Title
Explaining multidimensional Facebook benefits: A task-technology fit approach
Date Issued
01 January 2020
Access level
metadata only access
Resource Type
conference paper
Author(s)
Publisher(s)
IEEE Computer Society
Abstract
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.
Start page
4474
End page
4482
Volume
2020-January
Language
English
OCDE Knowledge area
Ciencias de la computación
Scopus EID
2-s2.0-85108178802
ISBN
9780998133133
Source
Proceedings of the Annual Hawai International Conference on System Sciences
Resource of which it is part
Proceedings of the Annual Hawai International Conference on System Sciences
ISSN of the container
15301605
ISBN of the container
9780998133133
Conference
Proceedings of the Annual Hawaii International Conference on System Sciences
Sources of information:
Directorio de Producción Científica
Scopus