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Using social network data to predict technology acceptance

Li, L., Goethals, F., Baesens, B., Giangreco, A. (2013) Using social network data to predict technology acceptance. In: 2013 International Conference on Information Systems. . ISBN 978-0-615-93383-2. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
https://aisel.aisnet.org/icis2013/proceedings/Rese...

Abstract

In contrast to popular literature on technology acceptance, this research-in-progress paper does not intend to build an explanatory model of technology acceptance but a predictive model so as to predict whether a specific person is likely to accept some technology. We show that the constructs that were identified in the classic UTAUT (such as performance expectancy, effort expectancy and social influence) can be used in a predictive model but that better predictions of system use can be made using knowledge about social networks that exist between people. Both social influence and social selection data are valuable to make predictions. Our approach is tested in the context of a video system which is part of an online learning platform, using a sample of 133 interconnected students.

Item Type: Conference or workshop item (Paper)
Subjects: H Social Sciences
H Social Sciences > H Social Sciences (General)
Divisions: Faculties > Social Sciences > Kent Business School > Marketing
Depositing User: Libo Li
Date Deposited: 12 Dec 2018 12:07 UTC
Last Modified: 30 May 2019 08:33 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70963 (The current URI for this page, for reference purposes)
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