Inclusive Leadership Unveiled: Driving <scp>CSR</scp> and Innovation Through a Moderated Mediation Framework
Bibliographic record
Abstract
ABSTRACT This study investigates the associations between employees perceived corporate social responsibility (CSR) and innovative work behaviour and examines the mediating role of organizational identification in the context of Indian hospitality and tourism industry. It also tests the moderating role of inclusive leadership in this mediated association. Using the social exchange theory (SET) framework, the study tested a moderated mediation model based on two‐wave survey data gathered from 263 employees and 24 supervisors. A significant association was found between CSR initiatives, employees' organizational identification and innovative work behavior. Inclusive leadership moderated the indirect effect of perceived CSR on employees' innovative work behavior via organizational identification. Social responsibility initiatives hold significant value from the standpoint of an employee motivation and engagement in a service‐driven context wherein organizations heavily rely on employees' attitudes, behaviors and performance for business sustainability and growth. Additionally, inclusive leaders are critical in building a supportive environment to facilitate employees' innovative work behavior. Organizations must therefore take holistic measures to educate employees about their social responsibility philosophy and encourage active communication regarding such initiatives. By examining the potential underlying mechanisms and boundary conditions, this paper has made a novel attempt to assert the role of organizational identification as a mediator and inclusive leadership as a moderator in the above‐mentioned association.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".