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Towards the new century the young generations of Hong Kong seem to be extremely marketing concerned, and brands are more important to them than ever before. Due to the change of fashion advertising from selling product to selling image, a new concept of consumer buying have emerged among these youth who are more complex, flexible, multifaceted and indulging different desires at different times. This study was designed to identify the change of such buying behaviour of young females on clothing brands. Four archetypes on female buying behaviour of clothing namely “Brand Cognizant”, “Peer Conformist”, “Style Leader” and “Value Seeker” were identified.

By means of the qualitative approach of existential-phenomenological interviews, this paper examines the non-utilitarian and emotional shopping motives and associated hehaviour of young female fashion consumers in Hong Kong. A number of such shopping motives are identified and discussed in the light of the shoppers' buying experience. Implications for fashion marketers are also mentioned.

Since its development by Tinbergen (1962), the gravity model of international trade has widely been applied to analyse the effect of various factors on trade relationships between countries. Past studies on trade gravity vary not only in the mix of model variables but also in how they have come into the analysis. This study reviews existing literature on bilateral trade with an aim to identify influential predictors such as changes of trade policy and national development strategy and highlight important yet understudied factors such as transport and logistics infrastructure, and sustainable development. To demonstrate the needs to examine these critical factors across industry sectors, the study presents the case of textiles and clothing (T&C) production and trade between China and its trading partners as an illustration. Through the literature review, it shows how the gravity model can be applied to address current issues in international trade arena such as the potential trade war between the US and China, China's Belt and Road Initiative (BRI), and other important factors shaping global T&C trade. This study offers future research directions for analysis of global trade in the T&C industry and contributes to the wider literature of international business and trade.

Background3D virtual simulation prototyping software combined with computer-aided manufacturing systems are widely used and are becoming essential in the fashion industry in the earlier stages of the product development process for apparel design. These technologies streamline the garment product fitting procedures, as well as improve the supply chain environmentally, socially, and economically by eliminating large volumes of redundant samples. Buyers can easily evaluate virtual samples that are showcased with full rotation views and visual draping effects without relying on physical prototypes before confirming orders. The approved designs can be transferred to the production line immediately, which shortens the communication, development, and production lead time between suppliers and buyers. Issues of non-standardized selection on garment sizing, ease allowance, and size of 3D avatar for creating 3D garments have been addressed by many researchers. Understanding the relationship between body dimensions, ease allowance, and apparel sizes before adopting virtual garment simulation is fundamental for satisfying high customer demands in the apparel industry. However, designers find difficulties providing the appropriate garment fit for customers without fully understanding the motivation and emotions of customers’ fitting preferences in a virtual world.A statement of objective The main purpose of this study is to investigate apparel sizes for virtual fitting, particularly looking at garment ease with consideration to body dimensions and the psychographic characteristics of subjects.SignificanceThe quantitative relationship between the pattern measurements, psychological characteristics, and 3D body measurements contributes to improving virtual fit predictions for implementing mass customization in the apparel industry. This new approach and the proposed method of virtual garment fitting model prediction on garment sizes using an Artificial Neural Network (ANN) is significant in prediction accuracy. The results of this project provide sustainable value in providing an ideal communication tool between manufacturers, retailers, and consumers by offering “perfect fit” products to customers. The project will also achieve the concept of mass customization and customer orientation, and generate new size fitting data that could bring a new level of end-user satisfaction.MethodsThe study proposes to develop a virtual garment fitting prediction model using an ANN for improving virtual garment design in terms of its fitting and sizing. The project investigated apparel sizes for virtual fitting with consideration of body dimensions and psychographic characteristics of subjects on garment ease for improving the size prediction of 3D garments. We recruited 50 subjects between the ages 18-35 years old to conduct 3D body scans and a questionnaire survey for physical and psychological segmentation, as well as fitting preferences evaluation through co-design operations on virtual garment simulation using a commercial software called Optitex. Discussion of resultsThe ease preferences from subjects were significantly different from the preset values on the software. The results from the study demonstrate that ANN is effective in modeling the non-linear relationship between pattern measurements, psychological characteristics, and body measurements. The pattern parameters predicted by the ANN model were accurate. The squared correlation coefficient (R2) increased from 0.96 to 0.99 after considering different segmentations of psychographic characteristics. The ANN prediction model is proven to be an effective method for garment pattern drafting, which can achieve an individual fit and is useful for implementing the virtual fitting model.