Paper Number
ECIS2025-1088
Paper Type
SP
Abstract
Individuals increasingly use portfolios of digital technologies that lead to work-life blending. When it comes to the analysis of this use, Information Systems (IS) literature upholds a strict separation between ‘work’ (e.g., business analytics, people analytics) and ‘life’ (e.g., quantified self). We address this mostly false dichotomy by studying data analytics habits in the context of digital nomadism, which is an extreme—and therefore revelatory—case of work-life blending. Based on our findings from qualitative interviews with digital nomads, we identify five dimensions in which they use data analytics to blend work and life: (1) health, (2) travel, (3) task management, (4) time management, and (5) self-development. Our findings contribute to the emerging debate on blurring boundaries between instrumental (‘work’) and leisurely (‘life’) technology use and pave the way for theoretically updating existing, dichotomous categories of data analytics practices.
Recommended Citation
Marx, Julian; Fischer-Pressler, Diana; and Schlagwein, Daniel, "Work-Life Blending with Data Analytics: Evidence from a Study of Digital Nomads" (2025). ECIS 2025 Proceedings. 2.
https://aisel.aisnet.org/ecis2025/persdata/persdata/2
Work-Life Blending with Data Analytics: Evidence from a Study of Digital Nomads
Individuals increasingly use portfolios of digital technologies that lead to work-life blending. When it comes to the analysis of this use, Information Systems (IS) literature upholds a strict separation between ‘work’ (e.g., business analytics, people analytics) and ‘life’ (e.g., quantified self). We address this mostly false dichotomy by studying data analytics habits in the context of digital nomadism, which is an extreme—and therefore revelatory—case of work-life blending. Based on our findings from qualitative interviews with digital nomads, we identify five dimensions in which they use data analytics to blend work and life: (1) health, (2) travel, (3) task management, (4) time management, and (5) self-development. Our findings contribute to the emerging debate on blurring boundaries between instrumental (‘work’) and leisurely (‘life’) technology use and pave the way for theoretically updating existing, dichotomous categories of data analytics practices.
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