IDEAS home Printed from https://ideas.repec.org/a/jas/jasssj/1998-3-1.html
   My bibliography  Save this article

Simulation of Order Fulfillment in Divergent Assembly Supply Chains

Author

Listed:

Abstract

Management of supply chains is a difficult task involving coordination and decision-making across organizational boundaries. Computational modeling using multi-agent simulation is a tool that can provide decision support for supply chain managers. We identify the components of a supply chain model and implement it in the Swarm multi-agent simulation platform. The model is used to study the impact of information sharing on order fulfillment in divergent assembly supply chains (commonly associated with the computer and electronics industries). We find that efficient information sharing enables inventory costs to be reduced while maintaining acceptable order fulfillment cycle times. This is true because information, which provides the basis for enhanced coordination and reduced uncertainty, can substitute for inventory.

Suggested Citation

  • Troy J Strader & Fu-ren Lin & Michael J Shaw, 1998. "Simulation of Order Fulfillment in Divergent Assembly Supply Chains," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 1(2), pages 1-5.
    • Handle: RePEc:jas:jasssj:1998-3-1
    as

    Download full text from publisher

    File URL: http://jasss.soc.surrey.ac.uk/1/2/5/5.pdf
    Download Restriction: no

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Uwe Cantner & Ivan Savin & Simone Vannuccini, 2019. "Replicator dynamics in value chains: explaining some puzzles of market selection," Industrial and Corporate Change, Oxford University Press, vol. 28(3), pages 589-611.
    2. Whan-Seon Kim, 2009. "Effects of a Trust Mechanism on Complex Adaptive Supply Networks: An Agent-Based Social Simulation Study," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(3), pages 1-4.
    3. Gek Woo Tan & Michael J. Shaw & Bill Fulkerson, 2000. "Web-based Supply Chain Management," Information Systems Frontiers, Springer, vol. 2(1), pages 41-55, January.
    4. Ojha, Divesh & Sahin, Funda & Shockley, Jeff & Sridharan, Sri V., 2019. "Is there a performance tradeoff in managing order fulfillment and the bullwhip effect in supply chains? The role of information sharing and information type," International Journal of Production Economics, Elsevier, vol. 208(C), pages 529-543.
    5. Fu-ren Lin & Shyh-ming Lin, 2006. "Enhancing the Supply Chain Performance by Integrating Simulated and Physical Agents into Organizational Information Systems," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(4), pages 1-1.
    6. Wei, Zelong & Song, Xi & Wang, Donghan, 2017. "Manufacturing flexibility, business model design, and firm performance," International Journal of Production Economics, Elsevier, vol. 193(C), pages 87-97.
    7. Roberto Dominguez & Salvatore Cannella, 2020. "Insights on Multi-Agent Systems Applications for Supply Chain Management," Sustainability, MDPI, Open Access Journal, vol. 12(5), pages 1-13, March.
    8. Luca Iandoli & Elio Marchione & Cristina Ponsiglione & Giuseppe Zollo, 2009. "Learning and Structural Properties in Small Firms’ Networks: A Computational Agent-Based Model," Research in Economics and Business: Central and Eastern Europe, Tallinn School of Economics and Business Administration, Tallinn University of Technology, vol. 1(1).
    9. Emerson, Denise & Zhou, Wei & Piramuthu, Selwyn, 2009. "Goodwill, inventory penalty, and adaptive supply chain management," European Journal of Operational Research, Elsevier, vol. 199(1), pages 130-138, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jas:jasssj:1998-3-1. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Flaminio Squazzoni). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.