Explaining multidimensional Facebook benefits: A task-technology fit approach

Edgardo R. Bravo, Hugo A. Bayona

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

Facebook has emerged as the most popular Social Network Site (SNS). The literature has studied extensively the factors that explain Facebook usage. Despite this, not equal attention has been devoted to explaining the benefits of this SNS. The few studies have considered impacts as one-dimensional; however, the literature shows that benefits could be conceptualized as a multidimensional construct. Besides, little is known about using the Task-Technology Fit model (TTF) to assess Facebook. In addressing this gap, this study aims to develop and empirically test a model that explains Facebook benefits in a multiple-way using a task-technology fit approach. Data collected from 240 Facebook users, analyzed using partial least squares technique (PLS). The results support the model empirically. This research integrates benefits, use, and task-technology fit into a single model to provide a more comprehensive perspective. Also, a multidimensional view allows us to consider both utilitarian and hedonic benefits as dimensions of value that can spawn greater continued use.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020
EditoresTung X. Bui
EditorialIEEE Computer Society
Páginas4474-4482
Número de páginas9
ISBN (versión digital)9780998133133
EstadoPublicada - 2020
Publicado de forma externa
Evento53rd Annual Hawaii International Conference on System Sciences, HICSS 2020 - Maui, Estados Unidos
Duración: 7 ene. 202010 ene. 2020

Serie de la publicación

NombreProceedings of the Annual Hawaii International Conference on System Sciences
Volumen2020-January
ISSN (versión impresa)1530-1605

Conferencia

Conferencia53rd Annual Hawaii International Conference on System Sciences, HICSS 2020
País/TerritorioEstados Unidos
CiudadMaui
Período7/01/2010/01/20

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