Interpreting destination image through theory building approach / Noraminin Khalid
Bibliographic record
Abstract
This qualitative study is an exploratory attempt at understanding destination image through the writings of the travel writers who have undergone the FAMiliarisation or FAM programs organised by Tourism Malaysia. The idea behind the program is for the writers to experience first hand specific destinations in Malaysia and then share their experiences through their travel writings. The main focus was the content of the articles or themes of particular magazines and their writings represented endorsed information. The data in the form of the travel articles (FAM articles) were collected with the assistance of Tourism Malaysia based on the suggested criteria established. FAM articles were collected for analyses representing writers from several countries including Australia, Canada, Brunei Darussalam, USA, United Kingdom and India to name a few. Using the qualitative method of content analysis and adapting the coding procedures of open, axial and selective codings from the grounded theory approach, this study analysed and interpreted selected travel articles written by the FAM writers. The findings are then integrated with the analysis of face-to-face interviews with international tourists and then further strengthened with literature. This study addresses the gaps between destination image theories and the depiction of such destination image by travel writers. It is postulated that writers will mould the perception of the destination and therefore enhance the understanding of destination image. Although the present depiction of destination image is very much relevant within most tourism contexts, what is perhaps not considered precisely is whether such interpretation still holds when the image is derived merely from textual data as they are interpreted by FAM writers. These writers provide the linkage between the destinations and the potential tourists. How they write, what they write, and their expressions of the destinations will influence potential tourists’ attractions to visit. What has yet to be addressed precisely also is the conceptualisation of the framework that describes the elements that form the destination image as it relates to a contextual perspective of Malaysia. The findings reveal that destination images of Malaysia can be divided into three main conceptualisations; a functional depiction of destination image through the portrayal of nature, festivals, people and history; the experiential values relating to excitement and emotional attachment, and the auxillary influence as shown by the spillover effect and FAMiliarity with specific places. The findings further reveal that such destination images lead to the possibility for undertaking psychographic segmentation of targeted travellers and ultimately emphasized the need for positioning strategies to be in place. This essentially led to the evolvement of possible destination branding and in the creation of destination loyalty. This study established that it was possible to derive destination image by interpreting the depth of the articles and through the expressions of the travel writers who very often narrated their experiences coherently through vivid depictions and emotions. It is suggested that future studies further test the evolving themes through empirical analyses that are more conclusive and statistically proven.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".