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Analyzing inter-organizational business processes

Author

Listed:
  • Robert Engel

    (Vienna University of Technology)

  • Worarat Krathu

    (Vienna University of Technology)

  • Marco Zapletal

    (Vienna University of Technology)

  • Christian Pichler

    (Vienna University of Technology)

  • R. P. Jagadeesh Chandra Bose

    (Vienna University of Technology)

  • Wil Aalst

    (Vienna University of Technology)

  • Hannes Werthner

    (Vienna University of Technology)

  • Christian Huemer

    (Vienna University of Technology)

Abstract

Companies are increasingly embedded in B2B environments, where they have to collaborate in order to achieve their goals. Such collaborations lead to inter-organizational business processes that may be commonly supported through the exchange of electronic data interchange (EDI) messages (e.g., electronic purchase orders, invoices etc.). Despite the appearance of XML, traditional approaches to EDI, such as EDIFACT and ANSI X.12, still play an overwhelmingly dominant role. However, such traditional EDI standards lack a notion of process. In other words, the exchanged business documents are typically not embedded in the context of other exchanged business documents. This has two shortcomings: (1) the inability to apply proven business process management (BPM) methods, including process mining techniques, in such settings; and (2) the unavailability of systematic approaches to business intelligence (BI) using information from exchanged EDI messages. In this article, we present the EDImine Framework for enabling (1) the application of process mining techniques in the field of EDI-supported inter-organizational business processes, and (2) for supporting inter-organizational performance evaluation using business information from EDI messages, event logs and process models. As an enabling technology, we present a method for the semantic preprocessing of EDIFACT messages to exploit this potentially rich source of information by applying state of the art BPM and BI techniques. We show the applicability of our approach by means of a case study based on real-world EDI data of a German consumer goods manufacturing company.

Suggested Citation

  • Robert Engel & Worarat Krathu & Marco Zapletal & Christian Pichler & R. P. Jagadeesh Chandra Bose & Wil Aalst & Hannes Werthner & Christian Huemer, 2016. "Analyzing inter-organizational business processes," Information Systems and e-Business Management, Springer, vol. 14(3), pages 577-612, August.
  • Handle: RePEc:spr:infsem:v:14:y:2016:i:3:d:10.1007_s10257-015-0295-2
    DOI: 10.1007/s10257-015-0295-2
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    References listed on IDEAS

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    1. J P C Kleijnen & M T Smits, 2003. "Performance metrics in supply chain management," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(5), pages 507-514, May.
    2. Kleijnen, J.P.C. & Smits, M.T., 2003. "Performance metrics in supply chain management," Other publications TiSEM 80777aed-0c9f-4ded-b0bb-f, Tilburg University, School of Economics and Management.
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    Cited by:

    1. Fatao Wang & Lihui Ding & Hongxin Yu & Yuanjun Zhao, 2020. "Big data analytics on enterprise credit risk evaluation of e-Business platform," Information Systems and e-Business Management, Springer, vol. 18(3), pages 311-350, September.
    2. Fatao Wang & Lihui Ding & Hongxin Yu & Yuanjun Zhao, 0. "Big data analytics on enterprise credit risk evaluation of e-Business platform," Information Systems and e-Business Management, Springer, vol. 0, pages 1-40.
    3. Wei Li & Qiling Zhou & Junying Ren & Samantha Spector, 2020. "RETRACTED ARTICLE: Data mining optimization model for financial management information system based on improved genetic algorithm," Information Systems and e-Business Management, Springer, vol. 18(4), pages 747-765, December.

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