Branding destinations with multisensory brand associations and evaluating its impact on behavioural pattern under the intervention of multiplex phenomenon of relationship-branding
Bibliographic record
Abstract
Image perception has been acknowledged as a critical component of branding.Perception of image is comparatively difficult for intangible entities like 'destination'.Research initiatives, thus far, has postulated destination branding on associations namely cognitive and affective image inputs.Multisensory brand associations were never tested for destination branding model, although, sensory brand associations were found to play major role in the tangible product branding and influence purchase behaviours.Further, attributional elements, specific to destination are assumed to play critical role in developing the brand identity leading to choice of destination.Perceived destination brand image was empirically tested for its influence on post-travel behaviours and was identified as one of the potent travel motives, however, the predictive capability of perceived destination brand image on favourable post-travel behaviours seems to fall off due to reasons unknown.Researchers like Fournier, observed that relationship-branding can induce favourable post-purchase behaviour.This study focuses on developing a destination brand model using conventional brand associations, namely cognitive and affective image inputs, and new associations, namely, attributional and sensory image inputs.The study further incorporates relationship-branding as a multiplex phenomenon and tested its possible intervening impact between perceived destination brand image and post-travel behaviours.The results established the destination brand model based on the image associations and confirmed the role of relationship-branding as a para-social and socio-emotional moderator to influence post-travel visitor behaviour.The study plugs in the gap that existed in the present body of knowledge addressing destination branding and reinforces the relationship theory in establishing the 'brand -purchase -post-purchase behaviour' triad.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".