Skip to main content

Research Repository

Advanced Search

Subjectivities in motion: Dichotomies in consumer engagements with self-tracking technologies

Zakariah, A.; Hosany, S.; Cappellini, B.

Subjectivities in motion: Dichotomies in consumer engagements with self-tracking technologies Thumbnail


Authors

A. Zakariah

S. Hosany



Abstract

With the rise of self-tracking technologies (STT), self-quantification has become a popular digital consumption phenomenon. Despite recent academic interests, self-tracking practices remain poorly understood, in particular, little is known on how consumers engage with STT and how such behavioural trends produce new subjectivities. This paper adopts a Foucauldian perspective of self-surveillance to explore: how do subjectivities emerge from consumer interactions and engagements with self-tracking technologies? Data were collected from twenty participants using an ethnographic research design over six months consisting of semi-structured interviews and participant observation. The findings reveal two sets of dichotomies in the way consumers engage with STT, categorised as: ‘health and indulgence’ and ‘labour and leisure’. Through these dichotomies of self-surveillance, four subjectivities emerged: ‘redemptive self’, ‘awardee’, ‘loyal’ and ‘innovator’. Our study presents subjectivities as a continual process of (re)configuration of the self, as consumers move from one dichotomy to another. At the practical level, our findings offer novel approaches to segment consumers by reviewing the different contours of consumer behaviour in their interactions with STT.

Citation

Zakariah, A., Hosany, S., & Cappellini, B. (2021). Subjectivities in motion: Dichotomies in consumer engagements with self-tracking technologies. Computers in Human Behavior, 118, Article 106699. https://doi.org/10.1016/j.chb.2021.106699

Journal Article Type Article
Acceptance Date Jan 10, 2021
Online Publication Date Jan 12, 2021
Publication Date 2021-05
Deposit Date Mar 3, 2021
Publicly Available Date Mar 29, 2024
Journal Computers in Human Behavior
Print ISSN 0747-5632
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 118
Article Number 106699
DOI https://doi.org/10.1016/j.chb.2021.106699
Public URL https://durham-repository.worktribe.com/output/1251548

Files





You might also like



Downloadable Citations