Modeling the predictors of mobile health adoption by Rohingya Refugees in Bangladesh: An extension of UTAUT2 using combined SEM-Neural network approach

Barua, Zapan; Barua, Adita

doi:10.1016/j.jmh.2023.100201

Cited by 3 publications

(1 citation statement)

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“…PLS-SEM is traditionally used for exploring linear relationships between constructs, while ANN is preferred for identifying nonlinear connections among variables [94]. Although SEM is commonly used in studying causal relationships, its integration with ANN is limited [95]. SEM's limitation lies in its ability to examine only linear relationships, potentially oversimplifying human decision-making processes.…”

Section: Artificial Neural Network (Ann) Modelmentioning

confidence: 99%

Unveiling the adoption of metaverse technology in Bangkok metropolitan areas: A UTAUT2 perspective with social media marketing and consumer engagement

Sritong,

Sawangproh,

Teangsompong

2024

PLoS ONE

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As the metaverse emerges as a transformative digital realm, its adoption and integration into various aspects of society are subjects of increasing scholarly and practical interest. This research investigated the factors influencing the intention to use metaverse technology (IU) in Bangkok metropolitan areas, with a particular focus on the extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, alongside the role of social media marketing (SMM) and consumer engagement (CE). To verify behavioral intention, gender, age, and experience are proposed as moderating factors affecting the constructs on individuals’ behavioral intention of metaverse technology usage. The study collected data from 403 Thai internet users living in Bangkok and its surrounding areas using an online questionnaire. Subsequently, the PLS-SEM method was employed to validate the research model’s robustness and reliability. Structural model analysis revealed significant relationships among constructs, highlighting SMM’s direct influence on UTAUT2 (β = 0.787) and CE (β = 0.211). Serial mediation analyzes demonstrated a fully mediating role of SMM influencing UI through CE (β = 0.572) and UTAUT2 (β = 0.306). Moderation analyzes revealed the association between SMM and IU, mediated through UTAUT2 and CE, is moderated by age and experience. Additionally, the integration of PLS-SEM and artificial neural network (ANN) models underscored the accuracy and predictive power of the proposed framework. The findings of this study not only contribute to academic literature but also offer practical implications for marketers aiming to navigate the metaverse landscape effectively. They emphasize the pivotal role of UTAUT2 constructs and the subtle interplay between SMM, CE, and IU in shaping successful marketing strategies.

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Section: Artificial Neural Network (Ann) Modelmentioning

confidence: 99%