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Utilizing the Push-Pull-Mooring-Habit framework to explore users’ intention to switch from offline to online real-person English learning platform

Bibliographic Data

ID12420508
AuthorsYu-Hsin Chen (0000-0001-9073-2819), Yu‐hsin Chen (0000-0002-7829-4008, National Taipei University of Technology, corresponding author), Ching‐Jui Keng (0000-0002-5002-695X, National Taipei University of Technology), Ching-Jui Keng
Year2018
Volume29
Issue1
Pages167-193
Publication date2018-12-03
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternet Research (JOURNAL)
Journal identifiersISSN: 1066-2243 • E-ISSN: 2054-5657
PublisherEmerald Publishing Limited (PUBLISHER • GB)
DOI10.1108/intr-09-2017-0343
OpenAlexW2902244215
LanguageEN
Citations received26
References cited83

Purpose The purpose of this paper is to develop an extended Push-Pull-Mooring-Habit (PPMH) framework in order to better understand users’ intention of switching from offline to an online real-person English learning platform service. Design/methodology/approach Based on 301 valid responses collected from an online survey questionnaire, structural equation modeling was employed to examine the research model. Findings The causal model was validated using SmartPLS 3.0, and all study hypotheses were supported. The results show that push effects (learning convenience, service quality and perceived price), pull effects (e-learning motivation, perceived usefulness), mooring effects (learning engagement, switching cost and social presences) and habit effects (relationship inertia) all significantly influence users’ switching intentions from offline to an online real-person English learning platform. Practical implications The findings should help online English learning service providers and marketers to understand the intention of offline English learning users to switch to an online real-person English learning platform, and develop related theories, services and regulations. Originality/value The present study extends the prior research of an online real-person English learning platform by providing PPMH as the general framework and demonstrating its efficacy in explaining user switching intentions

Business · Habit · Knowledge management · Machine learning · Online and offline · Originality · Service (business · Structural equation modeling · Computer Science · Customer Service Quality and Loyalty · Digital Marketing and Social Media · Psychology · Social Psychology · Technology Adoption and User Behaviour · Marketing

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Unique citing works26
Citations per year4,33
Citation span2020 - 2026 (7)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 26

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