The DOI matches its Crossref record.
Social‐media misuse a ticking time‐bomb for employers: Robust policies and procedures needed to reduce the risks
Abstract
Purpose: This article aims to highlight the risks employers face when employees use social media. Design/methodology/approach: The article considers each risk in turn, and suggests how it could be reduced. Findings: The major challenge for most employers is the development of a co‐ordinated human‐resource strategy that incorporates documented policies and procedures, an internal training program and robust record‐keeping. Practical implications: The article guides managers and HR specialists in assessing the exposure of their organizations/clients to the risks identified. Social implications: Attention is drawn to the growing problem of the misuse of social media across society as a whole. Originality/value: The article raises the issue of organizational awareness and preparedness to undertake challenges posed by social media.
Overview
Integrity signals
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Cites
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Interestingly, this is the least researched cell in Table 1 by repression researchers, but business scholarship readily advises companies on how to craft policies and practices that mitigate business risks through channeling (89–92).”
From Physical and virtual repertoires of contention (2022) · cites this paper as [92]
In the citing paper
“Organizations may have broad social media policies for employees that discourage controversial speech on social media and/or vet job candidates using material harvested from candidates’ social media posts, disadvantaging candidates with specific political beliefs (92).”
From Physical and virtual repertoires of contention (2022) · cites this paper as [92]
Citations
Cites
Still being checked.
Cited by
Earl, J. (2022) · Science Advances · doi:10.1126/sciadv.abl8198 · Cited by 250
Metadata
- Authors
- Field, J., & Chelliah, J.
- Affiliations
- University of Technology Sydney (AU)
- ORCID
- Chelliah, John
- Venue
- Human Resource Management International Digest
- Publisher
- Emerald
- Published
- 2012-10-12
- Volume
- 20
- Issue
- 7
- Pages
- 36-38
- ISSN
- 0967-0734 (ISSN-L)
- OpenAlex
- W1513063098
- Cited by
- 14
- References
- 0
- Citations by year
- 2024: 1 · 2022: 1 · 2021: 1 · 2020: 2 · 2019: 1 · 2017: 3 · 2016: 1 · 2014: 2 · 2013: 2
- FWCI
- 3.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.emerald.com/insight/site-policies (tdm)
- Locations
- Human Resource Management International Digest (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Cyberloafing and Workplace Behavior
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
- Social Sciences › Business, Management and Accounting › Industrial relations › Legal and Labor Studies
- Keywords
- social media misuse, employee social media use, social media policy, strategic human resource management, employee training, record keeping, organizational preparedness
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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Data sources
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.
