector of the linear regression model for which the ordinary ridge regression estimator performs best and performs worse when mean squared error is the measure of performance. In this paper the corresponding result is derived for generalized ridge regression for two risk functions: mean squared error and mean squared error of prediction.     

Different definitions of Δ-correct selection for the indifference zone formulation

The goal of the indifference zone formulation of selection (Bechhofer, 1954) consists of selecting the t best variants out of k variants with a probability of at least 1 − β if the parameter difference between the t ‘good’ variants and the k − t ‘bad’ variants is not less than Δ. A review of generalized selection goals not using this difference condition is presented. Within some general classes of distributions, the suitable experimental designs for all these selection goals are identical. Similar results are described for the problem of selecting the best variant in comparison with a control, or standard.     

The Serialist’s Mentee: Commitment,Communication, Collaboration

Abstract

This article is based on a presentation from the 2019 North Carolina Serials Conference that described the changing nature of the mentor/mentee relationship in the face of shrinking budgets, downsized technical services departments, and the profession-wide commitment to recruiting librarians at an earlier stage in their professional career. Mentors have had to focus more on the training aspect of said relationships than they did in the past in order to create a fully autonomous colleague. In the presentation, we shared our goals, challenges, and experiences as mentor and mentee in this new paradigm.     

Optimal designs for calibration of orientations

This paper concerns designed experiments involving observations of orientations following the models of Prentice (1989) and Rivest &Chang (2006). The authors state minimal conditions on the designs for consistent least squares estimation of the matrix parameters in these models. The conditions are expressed in terms of the axes and rotation angles of the design orientations. The authors show that designs satisfying U₁ + … + U_n = 0 are optimal in the sense of minimizing the estimation error average angular distance. The authors give constructions of optimal n‐point designs when n ≥ 4 and they compare the performance of several designs through approximations and simulation.     

High-dimensional regression in practice: an empirical study of finite-sample prediction,variable selection and ranking

Penalized likelihood approaches are widely used for high-dimensional regression. Although many methods have been proposed and the associated theory is now well developed, the relative efficacy of different approaches in finite-sample settings, as encountered in practice, remains incompletely understood. There is therefore a need for empirical investigations in this area that can offer practical insight and guidance to users. In this paper, we present a large-scale comparison of penalized regression methods. We distinguish between three related goals: prediction, variable selection and variable ranking. Our results span more than 2300 data-generating scenarios, including both synthetic and semisynthetic data (real covariates and simulated responses), allowing us to systematically consider the influence of various factors (sample size, dimensionality, sparsity, signal strength and multicollinearity). We consider several widely used approaches (Lasso, Adaptive Lasso, Elastic Net, Ridge Regression, SCAD, the Dantzig Selector and Stability Selection). We find considerable variation in performance between methods. Our results support a “no panacea” view, with no unambiguous winner across all scenarios or goals, even in this restricted setting where all data align well with the assumptions underlying the methods. The study allows us to make some recommendations as to which approaches may be most (or least) suitable given the goal and some data characteristics. Our empirical results complement existing theory and provide a resource to compare methods across a range of scenarios and metrics.     

Reassessing service courses in statistics

Service courses in statistics are frequently criticized by students as being unnecessary or Irrelevant to their educational goals. This article examine the teaching of undergraduates service courses. Indentifying several areas critical to the sucess of the courses.General Philosphing conceriningthe resoultions of the problems associated with the teaching of an undergraduates service courses are proposed as well as the specific suggestionsfor a course for a social science majors