Boosting customer orientation through coaching: a Canadian study
Bibliographic record
Abstract
Purpose – The purpose of this paper is to investigate to what extent bank manager's coaching, a managerial relationship behavior based on mutual trust, openness and quality of exchanges, affects front-line employee's performance through the mediating effect of salesperson's customer orientation. Design/methodology/approach – The paper conducted a non-experimental, cross-sectional study; a Canadian bank agreed to participate in the study and 122 financial advisors with sales responsibilities answered a web-based survey; data were analyzed using structural equation modelling. Findings – The paper found support for the hypotheses that managerial coaching behavior can help bank employees develop their customer orientation and increase their performance, as well as reduce opportunistic behavior (sales orientation). The paper found that the direct link between coaching and performance, plus the mediating effect of sales orientation and customer orientation (SOCO) can potentially explain a significant variation in employee's performance ( r 2=0.23). The paper also found that the hypothesized model provided better explanations of the phenomenon when compared with two rival models, one considering SOCO as a full mediator between coaching and performance, and the other one considering only the effect of coaching on performance. Originality/value – In the banking sector, practitioners and scholars are paying increased attention to the role of trust and relationship behaviors in the development of market orientation and customer relationships. The paper identified a key relationship behavior (customer orientation) and tests its impact as a mediator between a relationship managerial behavior (coaching) and business outcomes (performance) in an international banking setting (Canada).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.015 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".