The Effect of Internal Marketing on Organizational Citizenship Behavior an Applicable Study on the University of Jordan Employees
Bibliographic record
Abstract
A tremendous shifting of businesses at the present time forced organizations to live in a dynamic, ambiguous, and changeable environment. Due to these challenges, organizations need to apply the new marketing orientation that enhance businesses; and improve their businesses permanently to keep their competitive excellence. One of the main important factors to consider is by attracting new customers and maintaining healthy long-term relationship with them. This cannot be accomplished without improving the organizational performance through-out applying the internal marketing concepts which can be translated as seeing its employees as its first market (Sincic & Vokic, 2007). This paper discusses and investigates the effect of a set of internal marketing elements such as employees' motivation, communication, empowerment, and training on organizational citizenship behavior. The quantitative data collection approach is used to collect the suitable data from a sample of 300 fulltime employees. Results have explored new routes in how organizations can create, maintain, and enhance organizations' citizen behavior. Which indicate, that there is a positive relationship between internal marketing dimensions; and organizational citizenship behavior in varying magnitude. Furthermore, the investigation showed that the dominant dimension of internal marketing is the motivation; then followed by the communication with stronger impact on organizational citizenship behavior, where the surprising results that the empowerment; and training and development don’t have that much effect. Also, hypotheses were tested, and more information regarding data analysis, results' discussion and study limitations were presented in more details.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".