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The authors propose a model that describes how Auto-ID observations across a supply chain and historical observation data can be combined to produce an ongoing order location estimation over time. The model is based on probabilistic reasoning principles and the resulting location estimation can be used to support operational decisions as well as to assess the quality and value of tracking information. The authors provide explicit instructions as to how to use the proposed model and using an illustrative example, they demonstrate how the model can produce ongoing location estimates based on RFID read events.<\/p>","DOI":"10.4018\/jisscm.2012100101","type":"journal-article","created":{"date-parts":[[2012,9,26]],"date-time":"2012-09-26T01:18:07Z","timestamp":1348622287000},"page":"1-22","source":"Crossref","is-referenced-by-count":5,"title":["A Supply Chain Tracking Model Using Auto-ID Observations"],"prefix":"10.4018","volume":"5","author":[{"given":"Thomas","family":"Kelepouris","sequence":"first","affiliation":[{"name":"Institute for Manufacturing, University of Cambridge, Cambridge, UK"}]},{"given":"Duncan","family":"McFarlane","sequence":"additional","affiliation":[{"name":"Institute for Manufacturing, University of Cambridge, Cambridge, UK"}]},{"given":"Vaggelis","family":"Giannikas","sequence":"additional","affiliation":[{"name":"Institute for Manufacturing, University of Cambridge, Cambridge, UK"}]}],"member":"2432","reference":[{"key":"jisscm.2012100101-0","doi-asserted-by":"publisher","DOI":"10.4018\/jisscm.2010092905"},{"key":"jisscm.2012100101-1","doi-asserted-by":"publisher","DOI":"10.4018\/jisscm.2008100101"},{"key":"jisscm.2012100101-2","doi-asserted-by":"publisher","DOI":"10.1145\/1076211.1076212"},{"key":"jisscm.2012100101-3","doi-asserted-by":"publisher","DOI":"10.2307\/3007756"},{"key":"jisscm.2012100101-4","doi-asserted-by":"publisher","DOI":"10.1016\/0040-1625(79)90077-5"},{"key":"jisscm.2012100101-5","unstructured":"Cambridge University. 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