dc.contributor.advisor | Jérémie Gallien, David Roylance and Felipe Caro. | en_US |
dc.contributor.author | Correa, Juan R. (Juan Roza) | en_US |
dc.contributor.other | Leaders for Manufacturing Program. | en_US |
dc.date.accessioned | 2007-11-16T14:30:35Z | |
dc.date.available | 2007-11-16T14:30:35Z | |
dc.date.copyright | 2007 | en_US |
dc.date.issued | 2007 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/39596 | |
dc.description | Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2007. | en_US |
dc.description | Includes bibliographical references (p. 69). | en_US |
dc.description.abstract | Inditex is one of the world's largest fashion distributors, operating 3,100 stores in 64 countries; its brands currently include Zara, Pull and Bear, Massimo Dutti, Bershka, Stradivarius, Oysho, Zara Home and Kiddy's Class. The group's flagship company is Zara, which is the world's largest "fast fashion" company: through unique and carefully integrated design, manufacturing and distribution processes, Zara routinely achieves design-to-shelf leadtimes of 6 weeks against an industry average of 6 months, and introduces 11,000 references per season against an industry average of 3,000. Throughout the season, Zara currently ships every new incoming product to all 950 stores comprising its distribution network at the same time. Its operations group has recognized a large opportunity in customizing the assortment of products offered in each store based on local sales, and staggering shipments to stores of each new reference in order to acquire more accurate sales forecast and enable better subsequent inventory allocation decisions. My thesis will detail the development and implementation of new optimization models for dynamically allocating inventory across Zara's distribution network. | en_US |
dc.description.abstract | (cont.) It will build upon and expand an ongoing collaboration between Zara and a team of two faculty at MIT (Pr. Jeremie Gallien) and UCLA (Pr. Felipe Caro). In addition, it will also explore five of the most used fabrics in manufacturing in order to satisfy the "fast fashion" model. It will describe the preferred fabric properties and any manufacturing issues that arise as a result of the fabric choices. Specifically, it will detail how changes in the structure of the fabric affect its final properties. | en_US |
dc.description.statementofresponsibility | by Juan R. Correa. | en_US |
dc.format.extent | 80 p. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.rights | M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. | en_US |
dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | |
dc.subject | Sloan School of Management. | en_US |
dc.subject | Materials Science and Engineering. | en_US |
dc.subject | Leaders for Manufacturing Program. | en_US |
dc.title | Optimization of a fast-response distribution network | en_US |
dc.type | Thesis | en_US |
dc.description.degree | S.M. | en_US |
dc.description.degree | M.B.A. | en_US |
dc.contributor.department | Leaders for Manufacturing Program at MIT | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Materials Science and Engineering | |
dc.contributor.department | Sloan School of Management | |
dc.identifier.oclc | 176090173 | en_US |