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What drives customer satisfaction and word of mouth in mobile commerce services? A UTAUT2-based analytical approach

Zoran Kalinić (Faculty of Economics, University of Kragujevac, Kragujevac, Serbia)
Veljko Marinković (Faculty of Economics, University of Kragujevac, Kragujevac, Serbia)
Aleksandar Djordjevic (Faculty of Economics, University of Belgrade, Belgrade, Serbia)
Francisco Liebana-Cabanillas (Department of Marketing and Market Research, University of Granada, Granada, Spain)

Journal of Enterprise Information Management

ISSN: 1741-0398

Article publication date: 28 October 2019

Issue publication date: 22 January 2020

2550

Abstract

Purpose

The purpose of this paper, which is based on the UTAUT2 model, is to develop and evaluate a predictive model of customer satisfaction related to mobile commerce (m-commerce) and the willingness to recommend this service to others.

Design/methodology/approach

The study was conducted based on a sample of 402 respondents. Confirmative factor analysis was used to evaluate the validity of the model, while structural equation modeling (SEM) was used to test the hypotheses. Finally, artificial neural networks were used to rank the influence of the significant predictors obtained by SEM.

Findings

Trust was found to be the most significant driver of customer satisfaction, followed by performance expectancy and perceived value. In addition, affective commitment and satisfaction were identified as the strongest predictors of word of mouth (WOM).

Originality/value

The originality/value of the paper lies in the establishment of the connection between the independent variables of the UTAUT 2 model – trust, satisfaction, affective and continence commitment and WOM. Additionally, it is one of a small number of studies investigating customer commitments and their influence on WOM in m-commerce.

Keywords

Citation

Kalinić, Z., Marinković, V., Djordjevic, A. and Liebana-Cabanillas, F. (2020), "What drives customer satisfaction and word of mouth in mobile commerce services? A UTAUT2-based analytical approach", Journal of Enterprise Information Management, Vol. 33 No. 1, pp. 71-94. https://doi.org/10.1108/JEIM-05-2019-0136

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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