Explaining multidimensional Facebook benefits: A task-technology fit approach

Edgardo R. Bravo; Hugo A. Bayona

doi:10.24251/hicss.2020.547

Explaining multidimensional Facebook benefits: A task-technology fit approach

Edgardo R. Bravo, Hugo A. Bayona

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

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 tasktechnology 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.

Original language	English
Title of host publication	Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020
Editors	Tung X. Bui
Place of Publication	Honolulu
Pages	4474-4482
DOIs	https://doi.org/10.24251/hicss.2020.547
State	Published - 7 Jan 2020
Event	Hawaii International Conference on System Sciences - , United States Duration: 7 Jan 2020 → 10 Jan 2020 Conference number: 53 https://aisel.aisnet.org/hicss-53/

Conference

Conference	Hawaii International Conference on System Sciences
Abbreviated title	HICSS
Country/Territory	United States
Period	7/01/20 → 10/01/20
Internet address	https://aisel.aisnet.org/hicss-53/

Bibliographical note

"Proceedings of the 53rd Hawaii International Conference on System Sciences | 2020".
ISBN: 978-0-9981331-3-3

Publisher Copyright:
© 2020 IEEE Computer Society. All rights reserved.

Keywords

Facbook
Task-technology-Fit
Technological innovations
Communication

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10.24251/hicss.2020.547License: CC BY-NC-ND

http://hdl.handle.net/10125/64289License: CC BY-NC-ND

Cite this

@inproceedings{df3303e0a7284a0cb1c2a9d39aaae234,

title = "Explaining multidimensional Facebook benefits: A task-technology fit approach",

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 tasktechnology 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.",

keywords = "Facbook, Task-technology-Fit, Technological innovations, Communication",

author = "Bravo, {Edgardo R.} and Bayona, {Hugo A.}",

note = "{"}Proceedings of the 53rd Hawaii International Conference on System Sciences | 2020{"}. ISBN: 978-0-9981331-3-3 Publisher Copyright: {\textcopyright} 2020 IEEE Computer Society. All rights reserved.; Hawaii International Conference on System Sciences , HICSS ; Conference date: 07-01-2020 Through 10-01-2020",

year = "2020",

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doi = "10.24251/hicss.2020.547",

language = "English",

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T2 - Hawaii International Conference on System Sciences

AU - Bravo, Edgardo R.

AU - Bayona, Hugo A.

N1 - Conference code: 53

PY - 2020/1/7

Y1 - 2020/1/7

N2 - 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 tasktechnology 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.

AB - 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 tasktechnology 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.

KW - Facbook

KW - Task-technology-Fit

KW - Technological innovations

KW - Communication

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M3 - Conference contribution

SN - 978-0-9981331-3-3

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BT - Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020

A2 - Bui, Tung X.

CY - Honolulu

Y2 - 7 January 2020 through 10 January 2020

ER -

Explaining multidimensional Facebook benefits: A task-technology fit approach

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Keywords

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