Studying the Impact of Personality Constructs on Employees’ Knowledge Sharing Behavior Through Considering the Mediating Role of Intelligent Competencies in Project-Oriented Organizations
Bibliographic record
Abstract
The impacts of individual factors on knowledge management actions as well as the impacts of psychological attributes on employees’ knowledge sharing behavior are highly paid attention by many authors. Such attributes as dynamic environment, the expansion of organizational complexities, generating mass information and knowledge-orientation of project-oriented organizations have caused that focus on knowledge is extraordinarily increased in organizations.In many scientific documents, the then impacts by psychological traits on knowledge sharing behavior are expressed. Personality is seen as the most important predictor component of human behavior. Current paper studied the impact by employee’s personality constructs on their knowledge sharing behavior by considering the role of individuals’ intelligent competencies. Present study is a survey – type with descriptive approach. Its sample size was 118 scholars, employees and managers in project – oriented organizations while research data collection tool was an 80-item questionnaire. Its reliability was calculated by Chronbach’s alpha ratio while its content validity was determined by connoisseurs. PLS software package is used to test research hypotheses. Measuring the personality constructs is based on Five – Big Model (NEO) while measuring intelligent competencies is adapted to Boaytzs model. Data analysis shows the direct impact by personality constructs on knowledge sharing behavior while it does not support the mediating role by intelligent competencies in this regard.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".