Frontline employees' performance in the financial services industry: the significance of trust, empathy and consumer orientation
Bibliographic record
Abstract
Purpose Based upon social exchange theory, this study investigates the mediating effect of consumers' trust in banking industry frontline employees on two relationships: (1) the relation between consumers' perceptions of frontline employees' empathy and consumers' perceptions of frontline employees' performance, and (2) the relation between consumers' perception of frontline employees' customer orientation and consumers' perceptions of frontline employees' performance. Design/methodology/approach The authors used a time-lag research design to collect data through online questionnaires distributed in two waves. The sample comprises 375 respondents having experience and interaction with banking frontline employees. Findings Results confirm the mediating effect of consumers' trust in the banking industry on the relationships between their perceptions of frontline employees' empathy and consumer orientation on the one hand and their perceptions of frontline employees' performance on the other hand. Practical implications Results may be helpful to policymakers and managers in the service industries, prompting them to adopt approaches and strategies designed to build strong relationships with consumers, thus increasing consumers' trust and frontline employees' performance. Originality/value This study confirms the relevance of social exchange theory in understanding the role of consumers' trust and perceptions of frontline employees' empathy and consumer orientation in understanding their perception of frontline employee performance in the banking industry.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".