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Bidding

About: Bidding is a research topic. Over the lifetime, 15371 publications have been published within this topic receiving 294233 citations. The topic is also known as: competitive bidding.


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TL;DR: The Price Is Right game show was used as a laboratory to conduct a preference-free test of rational decision theory in an environment with substantial economic incentives as mentioned in this paper, and it was found that contestants' strategies are transparently suboptimal.
Abstract: The television game show The Price Is Right is used as a laboratory to conduct a preference-free test of rational decision theory in an environment with substantial economic incentives It is found that contestants' strategies are transparently suboptimal In response to this evidence, simple rules of thumb are developed that are shown to explain observed bidding patterns better than rational decision theory Further, learning during the show reduces the frequency of strategic errors This is interpreted as evidence of bounded rationality Finally, there is no evidence that a concern for fairness significantly alters bidding behavior Copyright 1996 by American Economic Association

109 citations

Journal ArticleDOI
TL;DR: In this paper, the problem of building optimal bidding strategies for competitive suppliers in a day-ahead energy market is addressed, where each supplier makes decisions on unit commitment and chooses the coefficients in the linear energy supply functions to maximize total benefits in the schedule day, subject to expectations about how rival suppliers will bid.

109 citations

Journal ArticleDOI
TL;DR: In this article, the authors examine the choice of levels at which bids will be allowed and also present a simple model of the role of the discrete levels in bidding strategy, and develop a model in which it is equilibrium behavior always to make the minimum allowed advance.

108 citations

Journal ArticleDOI
TL;DR: In this article, a mathematical model is proposed to help large consumers to derive bidding strategies to alter pool prices to their own benefit, and a stochastic complementarity model is developed to derive the bidding curves, and show the advantages of such bidding schemes with respect to non-strategic ones.
Abstract: The smart grid technology enables an increasing level of responsiveness on the demand side, facilitating demand serving entities—large consumers and retailers—to procure their electricity needs under the best conditions. Such entities generally exhibit a proactive role in the pool, seeking to procure their energy needs at minimum cost. Within this framework, we propose a mathematical model to help large consumers to derive bidding strategies to alter pool prices to their own benefit. Representing the uncertainty involved, we develop a stochastic complementarity model to derive bidding curves, and show the advantages of such bidding scheme with respect to non-strategic ones.

108 citations

Posted Content
TL;DR: Topics covered include user response prediction, bid landscape forecasting, bidding algorithms, revenue optimization, statistical arbitrage, dynamic pricing, and ad fraud detection are an invaluable text for researchers and practitioners alike.
Abstract: The most significant progress in recent years in online display advertising is what is known as the Real-Time Bidding (RTB) mechanism to buy and sell ads. RTB essentially facilitates buying an individual ad impression in real time while it is still being generated from a user's visit. RTB not only scales up the buying process by aggregating a large amount of available inventories across publishers but, most importantly, enables direct targeting of individual users. As such, RTB has fundamentally changed the landscape of digital marketing. Scientifically, the demand for automation, integration and optimisation in RTB also brings new research opportunities in information retrieval, data mining, machine learning and other related fields. In this monograph, an overview is given of the fundamental infrastructure, algorithms, and technical solutions of this new frontier of computational advertising. The covered topics include user response prediction, bid landscape forecasting, bidding algorithms, revenue optimisation, statistical arbitrage, dynamic pricing, and ad fraud detection.

108 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
2023566
20221,134
2021637
2020708
2019830