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旅游景区顾客的满意度指数模型

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  • 1. 南京大学城市与资源学系,南京 210093;
    2. 南京航空航天大学经管学院,南京 210016
汪侠 (1974-), 女, 安徽怀远人, 博士生, 主要从事旅游规划研究。E-mail: wangxia128@yahoo.com.cn

收稿日期: 2005-01-10

  修回日期: 2005-05-15

  网络出版日期: 2005-09-25

基金资助

国家自然科学重点基金项目 (40435013)

Tourist Attraction Customer Satisfaction Index Model

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  • 1. Department of Urban and Resources Sciences, Nanjing University, Nanjing 210093, China;
    2. School of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Received date: 2005-01-10

  Revised date: 2005-05-15

  Online published: 2005-09-25

Supported by

Key Project of National Natural Science Foundation of China, No. 40435013

摘要

在对现有国际主流顾客满意度指数模型进行改进的基础上,结合旅游景区的特点,构建了旅游景区顾客满意度指数 (TACSI) 模型。该模型是一个具有因果关系的结构方程模型,包括7个潜变量和23个观测变量,各潜变量之间存在着11种正负相关关系。以桂林象山公园为例进行了实证研究,运用LISREL统计软件对模型的检验结果表明,测量模型中的观测变量对顾客满意度的影响是显著的,测量模型具有较高的目标可靠性;结构模型中各潜变量之间的路径系数与假定基本符合;TACSI模型的整体拟合性能良好。此外,通过对TACSI模型与美国顾客满意度指数 (ACSI) 模型进行比较发现,TACSI模型具有比ACSI模型更强的解释能力,因而更具合理性。

本文引用格式

汪侠, 顾朝林, 梅虎 . 旅游景区顾客的满意度指数模型[J]. 地理学报, 2005 , 60(5) : 807 -816 . DOI: 10.11821/xb200505012

Abstract

Based on the improvement of current international major customer satisfaction index models, and taking the characteristics of tourist attraction into consideration, this paper puts forward a creative model of Tourism Attraction Customer Satisfaction Index (TACSI). It is a structural equation model with casual relationships, which is made up of 7 latent variables and 23 observed variables. There are 11 kinds of positive and negative correlativities among the 7 latent variables. Trunk Hill Park in Guilin is taken as an example in empirical study. By means of LISREL, the test result on TACSI model indicates that the measurement model has high goal dependability since the observed variables have a significant effect on customer satisfaction; the path coefficients between the latent variables are basically consistent with the assumption; and the whole TACSI model has a good goodness of fit. In addition, the authors compare the fitness result of TACSI model with ACSI model, which shows that TACSI model is more feasible because it can explain the variables better than ACSI model.

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