Abstract
Electronic markets provide virtual places for negotiation over the exchange of products. In such places entities representing buyers and sellers can interact and agree upon a product price. Both parties try to maximize their profit. The authors model such an interaction as a finite horizon bargaining game and try to quantify the maximum time of seller participation in the game. The estimated deadline indicates until when the interaction is profitable for the seller. The authors’ model defines the appropriate value for a patience factor which finally results in the seller deadline fully adapted in each product characteristics.
TopMarketplace Business Model
EMs are virtual places where entities present, negotiate and agree upon the purchase of specific products. When the negotiated products are pieces of information such markets are termed Information Markets (IMs). Information has a number of specific characteristics which differentiates it from the classical products such electronics, books, etc. First of all, the economics of information production indicate that the information production costs more when the first copy is produced and less for the additional pieces. Furthermore, information can be characterized as out-of-date more easily than classical products. For example, a stock price has greater value for limited time duration. Hence, sellers want to sell such products as soon as possible. Finally, information is always available to buyers. A seller negotiating DVD players has limited capabilities of delivery which can have negative result when they run out of products.
In general, EMs involve two main groups of entities: the buyers and the sellers. Buyers try to buy products at the lowest possible price while sellers try to sell products at the highest possible price. It is obvious, that there is a conflict of interests between these two groups. Hence, we can focus on their direct interaction and model this interaction as a Bargaining Game (BG) with incomplete information (Fudenberg & Tirole, 1991). Game theory (Rubinstein & Osborne, 1994) has been extensively studied by the research community. BGs have been thoroughly reviewed in Rubinstein’s study (1985a; 1985b). Rubinstein has studied a BG with alternating offers and has defined the equilibrium for such games. Fudenberg and Tirole (1983) studied a simple two person two-period BG and presented a solution using the perfect Bayesian equilibrium approach. However, there is a difficulty when studying BGs under incomplete knowledge.
Key Terms in this Chapter
Fuzzy Rule Base: A set of If-then rules which consists of the main reasoning component of a fuzzy system.
Fuzzy Logic: Mathematical technique for dealing with imprecise or incomplete information in a specified scenario.
Information market: Electronic market where the negotiated product is information.
Pricing Function: A function which results the price that an entity proposes when negotiating in an electronic market.
Intelligent Agent: Autonomous software component acting on behalf of its owner. It can learn its owner characteristics and preferences.
Seller Deadline: The time limit for which the seller stays in an interaction procedure with potential buyers.
Electronic market: A place where entities can negotiate and agree upon the exchange of products.