Information Visibility and Transparency in Supply Chains:
An Agent-Based Simulation Approach
Supply chain performance is hampered by the effects
of uncertainty. The sources of uncertainty are natural variability due to
the stochastic nature of demand, and systematic variance introduced by the
policies, actions, and delays of supply chain partners. A strategy
for reducing uncertainty is sharing information within the supply chain.
Questions arise as to the scope and degree of information sharing to maximize
benefits. In order to quantify the value of information sharing we have constructed
an agent-based simulation of a distributed supply chain network. Agents in
the supply chain are autonomous decision-making units situated at various
levels of the supply chain (manufacturing, wholesaler, distribution, retail,
etc). Agents are characterized by behavioral decision rules (e.g., ordering
policy, demand forecasting). Using our supply chain simulation, allows us
to quantify risk, and evaluate trade-offs between information sharing and
hiding, and cooperation and competition.
Charles M. Macal
Argonne National Laboratory
Center for Complex Adaptive Systems Simulation, Decision & Information
Sciences Division
macal@dis.anl.gov
Michael J. North
Argonne National Laboratory
Center for Complex Adaptive Systems Simulation, Decision & Information
Sciences Division
north@anl.gov
Edward P. MacKerrow
Los Alamos National Laboratory
Complex Systems Group, Theoretical Division
mackerrow@lanl.gov
George E. Danner
Industrial Science Inc.
george.danner@earthlink.net
Owen Densmore
Complexity Works Consulting
owen@backspaces.net
Joengseob Kim
Daegu University, Republic of Korea
kim@900exch.dis.anl.gov