La Adopción del Modelo de Aceptación de Tecnología en el E-commerce con la Inteligencia Artificial como Mediadora
DOI:
https://doi.org/10.5281/zenodo.14511604Palabras clave:
Comercio electrónico, Inteligencia artificial, Facilidad de uso, Utilidad, Modelo de aceptación de tecnologíaResumen
El rápido avance de la tecnología ha cambiado significativamente la forma en que los consumidores enfocan sus hábitos de compra. El volumen mundial del comercio en línea ha experimentado un aumento significativo, en gran parte debido a la pandemia de COVID-19, que ha acelerado el crecimiento del comercio electrónico. Cada vez más, los comerciantes en línea están incorporando tecnología de Inteligencia Artificial de vanguardia en sus plataformas para captar mejor las necesidades de los clientes y enriquecer el viaje de compra. Sin embargo, apenas se ha investigado cómo se adaptan y utilizan los consumidores las tiendas en línea potenciadas por la inteligencia artificial. Este estudio pretende examinar la conexión entre los elementos del Modelo de Aceptación de la Tecnología y el comercio electrónico, con la inteligencia artificial como mediadora en esta relación. Se realizó una encuesta a 352 participantes iraquíes que participan en compras en línea. Para el análisis de los datos se aplicó un modelo de ecuaciones estructurales. Tras establecer el modelo teórico inicial, se formuló y examinó un modelo anidado basado en el TAM. Los resultados mostraron que tanto la facilidad de uso como la utilidad como componentes del TAM influyen positivamente en la probabilidad de adopción de la IA y en su uso continuado entre los compradores en línea. Asimismo, la inteligencia artificial influye positivamente en la adopción del comercio electrónico por parte de los clientes. Por último, la inteligencia artificial desempeña un papel mediador entre el Modelo de Aceptación de la Tecnología y el comercio electrónico. Estos resultados ofrecen información valiosa para los minoristas en línea que buscan mejorar la adopción de la IA por parte de los clientes.
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Derechos de autor 2024 Aram Massoudi, Muslim N. Zaidan, Azwar Qasim Agha
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
