Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/15264
Title: Analysis of Factors that Influence Customers' Willingness to Leave Big Data Digital Footprints on Social Media: A Systematic Review of Literature
Authors: Muhammad, SS
Dey, BL
Weerakkody, V
Keywords: big data digital footprint;social media;privacy and security;technology;personal behaviour;social influence
Issue Date: 15-Oct-2017
Citation: Muhammad, S.S., Dey, B.L. and Weerakkody, V. (2018) 'Analysis of Factors that Influence Customers’ Willingness to Leave Big Data Digital Footprints on Social Media: A Systematic Review of Literature', Information Systems Frontiers, 20, pp. 559 - 576. doi: 10.1007/s10796-017-9802-y.
Abstract: Big data has been discussed extensively in existing scholarly works but scant consideration is given to customers’ willingness to generate and leave big data digital footprints on social media, especially in the light of the profusely debated issue of privacy and security. The current paper endeavours to address this gap in the literature by developing a conceptual framework. In doing so, this paper conducts a systematic review of extant literature from 2002 to 2017 to identify and analyse the underlying factors that influence customers’ willingness to leave digital footprints on social media. The findings of this review reveal that personal behaviour (intrinsic psychological dispositions), technological factors (relative advantage and convenience), social influence (social interaction, social ties and social support) and privacy and security (risk, control and trust) are the key factors that influence customers’ willingness to generate and leave big data digital footprints on social media. The conceptual framework presented in this paper advances the scholarship of technology adoption and use and provides useful direction for future empirical research for both academics and practitioners.
URI: https://bura.brunel.ac.uk/handle/2438/15264
DOI: https://doi.org/10.1007/s10796-017-9802-y
ISSN: 1387-3326
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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Fulltext.pdfThis is a pre-copyedited, author-produced version of an article accepted for publication in Information Systems Frontiers following peer review. The final authenticated version is available online at https://doi.org/10.1007/s10796-017-9802-y.445.61 kBAdobe PDFView/Open


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