(1) Model elements and relationships: supply chains assume an integrated approach
to physical transformation, data processing, and decision-making. Especially, the
allocation of control policies to specific chain members, and relationships, such as
hierarchy and coordination, deserve explicit attention as decision variables. This
requires the explicit notion of actors, roles, control policies, processes, and flows in
the model.
(2) Model dynamics: the control of dynamic effects within the supply chain, as reflected
in e.g., stock levels and lead times, is an important issue given the many parties
involved. Therefore, the logistics of control, i.e., the timing and execution of
decision activities, should be explicit. This requires the ability to determine the
dynamic system state, calculate the values of multiple performance indicators at all
times, and even more important, allocate performance indicators to the relevant
supply chain stages.
(3) User interface: the active and joint participation of the problem owners, i.e., the
supply chain partners, in the simulation study is required for two reasons
(Hurrion 1991, McHaney and Cronan 1998, Bell et al. 1999, Robinson 2002).
First, as a means to create trust in the solution and among the parties involved,
so there is a better chance of acceptance of the outcomes of the study. Second,
the quality of the solution may be improved. This refers to model correctness as
well as the performance of the chain scenario. Clearly, it is almost impossible
for the analyst to have all relevant information on chain dynamics. Therefore,
the domain related contribution of the problem owner in terms of alternative
solutions is vital to the success of the project. Given the foreseen role of the
problem owners, an explicit choice and representation of decision variables that
appeal to their imagination is important. This boils down to visibility and