Value of Sparse RFID Traceability Information in Asset Tracking during Migration Period

We present a model to infer the location of assets in a supply chain network by using sparse traceability information. We also evaluate the model by a numerical study and get a result that the model successfully differentiate the probability of the location of the lost asset. The sparseness of the traceability information is a typical problem when an existing supply chain is migrating to an RFID-enabled one, and the lack of models that quantitatively show the value of sparse information delays this migration process. Our model is a solution to this situation. The target industry we focus on in this study is the returnable transport item rental service industry, in which RFID deployment has been already started. This model in conjunction with a simulator used to evaluate the model will be used as a tool to accelerate the deployment.