Deliverables 2002, Quarter 1-3

Some papers may only be accessible by members of the Trade Agents project.

[2D2.2] Bundling and Recommendation for Information Brokerage. (restricted access only)
In this paper, we discuss some of the consequences on-line dynamic bundling and/or pricing of (information) goods, and (automatic) recommender systems can have for information brokerage. We argue that dynamic bundling/pricing enhances especially the value extracting (or profit generating) capacity of an information broker. Recommerder systems, on the other hand, enhance through, for example, customer lock-in especially the value generating capacity of an information broker. More traditional (automatic) recommender systems have a number of drawbacks. We outline how recommendation based on sales statictics can circumvent these difficulties. We discuss especially the advantages and challenges of integrating dynamic bundling/pricing into such recommender systems. Keywords: value creation; value extraction; information brokerage; dynamic pricing; recommender systems.

[2D2.1] An Agent-Based Simulation for Market-Based Consumer Attention Allocation. (restricted access only)
In today's society consumers are exceedingly overwhelmed with both relevant and irrelevant information, the latter becoming more and more of a problem.This is especially pronounced on the Internet, where many advertisers attempt to reach potential customers. Lately, however, the traditional and undirected advertisements in the form of banners have shown to be less effective than predicted profit-wise. As a result, more and more companies focus on presenting targeted ads, which take into account information like the consumer's background and presumed product proferences. Displaying fewer but more relevant ads shown to be more effective, and as a result consumer-level marketinginformation has become a valueable asset.

[2D1.1] Bargaining with Posterior Opportunities: An Evolutionary Social Simulation (restricted access only)
Negotiations have been extensively studied theoretically throughout the years. A well-known bilateral approach is the ultimatum game, where two agents negotiate on how to split a pie or a "dollar": the proposer makes an offer and responder can choose to accept or reject. In this paper a natural extension of the ultimatum game is presented, in which both agents can negotiate with other opponents in case of a disagreement. This way the basics of a competetive market are modelled where for instance a buver can try several sellers before making a purchase decision. The game is investigated using an evolutionary simulation. The outcomes appaer to depend largely on the information available to th agents. We find that if the agents' number of future bargaining opportunities is commonly known, the proposer has the advantage. If this information is held private, however, the responder can obtain a larger share of the pie. For the first case we also provide a game-theoretic analysis and compare the outcome with evolutionary results. Furthermore, the effects of search costs and allowing multiple issues to be negotiated simultaneously are investigated.

[2D6.1] Business Case 'Financial Information Brokerage' (restricted access only)