Creative leadership, innovation climate and innovation behaviour: the moderating role of knowledge sharing in management
Bibliographic record
Abstract
Purpose Innovation, in most enterprises, originates from employees. In this study, how organizational climate, creative leadership ability and emotional reaction to imposed change impact on innovative behaviour of employees vis-à-vis knowledge sharing within the workplace is explored. Design/methodology/approach Adopting a social cognitive perspective, a model is constructed to explain factors influencing the innovation behaviour of employees along two key aspects, that is, organizational climate (innovation vs risk-taking climate) and creative leadership ability (leadership skills, vision incentive) vis-à-vis other moderating factors. A survey questionnaire, administered to a total of 311 manufacturing employees in China, was used to verify the proposed research model via Smart PLS. Findings Results unveil several key factors impacting positively on creative leadership in organizations. Specifically, creative leadership ability, emotional reaction to imposed change, innovation climate and knowledge sharing are found to impact positively on innovation behaviour while supportive versus risk-taking climate as well as emotional reaction are found to impact positively on innovation climate. Additionally, knowledge sharing is found to regulate the relationship between innovation climate and innovation behaviour. Research limitations/implications While offering insights into the antecedent factors of innovation behaviour, the study extends research on the intermediary role of innovation climate and employees' innovation behaviour. Additionally, it improves one's understanding on the moderating role between knowledge sharing and innovation behaviour. Practical implications The study findings will assist enterprises in diagnosing the implementation environment of innovation strategy, thereby providing a reference for training enterprise leadership while improving the employees' understanding of innovation and reform in the workplace. Originality/value The study contributes both theoretical and managerial thinking on the extent in which organizational climate and creative leadership ability may and/or should be evolved appropriately to support, encourage and nurture employees' innovation behaviour in the workplace.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".