{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T23:20:17Z","timestamp":1769815217830,"version":"3.49.0"},"reference-count":30,"publisher":"World Scientific Pub Co Pte Lt","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Info. Tech. Dec. Mak."],"published-print":{"date-parts":[[2006,12]]},"abstract":"<jats:p> Customized goods and services occur when their respective supply and demand chains are managed in a simultaneous and real-time manner. From a research perspective, we classify the methods that are employed in the management of these chains, based on whether supply and\/or demand are flexible or fixed. Interestingly, our classification scheme highlights a critical and rewarding research area at which both supply and demand are flexible, thus manageable. Simultaneous management of supply and demand chains sets the stage for mass customization which is concerned with meeting the needs of an individualized customer market. Simultaneous and real-time management of supply and demand chains, in turn, set the stage for real-time mass customization (e.g. wherein a tailor first laser scans an individual's upper torso and then delivers a uniquely fitted jacket within a reasonable period, while the individual is waiting). The benefits of real-time mass customization cannot be over-stated as products and services become indistinguishable and are co-produced in real-time, resulting in an overwhelming economic advantage. Customized goods and services can only be achieved through sophisticated data mining techniques that can define the customization requirements from both a supply and a demand chain perspective, techniques that can obtain pertinent information from the mass of non-homogeneous data, in order to make informed customization decisions. <\/jats:p>","DOI":"10.1142\/s0219622006002167","type":"journal-article","created":{"date-parts":[[2006,12,12]],"date-time":"2006-12-12T07:59:30Z","timestamp":1165910370000},"page":"683-698","source":"Crossref","is-referenced-by-count":16,"title":["DATA MINING REQUIREMENTS FOR CUSTOMIZED GOODS AND SERVICES"],"prefix":"10.1142","volume":"05","author":[{"given":"JAMES M.","family":"TIEN","sequence":"first","affiliation":[{"name":"Department of Decision Sciences and Engineering Systems, Rensselaer Polytechnic Institute, Troy, New York 12180, USA"}]}],"member":"219","published-online":{"date-parts":[[2011,11,20]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1108\/09600039210016995"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1108\/09600039410070975"},{"key":"rf3","first-page":"10","volume":"36","author":"Quinn F. 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