Assessment of EPCIS standard for interoperable tracking in the supply chain

Kary Främling (Corresponding author), Sagar Parmar, Ville Hinkka, Jaakko Tätilä, Dirk Rodgers

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

16 Citations (Scopus)

Abstract

With increasing globalization and loosely-coupled business relations between different companies, the importance of information exchange standards is increasing. GS1's Electronic Product Code Information Services (EPCIS) is currently one of the main standards proposed for inter-organizational data exchange for track and trace purposes in the supply chain. However, despite its strong industrial background and maturity, EPCIS is not yet used as a global standard for trace and track applications. This paper attempts to analyze why EPCIS has not been universally adopted as a global data-exchange standard for track and trace by analyzing three application areas where the use of EPCIS should provide substantial benefits. The results of this analysis should provide useful insights into the challenges of introducing new, global standards and guidelines for similar initiatives in the future.

Original languageEnglish
Title of host publicationService Orientation in Holonic and Multi Agent Manufacturing and Robotics
PublisherSpringer
Pages119-134
Number of pages16
ISBN (Electronic)978-3-642-35852-4
ISBN (Print)978-3-642-35851-7
DOIs
Publication statusPublished - 1 Jan 2013
MoE publication typeA4 Article in a conference publication

Publication series

SeriesStudies in Computational Intelligence
Volume472
ISSN1860-949X

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Keywords

  • EPCIS
  • Inter-organizational data exchange
  • Interoperability
  • Supply chain management
  • Track and trace

Cite this

Främling, K., Parmar, S., Hinkka, V., Tätilä, J., & Rodgers, D. (2013). Assessment of EPCIS standard for interoperable tracking in the supply chain. In Service Orientation in Holonic and Multi Agent Manufacturing and Robotics (pp. 119-134). Springer. Studies in Computational Intelligence, Vol.. 472 https://doi.org/10.1007/978-3-642-35852-4_8