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Record W3098564219 · doi:10.6000/2371-1647.2020.06.02

The Impact of Cyberloafing on Employees’ Job Performance: A Review of Literature

2020· review· en· W3098564219 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Advances in Management Sciences & Information Systems · 2020
Typereview
Languageen
FieldSocial Sciences
TopicCyberloafing and Workplace Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyJob performanceManagementBusinessSociologySocial psychologyJob satisfactionEconomics

Abstract

fetched live from OpenAlex

Objectives: A controversy exists since long, among the researchers about the impact of cyberloafing on employees’ job performance. Some researchers study that cyberloafing distracts employees from their job descriptions; while others argue that cyberloafing is quite helpful in different ways to add quality to employees’ work. The aim of this paper is to review the past literature in order to understand the impact of cyberloafing in shaping up or destructing employees’ job performance. Moreover, the paper highlights the methodological analysis based on literature review. Future recommendations for the use of the internet by employees on office computers as well as other social media devices to enhance employees’ job performance are given. Design: An organized review of the literature (1996- 2020) from information technology, business, management, and organizational behavior studies was performed. The topics studied were about internet, World Wide Web, cyberloafing, social media, employees’ job performance, employees’ engagement, employees’ productivity, and workplace environment. Data Sources: Different research platforms such as ‘Research gate’, ‘Emerald’, ‘Jstor’, ‘Google Scholar’, ‘SCOPUS’, ‘ELSEVIER’, ‘SCIENCE DATA’, ‘Core’, ‘ScienceOpen’, ‘ERIC’, ‘Paperity’ and internet were used to read up literature. Review Methods: Different articles written in English, related to employees’ behavior and performance as well as cyberloafing and social media, were studied. Results: The review of literature showed that cyberloafing and social media significantly impact employees’ job performance. However, the findings were not consistent, and both the positive and negative impacts of cyberloafing and social media on employees’ performance were found. Conclusion: The mixed findings indicate that cyberloafing can have both the positive and negative impact on employees’ job performance. In other words, a little bit cyberloafing is important for healthy communication, innovation and productivity; while the excessive unethical use of internet was found to have adverse effects on job performance. Therefore, it is recommended not to totally suppress cyberloafing but to devise cyberloafing control strategies which are equally acceptable to both the employees and employers. Hence, by the implementation of right cyberloafing control policies, positive outcomes of cyberloafing could be achieved.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.944
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.402
Teacher spread0.375 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it