The Impact of Product Innovation on Relationship Quality in Automotive Industry: Strategic Focus on Brand Satisfaction, Brand Trust, and Brand Commitment
Bibliographic record
Abstract
This study examines the effect of product innovation on relationship quality in automotive industry. Based on the review of literature, it is evident that there are very limited studies which have come across the effect of product innovation on relationship quality and its dimensions; brand satisfaction, brand trust, and brand commitment. Therefore, this study aims to contribute to the literature and body of knowledge on the actual relationship between such variables. The automotive sector in Malaysia was selected to conduct this study whereby the data were collected from passenger car users in Northern region of the country. The data were analyzed using SPSS and structural equation modeling (AMOS). The findings revealed that the research model fits the data significantly and achieved the recommended values for all fit indices. In particular, the findings supported the significant positive effect of brand satisfaction on brand trust. Consequently, brand trust has significant positive effect on brand commitment. Moreover, the findings indicated that product innovation has significant positive effect on relationship quality and its dimensions; brand trust, brand commitment, and brand satisfaction. The findings also demonstrated that the main contribution of this study lies in the examination of product innovation as an antecedent to relationship quality and its dimensions rather than looking on the frequently used antecedents. These results and their implications along with avenues for further research are also elaborated in this study.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".