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Towards the Meta-Modeling of Complex Inter-Organisationnel Collaborative Processes

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  • Kahina Semar-Bitah

    (Centre de Développement des Technologies Avancées and Université Badji Mokhtar Annaba, Annaba, Algeria)

  • Kamel Boukhalfa

    (USTHB University, Bab Ezzouar, Algeria)

Abstract

Enterprises are progressively embedded in business to business atmospheres, in order to achieve their common business objectives. Such collaborations lead to Inter-Organizational Business Processes. Therefore, IOBP modeling involves new challenges, mainly the ability to deal with autonomy, privacy, heterogeneity. As a contribution in this area, a IOBP meta-model was designed. This model takes into account the maximum concepts related to the collaboration. Where, the process is complex, and its model in a global way affects its vision and complicates its implementation and hence the idea of its analysis into sub-IOBP to reduce the complexity of the global collaborative process, to streamline information exchange and to facilitate the understanding of the process by partners. A set of Atlas Transformation Language (ATL) transformation rules has been defined to convert Unified Modeling Language (UML) models to Business Process Model and Notation. Finally, the application of our approach has been demonstrated through a framework which can solve the problem of generic IOBP.

Suggested Citation

  • Kahina Semar-Bitah & Kamel Boukhalfa, 2019. "Towards the Meta-Modeling of Complex Inter-Organisationnel Collaborative Processes," International Journal of E-Business Research (IJEBR), IGI Global, vol. 15(3), pages 16-34, July.
    • Handle: RePEc:igg:jebr00:v:15:y:2019:i:3:p:16-34
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    Cited by:

    1. Vítor Ribeiro & João Barata & Paulo Rupino Cunha, 2024. "Modeling inter-organizational business process governance in the age of collaborative networks," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-27, December.
    2. Cindy-Pamela Lopez & Jose Aguilar & Marco Santorum, 2023. "Autonomous VOs management based on industry 4.0: a systematic literature review," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1275-1291, March.

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