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AML Modeling of Trust in Supply Chain Management

Author

Listed:
  • Yacine Ouzrout
  • S. A. Hossain
  • Olivier Lavastre

    (CERAG - Centre d'études et de recherches appliquées à la gestion - UPMF - Université Pierre Mendès France - Grenoble 2 - CNRS - Centre National de la Recherche Scientifique)

  • Ludivine Chaze-Magnan

    (CERAG - Centre d'études et de recherches appliquées à la gestion - UPMF - Université Pierre Mendès France - Grenoble 2 - CNRS - Centre National de la Recherche Scientifique)

  • Carine Dominguez-Pery

    (CERAG - Centre d'études et de recherches appliquées à la gestion - UPMF - Université Pierre Mendès France - Grenoble 2 - CNRS - Centre National de la Recherche Scientifique)

Abstract

Agent Modeling Language (AML) is a semiformal visual modeling language for specifying, modeling and documenting systems in terms of concepts drawn from Multi Agent Modeling (MAS) theory. Supply chain management (SCM) is the management of network of interconnected business which spans all movements of services and goods from the point of origin to the point of consumption. In SCM, Trust modeling is an important and crucial aspect from the perspective of sustainability of the supply chain and efficient performance in business. In the supply chain, the more we trust, the more we exchange information on demand and on forecast of the last customer so as with the level of stock and on the forecast of the suppliers. In this work, we attempted to model the Trust in SCM using AML and proposed a MAS SCM model of trust in supply chain management. The proposed model is implemented using JADE and the simulation results demonstrated the impact of trust in supply chain along with the evolution of trust.

Suggested Citation

  • Yacine Ouzrout & S. A. Hossain & Olivier Lavastre & Ludivine Chaze-Magnan & Carine Dominguez-Pery, 2010. "AML Modeling of Trust in Supply Chain Management," Post-Print halshs-00641243, HAL.
    • Handle: RePEc:hal:journl:halshs-00641243
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00641243
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