Bibliographic record
Abstract
Nowadays, marketing has changed from its primary state of gaining customer satisfaction to a tool to achieve the goal of competitive advantage.Thus, it is observed that most of the most successful companies in the world have started to reduce costs and increase their productivity, which is not possible regardless of customers' demands and needs.Therefore, attempts to retain great numbers of customer lead marketers to examine customer-perceived value.The concept of perceived value is closely related to concepts such as customer satisfaction, customer absorption, loyalty, and growth in market share, especially offering value to the customer leads to competitive advantage.The purpose of this research was to investigate the relationship between shopping mall environment with customer-perceived value (CPV), customer satisfaction, and loyalty in chain stores in Kermanshah.The study is applied in terms of purpose, and in terms of data type, it is descriptive-survey.The study of the subject literature was through library study such as books, journals, dissertations, articles, etc.Data were collected through a questionnaire and analyzed by statistical methods.Regarding the subject, the study population consisted of customers of Refah and Etka stores in Kermanshah, whose number is unknown.The sample size was determined 384 using Morgan Table, and sampling was random sampling.After analyzing the data, using correlation and structural equations, it was determined that the shopping center environment had a positive and significant effect on CPV, customer satisfaction and loyalty.In addition, CPV had a positive and significant impact on customer satisfaction and loyalty.Therefore, it is suggested that the managers of Refah and Etka stores try to supply the products and services tailored to the expectations and requests of customers, and according to the location of the store in the urban context and its different characteristics, they should emphasize particular goods and services.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.939 | 0.936 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".