Salesperson's listening ability as an antecedent to relationship selling
Bibliographic record
Abstract
Purpose – In this study, active empathetic listening is purposed as being an antecedent to a salesperson's communication skill, ability to maintain quality relationships and build trust. The study proposes that communication skill, relationship quality and trust all moderate the relationship between AEL and sales performance. Design/methodology/approach – Survey research using salespersons was conducted; structural equation modeling was used to test the hypotheses of the model. Findings – The findings confirmed that AEL was positively related to salespersons' communication skills, relationship quality and trust. The proposed moderators of communication and trust received support when predicting sales performance. Research limitations/implications – This was the first empirical study to examine the role of AEL in a relationship selling model. AEL was found to directly affect levels of trust, relationship quality and overall communication skills of salespeople. More research on the role of AEL in the relationship selling process should be investigated. Practical implications – Managers that focus on long-term relationships in a dyadic buyer-seller relationship may benefit most from this study. A scale that can be used to measure existing levels of AEL in the sales force is included. AEL may better enable salespeople to develop long-term relationships with their customers. Originality/value – This study examines a form of listening (AEL) that is proposed to be superior to other forms of listening within the personal selling context. Presently little research on the importance of listening and its impact on relationship building exists. This is the first study to test AEL as an antecedent to relationship skills of salespeople.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".