SIG - Adoption and Diffusion of IT
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Paper Type
Complete
Paper Number
1629
Description
Using self-reported measures for compulsive smartphone use introduces biases. According to the extended version of the social value framework, the extent to which self-reports are prone to social desirability responding (SDR) bias is further going to vary between individuals. The impact of these individual factors on self-reported smartphone use has not been researched extensively. We use an explorative mixed-method approach combining real-world smartphone usage data collected through mobile data donations and relate them to survey instruments capturing the users' ability to self-assess their use and self-reported compulsive use. We contribute to IS literature by employing cluster analysis to derive four distinct types of smartphone users based on their self-reporting behavior (unaware user, light user, heavy user, aware user). We show that, unlike demographic variables, screen time might be an indicator of whether users over- or underestimate their use and that high IT mindfulness and compulsive smartphone use can coexist.
Recommended Citation
Eichner, Arvid Alexander and Lingnau, Nicholas Valentin, "Choice or Compulsion? – A Typology of Self-Reported Smartphone Use" (2022). AMCIS 2022 Proceedings. 6.
https://aisel.aisnet.org/amcis2022/sig_adit/sig_adit/6
Choice or Compulsion? – A Typology of Self-Reported Smartphone Use
Using self-reported measures for compulsive smartphone use introduces biases. According to the extended version of the social value framework, the extent to which self-reports are prone to social desirability responding (SDR) bias is further going to vary between individuals. The impact of these individual factors on self-reported smartphone use has not been researched extensively. We use an explorative mixed-method approach combining real-world smartphone usage data collected through mobile data donations and relate them to survey instruments capturing the users' ability to self-assess their use and self-reported compulsive use. We contribute to IS literature by employing cluster analysis to derive four distinct types of smartphone users based on their self-reporting behavior (unaware user, light user, heavy user, aware user). We show that, unlike demographic variables, screen time might be an indicator of whether users over- or underestimate their use and that high IT mindfulness and compulsive smartphone use can coexist.
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