Assessing and measuring sales culture within commercial banks in Jordan
Bibliographic record
Abstract
Purpose This study aims to assess and measure the sales culture within the commercial banks in Jordan, and to provide top management of these banks with the database which may be required for improving the banks' selling effectiveness. Design/methodology/approach The study has been conducted on a convenience sample of 1,000 employees selected from those of all the commercial banks operating in Jordan. Sales culture was measured by using the Sales Culture Index (SCI), consisting of 65 statements. The data required for this study were collected by a self‐structured questionnaire. Findings The findings of the study indicate that the overall employees' perception of sales culture in the surveyed banks is moderate. However, the sales culture in the non‐Jordanian banks was stronger than that in the Jordanian banks. Research limitations/implications As is the case in any study, some limitations relevant to this study cannot be abandoned. For instance, the findings of this study are based on self‐report perceptions of both the employees and the customers. Data collected by this approach may or may not be accurate to that extent, which reflects the respondents' real feelings. Practical implications The results of this study would enable management in the commercial banks in Jordan to design internal marketing programs aimed at building a strong service‐minded sales culture among employees. Originality/value This is a first attempt to assess and measure the sales culture in the commercial banks in Jordan.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".