The Role of Utilitarian, Brand value, Aesthetic, and the Cultural Factors on the Intention to Repurchase Smart Phones of Apple
Bibliographic record
Abstract
Today, in the highly competitive world of business, having loyal customers is a valuable asset for businesses and companies. In the same vein, the re-purchase intention plays a vital role and identifying and improving its influential factors can boost this valuable asset. Therefore, the main objective of the present study is to study the role of utilitarian, brand value, aesthetic, and the cultural factors on the intention to re-purchase Apple smartphones. This study is applied and has a descriptive-correlative design. The statistical population consisted of approximately 6000 students of management at the Central Branch of Tehran Azad University. The sample size was calculated 361 people using Morgan table. The simple random sampling method used. To test the research hypothesis, structural equation modeling (SEM) by Lisrel has been used. The findings show that product’s design, perceived quality, subjective norms and brand popularity were the factors that have had a positive effect both directly and through the intermediary variable of socio-cultural reputation on the intention to repurchase this product.
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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".