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The human body has the same basic size data but has different surface morphology, resulting in the unfitness even under the same size specification. The purpose of this study was to solve the local fitness problems by representing and quantifying the human surface morphological difference.

Firstly, the 3D point cloud for 323 female students was scanned, and the cross-section layers of the “waist-to-thigh” zone were determined. Secondly, the space vector based on the space Euclidean distance was extracted to represent and quantify the surface morphological difference. And the Principal Component Analysis and K-means were adopted to subdivide the target zone. Thirdly, the pattern based on the subdivision results and surface flattening was generated. Additionally, the fitness was evaluated by the subjective and objective assessments, separately.

The space vector could represent and quantify the shape morphology of the “waist-to-thigh” zone. It had successfully achieved the human body subdivision and corresponding pattern generation for the “waist-to-thigh” zone. And the pattern based on the shape subdivision and surface flattening of the space vector could effectively improve the wearing fitness. Particularly in the waist and crotch area of trousers, the obvious wrinkles had been solved because the space vector is more in line with the shape morphology characteristics.

The proposed method could represent and quantify the difference in human surface morphology in a 3D manner. It solved the unfitness problem caused by the same body size but different shape surface morphology. And it will contribute to the fitness improvement of the trousers.

Due to ginger holds a special and indispensable place in Chinese cuisine, understanding consumers’ preferences for organic ginger is of significance, especially given the growing interest in organic food products and sustainable agriculture. This study thus examines Chinese consumers’ preference for fresh ginger and the sources of their preferences heterogeneity for organic ginger consumption.

The study is using choice experiment (CE) method and mixed logit (MXL) modeling with 1,312 valid samples. The participants are regular consumers who are 18 years old or above and had bought fresh ginger within the past 12 months.

The results show that consumers prefer organic product certification labeling ginger to conventional ginger, preferred to purchase ginger at wet markets to at supermarkets or online, and preferred either ginger with regional public brand or private brand to unbranded ginger. Results also indicate that age, education level, income, purchasing experience of organic and branded ginger, and cognition of ginger health benefits are the sources of heterogeneity in consumer preferences for organic ginger.

This study contributes to ginger growers, marketers and policy makers. This study tracks how consumers' preferences change under different attribute combinations, capture the complex preference structure of consumers, and help reveal the motivations behind consumers' preferences for organic ginger. These findings will be crucial for developing marketing strategies, promoting organic products, and meeting consumer needs.