Bidding Behavior (bidding + behavior)

Distribution by Scientific Domains
Business, Economics, Finance and Accounting100%

Selected Abstracts

Reverse Auctions with Multiple Reinforcement Learning Agents,

DECISION SCIENCES, Issue 1 2008
Subhajyoti Bandyopadhyay
ABSTRACT Reverse auctions in business-to-business (B2B) exchanges provide numerous benefits to participants. Arguably the most notable benefit is that of lowered prices driven by increased competition in such auctions. The competition between sellers in reverse auctions has been analyzed using a game-theoretic framework and equilibria have been established for several scenarios. One finding of note is that, in a setting in which sellers can meet total demand with the highest-bidding seller being able to sell only a fraction of the total capacity, the sellers resort to a mixed-strategy equilibrium. Although price randomization in industrial bidding is an accepted norm, one might argue that in reality managers do not utilize advanced game theory calculations in placing bids. More likely, managers adopt simple learning strategies. In this situation, it remains an open question as to whether the bid prices converge to the theoretical equilibrium over time. To address this question, we model reverse-auction bidding behavior by artificial agents as both two-player and n -player games in a simulation environment. The agents begin the game with a minimal understanding of the environment but over time analyze wins and losses for use in determining future bids. To test for convergence, the agents explore the price space and exploit prices where profits are higher, given varying cost and capacity scenarios. In the two-player case, the agents do indeed converge toward the theoretical equilibrium. The n -player case provides results that reinforce our understanding of the theoretical equilibria. These results are promising enough to further consider the use of artificial learning mechanisms in reverse auctions and other electronic market transactions, especially as more sophisticated mechanisms are developed to tackle real-life complexities. We also develop the analytical results when one agent does not behave strategically while the other agent does and show that our simulations for this environment also result in convergence toward the theoretical equilibrium. Because the nature of the best response in the new setting is very different (pure strategy as opposed to mixed), it indicates the robustness of the devised algorithm. The use of artificial agents can also overcome the limitations in rationality demonstrated by human managers. The results thus have interesting implications for designing artificial agents in automating bid responses for large numbers of bids where human intervention might not always be possible. [source]

Precautionary Bidding in Auctions

ECONOMETRICA, Issue 1 2004
Péter Esö
We analyze bidding behavior in auctions when risk-averse buyers bid for a good whose value is risky. We show that when the risk in the valuations increases, DARA bidders will reduce their bids by more than the appropriate increase in the risk premium. Ceteris paribus, buyers will be better off bidding for a more risky object in first price, second price, and English auctions with affiliated common (interdependent) values. This "precautionary bidding" effect arises because the expected marginal utility of income increases with risk, so buyers are reluctant to bid so highly. We also show that precautionary bidding behavior can make DARA bidders prefer bidding in a common values setting to bidding in a private values one when risk-neutral or CARA bidders would be indifferent. Thus the potential for a "winner's curse" can be a blessing for rational DARA bidders. [source]

Efficiency of Large Private Value Auctions

ECONOMETRICA, Issue 1 2001
Jeroen M. Swinkels
We consider discriminatory and uniform price auctions for multiple identical units of a good. Players have private values, possibly asymmetrically distributed and for multiple units. Our setting allows for aggregate uncertainty about demand and supply. In this setting, equlibria generally will be inefficient. Despite this, we show that such auctions become arbitrarily close to efficient if they are "large," and use this to derive an asymptotic characterization of revenue and bidding behavior. [source]

Effects of Information on Consumers' Willingness to Pay for Golden Rice

ASIAN ECONOMIC JOURNAL, Issue 4 2009
Dinah Pura T. Depositario
D44 We examine the effects of information on consumer bidding behavior using a uniform-price auction with four units supply for golden rice. Our findings show that mean willingness to pay (WTP) bids are highest under positive information, followed by no information, negative information, and unexpectedly lowest with two-sided information. Participants might have put more weight on the negative when faced with both positive and negative information. There is also a minor difference in WTP with respect to the reference price between positive information and no information. Furthermore, the marginal effect on WTP of positive information vis-à-vis no information is minimal. This suggests that the positive information faced by consumers might not be compelling enough to drastically increase WTP bids for a genetically modified product such as golden rice. [source]