The impact of Knowledge Management (KM) and Organizational Commitment (OC) on employee job satisfaction (EJS) in banking sector of Pakistan
Bibliographic record
Abstract
Purpose: The purpose of this paper is to examine the impact of knowledge management practices and organizational commitment could be a way to nurture job satisfaction and examine how knowledge management practices and organizational commitment can increase individual employees’ job satisfaction. Design/methodology/approach: A theoretical model concerning the connections between sixfacets of Knowledge Management (knowledge acquisition, knowledge sharing, knowledge creation, knowledge application,knowledge codification and knowledge retention), two facets of Organizational Commitment (Keeping up organizational image and Responding to organizational greediness)and job satisfaction is proposed. Then data is collected through face to face questionnaire and also online web based questionnaires and sample is selected on convenience based from the banking sector organization of Pakistan. Findings:organization commitmentand knowledge management process in one’s working environment is significantly linked with high employee job satisfaction. Especially intra-organizational knowledge sharing knowledge application and knowledge creationalso organization commitment (coping with attachment) seems to be a key factors promoting satisfaction with one’s job in most employee. Practical implications:organization commitment and knowledge management has a strong impact on employee job satisfaction, and therefore, managers are advised to implement knowledge management and organization commitment activities in their organizations, not only for the sake of improving knowledge worker performance but also for improving their well-being at work. Originality/value: This paper produces knowledge on a practices of KM and organizational commitment that has been largely unexplored in previous all research, individual job satisfaction. Also, it promotes the knowledge management and organizational commitmentliterature to the next stage where the impact of knowledge management and organizational commitment is not explored as a “one size fits all” type of a phenomenon, but rather as a contingent and contextual issue. Keywords:Knowledge Management, Knowledge Management Practices,Knowledge Acquisition, Knowledge Sharing, Knowledge Creation, Knowledge Codification, Knowledge Retention, Organizational Commitment, Job satisfaction.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".