中国高等教育顾客满意度指数模型及其应用

教育事业为公共服务的重要领域,“组织依存于顾客”也同样适用于高等学校,高校应注重来自顾客的信息,注重学生的满意度水平。本文建立了中国高等教育顾客满意度指数模型(CHE-CSI),并对沈阳市6所高等学校的学生满意度进行了测评。在分析方法上,本文应用了SPSS13.0和结构方程模型分析软件LISREL,对影响高等学校顾客满意度的重要因素进行了分析,得出6所高校的顾客满意度指数得分,进而提出了提升中国高等教育顾客(学生)满意度的改进措施。     

基于ACSI模型的物流企业顾客满意测评模型的建立

首先对顾客满意的相关理论进行了阐述,并且对顾客满意度指数模型及结构方程等理论进行了分析,在上述理论分析的基础上,结合物流企业的实际特点,初步构建了基于ACSI模型的物流企业顾客满意测评模型,然后以物流企业顾客为调查样本,运用偏最小二乘法,通过Visualpls1.04b1软件对物流企业顾客满意测评模型进行了实证研究,进一步验证了该模型。     

我国远程开放教育顾客满意度测评体系构建

顾客满意度指数是近年来许多国家和地区积极开展研究和采用的一种新的经济指标.在现代远程开放教育中引入顾客满意,具有重要的意义.继承美国顾客满意度.ACSI模型的一些核心概念和架构,同时吸收其它模型的一些创新之处,在8个结构变量的基础上,通过结构调整和综合因素分析,给出顾客满意度测评的模型架构、指标体系和计算方法,建构具有广泛适用性的我国远程开放教育顾客满意指标(ODE-CSI)模型,以测量我国远程开放教育的整体质量的评价效果.     

基于结构方程模型的高职学生短期岗位实习满意度实证研究

基于美国顾客满意度指数模型、中国高等教育顾客满意度指数模型等相关模型,结合我国职业教育的特点,构建了学生短期岗位实习满意度概念模型及研究假设。研究共收集了221名学生的调查数据,并通过结构方程模型进行检验。结果表明:在学生短期岗位实习时,企业对实习的服务支持、实习的服务支持对学生的实习感知、实习感知对实习体验、实习体验对实习满意、实习满意对实习意愿等均有极显著的正面影响。     

基于学生满意度的德育评价模型的开发与应用

高校德育工作急需系统深入的量化评价方法与工具。从高校的研究生群体视角开展实证研究,引入顾客满意理论对高校研究生德育工作进行评价,以顾客满意指数模型与SERVQUAL模型为基础,应用结构方程模型,调研分析深圳地区五所高等院校以及香港地区四所大学,开发了基于学生满意度的德育评价模型,探讨了深港高校德育质量、感知价值、学生满意和行为意向之间的关系,并设计了测量基于学生满意度的德育评价量表。     

可分离变量微分方程的人口总量预测模型

利用我国大陆1949²010人口统计数据,对指数增长模型(马尔萨斯人口模型)和阻滞增长模型(Logistic模型)做出检验,并用它预测20112010人口统计数据,对指数增长模型(马尔萨斯人口模型)和阻滞增长模型(Logistic模型)做出检验,并用它预测2011²080年我国大陆人口.     

公路行业职业教育质量评价模型研究

采用结构方程模型方法构建了以顾客为评价主体的"公路系统应用型人才培养质量评价模型",模型由毕业生版和企业版组成,本文主要介绍了企业版模型。该模型较全面地覆盖了顾客认知的培养过程及培养效果;以外部顾客为评价主体,一定程度克服了人为的主观性和随意性;变量体系凸显了行业的职业特点,适用于公路系统职业教育的培养质量评价。     

高等教育服务的顾客满意度指数模型研究

在借鉴国内外高等教育顾客满意度测评的基础上,结合我国高等学校的具体情况,综合各方面因素,作者尝试提出了一个高等教育服务的顾客满意度指数模型。通过对河南省六所高校所做的调查进行了验证研究,并在研究分析的基础上给出了相应的结论及建议。     

基于顾客满意的高等教育服务模型

高等教育的产出是指高等教育服务。高等教育服务的的基本特性是无形性、同时性、差异性及产品的双重性。高等教育服务质量的高低是由接受高等教育服务的顾客对高等教育服务质量的评价所决定的。由于高等教育服务的顾客满意的主体包括外部顾客(学生、家庭、社会)和内部顾客(高校的教职员工),高等教育服务模型要以内部顾客和外部顾客满意为基础,建立起高等教育服务供需双方的良性关系。     

攀枝花北京华联顾客满意度实证研究

我国零售业企业间的竞争日趋激烈,维护并提升顾客的满意度对企业取得竞争优势、吸引消费者重复购买、培育消费者忠诚至关重要.文章构建了大型超市顾客满意度指数评价模型,并以攀枝花北京华联的顾客为研究对象采用结构方程模型进行模型验证.并检验了文章所提出的顾客满意度影响因素的假设,据此提出了针对攀枝花北京华联及中国的大型连锁超市提高顾客满意度的对策和建议.     

基于结构健康监测的润扬悬索桥有限元模型修正与验证

采用大型有限元分析软件ANSYS建立了润扬悬索桥的三维有限元模型并对其进行了自振特性分析,同时计算了各种工况下大桥的应力及位移响应.基于灵敏度的物理意义以及罚函数的思想,提出了一种结构有限元模型修正的新方法.该方法仍以自振特性为目标函数,以结构设计参数为待修正参数,但设计参数的上下限根据测试所得静力响应值和理论值的对比以及工程经验来确定,因此静力响应可用于验证修正后的有限元模型.采用结构健康监测系统数据及提出的方法对大桥有限元模型进行了修正与验证,得到了能够较好地反映大桥整体动静力性能的有限元基准模型,为润扬悬索桥的健康监测和损伤预警提供了研究基础.     

A Simulation Study of Polychoric Instrumental Variable Estimation in Structural Equation Models

Data collected from questionnaires are often in ordinal scale. Unweighted least squares (ULS), diagonally weighted least squares (DWLS) and normal-theory maximum likelihood (ML) are commonly used methods to fit structural equation models. Consistency of these estimators demands no structural misspecification. In this article, we conduct a simulation study to compare the equation-by-equation polychoric instrumental variable (PIV) estimation with ULS, DWLS, and ML. Accuracy of PIV for the correctly specified model and robustness of PIV for misspecified models are investigated through a confirmatory factor analysis (CFA) model and a structural equation model with ordinal indicators. The effects of sample size and nonnormality of the underlying continuous variables are also examined. The simulation results show that PIV produces robust factor loading estimates in the CFA model and in structural equation models. PIV also produces robust path coefficient estimates in the model where valid instruments are used. However, robustness highly depends on the validity of instruments.     

Robustness Conditions for MIIV-2SLS When the Latent Variable or Measurement Model is Structurally Misspecified

Most researchers acknowledge that virtually all structural equation models (SEMs) are approximations due to violating distributional assumptions and structural misspecifications. There is a large literature on the unmet distributional assumptions, but much less on structural misspecifications. In this paper, we examine the robustness to structural misspecification of the model implied instrumental variable, two-stage least square (MIIV-2SLS) estimator of SEMs. We introduce two types of robustness: robust-unchanged and robust-consistent. We develop new robustness analytic conditions for MIIV-2SLS and illustrate these with hypothetical models, simulated data, and an empirical example. Our conditions enable a researcher to know whether, for example, a structural misspecification in the latent variable model influences the MIIV-2SLS estimator for measurement model equations and vice versa. Similarly, we establish robustness conditions for correlated errors. The new robustness conditions provide guidance on the types of structural misspecifications that affect parameter estimates and they assist in diagnosing the source of detected problems with MIIVs.     

Bayesian Data-Model Fit Assessment for Structural Equation Modeling

Bayesian approaches to modeling are receiving an increasing amount of attention in the areas of model construction and estimation in factor analysis, structural equation modeling (SEM), and related latent variable models. However, model diagnostics and model criticism remain relatively understudied aspects of Bayesian SEM. This article describes and illustrates key features of Bayesian approaches to model diagnostics and assessing data–model fit of structural equation models, discussing their merits relative to traditional procedures.     

Bayesian Estimation of the True Score Multitrait–Multimethod Model With a Split-Ballot Design

This article examines whether Bayesian estimation with minimally informed prior distributions can alleviate the estimation problems often encountered with fitting the true score multitrait–multimethod structural equation model with split-ballot data. In particular, the true score multitrait–multimethod structural equation model encounters an empirical underidentification when (a) latent variable correlations are homogenous, and (b) fitted to data from a 2-group split-ballot design; an understudied case of empirical underidentification due to a planned missingness (i.e., split-ballot) design. A Monte Carlo simulation and 3 empirical examples showed that Bayesian estimation performs better than maximum likelihood (ML) estimation. Therefore, we suggest using Bayesian estimation with minimally informative prior distributions when estimating the true score multitrait–multimethod structural equation model with split-ballot data. Furthermore, given the increase in planned missingness designs in psychological research, we also suggest using Bayesian estimation as a potential alternative to ML estimation for analyses using data from planned missingness designs.     

托幼服务治理模式国际比较及中国路径选择

在后工业化、老龄化、全球化等背景下,增加托幼服务供给成为全球性的政策选择。经过几十年的发展,西方发达国家的托幼服务治理模式存在显著的制度差异,形成了三种典型的托幼服务治理模式:托幼整合模式(以瑞典为例)、托幼分离的双轨模式(以法国为例)和托幼关系复杂的多元模式(以美国为例)。不同治理模式的形成和变革受制于其所处的社会、经济和制度环境,在发展中也面临着不同的挑战。新时期我国建构托幼服务治理体系应该采用分阶段策略,建立合理的成本分担机制,鼓励地方实践的多元化,并最终完成托幼服务的整合。     

Student Models of Instructional Design

Mental models are one way that humans represent knowledge (Markman, 1999). Instructional design (ID) is a conceptual model for developing instruction and typically includes analysis, design, development, implementation, and evaluation (i.e., ADDIE model). ID, however, has been viewed differently by practicing teachers and instructional designers (Kennedy, 1994). In a graduate ID course students constructed their own ID models. This study analyzed student models for (a) what ADDIE components were included (by teacher, nonteacher), and (b) model structural characteristics (by teacher, nonteacher). Participants included 178 students in 12 deliveries of a master's level ID course (115 teachers, 63 nonteachers). Our conceptual ID model is presented, and the ID model task is described. Students most frequently represented design, followed by program evaluation, needs assessment, development, and implementation. In terms of structural characteristics, 76 models were characterized as metaphoric, 61 dynamic, and 35 sequential. Three interrelated conclusions and implications for ID learning are offered. Susan G. Magliaro [sumags@vt.edu] is Director of the School of Education and the Center for Teacher Education at Virginia Tech. Neal Shambaugh is Assistant Professor of Instructional Design & Technology in the College of Human Resources & Education at West Virginia University. An erratum to this article is available at .     

Evaluation of Structural Relationships in Autoregressive Cross-Lagged Models Under Longitudinal Approximate Invariance:A Bayesian Analysis

To infer longitudinal relationships among latent factors, traditional analyses assume that the measurement model is invariant across measurement occasions. Alternative to placing cross-occasion equality constraints on parameters, approximate measurement invariance (MI) can be analyzed by specifying informative priors on parameter differences between occasions. This study evaluated the estimation of structural coefficients in multiple-indicator autoregressive cross-lagged models under various conditions of approximate MI using Bayesian structural equation modeling. Design factors included factor structures, conditions of non-invariance, sizes of structural coefficients, and sample sizes. Models were analyzed using two sets of small-variance priors on select model parameters. Results showed that autoregressive coefficient estimates were more accurate for the mixed pattern than the decreasing pattern of non-invariance. When a model included cross-loadings, an interaction was found between the cross-lagged estimates and the non-invariance conditions. Implications of findings and future research directions are discussed.     

Quality evaluation and its application to surface water ecosystem based on maximum flux principle

Based on the maximum flux principle(MFP),a water quality evaluation model for surface water ecosystem is presented by using self-organization map(SOM) neural network simulation algorithm from the aspect of systematic structural evolution.This evaluation model is applied to the case of surface water ecosystem in Xindu District of Chengdu City in China.The values reflecting the water quality of five cross-sections of the system at different developing stages are obtained,with stable values of 1.438,2.952,1.86...