Comparing the direct, indirect and comparative effects of salespersons’ client and product knowledge in the financial services industry
Bibliographic record
Abstract
Purpose The purpose of this study is to empirically examine and compare the effects of bankers’ customer knowledge and product knowledge on client satisfaction, trust, positive word of mouth and purchase intentions in the financial services industry. Design/methodology/approach This study investigated real-life buyer–seller dyads involving 402 bankers and 697 clients. Structural equation modeling was used for data analysis to test the proposed model. Findings In the client sample, bankers’ client knowledge demonstrated a stronger effect on client satisfaction and trust than product knowledge. In the banker sample, product knowledge had a stronger impact on client trust than client knowledge. In both samples, client satisfaction had a stronger effect on both positive word of mouth and purchase intentions than client trust. Practical implications Managers should consider client knowledge and human relations skills as major factors in their personnel selection and training strategies. At the marketing management level, it is suggested that policies and decisions of financial institutions must favor an in-depth understanding and sharing of knowledge of clients. Originality/value To the best of the author’s knowledge, this study is one of the first research to empirically compare the effects of bankers’ client knowledge and product knowledge, from both the client and banker perspectives. Although salesperson knowledge of customers has been assumed to be a key element of the marketing concept, it has received little attention despite its high managerial relevance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".