Existing e-commerce systems employ a pull model of marketing where buyers, possibly through agents, search the e-market for suppliers offering the product of their choice. In contrast, the push model where supplier's agents approach buyers with their products, has been relatively less investigated. Push strategies are particularly appropriate for commodities that have a short shelf-life and, therefore, an elastic demand curve, allowing suppliers to exploit unexpected supply. The speed and low cost of e-commerce makes it particularly suited to the push paradigm.
We consider time-limited goods in a supplier driven marketplace that employs the push model of marketing. When constrained by a strict deadline to sell the good, the supplier uses a mobile sales agent that visits every buyer and estimates the short run demand curve of the good. At every buyer, the sales agent also employs a heuristic technique called the Maximum Returns Algorithm to recalculate the price of the good, so that the supplier can obtain the best possible gross returns from trading with the buyers. On the other hand, when the deadline to sell is not stringent, the sales agent negotiates the exchange at a point that improves both the buyer's utility and the supplier's profit, as compared to the exchange point without negotiation. Our company evaluates the performance of two multi-object auction models: sequential and simultaneous, using different performance measures. The objects put up for auction have different synergies for different bidders. We define different types of bidders who can exist in these multi-object auction models. The classification of bidders is based on the bidding strategies they use. We then study the effects of different parameters in auction and bidding strategies, on the performance of these auction models by simulating them using a JAVA based framework.
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