Consumers' perceived quality of imported product has been an impediment to business in the Nigeria garment industry. To improve patronage of made-in-Nigeria garment designs, the first step is to understand what the consumer expects, then proffer ways to meet this expectation through product redesign or improvement of the garment mass production process. The purpose of this study is to investigate drivers of consumers' value for typical Nigerian garment design (NGD). Using survey data from 522 respondents, an integrated quality function deployment (QFD) and functional, expressive and aesthetic (FEA) Consumer Needs methodology helps to minimize incorrect understanding of potential consumer's requirements in mass produced garments. Out of the sixteen identified quality characteristics, six themes emerged as drivers of consumer's satisfaction: (1) Style variety (2) Dimensions (3) Finishing (4) Fabric quality (5) Garment Durability and (6) Aesthetics. Existing NGD is found to lead foreign designs in terms of its acceptance for informal events, style variety and fit while there is a need for improvement of other quality characteristics. Local designers may consider adoption of QFD-FEA framework to improve quality of NGD, overall customer's acceptance and NGD mass production process. A conceptual model of NGD acceptance in the context of consumer's inherent characteristics, social and the business environment is proposed.

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Recognition of clothing categories is an appealing study to emerging applications such as computer aided fashion design for mass customization and e-commerce. In the study, the description and classification of clothing styles is established based on the preference index heuristic. Specifically, we take advantage of consumer’s visual perception of clothing and their free choice description to; understand, characterise and, classify clothing styles. Evaluated on a dataset with 60 style samples of male clothing, the procedure demonstrates promising results in recognizing five clothing categories. Keyword: Clothing, Semantic Attributes, Heuristics, Styles, Computer-Aided Fashion Design

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