By Clemens van Dinther
In the final years digital markets, specifically on-line auctions, became extremely popular and obtained increasingly more cognizance in either, company (B2B) in addition to in public perform (B2C and C2C). technological know-how, even though, remains to be faraway from having studied all phenomena and results which might be saw on digital markets. This booklet exhibits that and the way software program brokers can be utilized to simulate bidding behaviour in digital auctions. the most emphasis of this e-book is to use computational economics to industry idea. It summarizes the most typical and updated agent-based simulation equipment and instruments and develops the simulation software program AMASE. On foundation of the brought tools a version is proven to simulate bidding behaviour less than uncertainty.
The e-book addresses researchers, desktop scientists, economists and scholars who're drawn to employing agent-based computational how to digital markets. It is helping to profit extra approximately simulations in economics as a rule and customary agent-based equipment and instruments particularly.
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Extra info for Adaptive Bidding in Single-Sided Auctions Under Uncertainty: An Agent-based Approach in Market Engineering
In take-over bidding. Let us assume two competitors that are bidding on the acquisition of a supplier. Competitor A may be able to integrate the supplier and would thereby realise greater synergies than competitor B. Therefore, competitor A values the acquisition higher than competitor B and both competitors have diﬀerent (and independent) private values concerning that issue. 10. Common-values In the common-values model a good has the single true valuation which is the same for every agent, but this value is not known.
2. Market Engineering 37 of the object to be traded. Each party is allowed to choose or associate weights from an underlying ontology; attributes can be chosen as being ﬁx or ﬂexible. The chosen weights determine the utility function, being selected automatically by the software as an element of a set of diﬀerent preference or utility functions MARI oﬀers. Based on the identiﬁed preference function and weights, the system matches possible sellers to buyers due to a certain request and determines the price to pay.
602]. In the Englishauction model the expected takeover price is the minimum of the valuation of the two bidders. In this case the takeover price is maximized if the costs for information acquisition are minimized. In the author’s model with costly information, the ﬁrst bidder’s willingness to incur the acquisition costs may result in a high signal that deters competing bidders, and thus, avoids costly counterbidding. This might lead to a takeover price below the minimum of the two valuations also in cases where both bidders make oﬀers.