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The Analysis of Antecedents of Customer Loyalty in the Australian Mobile Telecommunication Market

H. Bhatti,A. Abareshi,S. Pittayachawan

Published 2017 in International Conference on e-Business

ABSTRACT

Marketing mix factors such as price product value, facilitating conditions, and social influence; and factors such as customer satisfaction, customer experience, habit, hedonic motivation, performance expectancy, effort expectancy are the major antecedents of customer loyalty. As, loyal customers may buy more services and have a positive word-of-mouth effect. Moreover, it is evident from previous literature that the cost of selling service to new customers is much higher than the cost of retaining existing customers. Furthermore, it is evident fact from telecommunication industry ombudsman Australia reports that companies are still losing customers at a formidable rate. In this context, the main aim of this paper is to examine the relationships between these factors and customer loyalty, and the relationships among these factors in the Australian mobile service scenario. Data for this study was obtained from 1,985 mobile phone users in Australia via online questionnaire using a marketing company Research Now. The data was analysed by structural equation modelling (SEM) to test all the relationships between variables in the model. The findings of this research focus on the measurement model fit part only. The analysis results showed that perceived customer experience is a necessary but not sufficient condition for customer loyalty. In order to generalize the findings from this research, this research model should be used in different service industries with different geographic samples. The contribution of this research is to model all the relationships between customer loyalty and its antecedents, and to test these relationships simultaneously. In this paper, the effects of all the factors on customer loyalty are tested simultaneously via structural equation modelling (SEM) and this paper only focuses on model fit.

PUBLICATION RECORD

  • Publication year

    2017

  • Venue

    International Conference on e-Business

  • Publication date

    Unknown publication date

  • Fields of study

    Business, Economics, Computer Science

  • Identifiers
    DOI 10.5220/0006419100910099
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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