n South African Journal of Libraries and Information Science - A theoretical model to predict customer satisfaction in relation to service quality in selected university libraries in Sri Lanka
|Article Title||A theoretical model to predict customer satisfaction in relation to service quality in selected university libraries in Sri Lanka|
|© Publisher:||Library and Information Association of South Africa (LIASA)|
|Journal||South African Journal of Libraries and Information Science|
|Author||Chaminda Jayasundara, Patrick Ngulube and Mabel K. Minishi-Majanja|
|Publication Date||Jan 2009|
|Pages||179 - 194|
|Keyword(s)||Disconfirmation, Expectancy disconfirmation, Models, Performance-only, Service quality in academic libraries and User satisfaction|
University library administrators in Sri Lanka have begun to search for alternative ways to satisfy their clientele on the basis of service quality. This article aims at providing a theoretical model to facilitate the identification of service quality attributes and domains that may be used to predict customer satisfaction from a service quality perspective. The effectiveness of existing service quality models such as LibQUAL, SERVQUAL and SERVPREF have been questioned. In that regard, this study developed a theoretical model for academic libraries in Sri Lanka based on the disconfirmation and performance-only paradigms. These perspectives were considered by researchers to be the core mechanism to develop service quality / customer satisfaction models. The attributes and domain identification of service quality was carried out with a stratified sample of 263 participants selected from postgraduate and undergraduate students and academic staff members from the faculties of Arts in four universities in Sri Lanka. The study established that responsiveness, supportiveness, building environment, collection and access, furniture and facilities, technology, Web services and service delivery were quality domains which can be used to predict customer satisfaction. The theoretical model is unique in its domain structure compared to the existing models. The model needs to be statistically tested to make it valid and parsimonious.
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