Relationship between Social Networking Platforms and Performance of Virtual Teams in Nigeria Telecomunnication Industry
Bibliographic record
Abstract
The study examined a relationship between social networking platforms and performance of virtual teams in Nigeria telecommunication industries. Opinions of one hundred and eleven virtual team members from three giant telecommunication firms in Enugu and Lagos, Nigeria participated in the study.MTN Nigeria, Globacom Nigeria and Airtel Nigeria were sampled using self-designed questionnaire. Two research hypotheses were tested. It was found out that that there was a significant relationship between types of social networking platforms used (Facebook, Skype, MySpace, Instagram. and Linked) in the workplace on performance of virtual teams {X2 (2) =211.108; p<.05}. Regression results indicated that the overall model fit five predictors (types of organization, team membership, job position, social networking platforms, and sex) was questionable (-2 Log Likelihood = 92.683) but was statistically reliable in distinguishing between virtual team performances X2 (5) = 54.352, p < .05). Useful recommendations that would enhance a synergy between virtual team members and healthy social network platforms were suggested.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".