Using an intelligent agent to classify competitor behavior and develop an effective E-market counterstrategy

Internet markets allow online sellers to rapidly update prices. By employing intelligent software agents known as pricebots, the re-pricing process can be streamlined and automated. Developing the pricebot re-pricing logic requires an understanding of the optimal pricing strategy in relation to competitors’ strategies. simulation to construct a decision table of the most effective counterstrategy for several competitor strategy combinations. We then design a neural network for classifying the strategies of the competition, which allows us to look up the optimal counterstrategy in the decision table. Our findings indicate that a pricebot armed with the decision table and neural network classifier can recognize when the market is such that no entrant can gain a profit advantage beyond the profit achieved at a common price floor, and in other cases where higher profits are possible, the agent is able to achieve statistically significant profit improvements over the no-pricebot case.