Can strategic HRM bundles decrease emotional exhaustion and increase service recovery performance?
Bibliographic record
Abstract
Purpose Through the lens of conservation of resource theory and the model of ability, motivation and opportunity (AMO), this study tests the relationship between high performance work practices (HPWP), emotional exhaustion and service recovery performance (SRP). It examines the direct effect of AMO bundles on emotional exhaustion and the indirect effect of these bundles on SRP via emotional exhaustion. Design/methodology/approach In a sample of 1,664 flight attendants from Canada, Germany and France, this study uses a quantitative method. Using AMOS V.24, CFA was used to test quality of scales, model fit as well as the direct effects. The method of Monte Carlo (parametric bootstrap) and more precisely bias corrected percentile method were used to test the mediation mechanism, based on 5,000 bootstrapping and 95% confidence intervals. Findings Results show that all AMO bundles can be considered as a resource caravan passageway protecting employees against resources loss and allowing them to perform well and to recover service after a failure. They reveal that each bundle has a direct, negative link with emotional exhaustion, a health-related well-being and an indirect effect on SRP via emotional exhaustion. Research limitations/implications The finding further highlights the need to distinguish between AMO dimensions in strategic HRM research and practice. The cross-sectional nature of this study limits the establishment of causal links between variables. The author encourages future researchers to adopt a research design enabling to collect data at two or three-time periods and involving multi-source data. Practical implications Companies should be aware of the mechanisms through which HPWP influence the occupational health and performance of flight attendants and consider that “different bundles can have different effects” as important when they would redesign their HRM practices. In turn, it is rather opportunity enhancing HPWP (e.g. empowerment, work teams) that will be the most efficient in improving SRP. In a customer service context, and for flight attendants who work for prolonged hours with sometimes demanding passengers, it seems very important that airlines empower their flight attendants to use their skills and abilities to respond to problems arising onboard, either from service failures or any complaint a passenger may have. Employers should aim to create pools of practices designed to enrich and protect the resources of their employees allowing them to reduce emotional exhaustion. Originality/value This research study contributes therefore to the HRM-well-being-individual and/or organizational performance debate in a very particular context, by using the AMO framework to test the proposed relationship. In doing so, this study advances the theoretical and empirical evidence on how HR systems and AMO framework can be applied in this setting. The findings allow distinguishing which bundle of HRM is the most influential on emotional exhaustion, which can advance the literature in strategic human resource management. The paper adds to the literature by addressing the role of emotional exhaustion rather than happiness-related measures of well-being. Thus, our results stress the importance of health-related well-being, and emotional exhaustion, as an important pathway through which AMO-bundles influence performance outcomes and confirm that there are different well-being pathways to consider in the HRM-performance relationship. By using different bundles of AMO, the study advances the literature by showing that each bundle could have a different effect as the findings show that only opportunity enhancing HPWPs still directly impacted SRP after introducing the mediator (emotional exhaustion).
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".