The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Personal Internet use at work: Understanding cyberslacking
Abstract
Cyberslacking, typically defined as the use of Internet and mobile technology during work hours for personal purposes, is a growing concern for organizations due to the potential in lost revenue; however, the majority of academic research in this area has focused on a limited number of cyberslacking behaviors and/or employed small, non-representative samples. In order to address these limitations, the present study employs a nationally representative sample of American workers and tests the relationship between nine cyberslacking behaviors and a variety of demographic and work-specific predictors. Three measures of cyberslacking are employed to provide a richer analysis of the phenomenon: individual behaviors, frequency of cyberslacking, and variety of cyberslacking. Results indicate that being younger, male, and a racial minority positively predict cyberslacking variety and frequency, as do routinized Internet use at work and higher perceived Internet utility. Results are discussed as to how the present study expands on previous research, and directions for future research are indicated.
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Smartphone use and academic performance: A literature review
Amez, S., & Baert, S. (2020) · International Journal of Educational Research · doi:10.1016/j.ijer.2020.101618 · Cited by 268
Feeling interrupted—Being responsive: how online messages relate to affect at work
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Psychosocial Modeling of Insider Threat Risk Based on Behavioral and Word Use Analysis
Greitzer, Kangas, Noonan, Brown, & Ferryman (2013) · e-Service Journal · doi:10.2979/eservicej.9.1.106 · Cited by 47
Metadata
- Authors
- Vitak, J., Crouse, J., & LaRose, R.
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2011-09
- Volume
- 27
- Issue
- 5
- Pages
- 1751-1759
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W1965851068
- Cited by
- 393
- References
- 31
- FWCI
- 34.76
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
