Study on Pricing Model of Online Auction Under Competitive Strategy
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MICROECONOMICS and POLICY ANALYSIS - U8213 Professor Rajeev H
MICROECONOMICS AND POLICY ANALYSIS - U8213 Professor Rajeev H. Dehejia Class Notes - Spring 2001 Auctions Wednesday, February 14 Reading: Handout, Thaler, Milgram There are two basic forms of auctions: Sealed bid submissions and open bids. In a sealed bid auction individuals do not know what others are bidding. Two types of Sealed Bid Auctions: 1st Price sealed bid auction: The highest bid submitted will be the winning bid. The winner pays what he/she bid. 2nd Price sealed bid auction: Everyone submits sealed bids and the winner is the one who submits the highest bid BUT the price paid by the winner is the 2nd highest bid submitted. Two types of open auctions: English auction: The bidding starts low and incrementally rises until someone is the highest bidder and no one is willing to outbid the highest bidder. Dutch auction: The price starts very high and is keeps going down until someone bids. The first person to bid wins. Why Study Auctions? 1) Auctions can be an efficient method of valuing goods. For example: rights to air waves, signals and bandwidth. The government auctioned off parts of the spectrum in anticipation of new technology. The auctions were appealing because well- structured auctions get people to reveal the true valuation of the good. The company (private entity) actually ends up paying to the government what the good is worth to them. It turned out with these auctions that the willingness to pay for a slice of the spectrum, as revealed by the auction outcome, was much higher than expected. 2) Procurement: Governments and entities want to procure goods and services at the lowest possible price (like an auction in reverse). -
A Fair and Secure Reverse Auction for Government Procurement
sustainability Article A Fair and Secure Reverse Auction for Government Procurement Chia-Chen Lin 1,*, Ya-Fen Chang 2, Chin-Chen Chang 3 and Yao-Zhu Zheng 4 1 Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan 2 Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, Taichung 40401, Taiwan; [email protected] 3 Department of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, Taiwan; [email protected] 4 Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan; [email protected] * Correspondence: [email protected] Received: 21 August 2020; Accepted: 12 October 2020; Published: 16 October 2020 Abstract: With the development of e-commerce, the electronic auction is attracting the attention of many people. Many Internet companies, such as eBay and Yahoo!, have launched online auction systems. Many researchers have studied the security problems of electronic auction systems, but few of them are multi-attribute-based. In 2014, Shi proposed a provable secure, sealed-bid, and multi-attribute auction protocol based on the semi-honest model. We evaluated this protocol and found that it has some design weaknesses and is vulnerable to the illegal operations of buyers, which results in unfairness. In this paper, we improved this protocol by replacing the Paillier’s cryptosystem with the elliptic curve discrete (ECC), and we designed a novel, online, and multi-attribute reverse-auction system using the semi-honest model. In our system, sellers’ identities are not revealed to the buyers, and the buyers cannot conduct illegal operations that may compromise the fairness of the auction. -
Common-Value Auctions with Liquidity Needs: an Experimental
CommonValue Auctions with Liquidity Needs: An Experimental Test of a Troubled Assets Reverse Auction Lawrence M. Ausubel, Peter Cramton, Emel Filiz‐Ozbay, Nathaniel Higgins, Erkut Ozbay, and Andrew Stocking* 21 May 2009 Abstract We experimentally test alternative auction designs suitable for pricing and removing troubled assets from banks’ balance sheets as part of the financial rescue. Many individual securities or pools of securities are auctioned simultaneously. Securities that are widely held are purchased in auctions for individual securities. Securities with concentrated ownership are purchased as pools of related securities. Each bank has private information about its liquidity need and the true common value of each security. We study bidding behavior and performance of sealed‐ bid uniform‐price auctions and dynamic clock auctions. The clock and sealed‐bid auctions resulted in similar prices. However, the clock auctions resulted in substantially higher bank payoffs, since the dynamic auction enabled the banks to better manage their liquidity needs. The clock auctions also reduced bidder error. The experiments demonstrated the feasibility of quickly implementing simple and effective auction designs to help resolve the crisis. (JEL D44, C92, G01, G21. Keywords: financial crisis, uniform‐price auction, clock auction, market design, experiments, troubled assets, TARP.) 1 Introduction On 3 October 2008, the US Congress passed and the President signed the Emergency Economic Stabilization Act of 2008 (Public Law 110‐343). The Act established the $700 billion Troubled Asset Relief Program (TARP). It authorized the US Treasury to purchase troubled assets in order to restore liquidity to financial markets, favoring. the use of market mechanisms such as reverse auctions for asset purchases. -
Shill Bidding in English Auctions
Shill Bidding in English Auctions Wenli Wang Zoltan´ Hidvegi´ Andrew B. Whinston Decision and Information Analysis, Goizueta Business School, Emory University, Atlanta, GA, 30322 Center for Research on Electronic Commerce, Department of MSIS, The University of Texas at Austin, Austin, TX 78712 ¡ wenli [email protected] ¡ [email protected] [email protected] First version: January, 2001 Current revision: September 6, 2001 Shill bidding in English auction is the deliberate placing bids on the seller’s behalf to artificially drive up the price of his auctioned item. Shill bidding has been known to occur in auctions of high-value items like art and antiques where bidders’ valuations differ and the seller’s payoff from fraud is high. We prove that private- value English auctions with shill bidding can result in a higher expected seller profit than first and second price sealed-bid auctions. To deter shill bidding, we introduce a mechanism which makes shill bidding unprofitable. The mechanism emphasizes the role of an auctioneer who charges the seller a commission fee based on the difference between the winning bid and the seller’s reserve. Commission rates vary from market to market and are mathematically determined to guarantee the non-profitability of shill bidding. We demonstrate through examples how this mechanism works and analyze the seller’s optimal strategy. The Internet provides auctions accessible to the general pub- erature on auction theories, which currently are insufficient to lic. Anyone can easily participate in online auctions, either as guide online practices. a seller or a buyer, and the value of items sold ranges from a One of the emerging issues is shill bidding, which has become few dollars to millions. -
Internet Auctions and Virtual Malls
Internet Auctions and Virtual Malls Is this Booklet Right for You? If you are a small business owner looking for alternatives to creating your own e-commerce website and want to sell online, then you will find this booklet useful. Even if you already have your own website, you can use this booklet to learn more about where you can sell (or buy) products and services online (e.g. Internet Auctions). You can also consider virtual malls or e-mall services where your site is listed along with others. E-malls are discussed later in this booklet. What is an Internet Auction? Internet auctions bring people and/or businesses together on Examples of Auction Websites one website to buy and sell • www.uBid.com (general auction site). products and services. Buying and selling processes vary • www.eBay.com (general auction site). across auction sites; so make • www.alibaba.com (general auction site). sure you familiarize yourself with these techniques by • www.bidville.com (general auction site). visiting these websites. • www.liquidation.com (commercial surplus inventory and government surplus assets – a wide variety of product categories). Most auction sites act as hosts for other businesses or individuals. • www.dovebid.com (global provider of capital asset auction, Generally the host of the website valuation, redeployment, and management services). organizes the site, provides • www.elance.com (focuses on services. You can search for a service product information, displays provider by category or post your project and receive proposals the product and processes from service providers). payments online. A fee is charged Sources: Index of the web.com www.indexoftheweb.com/Shopping/Auctions.htm to list the product or service and/ www.emarketservices.com, http://www.e-bc.ca/pages/resources/internet-auctions.php or a commission is taken on each completed sale. -
Game Theory 2021
More Mechanism Design Game Theory 2021 Game Theory 2021 Ulle Endriss Institute for Logic, Language and Computation University of Amsterdam Ulle Endriss 1 More Mechanism Design Game Theory 2021 Plan for Today In this second lecture on mechanism design we are going to generalise beyond the basic scenario of auctions|as much as we can manage: • Revelation Principle: can focus on direct-revelation mechanisms • formal model of direct-revelation mechanisms with money • incentive compatibility of the Vickrey-Clarke-Groves mechanism • other properties of VCG for special case of combinatorial auctions • impossibility of achieving incentive compatibility more generally Much of this is also (somewhat differently) covered by Nisan (2007). N. Nisan. Introduction to Mechanism Design (for Computer Scientists). In N. Nisan et al. (eds.), Algorithmic Game Theory. Cambridge University Press, 2007. Ulle Endriss 2 More Mechanism Design Game Theory 2021 Reminder Last time we saw four auction mechanisms for selling a single item: English, Dutch, first-price sealed-bid, Vickrey. The Vickrey auction was particularly interesting: • each bidder submits a bid in a sealed envelope • the bidder with the highest bid wins, but pays the price of the second highest bid (unless it's below the reservation price) It is a direct-revelation mechanism (unlike English and Dutch auctions) and it is incentive-compatible, i.e., truth-telling is a dominant strategy (unlike for Dutch and FPSB auctions). Ulle Endriss 3 More Mechanism Design Game Theory 2021 The Revelation Principle Revelation Principle: Any outcome that is implementable in dominant strategies via some mechanism can also be implemented by means of a direct-revelation mechanism making truth-telling a dominant strategy. -
And Information Aggregation)
Introduction to Auctions (and information aggregation) Saša Pekeč Decision Sciences The Fuqua School of Business Duke University October 29, 2008 Outline of the Topics •Scoring rules • Prediction markets • Auctions: clean and oversimplifying view • Auctions: messy but closer to reality • Information aggregation results Information Aggregation • Surveys • Opinion Polls • Aggregating votes / ratings / review scores / … • Eliciting and aggregating expert opinions … Issues: • info quantity • info quality • representativeness • incentives Single Data Point Info Quality •stats • machine learning Add incentives: Example: Binary event E (thumbs up/down, yes/no, 0/1) Elicit probability estimate of E=1: p. Brier score: B(p)= 1-(E-p)2 If r reported instead of p: E[B(r)|p]= p(1-(1-r)2)+(1-p)(1-r2) maximized at r=p ( d/dr : 2p(1-r)-2(1-p)r ) Truthful reporting maximizes Brier score Scoring Rules • Consider a probability forecast for a discrete event with n possible outcomes (“states of the world”). • Let ei = (0, ..., 1, ..., 0) denote the indicator vector for the ith state (where 1 appears in the ith position). • Let p = (p1, ..., pn) denote the forecaster’s true subjective probability distribution over states. • Let r = (r1, ..., rn) denote the forecaster’s reported distribution (if different from p). (Also, let q = (q1, ..., qn) denote a baseline distribution upon which the forecaster seeks to improve.) Slide thx to R.Nau Proper Scoring Rules • The scoring rule S is [strictly] proper if S(p) ≥ [>] S(r, p) for all r [≠p], i.e., if the forecaster’s expected score is [uniquely] maximized when she reports her true probabilities. -
Spectrum Auctions from the Perspective of Matching
Spectrum Auctions from the Perspective of Matching Paul Milgrom and Andrew Vogt May 5, 2021 1 Introduction In July 1994, the United States Federal Communications Commission (FCC) conducted the first economist-designed auction for radio spectrum licenses. In the years since, governments worldwide have come to rely on auction mecha- nisms to allocate { and reallocate { rights to use electromagnetic frequencies. Over the same period, novel uses for spectrum have dramatically increased both the demand for licenses and auction prices, drawing continued attention to the nuances of spectrum markets and driving the development of spectrum auction design. In August 2017, the FCC completed the Broadcast Incentive Auction, a two-sided repurposing of an endogenously-determined quantity of spectrum that ranks among the most complex feats of economic engineering ever under- taken. The next generations of mobile telecommunications are poised to extend this growth, and to demand further innovation in the markets and algorithms that are used to assign spectrum licenses. What does all of this have to do with matching theory? Spectrum auctions differ from canonical matching problems in meaningful ways. Market designers often emphasize that a key element of matching markets is the presence of preferences on both sides of the market. In a marriage, for example, it is not enough that you choose your spouse; your spouse must also choose you. This two-sided choice structure applies also to matches between students and schools and between firms and workers, but not to matches between telecommunications companies and radio spectrum licenses. It is a different matching element that is often critically important in ra- dio spectrum auctions. -
Introduction to Auctions Protocols Revenue and Optimal Auctions Common Value Auctions
Auctions Kate Larson Introduction Auction Protocols Common Auction Introduction to Auctions Protocols Revenue and Optimal Auctions Common Value Auctions Vulnerabilities Kate Larson in Auctions Beyond Single Cheriton School of Computer Science Item Auctions University of Waterloo Summary Outline Auctions Kate Larson 1 Introduction Introduction Auction Protocols 2 Auction Protocols Common Auction Protocols Common Auction Protocols Revenue and Optimal Auctions Common Value Revenue and Optimal Auctions Auctions Common Value Auctions Vulnerabilities in Auctions Beyond Single 3 Vulnerabilities in Auctions Item Auctions Summary 4 Beyond Single Item Auctions 5 Summary Auctions Auctions Kate Larson Methods for allocating goods, tasks, resources,... Introduction Participants Auction auctioneer Protocols Common Auction bidders Protocols Revenue and Optimal Auctions Enforced agreement between auctioneer and the Common Value Auctions winning bidder(s) Vulnerabilities in Auctions Easily implementable (e.g. over the Internet) Beyond Single Conventions Item Auctions Summary Auction: one seller and multiple buyers Reverse auction: one buyer and multiple sellers Todays lecture will discuss the theory in the context of auctions, but this applies to reverce auctions as well (at least in 1-item settings). Auction Settings Auctions Kate Larson Introduction Private value: the value of the good depends only on Auction the agent’s own preferences Protocols e.g a cake that is not resold of showed off Common Auction Protocols Revenue and Common value: an agent’s value of an item is Optimal Auctions Common Value determined entirely by others’ values (valuation of the Auctions item is identical for all agents) Vulnerabilities in Auctions e.g. treasury bills Beyond Single Item Auctions Correlated value (interdependent value): agent’s Summary value for an item dpends partly on its own preferences and partly on others’ value for it e.g. -
Forward Auction Bidding System User Guide Disclaimer
FCC Incentive Auction Forward Auction Clock Phase Bidding System USER GUIDE Last updated: July 22, 2016 Forward Auction Bidding System User Guide Disclaimer DISCLAIMER The Federal Communications Commission (the “Commission”) will make available a web-based Auction System for incentive auction bidding purposes. The Commission makes no warranty whatsoever with respect to the Auction System. In no event shall the Commission, or any of its officers, employees or agents, be liable for any damages whatsoever (including, but not limited to, loss of business profits, business interruption, loss of business information, or any other loss) arising out of, or relating to the existence, furnishing, functioning or use of the Auction System that is accessible to bidders in connection with this auction. Moreover, no obligation or liability will arise out of the Commission’s technical, programming or other advice or service provided in connection with the Auction System. The examples that appear in this document are based on fictitious data and do not represent the actual data for this auction. Additionally, they do not reflect any predictions or assumptions about the actual bidding in the auction, the number of rounds, or the outcome of the auction. Any similarity to actual company names, PINs, FCC Registration Numbers (FRNs), or other personal information is coincidental. COPYRIGHT NOTICE Copyright © 2005–2016 by Power Auctions LLC. The software service makes use of proprietary technology protected by US Patent Numbers 7,062,461; 7,165,046; 7,343,342; 7,467,111; 7,870,050; 7,899,734; 7,966,247; 8,447,662; and 8,762,222. -
Annual Registration Fee $100
Auction Terms and Conditions Welcome to Capital City Auto Auction As a “Buyer” with Capital City Auto Auction (CCAA) you agree to be bound by the following Auction Terms and Conditions. CCAA may amend these terms and conditions at any time, without prior notice. Online Account: CCAA operates as an online auction. All searches, bidding and sale communications are made electro nically via the internet. Buyers must have computer access, an active email address, and register online at CapitalCityAutoAuction.Com with a unique username and password. Most items (Vehicle) at CCAA are donations, and are being sold by a charitable organization. CCAA has NO information regarding the condition or history of any Vehicle. NO physical or mechanical inspections have been performed by CCAA. Vehicles are NOT test driven; CCAA cannot verify drivability or attest to the condition, or soundness of the Vehicle, including but not limited to, the Powertrain, Drivetrain, Suspension, or Electrical Systems. CCAA provides a general description of each Vehicle; however, mechanical problems may be present which are not apparent, visible, or known by CCAA. CCAA is not responsible for the accuracy or incomplete descriptions of Vehicles. Conditions of Sale: All Vehicles sold at CCAA are sold "As-Is, Where-Is, With All Faults", With No Warranty, Expressed or Implied, Including But Not Limited To, Any Warranty of Fitness or Merchantability. Any and all information provided by CCAA in writing, verbally, or in image form pertaining to any auction item, including (when available) the Vehicle Identification Number and License Plate Number, is solely for the Buyer’s convenience. -
An Experimental Study of the Generalized Second Price Auction
An experimental study of the generalized second price auction. Jinsoo Bae John H. Kagel The Ohio State University The Ohio State University 6/18/2018 Abstract We experimentally investigate the Generalized Second Price (GSP) auction used to sell advertising positions in online search engines. Two contrasting click through rates (CTRs) are studied, under both static complete and dynamic incomplete information settings. Subjects consistently bid above the Vikrey-Clarke-Grove’s (VCG) like equilibrium favored in the theoretical literature. However, bidding, at least qualitatively, satisfies the contrasting outcomes predicted under the two contrasting CTRs. For both CTRs, outcomes under the static complete information environment are similar to those in later rounds of the dynamic incomplete information environment. This supports the theoretical literature that uses the static complete information model as an approximation to the dynamic incomplete information under which advertising positions are allocated in field settings. We are grateful to Linxin Ye, Jim Peck, Paul J Healy, Kirby Nielsen, Ritesh Jain for valuable comments. This research has been partially supported by NSF grant SES Foundation, SES- 1630288 and grants from the Department of Economics at The Ohio state University. Previous versions of this paper were reported at the 2017 ESA North American Meetings in Richmond, VA. We alone are responsible for any errors or omissions in the research reported. 1 1. Introduction Search engines such as Google, Yahoo and Microsoft sell advertisement slots on their search result pages through auctions, among which the Generalized Second Price (GSP) auction is the most prevalent format. Under GSP auctions, advertisers submit a single per-click bid.