The Impact of Personal Selling on the Purchasing Behavior towards Clothes: A Case Study on the Youth Category
Bibliographic record
Abstract
This study aimed to find the impact of personal selling on the purchasing behavior for youth in buying clothes. To achieve the objectives of the study, hypotheses were formulated and tested on a sample of the target community made up of 289 young men and women. The questionnaire design (32) was divided into five dimensions, four dimensions based on the personal characteristics of salespersons and their display of goods, characteristics of clothing stores, promotion done by salespersons in the sale of clothing, and the fifth focused on youth’s clothes purchasing behavior. The results of the study showed that 76.7% of males and 99.1% of females prefer to purchase from clothing retail stores. The sampling showed that salespersons in retail stores are honest in dealing with their customers but do not have the ability to negotiate with them. They neither have the required sales skill nor play a big role in stimulating sales, and they do not grant discounts to customers. The study recommended the importance of training and qualification for salespersons in personal selling to help them deal truthfully with customers and develop the ability to negotiate. Salespersons should be granted the authority to give discounts to customers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".