创意团队隐性知识转移绩效影响因素的实证研究

文章采用问卷调研获取一手数据,运用PLS—SEM方法测度了各类因素对创意团队隐性知识转移绩效的影响。研究发现,PLS—SEM方法对观测数据拟合精度较高,在样本数据非正态分布、共线性等情况下仍然稳定。实证结果表明:团队情境、吸收能力、转移意愿、转化能力、媒介丰富度由大到小对创意团队隐性知识转移绩效产生正向影响,而隐性知识特性必须通过对知识源转化能力的显著负影响才能间接影响知识转移绩效。     

偏最小二乘(PartialLeast Square)方法的拟合指标及其在满意度研究中的应用

本文在对顾客满意度模型及PLS方法进行简单介绍的基础上,对PLS的拟合指标,包括共同因子、多元相关平方和冗余,进行了讨论。     

基于PLS-SEM的大学生求学满意度研究

在建立大学生求学满意度指数模型的基础上,运用偏最小二乘的结构方程模型对所建立的模型进行了参数求解和检验.实证研究表明:所建立的大学生求学满意度指数模型拟合度较高,并较好地刻画了各变量之间的系数.     

满意度模型及其在大学生与父母亲子关系研究中的应用

为探索我国大学生群体与父母亲子关系的内在机制,将满意度模型运用到亲子关系这一领域,主要贡献包括三个方面:基于对国内外文献的归纳和提炼,创新性地建立了大学生与父母亲子关系的指标体系;对美国客户满意度模型进行了修改,得到亲子关系满意度模型;以及运用结构方程模型研究亲子关系满意度的内在机制.     

校企合作、企业环境与知识转移绩效——以长三角医疗器械产业为例

本文在长三角地区医疗器械产业问卷调研的基础上,构建了校企合作、企业环境与知识转移绩效间关系的概念模型,并利用结构方程模型(SEM)对理论模型进行了实证研究.研究结果表明:校企合作与企业吸收能力以及企业所处的环境有着密切的关系,企业环境与知识溢出以及企业潜在和实际吸收能力具有正相关关系.最后在理论和实证分析的基础上提出了提高我国校企合作和知识转移绩效的建议.     

误差相关的半变系数模型的估计

本文在误差相关的情况下, 研究半变系数模型的估计, 通过改进PLS估计, 给出了函数系数和常数系数的估计, 证明了估计的渐近正态性; 最后, 模拟研究说明了所提方法的有效性.     

多元成分数据的对数衬度偏最小二乘通径分析模型

本文研究多元成分数据的路径关联关系的建模问题,提出多元成分数据的对数衬度PLS通径分析模型.将中心化对数比变换与PLS通径分析方法相结合建立模型,其主要优势在于:①PLS通径分析模型对数据没有严格的分布假设要求,特别适于成分数据这类分布复杂的数据建模;②成分数据中心化对数比变换后的变量完全多重相关,PLS方法能够有效解决这一问题;③PLS通径分析模型特别适于多元成分数据这类具有层次关系的数据结构的建模,通过结构模型揭示多元成分数据之间的整体性路径关联关系,通过测量模型揭示成分数据与其成分分量之间的构成关系.更重要的是,本文的方法研究遵循成分数据所特有的代数基本理论,推导出模型的成分数据对数衬度隐变量的表达形式,从理论上证明了该建模方法的科学合理性.最后,将本方法用于北京市三次产业的投资结构、GDP结构、就业结构的路径关联关系的分析中,通过实证研究验证模型的可行性和应用价值.     

基于广义最大熵的顾客满意度测评研究

本文提出了应用广义最大熵（Generalized Maximum Entropy,简称 GME）的方法对顾客满意度进行测评,该方法能够处理有限的或者不完全数据.采用了一个应用于美国顾客满意指数（ACSI）的简单模型生成仿真数据,比较GME和PLS两种方法的性能.仿真结果表明,与PLS方法相比,GME方法具有更高的拟合精度和较低的预测误差,在样本数据较少时,表现更为明显.     

运动健身类APP用户持续使用意愿影响因素的研究

移动数字时代的到来,人们更习惯借助手机软件进行随时随地健身.运动健身类APP市场竞争愈发激烈,要想在市场上立足,留住老用户与吸引新用户同样重要.针对APP用户的使用感知和满意度等展开问卷调研,通过构建结构方程模型对用户持续使用意愿的影响因素进行了实证研究.结果表明感知易用性对满意度产生显著影响,感知有用性和满意度均对用户的持续使用意愿产生显著影响.     

基于SEM的气象服务公众满意度测评模型

文章在传统顾客满意度测评模型(ACSI)的核心概念和架构的基础上,结合气象服务独特的特点,对其进行了修改和更新,构建了气象服务公众满意度测评的结构方程模型。并进行了相应的实证研究。通过问卷调查获得数据,运用SPSS和SAS等统计软件进行检验,经过一次修改得到较好的拟合模型,在研究分析的基础上给出相应的结论和建议。     

构成型顾客满意模型的偏最小二乘路径建模及其应用

本文研究了偏最小二乘路径建模在顾客满意模型中的应用,特别是引入了构成型关系的模型。本文首先比较了构成型模型和反映型模型的区别,并详尽阐述了构成型模型的偏最小二乘建模原理,接着构建了电信企业顾客满意度指数模型,并考虑了如何在指数模型中引入构成型外部关系.利用该电信企业的数据,比较分析了构成型模型(顾客期望和质量感知潜变量调整为构成型关系)和反映型模型(所有潜变量均为反映型关系)的实证结果,研究表明在为企业提供改善顾客满意水平的信息上两种模型具有较好的相似性,但是构成型模型能够提供更加稳定的结果,从而验证了顾客满意模型中引入构成型模型的可行性.     

Measuring Customer Satisfaction Using a Collective Preference Disaggregation Model

A new model to assess customer satisfaction is developed through this paper. The proposed model is based on the principles of multicriteria analysis, using ordinal regression techniques. The procedure uses survey's data on customer satisfaction criteria and disaggregates simultaneously all the global satisfaction judgments via a linear programming disaggregation formulation. The model provides collective global and partial satisfaction functions as well as average satisfaction indices. These results sufficiently describe customer behavior and they can be used in the strategic planning of an organization. The implementation of the model in three real world applications is used for illustration and for testing the model's reliability. Finally, several extensions and future research in the area of customer satisfaction analysis are discussed.     

Productivity and customer satisfaction in Swedish pharmacies: A DEA network model

This paper presents a Data Envelopment Analysis (DEA) network model that allows inclusion of customer satisfaction in efficiency and productivity measures. The network consists of a production node and a consumption node and offers flexibility in modelling the production and consumption process where a firm-specific allocation of input resources to production and customer oriented activities is allowed. The proposed model is applied on a sample of Swedish pharmacies with organizational objectives that necessitates a monitoring of efficiency and productivity as well as customer satisfaction. Estimation results from the network model and a direct productivity model (without customer satisfaction) are compared and indicate that the technical efficiency is lower under the network model. The productivity results indicate productivity progress under both models, albeit with a slower rate of change under the network model.     

Modeling customer satisfaction with new product design using a flexible fuzzy regression-data envelopment analysis algorithm

The success of new products depends greatly on customer satisfaction and meeting the customer needs is vital for new product development. By incorporating customer needs in the design and development process, organizations can improve productivity for their new products and reduce the risks associated with new product markets. Hence, design teams require methods to model customer satisfaction when setting the associated product design attributes. Thus, different approaches have been developed for modeling the relationship between customer satisfaction and product design parameters. In this study, 16 well-known fuzzy regression (FR) models are considered to understand the relationship between customer satisfaction and new product design. The design of FR models is based on the 4Ps marketing mix (product, price, place, and promotion) concept in fuzzy environments. A flexible algorithm is then presented based on the index of confidence, error measures, and data envelopment analysis for selecting the best FR model. The applicability and usefulness of the proposed algorithm is demonstrated experimentally based on an actual case study, where the flexible algorithm is employed to predict customer satisfaction with a new product design in the freezer/refrigerator industry.     

Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis

Customer satisfaction is a key dimension driving business outcomes and performance of processes in service and product organizations. Measuring customer satisfaction is typically based on self‐declared or interview‐based questionnaires where users or consumers are asked to express opinions on statements, or satisfaction scales, mapping out various interactions with the service provider or product supplier. The topic has gained importance in recent years with researchers proposing new models and methods for designing, implementing, and analyzing customer satisfaction surveys. This paper builds on material presented in a recent edited book entitled Modern Analysis of Customer Satisfaction Surveys (Kenett and Salini, 2011). The book provides a comprehensive exposition of a variety of models that have all been applied to the same data set by leading experts. These models generate a variety of management insights. Combining models opens up opportunities for further research and applications. Specifically, we suggest that an integrated analysis, aggregating several approaches to survey data analysis, may prove effective in increasing the information quality derived from of a customer satisfaction survey. Copyright © 2011 John Wiley & Sons, Ltd.     

An evaluation approach to engineering design in QFD processes using fuzzy goal programming models

Quality function deployment (QFD) is a product development process used to achieve higher customer satisfaction: the engineering characteristics affecting the product performance are designed to match the customer requirements. From the viewpoint of QFDs designers, product design processes are performed in uncertain environments, and usually more than one goal must be taken into account. Therefore, when dealing with the fuzzy nature in QFD processes, fuzzy approaches are applied to formulate the relationships between customer requirements (CRs) and engineering design requirements (DRs), and among DRs. In addition to customer satisfaction, the cost and technical difficulty of DRs are also considered as the other two goals, and are evaluated in linguistic terms. Fuzzy goal programming models are proposed to determine the fulfillment levels of the DRs. Differing from existing fuzzy goal programming models, the coefficients in the proposed model are also fuzzy in order to expose the fuzziness of the linguistic information. Our model also considers business competition by specifying the minimum fulfillment levels of DRs and the preemptive priorities between goals. The proposed approach can attain the maximal sum of satisfaction degrees of all goals under each confidence degree. A numerical example is used to illustrate the applicability of the approach.     

基于期望视角的感知服务质量与顾客满意度区别研究

从期望出发,比较顾客视角的感知服务质量与满意度的区别。首先对期望概念进行明确界定,借鉴卡诺模型分类方法划分期望类别,基于重要性维度得到期望的三个类别:核心属性期望、重要属性期望和附加属性期望。以餐饮行业为实证研究背景,比较期望视角下的顾客满意度和感知服务质量的区别。发现核心属性期望、重要属性期望对顾客的服务质量评价影响更大,而附加属性期望对顾客的满意度评价影响更大。最后,给出企业对顾客期望、服务质量与顾客满意度的管理意义。     

Product concept and prototype flexibility in manufacturing: Implications for customer satisfaction

A rapidly changing competitive landscape and dynamic customer expectations require manufacturing firms to seek flexibility in product development. Product concept flexibility (i.e., developing design options) and product prototype flexibility (i.e., creating working models) emerge as effective ways to quickly develop new products that meet competitive challenges and satisfy customer demands. Product concept flexibility enables firms to fully explore various product definitions and ideas. Product prototype flexibility allows firms to gather customers’ feedback and investigate design feasibility. Using data from 273 manufacturing firms, this research tests mediating, moderating, and additive models that relate product concept flexibility, product prototype flexibility, and customer satisfaction. The results indicate that firms with high product concept flexibility are more likely to benefit from prototype flexibility than firms with low product concept flexibility, and that product concept flexibility and product prototype flexibility act independently and additively to predict customer satisfaction.