Conflict with customers: the limits of social support and job autonomy in preventing burnout among customer service workers
Bibliographic record
Abstract
Purpose The purpose of this study is to examine the burnout of workers in customer service roles as a result of conflict with customers; and the role that coworker support, non-work-related social support and job autonomy play in buffering customer service workers from conflict with customers. Design/methodology/approach A sample of 191 young customer service workers completed an online self-report questionnaire. Findings Although it was found that coworker support, non-work-related social support and job autonomy moderated the relationship between customer conflict and burnout, the form of the interactions was not as expected. Rather than buffering customer service workers specifically against customer conflict, it was found that as customer conflict intensifies, it gradually erodes the positive benefits that coworker support, general social support and job autonomy have in preventing burnout as a result of general work stress. Originality/value This study is one of few to empirically investigate the unique stressors experienced by customer service workers. It also expands understanding of social support and job autonomy in the context of work stress, demonstrating that there are limits to the effectiveness of these personal and organizational resources in preserving worker well-being.
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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 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".