Notice of RetractionAgent-based modeling of supply chain network for adaptive pricing strategy

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

In a multiple supplier - multiple retailer supply chain network, multiple price competitive forces interact to influence firm price decisions. These forces include: (1) the supplier level competition each supplier faces from others producing the same product, (2) the retailer level competition among the retailers selling the same set of goods, and (3) the vertical interaction competition between the retailer and supplier. This study examines the influence of adaptive pricing strategy on supplier or retailer performance. This investigation views supply networks as a complex adaptive system, uses agent-based modeling and simulation (ABMS) to construct the competitive multiple supplier - multiple retailer supply network, and applies competition theory, fuzzy logic, and genetic algorithms to model the pricing adaptive behavior. The simulation results demonstrate that: Supplier level performance lags retailer level performance, regardless of the type of adaptive pricing strategy suppliers adopt. At the supplier level, the performance of suppliers following an open adaptive pricing strategy (low exploitation high exploration) exceeds that of suppliers following a closed adaptive pricing strategy (high exploitation low exploration). At the retailer level, the performance of retailers following a closed adaptive pricing strategy (high exploitation low exploration) exceeds that of suppliers following an open adaptive pricing strategy (low exploitation high exploration).