Bibliographic record
Abstract
Purpose Using a modified version of the service profit chain, the purpose of this paper is to examine the mediating role of service climate (SC) by exploring predictors of SC (i.e. service training (ST), managerial practices (MP), physical design (PD), and job design ( JD), job satisfaction ( JS), and employee empowerment) on service quality (SQ), client satisfaction (CS) with service, and client empowerment (CE). The larger proposition being that certain structural variables, through their impact on SC have the potential to positively influence outcomes in health care. Design/methodology/approach Registered nurses (N=180) from emergency departments across one province in Canada provided information about internal SQ (i.e. ST, MP, PD, and JD), JS, feelings of empowerment, and SC. Furthermore, these nurses provided information on external SQ, CS with service, and CE by responding to questions from the vantage point of the client. The data were analyzed using statistical package for the social sciences; structural equation modelling (SEM) was implemented using LISREL. Findings SEM analyses showed that JS and empowerment only partially mediated the relationship between MP, PD, and JD and SC. In addition, SQ, CS with service, and CE were fully mediated by SC. Research limitations/implications A limitation of this study is that the researcher used only employee (nurses) data rather than employee and client data simultaneously in the research model. Future research should be done on the service profit chain theory to incorporate both viewpoints. In addition, research could be carried out in other service occupations and organizations to test the invariance of the research model. Practical implications The results should lead health care managers to consider the importance of emphasizing internal SQ features that facilitate SC in health care. Originality/value This contribution of this research is apply the service profit chain framework in exploring the role of SC in health care. In addition, emphasize the importance of the PD of emergency department to creating a climate for service in health care.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".