روش تطبیق توسعه برای بهبود اثر معامله در بازار مزایده با انحصار دوجانبه
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|9459||2012||10 صفحه PDF||سفارش دهید||6234 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Electronic Commerce Research and Applications, Volume 11, Issue 1, January–February 2012, Pages 4–13
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.
In electronic commerce (EC), information about commodities and transactions is transparent to buyers and sellers. Information transcends boundaries of geographical regions and human factors, and all traders can interact with each other and make deals in the e-market. EC can shorten supply chain nodes and increase procurement and marketing efficiency to achieve the goal of enhancing industrial competitiveness (Ghenniwa et al. 2005). In many EC business models, the auction mechanism promotes additional and new opportunities for business. Typical auction mechanisms include the English auction, Dutch auction, first price sealed bid auction, second price sealed bid auction, and double auction (McAfee and McMillan 1987). The most significant difference between the double auction mechanism and the aforementioned types of auctions is that multiple buyers and sellers can simultaneously submit their bids in a double auction. The auction market specialist can establish conditions for the success of buyer and seller transactions according to the attributes of the auction object, which is referred to as the matching policy. For example, the matching policy can set the conditions to allow the buyer with the highest bid price and the seller with the lowest asking price to successfully complete the transaction. Labys and Granger (1970) assert that the double auction mechanism applies to the following situations: (a) The commodity in the transaction possesses is easily assessable and classifiable standard specifications; (b) Information disclosure allows the participants in the transaction to acquire consistent price information; and (c) The number of transactions of both sellers and buyers should be sufficient to allow continuous transactions. Double auctions are further classified as either an asynchronous double auction (ASDA) or a synchronous double auction (SDA) (Friedman, 1991 and Friedman and Rust, 1993); early double auctions were ASDAs. The New York Stock Exchange and Chicago Mercantile Exchange adopted this type of mechanism in the earlier phases of their operations. However, in recent years, academics in SDA research have placed more emphasis on the performance of trader agent strategies and market efficiency in the single market environment. Niu et al. (2007) indicated that in the real-world environment, several markets are often observed to be selling the same commodity, and the trader agents move between markets with the objective of buying low and selling high or avoiding risks. To compare the differences among market operation strategies, the authors employed the Java Auction Simulator API (JASA).1 Niu compared the market share and profit performance of each market operation strategy with different trader agent strategies and market selection strategies in the fixed charge market, homogeneous market, and heterogeneous market environments. The Trading Agent Competition (TAC)2 in the JASA project proposes a TAC Market Design competition platform (JCAT)3 to study how market specialist agents could attain the best performance in the double auction market. JCAT encourages the research, design, and application of a market mechanism to increase market operation efficiency. The participating teams in the competition can design a market specialist agent to operate market strategies that facilitate automatically adaptation of the market to continuously changing conditions in the competitive environment. As compared to the English auction and Dutch auction, the JCAT platform has more similarities to the futures market. In both JCAT and the futures market, buyers and sellers can shout a price at the same time. The market can charge a transaction fee by matching buyers and sellers to complete a transaction. Furthermore, traders can migrate among the markets to pursue the highest transaction profit and prospect for successfully transactions. In the JCAT platform, the system simulates the traders’ shouting and market migration behaviors. However, JCAT is more attentive to the role of market policies. The market proprietor must consider how to implement an efficient policy that will attract the highest number of traders and match them in the market to gain the highest market share and profit. In this research study, we use the JCAT platform to investigate the impact of different double auction market policies on trader agents. We propose an expansion matching method to modify the shout accepting policy to improve market performance. The aim of this study is to improve existing matching policies, thus enabling market specialists to adapt to competitive situations and achieve equilibrium between market share and transaction success rate. The remainder of this paper is organized as follows. In Section 2, the TAC Market Design competition is introduced, and the policies of market specialists and traders are summarized. In Section 3, the evaluation experiment design and results are described. The evaluation experiment is conducted to study the impact of shout accepting policy on market performance; the results can be applied to design a better policy. In Section 4, our expansion matching method is discussed in detail. The verification experiments are conducted to evaluate our method, and the experiment results are presented in Section 5. Finally, implications and conclusions are discussed in Section 6
نتیجه گیری انگلیسی
In this research study, we used the JCAT experiment platform to evaluate the effects of market policies on market performance indicators. The results were analyzed to determine approaches for improving market policies and enhancing market efficiency. Based on the results of evaluation experiments, we propose an expansion matching method in which specialists can adapt to the market by changing the shout accepting range and achieve better market performance. In the expansion matching method, the specialist can extend or shrink the shout matching range to enhance market performance. We applied the method to modify SA, EB, and TB shout accepting policies. In the verification experiments, the three modified specialists competed with the other primitive ones in a multi-specialist market. Expansion matching resulted in significant improvements in market effectiveness in the verification experiments. Based on this method, we could adjust the market’s performance in advance. For example, to increase market share, we can extend the shout accepting range aggressively. Conversely, if the transaction success rate decreases and is lower than an expected value, then the specialist can shrink the shout accepting range. The double auction market is becoming increasingly important in electronic commerce. How to maintain a high performance market is a critical issue to the market owner, buyers, and sellers, and the expansion matching method can be applied to design an efficient market that can enhance the development of the double auction market. This research has highlighted the shout accepting policy research in the double auction market.