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Agent Based Simulation of Business Model Ontologies Value in Enterprise Context

Application to the Customer Relationship Management

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Intelligent Systems and Applications (IntelliSys 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 869))

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Abstract

The Business Value of new technologies is not trivial to evaluate. Using simulation can contribute to understand the impact of using ontologies in enterprise context when practical cases are scarce or when the technology is embedded behind a software system. Focusing on Business Model Ontologies (BMOs) and Customer Relationship Management (CRM) business function, this paper describes: (1) the architecture; (2) the implementation (including the internal behaviour); and (3) a first experimentation of the Business Model Ontology Simulator (BMOSIM). It aims at evaluating the impact of BMOs on the enterprise performance through the use of the Agent-Based Simulation (ABS) through the MaDKit platform.

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Author information

Authors and Affiliations

  1. Ecole Supérieure en Informatique, Sidi-Bel-Abbès, Algeria

    Hichem Benaissa Anouar Badsi

  2. LMCS Laboratory, Ecole Nationale Supérieure d’Informatique (ESI), Algiers, Algeria

    Abessamed Réda Ghomari

  3. Ecole Nationale Supérieure de Technologie (ENST), Algiers, Algeria

    Leila Zemmouchi-Ghomari

Authors
  1. Hichem Benaissa Anouar Badsi
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  2. Abessamed Réda Ghomari
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  3. Leila Zemmouchi-Ghomari
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Corresponding author

Correspondence to Hichem Benaissa Anouar Badsi .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, UK

    Rahul Bhatia

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Badsi, H.B.A., Ghomari, A.R., Zemmouchi-Ghomari, L. (2019). Agent Based Simulation of Business Model Ontologies Value in Enterprise Context. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 869. Springer, Cham. https://doi.org/10.1007/978-3-030-01057-7_55

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