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The double auction is an important transaction mechanism in electronic commerce. Buyers and sellers can interact and be matched with each other in a double auction e-market. Consequently, enhancing the effectiveness of the double auction market to help traders successfully complete their transactions is an important issue. In this research study, Trading Agent Competition (TAC) data were collected to examine double auction market mechanisms. The TAC is a worldwide, renowned competition in which intelligent agents are employed to simulate business/market operations, and the TAC Market Design (CAT) tournament is an individual TAC competition that focuses on the double auction market. Thus, we conducted simulation experiments on the CAT competition platform, and the transaction data were analyzed to identify the impact of market design strategies on market performance, such as market share, market profit and transaction success rate. Based on these results, we developed an expansion matching method to enhance market performance, and we conducted verification experiments to evaluate our method. The results show that our expansion matching method promotes improved performance of market policies in the double auction market. |
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