본 연구에서는 게임머니를 대상으로 거래비용을 추정하였다. 거래비용을 크게 거래기회의 탐색, 협상, 감시 및 강제의 세가지 유형으로 구분하고 거래기회의 탐색비용을 중심으로 분석을 진행하였다. 연구에서는 게임머니를 거래하는 온라인 아이템중개사이트로부터 리니지 게임의 42개 서버 중 3개 서버와 관련된 2010년 및 2011년의 게임머니 거래자료를 받아 이용하였다. 일부 거래비용 항목이 방법론의 한계로 누락되었으나 누락된 항목을 제외하고도 거래비용은 거래금액의 15.13%에 해당하는 것으로 분석되었다. 이는 게임머니와 같이 품질의 검증이 필요 없는 표준화된 거래 대상의 온라인 거래에서도 거래비용 수준이 상당히 높게 나타고 있음을 보여주며, 거래비용 관리의 경제적, 경영적 중요성을 부각하는 의미가 있다
This paper tries to estimate transaction cost in online trade. For this, we assume that the changes in transaction price reflect transaction cost. With this assumption, we derived some equations which calculate transaction costs and applied those equations to two exchange sites for game money. In the sites, game money for Lineage(MMORPG game) are exchanged and transaction data were stored. In case of Lineage, 42 servers are operated and we select 3 servers from them. The database used includes all actual transaction prices and exchage amount related to those three servers at every day in the year 2010 and 2011. To estimate the transaction cost, we categorized transaction cost into three types: cost for searching transaction opportunity, cost for negotiation, and monitoring and enforcement cost. In the exchange sites, most people just search and accept the asking price. Hence, we assumed cost for negotiation as zero. In case of monitoring and enforcement cost, commission to the sites and cost for settlement are included. The commission was reported by the sites and the settlement cost was not analyzed in this paper. Hence, the main concern of this paper is cost for searching transaction opportunity. The searching cost can be different according to the actual behavior of players and we categorized those into three types; searching asking price, comparing asking price among sites, and suggesting asking price and waiting cost. To derive methodology for measuring transaction cost, some assumptions are used. The first and most important assumption is that the intrinsic value of the game money does not change in short time, at least within one day. By this assumption, all changes in the actual price can be recognized to reflect the transaction cost. Second, among three types of searching costs, cost for `suggesting asking price and waiting cost` is highest, the maximum value. In the case, the one who suggest the price accepts most transaction cost, and the opposite accept less favorable suggested price instead of avoiding transaction cost. In other cases, the players divides the maximum transaction cost. Hence, we assume that the maximum transaction cost is the total search cost for both players. Third, the commission to the site, which is paid by the seller, is reflected to the price and we assume that it is actually paid by both players jointly. Hence, the total transaction cost for both players includes `suggesting asking price and waiting cost,` commission, and cost for settlement. In this analysis, cost for settlement was not analyzed. Using those assumptions, we derived some equations for measuring transaction costs and applied them to the data described above. The result is as follows. The maximum search cost, suggesting asking price and waiting cost, was estimated as 11.33% of the traded amount. If we add the commission (3.8%) to the value, the sum becomes 15.13%. This value does not include `settlement cost.` Furthermore, considering the assumptions, the value is underestimated. Considering the estimated value, the transaction cost is considered to be still very high relative to the traded amount even though it is online trade and the object is standardized information good. This result shows the importance of enhancing efficiency with respect to transaction cost. Specifically, the level of commission is less than 25.12%(3.8%/15.13%) of total transaction cost considering underestimation and factors which are not estimated. Hence, by making more sophisticated trade system, the users and the sites can be better results; higher revenue and less transaction cost.