가격결정요인분석을 통한 미술품 온라인 경매 특성 연구

As the interests of arts market and the investment increases, the artwork auction market is growing very quickly. The global artwork auction market has grown from $3.6 billion in 2004to $13 billion in 2010, and so did the domestic artwork auction market. With this expansion, a new area emerged: the online artwork auction market. Since 2006, as the offline artwork auction market grew very quickly, the online artwork auction market also grew quickly. Previous studies have suggested that the online artwork auction would be a reasonable alternative to offline artwork auction market. This study empirically shows if online artwork auctions could be better in mitigating winner's curse problems than traditional offline artwork auctions in Korea. In this study, we used action fetching price data of 3,108 paintings by Korean artists which have been sold over the period from June 2010 to March 2011 provided by Korean Art Price Appraise Association. We analyzed the impacts of price determinants that were found in previous studies on the fetching price. The price determinants include artists' reputation,material of paintings, and size of paintings. We also controlled artists' survival status, types of objects paintings, and timing of the sales of the paintings. First, artists' reputations have positive and significant influence on both online and offline auction fetching prices. To see the different impacts between online and offline action prices,we conducted t-test and found that the t-value of online auction(t-value= 6.737) was lower than that of offline auction(t-value=16.103). So we confirmed that online auction price is less affected by artist's reputation than offline auction price is. Second, material of paintings had different impacts on fetching prices of online and offline auctions. We found all positive and significant relationships between types of materials and offline auction fetching prices, but no relationships were found to online prices. Thus, material of paintings does have different impacts on online and offline fetching prices as expected. Third, size of the paintings have significant impacts on both online and offline auction fetching prices. We couldn't find any difference between size impacts on fetching price of two auctions. Thus, the hypothesis on this was not supported. Next, we investigated if there are differences in the fetching prices compared to the estimate prices between online and offline auctions. We found that the average of online artwork auction fetching prices over estimate prices was 0.724, which was significantly lower than the average of offline fetching/estimate prices of 1.996. This means online bidders buy paintings at far lower price than offline bidders do. We could figure out that the online art auctions have many differences compare to offline art auctions. The difference may come from the fact that online art auctions have more accessibility without space and time limitations than offline ones, and online buyers would be more sensitive to price due to the lack of first-hand looking. The fact that online fetching prices compared to estimate prices are lower that offline cases would imply that online buyers could collect information actively not only from the information that auction company provides but also from other sources. It can be interpreted that online buyers would show more reasonable and rational behaviors than offline buyers. This may imply that online artwork auction market could be a proper alternative to offline artwork auction market where winner's curse problems exist. Thus, we empirically show and support the rational of the online artwork auction market.