Abstract
PurposeThis study seeks to explore digital natives' mobile usage behaviors and, in turn, develop an analytic framework that helps articulate the underlying components of mobile addiction syndrome (MAS), its severity levels and mobile usage purposes.Design/methodology/approachThe investigation adopts a survey method and a case study. The results of the former are based on 411 random classroom observations and 205 questionnaire responses, and the insights of the latter are derived from 24 interviews and daily observations.FindingsThe findings validate five distinctive signs that constitute MAS and their significant correlations with each of the Big Five personality traits. Classroom observations confirm the prevalence of addiction tendency among digital natives in the research context. Seven levels of MAS and six different mobile usage purposes further manifest themselves from case analysis. There appears to be a sharp contrast between the addicted and non-addicted groups in their mobile purposes and behavioral patterns. Additionally, family relationships seem influential in shaping non-addictive mobile usage behaviors.Research limitations/implicationsPsychological perspectives on MAS may be important but insufficient. Empirical investigation on a global scale, especially with distinctive cross-cultural comparisons, will be highly encouraged. How MAS evolves over time should also serve as future research interests.Practical implicationsTeaching pedagogy of college education might need certain adjustments to intrigue digital natives' learning interests. Future managers might also need to adopt better performance measurements for digital natives who barely separate work from personal matters in their mobile devices.Social implicationsParents and healthcare institutions may need to develop response mechanism to tackle this global issue at home and in society. The long-term effects of the COVID-19 pandemic on MAS might also deserve global attention.Originality/valueThe analytic framework developed provides an original mechanism that can be valuable in identifying MAS severity and associated behavioral patterns.
Subject
Library and Information Sciences,Computer Science Applications,Information Systems
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