Consumers’ Attitudes towards Brand Extensions: An Analysis on Food and Textile Industries in Turkey
Bibliographic record
Abstract
Brand extensions refer to use an established brand name in new product or product categories and are extensively applied as a marketing strategy. Brand extension success factors vary according to cultures. Consumers’ attitude towards extensions is modified on the basis of their cognitional reactions and relations between the parent brand and extended product and/ or product categories. This study aims at conducting an exploratory research and revealing the relationship between the parent brand and the extended brand. More specifically, the impact of parent brand loyalty on the extension is explored. Therefore, the main objective is to evaluate the attitudes of consumers towards brand extensions through brand loyalty. The study analyzes consumers’ attitudes towards brand extensions specifically in food and textile industries. This is in particular to portray that consumers respond positively to brand extensions in various industries due to different motivations. During the methodology application process, in-depth interviews were carried out with 16 participants who were selected from employees working for public and private institutions in Ankara, the capital of Turkey. The interviews were conducted in two stages. During the first stage, the interviews lasted approximately 45 minutes and consisted of open-ended questions about participants’ brand choices, reasons for choosing the brands they use. The goal was to evaluate their brand loyalty levels. In addition, the participants were provided with the definition of brand extension and their reactions towards extension were noted. In the second stage, the participants were asked to evaluate their attitudes towards brand extensions in food and textile industries along with the factors that have impact on their evaluations. The participants were specifically observed in terms of their approach to brand extensions where the extension was in a totally different sector from the parent brand. The results indicate that brand awareness has a significant impact on brand extensions with regards to quality and trust. However, this impact is at the highest level when the extension is within the same sector with the parent brand. Whenever the extension is in a different sector, consumers not only have negative attitudes toward that extension but also become suspicious about the parent brand. Thus, quality and trust are pivotal factors influencing consumers’ positive attitudes towards brand extensions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".