Much of the emphasis on competitiveness in the past decade has been focused on re-engineering
processes. Out of the re-engineering processes, new technical capabilities have emerged that can
allow manufacturers and retailers the ability to close the gap between what they provide to the
marketplace and what the consumer actually purchases. The potential to develop technologies that
allow the consumer to generate the sale to make the decisions up front removes the impact of
guesswork, forecasting, and large inventories for retailers and manufacturers.
This project is unique in that it focuses on understand consumer preferences. A key component
for industry competitiveness is not that we can obtain critical body measurements but that we
understand how to translate these measurements into apparel items that satisfactorily fit what are
becoming more and more diverse consumer segments. The process of accessing fit appears to be
straightforward, but consumers consistently list fit among their major dissatisfactions with garment
purchases. One recent study of sizing (Goldsberry, 1993) found that 69% of over 4,000
respondents were dissatisfied with the fit of read-to-wear.
Fit is a significant problem for retailers. This problem is compounded for retailers and direct
marketers who sell prepackaged apparel. The emerging potential for increased apparel sales in an
electronic environment heightens the need to better define fit from a consumer perspective. This project complements and extends the technical work currently in process at [TC]2, University of North Carolina in Greensborough, and Nottingham Trent University.
Intelligent Systems
Sponsored by the
National Textile Center
