Journal article
Vitality and learning: the impact of mobile technology use across work–nonwork boundaries on job performance
Behaviour & information technology, Vol.43(12), pp.2907-2929
10/2024
DOI: 10.1080/0144929X.2023.2262605
Abstract
This study categorises mobile technology use into four types, taking into account two dimensions: the nature of the matters (work-related and non-work-related) and the boundaries (work and nonwork time). Furthermore, this study focuses on mobile technology use across boundaries. Drawing upon SDT, this study refines mobile technology use across work-nonwork boundaries into 2*2 categories based on the different ways in which it crosses the work-nonwork boundary, namely, work invading nonwork time (work-to-nonwork time), nonwork intruding on the realm of work time (nonwork-to-work time) as well as individual's willingness of behaviour (active and passive). Moreover, relying on COR theory, we introduce the mediating role of thriving at work (learning and vitality) in the relationship between across-boundary mobile technology use and job performance. This study shows that work-to-nonwork time active use and nonwork-to-work time active use have positive and inverted U-shaped effects on job performance separately, and both nonwork-to-work time and work-to-nonwork time passive use have negative effects on job performance. In addition, learning mediates the positive relationship between work-to-nonwork time active use and job performance, while vitality mediates the relationship between nonwork-to-work time active use and job performance, as well as between work-to-nonwork time passive use and job performance.
Details
- Title: Subtitle
- Vitality and learning: the impact of mobile technology use across work–nonwork boundaries on job performance
- Creators
- Mi Zhou - Xi'an Jiaotong UniversityWei Liu - Xi'an Jiaotong UniversityWeiguo Fan - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Behaviour & information technology, Vol.43(12), pp.2907-2929
- DOI
- 10.1080/0144929X.2023.2262605
- ISSN
- 0144-929X
- eISSN
- 1362-3001
- Grant note
- DOI: 10.13039/501100001809, name: National Natural Science Foundation of China, award: 71872142
- Language
- English
- Electronic publication date
- 09/27/2023
- Date published
- 10/2024
- Academic Unit
- Business Analytics
- Record Identifier
- 9984473619302771
Metrics
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