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[EN] This study empirically validates a technology acceptance model (TAM)-based framework for predicting technology adoption, integrating core constructs perceived usefulness (PU), perceived ease of use (PEOU), and social norms (SN) to examine their influence on behavioural intention and actual usag...

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Detalles Bibliográficos
Autores: Kalumendo, Rodrigue, Vagheni, Paluku Norbert, Pierre, Ntumba Malu, Tandele Rufin, Tabiaki
Tipo de recurso: artículo
Fecha de publicación:2026
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/232182
Acceso en línea:https://riunet.upv.es/handle/10251/232182
Access Level:acceso abierto
Palabra clave:Technology Acceptance Model (TAM)
Perceived usefulness
Perceived ease of use
Social norms
Behavioural intention
Technology adoption
PLS-SEM
Digital literacy
Structural equation modelling
Emerging economies
Descripción
Sumario:[EN] This study empirically validates a technology acceptance model (TAM)-based framework for predicting technology adoption, integrating core constructs perceived usefulness (PU), perceived ease of use (PEOU), and social norms (SN) to examine their influence on behavioural intention and actual usage. Using partial least squares structural equation modelling (PLS-SEM), the measurement model demonstrated strong reliability and validity, while the structural model confirmed all hypothesised relationships.  PU emerged as the most influential predictor of intention, and behavioural intention fully mediated the link between perceptual antecedents and usage. The model explained 42.3% of the variance in intention and 34.3% in usage, with Q² values confirming substantial predictive relevance. These findings contribute to the literature by reaffirming the centrality of intention in technology adoption and by highlighting the complementary role of social norms in shaping user behaviour. The study offers theoretical and practical insights for designing inclusive digital strategies, particularly in emerging economies.