MobLab
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Aa

Display Ad Auction

Game Description

Advertisers compete to display their ad on the Steaming Panda Spa website. For every impression (a user visiting the website) the auctioneer uses a sealed-bid auction to determine which advertiser will show its ad.

Learning Objective 1: How to Bid in Optimally in (thin) Auctions with Different Formats

The equilibrium bidding strategy depends on the pricing rule and value distribution of N bidders. When winners pay the second highest bid, the weakly dominant strategy is for each bidder to bid her value. When winners pay their bid, a bidder has an incentive to shade her bid.

Learning Objective 2: Experience Different Auction Designs as an Auctioneer

The auctioneer evaluates the outcome of different auction designs: changing reserve price or running first price vs. second price auctions.

Learning Objective 3: Revenue Maximization

Compute the “optimal reservation price” for the second price auction and “optimal shading strategy” for a bidder in the first price auction setting.

Brief Instructions

Each advertiser has their individual (private) value assigned prior to the auction depending on the display ad metrics shared by the website publisher. By default the private value is drawn randomly from either a ‘low’ uniform distribution, such as [0,100], or ‘high’ uniform distribution, such as [50,150] (See Bidder Value Distribution). Each advertiser can only submit one bid in each auction simultaneously and independently from other advertisers. In addition, the advertisers get to observe if there is any auction design adjustment, such as introduction of a Reserve Price or changing from second price to first price auction.

Key Treatment Variations

Bidder Value Distributions

Edit bidder uniform value ranges under the Basic Tab in the game configuration. The Value Distribution can be Fixed, Rotate, or Random. Fixed will keep the same value range across rounds. Rotate will rotate the value ranges between the players in order. Random will randomly assign a value range to a player.

Price Rule

Equilibrium bidding strategy depends on the pricing rule. With Price Rule=First Price, the winning bidder pays her bid. With Price Rule=Second Price, the winning bidder will pay the second highest bid.

Reserve Price

Setting a Reserve Price sets the minimum price the seller must receive in order to part with an item. For the second-price auction, if the highest non-winning bid isless than the reserve price, then those bidding at or above the Reserve Price pay the Reserve Price.

Configurable Price Rule and Reserve Price

By checking the configurable price Reserve Price/ Reserve Price, auctioneers will be able to determine the Reserve Price/ Reserve Price for their individual group of bidders.

Results

The top summary table presents the aggregate statistics: Round, Group Number, Number of Bidders, Pricing Rule, Reserve Price, Highest Bid, and Revenue.

Table 1: Summary Table (Click image to expand.)

The aggregate graph shows bidder values on the x-axis and their bids on the y-axis. The 45 degree dashed green line illustrates where value = bid and first and different colors/shapes denote first and second price bids.

Graph 1: Aggregate Graph (Click image to expand.)

The economic gain division graph is a stacked aggregate bar chart by round and by type of auction aggregate auctioneer revenue and aggregate bidder surplus.

Graph 2: Economic Gain Division Graph (Click image to expand.)

The reserve graph shows the set reserve price on the x-axis and the auctioneer revenue on the y-axis. Different colors/shape denote first and second price bids.

Graph 3: Reserve Graph (Click image to expand.)

The final charts show the highest bid on the x-axis and difference between highest and second highest bid on the y-axis. Different colors/shape denote first and second price bids.

Graph 4: Highest Bid Difference Graph (Click image to expand.)

Robot Play

Bidder

Robot submits a bid equal to their value.

Auctioneer

Robots will not configure a price rule and reserve price but rather will choose whatever is picked by the instructor in the configuration screen.

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