Outsourcing to a Powerful Contract Manufacturer: The Effect of Learning‐by‐Doing

The contract manufacturing industry has grown rapidly in recent years as firms have increasingly outsourced production to reduce costs. This growth has created powerful contract manufacturers (CMs) in several industries. Achieving a competitive cost position is often a primary motive for outsourcing. Outsourcing influences both the original equipment manufacturer's (OEM) and the CM's production levels, and, therefore, through learning‐by‐doing renders future costs dependent on past outsourcing decisions. As such, outsourcing should not be viewed as a static decision that, once made, is not revisited. We address these considerations by analyzing a two‐period game between an OEM and a powerful CM wherein both firms can reduce their production costs through learning‐by‐doing. We find that partial outsourcing, wherein the OEM simultaneously outsources and produces in‐house, can be an optimal strategy. Also, we find that the OEM's outsourcing strategy may be dynamic—i.e., change from period to period. In addition, we find both that the OEM may engage in production for leverage (i.e., produce internally when at a cost disadvantage) and that the CM may engage in low balling. These and other findings in this paper demonstrate the importance of considering learning, the power of the CM, and future periods when making outsourcing decisions.     

公费师范生学习动力的现状、问题与对策 ——基于西部地区5所高师院校的调查研究

公费师范生政策是国家在优先发展教育事业,建设教育强国的战略背景下做出的重大举措。学习动力是反映公费师范 生学习现状与从教信念,影响学习效果与就业能力的重要因素。课题组立足于公费师范生培养的现实状况,选取西部5所高 师院校的在读公费师范生作为研究对象,从相关政策、自身因素、教育因素以及环境因素四个方面进行实证调查,针对目前存 在的突出问题,提出要遵循严准入、重过程、强指导的思路,着力从政府、社会、高校以及学生四个主体维度,以政策支持、服务 保障、教育管理、自我提升等方面多管齐下协同联动,共同致力于培养安心从教、热心从教的公费师范生。     

基于问题导向的翻转课堂教学模式实践研究 ——以“综合英语”课程为例

信息技术的飞速发展,给专业英语教学的变革带来了机遇。以现代信息技术如网络和移动终端为支撑,构建基于问题导 向的4A式翻转课堂教学模式,并用该模式开展了为期一个学期和一个寒假的教学实践。通过问卷调查和访谈,并对收集的数 据进行统计与分析,研究结果显示：学生对该模式的满意度较高。该模式对语言提升和能力提升有明显的促进作用,不足在于 对时间、环境、教师及时有效的课下指导要求较高,并提出了针对性的改进建议,讨论与反思以优化该模式的教学效果。     

杜威经验观对幼儿园主题课程设计的启示

杜威认为经验是人与环境交互作用的所有方式,是人在世界中的行动与其结果的关联,不仅是对过去的回顾,也包含向未来行动的探索。据此,杜威提出课程的目标就是要提升学习者经验,以更好地生活;课程内容应尊重学习者生活经验;课程应保证学习者亲身经验。对幼儿园主题课程设计来说,杜威的经验观有以下三方面启示,第一,幼儿园主题课程以提供促进幼儿生长的经验为课程目标;第二,以幼儿生活经验为课程内容;第三,要采用“做中学”的经验教学法。     

藏族非英语专业大学生英语学习策略调查与分析

本文根据Oxford编制的语言学习策略量表(SILL),对青海地区藏族非英语专业大学生的英语学习策略进行统计分析。通过问卷调查发现藏族大学生的总体策略使用水平呈中等较低水平,使用频率最高的是无认知策略,较低的是记忆策略和认知策略。他们英语学习最大的困难在于语言策略意识淡漠,词汇储备不足,最后本文提出了在现行条件下解决的相应对策。     

医学研究生心理资本、社会支持与学习倦怠的关系研究

探讨医学研究生心理资本、社会支持与学习倦怠的关系。采用心理资本问卷、社会支持问卷和学习倦怠问卷对249名医学研究生进行调查。结果发现,医学研究生学习倦怠得分为（2.49±1.04）分,其中13.6%的学生为高度学习倦怠;学习倦怠及其三个维度与心理资本、社会支持均呈显著负相关（P＜0.05）;多元线性回归分析显示乐观和对支持的利用度是学习倦怠的有效预测变量,能够解释医学研究生学习倦怠35.3%的变异。相关教育部门应加强医学研究生积极心理资本的培养以预防和降低学习倦怠的发生。     

A Bayesian Learning Coefficient of Generalization Error and Vandermonde Matrix-Type Singularities

The coefficient of the main term of the generalization error in Bayesian estimation is called a Bayesian learning coefficient. In this article, we first introduce Vandermonde matrix type singularities and show certain orthogonality conditions of them. Recently, it has been recognized that Vandermonde matrix type singularities are related to Bayesian learning coefficients for several hierarchical learning models. By applying the orthogonality conditions of them, we show that their log canonical threshold also corresponds to the Bayesian learning coefficient for normal mixture models, and we obtain the explicit computational results in dimension one.     

An improved comorbidity summary score for measuring disease burden and predicting mortality with applications to two national cohorts

Abstract

Research involving administrative healthcare data to study patient outcomes requires the investigator to account for the patient’s disease burden in order to reduce the potential for biased results. Here we develop a comorbidity summary score based on variable importance measures derived from several statistical and machine learning methods and show it has superior predictive performance to the Elixhauser and Charlson indices when used to predict 1-year, 5-year, and 10-year mortality. We used two large Veterans Administration cohorts to develop and validate the summary score and compared predictive performance using the area under ROC curve (AUC) and the Brier score.     

Accuracy,confidence and consensus in bayesian hypothesis inference

Interest centres on a group of statisticians , each supplied with the same n sample datapoint sandmaking formal Bayesian inference with a common likelihood function but differing prior knowledge and utility functions.

Definitions are proposed which quantify, in a commensurable way, the inference processes of “accuracy”, “confidence” and “consensus” for the case of hypothesis inference with a fixed sample size n.

The general significance of comparing the three quantifiers is considered. As n increases the asymptotic behaviour of the quantifiers is evaluated and it is found that the three rates of convergence are of the same order as a function of n. The results are interpreted and some of their implications are discussed.     

An Algorithm for Unconstrained Quadratically Penalized Convex Optimization

Estimators are often defined as the solutions to data dependent optimization problems. A common form of objective function (function to be optimized) that arises in statistical estimation is the sum of a convex function V and a quadratic complexity penalty. A standard paradigm for creating kernel-based estimators leads to such an optimization problem. This article describes an optimization algorithm designed for unconstrained optimization problems in which the objective function is the sum of a non negative convex function and a known quadratic penalty. The algorithm is described and compared with BFGS on some penalized logistic regression and penalized L ^3/2 regression problems.