DECODING TACIT KNOWLEDGE IN TECHNICAL DESIGN
| dc.contributor.author | Yang, Yoon | |
| dc.contributor.chair | Baytar, Fatma | en_US |
| dc.contributor.committeeMember | Humphreys, Lee | en_US |
| dc.date.accessioned | 2023-03-31T16:40:43Z | |
| dc.date.issued | 2022-12 | |
| dc.description | 99 pages | en_US |
| dc.description.abstract | This study attempted to understand fit sessions in the apparel product development process and focused on capturing the tacit knowledge of technical design team members. Because fit sessions have not been studied thoroughly as they were considered company secrets, the study also proposed a new framework for documenting the fit session decision-making process, which combined the team mental model and seeing-moving-seeing methods. Data collection included one case study of fit session observation with follow-up interviews and individual interviews with five fit models. Participants of the study were recruited by snowball sampling and word of mouth. The findings provided a broad set of insights around the tacit knowledge of technical designers and fit models and how they make decisions during fit sessions. It was found that to solve garment fit issues, technical designers had priorities in resolving them as some of these solutions derived from misfit cases observed on different garments. The power dynamics in the fit sessions kept changing as each fit session participant had their own professional knowledge. This study also highlighted the various topics discussed in fit sessions. These insights could be beneficial for the fashion technology industry as they develop new technologies to support the apparel product development process as well as for the apparel brands as they develop a competitive edge through utilizing stored tacit knowledge to simplify fit sessions. | en_US |
| dc.identifier.doi | https://doi.org/10.7298/fnmx-a276 | |
| dc.identifier.other | Yang_cornell_0058_11634 | |
| dc.identifier.other | http://dissertations.umi.com/cornell:11634 | |
| dc.identifier.uri | https://hdl.handle.net/1813/113059 | |
| dc.language.iso | en | |
| dc.title | DECODING TACIT KNOWLEDGE IN TECHNICAL DESIGN | en_US |
| dc.type | dissertation or thesis | en_US |
| dcterms.license | https://hdl.handle.net/1813/59810.2 | |
| thesis.degree.discipline | Fiber Science and Apparel Design | |
| thesis.degree.grantor | Cornell University | |
| thesis.degree.level | Master of Arts | |
| thesis.degree.name | M.A., Fiber Science and Apparel Design |
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