Limiting Obstacles to Success of RFID and the EPCglobal Network in Logistics

  • Dieter Uckelmann
Chapter
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Abstract

The technical advantages of RFID over barcode, such as no need for a line of site and bulk reading capabilities, have raised high hopes for RFID to close the information gap between the ‘real’ and the ‘virtual’ world (Fleisch et al. 2005). The goal of this chapter is to prove and explain why RFID, while offering new potentials, yet has failed to revolutionise the market. Firstly, there is an introduction to the history and the technical fundamentals of RFID and related technologies in order to provide the relevant background information. Secondly, a qualitative analysis of economic predictions, based on publicly available analyst reports and research studies, is provided. It will be shown that an unclear ROI and difficult or missing cost benefit allocation are two important reasons for the slow adoption of RFID in supply chains. Thirdly, the basics of the EPCglobal Framework Architecture, which is the most accepted technical approach concerning a networked infrastructure for product-related information exchange between businesses based on RFID, are explained. Fourthly, the currently limited business model of the EPCglobal Network is analysed based on the business model canvas from Osterwalder and Pigneur (2010). Finally, a larger vision of the Internet of Things, including a definition and a technical framework, is developed in the last paragraph of this chapter. The gap between the EPCglobal Network and the Internet of Things, which provides a more open, comprehensive and feature-rich approach, stretching beyond supply-chain optimisation and embracing companies, public institutions and private end-users, is clarified. Anyhow, the EPCglobal Framework Architecture provides a flexible design that may be used as a fundament for further extensions towards a more holistic Internet of Things infrastructure.

Keywords

Supply Chain Discovery Service Electronic Product Code Business Model Canvas Application Level Event 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dieter Uckelmann
    • 1
  1. 1.HFT StuttgartStuttgartGermany

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