4.6 Article

Crafting a smartphone repurchase decision making process: Do crossMark brand attachment and gender matter?

期刊

TELEMATICS AND INFORMATICS
卷 34, 期 4, 页码 34-56

出版社

ELSEVIER
DOI: 10.1016/j.tele.2016.12.009

关键词

Smartphone repurchase intention; Brand attachment; Gender differences; Partial least squares structural equation; modelling (PLS-SEM); Artificial neural network analysis (ANN); Partial least squares multi-group analysis; (PLS-MGA)

资金

  1. Universiti Tunku Abdul Rahman Research Fund [IPSR/RMC/UTARRF/2015-C2/H01]

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In this fast changing digital era, smartphones users tend to change their smartphones regularly. Therefore, retaining existing consumers has been a challenging task for smartphone manufacturer brands. Given the status quo in smartphone industry and deficiencies in smartphone research, this study proposes a model that integrates Expectation Confirmation Model and brand attachment to shed light on smartphone repurchase decision making process. Besides, gender differences are also accounted for in the model. This study employs a two-staged approach, namely PLS-ANN, in analysing the data collected from 510 existing smartphone owners. Partial least squares structural equation modelling was firstly engaged, and followed by artificial neural network analysis. Besides, a non-parametric partial least squares multi-group analysis has also been conducted to discover gender differences in such decision making process. The results suggest that brand attachment is the most influential and relevant driver of consumers' intention to repurchase smartphones from current brand (measured by continuance intention). Moreover, male consumers are more sensitive to the influence of brand attachment in developing their satisfaction and continuance intention, while female consumers are relying more on perceived usefulness. Interestingly, perceived usefulness does not significantly influence male consumers in continuance intention development. Practical and theoretical implications are subsequently offered. (C) 2016 Elsevier Ltd. All rights reserved.

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