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Structural equation modeling and artificial neural networks approach to predict continued use of mobile taxi booking apps: the mediating role of hedonic motivation

Abdul Waheed Siyal (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Hongzhuan Chen (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Gang Chen (School of Management, Fudan University, Shanghai, China)
Muhammad Mujahid Memon (Sukkur IBA, Sukkur, Pakistan)
Zainab Binte (The University of Lahore, Lahore, Pakistan)

Data Technologies and Applications

ISSN: 2514-9288

Article publication date: 15 December 2020

Issue publication date: 21 June 2021

463

Abstract

Purpose

Mobile taxi booking apps (MTB) have revolutionalized the transportation industry. As taxis can be hired via smartphones, irrespective of any time or place, the business platform for taxi service has completely changed. Now customers are saved from the hassle of going to the designated taxi stands or waiting along the roadside. But, the long-term sustainability of this service depends on its continued use. Therefore, this study aims to explore factors that hedonically incline people toward continuance of MTB. To achieve the purpose, the unified theory of acceptance and use of technology (UTAUT) was extended with mediation effects of hedonic motivation.

Design/methodology/approach

The data were collected from existing users of MTB and analyzed through structural equation modeling and revalidated via artificial neural networks.

Findings

The statistical results show that the main factors of UTAUT substantially create hedonic motivation to use the apps and significantly mediate their effects on behavioral intention to continue using MTB. However, mediation between social influence and continuity intent was not statistically supported. The findings represent important contributions to the extended UTAUT.

Practical implications

This study adds value to the theoretical horizon and also presents M-taxi companies with useful and pertinent plans for efficient designing and effective implementation of MTB. Moreover, limitations and suggestions for future researchers are also discussed.

Originality/value

This study extends UTAUT with the mediating role of hedonic motivation to predict continued use of MTB, which further initiates the applicability of UTAUT in a new setting and a new perspective (post adoption). This, in turn, significantly expands theory by using hedonic motivation as an important attribute that could mediate impact of all main antecedents to shape customers loyalty toward system use.

Keywords

Acknowledgements

This research was supported in part by Planning Funds for Humanities and Social Sciences; Ministry of Education of China under Grant No. 18YJA630008, and in part by National Social Science Foundation of China (No. 19BJY094).

Citation

Siyal, A.W., Chen, H., Chen, G., Memon, M.M. and Binte, Z. (2021), "Structural equation modeling and artificial neural networks approach to predict continued use of mobile taxi booking apps: the mediating role of hedonic motivation", Data Technologies and Applications, Vol. 55 No. 3, pp. 372-399. https://doi.org/10.1108/DTA-03-2020-0066

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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