The Internet Economy includes various online markets with billions of transactions. We study pricing problems in such markets.
In a labor market with multiple workers and tasks, a worker possibly has several skills and a task requires one worker with a certain skill. To price the transactions and pair workers and tasks, we propose truthful stable pricing mechanisms to not only maximize the market revenue but also ensure the fairness for both workers and task owners.
In an advertising market, an advertiser pays for showing ads to its target users. From crawled data, we find that the prices of showing ads to users with different attributes vary a lot. We then design targeting strategies to help advertisers reach more target audience, with provable guarantee. For markets, we design revenue-maximizing pricing mechanisms that prevent arbitrage.