期刊
INFORMATION SYSTEMS FRONTIERS
卷 6, 期 4, 页码 325-340出版社
SPRINGER
DOI: 10.1023/B:ISFI.0000046375.72726.67
关键词
service quality; customer value; customer satisfaction; behavioral intentions; moderating effect; telecommunication industry; China
Service quality, customer satisfaction and customer value have become the priority of both manufacturers and service provider in the increasingly intensified competition for customers in today's customer-centered era. However, findings regarding service quality, customer satisfaction and customer value are rather divergent and related studies are fragmented, especially for the complicated interrelationships among them. Thus, less is known about the relative impacts of quality-related factors on customer value and customer satisfaction up to now and the moderating role of customer value in the relationship between service quality and customer satisfaction has been neglected. Further, it is very difficult to find related studies, supported by evidence, that focus on service quality, customer satisfaction and customer value, and their influences on customer behavior intentions in the telecommunication industry. In this paper, much attention is paid to the measurement model of service quality in China's mobile communication market based on the well-known SERVQUAL model, but with reasonable modification on the basis of focus group discussions and expert opinions to reflect the specific industry attributes and the special culture of China. By taking a disaggregated approach, the key drivers of service quality, customer value and customer satisfaction are first identified and the impact of customer perceived sacrifice on customer value is emphasized. Then attention is given to the systematic study of the dynamic relationships among them, especially the moderating effect of customer value on the relationship between service quality and customer satisfaction, which is followed by the examination of their influences on behavior intentions of customers. Results are based on the development of structural equation models using Partial Least Square technique.
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