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Taxi within a grab? A gender-invariant model of mobile taxi adoption
Journal
Industrial Management & Data Systems
ISSN
0263-5577
Date Issued
2020-12-17
Author(s)
Keng-Boon Ooi
Fang-Ee Foo
Garry Wei-Han Tan
DOI
https://doi.org/10.1108/IMDS-04-2020-0239
Abstract
Purpose
The paper intends to examine mobile taxi (m-taxi) adoption, so as to close the gap in the current literature and clarify the behaviour of users by synthesising technological factors that are related to the characteristics of m-taxi applications with non-technological factors that are associated with the psychological characteristics of customers. The moderating effects of gender were also tested.
Design/methodology/approach
A self-administered questionnaire was adopted for data collection with 415 useable responses. The theoretical lens was tested via partial least squares-structural equation modelling. Additionally, state-of-the-art techniques such as permutation and multigroup analysis were applied.
Findings
Results indicate that social pressure, technology anxiety, effort expectancy, performance expectancy, and service and system quality are not significantly related to behavioural intention. Also, findings show no significant differences among gender in this study, which suggests that the model is invariant across gender groups.
Originality/value
This study provides a novel insight by taking a broader perspective of ride-hailing terminology by considering both taxis and private vehicles.
The paper intends to examine mobile taxi (m-taxi) adoption, so as to close the gap in the current literature and clarify the behaviour of users by synthesising technological factors that are related to the characteristics of m-taxi applications with non-technological factors that are associated with the psychological characteristics of customers. The moderating effects of gender were also tested.
Design/methodology/approach
A self-administered questionnaire was adopted for data collection with 415 useable responses. The theoretical lens was tested via partial least squares-structural equation modelling. Additionally, state-of-the-art techniques such as permutation and multigroup analysis were applied.
Findings
Results indicate that social pressure, technology anxiety, effort expectancy, performance expectancy, and service and system quality are not significantly related to behavioural intention. Also, findings show no significant differences among gender in this study, which suggests that the model is invariant across gender groups.
Originality/value
This study provides a novel insight by taking a broader perspective of ride-hailing terminology by considering both taxis and private vehicles.
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