General image, perceptions and consumer segments of luxury seafood in China
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore Chinese consumers’ perceptions towards a luxury seafood – lobster, and identify the important perceptions that influence Chinese consumers’ general image of lobster. It also recognises Chinese consumer segments based on their perceptions towards lobster. Design/methodology/approach The data were collected through an online survey ( n =882, in two Chinese cities: Shanghai and Qingdao). The surveys explored consumer’s perceptions and general image of lobster. Descriptive analysis, partial least squares regression and cluster analysis were conducted for data analyses. Findings Findings show that the most important perceptions regarding lobster by Chinese consumers are umami, delicious, high in protein, expensive, nutritious, upscale, red colour and bring back appetite. Chinese consumers’ general image of lobster is positively linked to perception items, such as delicious, western flavour, umami, nutritious, high in protein, enjoy, upscale and appetite; and is negatively linked to perception items: spicy/hot, Chinese flavour and risk in illness. Three consumer segments are identified: western-flavour-lovers (35.4 per cent), Chinese-flavour-lovers (32.8 per cent) and negative-believers (31.8 per cent). Significant differences were recognised in the socio-demographic distribution among these three segments including, city, income, marital status, educational level, occupation and age. Originality/value This is the first study to present information regarding consumers’ perceptions, general image and segments towards luxury seafood in the world’s largest East-Asian country – China. The findings from this study can help global seafood marketers and exporters to better understand Chinese consumers which should assist them in developing effective marketing strategies for their luxury seafood products in this major market.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".