• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.159-170
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• 2011

In procurement auctions, auction frequency and transaction volume per auction have been analyzed as important factors in determining auction performance. However, there is no empirical study on the effect of auction frequency and transaction volume in procurement auction. Current studies mainly focus on bidder behavior analysis and new system design in procurement auction. In the study, we analyze the effect of two factors on relative winning price empirically by using real auction data from MRO procurement outsourcing company in Korea. From the results, we find the winning price is lower when the frequency of auction with same item category is lower. The low frequency of auctions means participating bidders have limited information of previous auctions and they bid their best price to win the current auction due to less opportunity of reopening the auction in near future. The larger purchase amounts of MRO items didn’t results in lower winning price, contrary to our hypothesis. The possible reason is that the price of MRO items already reflects the economy of scales and the increased volume per auction do not cause the further discount of MRO items from the auction.

• Asia pacific journal of information systems
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• v.20 no.4
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• pp.81-100
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• 2010

This study investigates the impact of website contents on Internet auction success. Based on the marketing concepts of stimuli, consumer behavior, and product involvement, the research model presents the theoretical relationships between the key factors of website contents and Internet auction performance. This study examines particularly four dimensions of website contents including transaction features, auction-specific features, seller's reputation, and information quality, which are deemed to have significant impact on the Internet auction performance, Each dimension of website contents is hypothesized to have a unique impact on a bidder's decision-making, which may vary depending on the bidder's level of involvement in the product. While transaction and auction-specific features serve as necessary components for successful auctions, a seller's reputation and information quality, as parts of satisfactory requirements, acutely affect bidders' decisions, especially those with high involvement to buy the product through a particular auction site. The outcomes of the analysis, in general, support the proposed model. The study results also provide meaningful Implications on ways in which auction websites can be improved for both sellers and auction service providers.

• KDI Journal of Economic Policy
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• v.43 no.3
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• pp.55-77
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• 2021

In Korea, local governments and local agencies had to apply a version of the first price auction augmented by an ex-post screening process when they procure construction contracts. However, this first price auction had been criticized because it was felt that too much price competition could lead to poor ex-post performance in construction. In response, the existing auction method was recently replaced by a version of the average price auction with a similar screening process. This paper empirically examines the effectiveness of this reform and finds that the replacement only increases the fiscal burden of local governmental bodies without making any improvement in the ex-post performance.

• Journal of Information Technology Applications and Management
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• v.12 no.1
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• pp.141-155
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• 2005

It is very important that sellers provide reasonable reserve prices for auction items in internet auction systems. Recently, an agent has been proposed to generate reserve prices automatically based on the case similarity of information retrieval theory and the moving average of time series analysis. However, one problem of the previous approaches is that the recent trend of auction prices is not well reflected on the generated reserve prices, because it simply provides the bid price of the most similar item or an average price of some similar items using the past auction data. In this paper. in order to overcome the problem. we propose a method that generates reserve prices based on the moving average. the exponential smoothing, and the least square of time series analysis. Through performance experiments. we show that the successful bid rate of the new method can be increased by preventing sellers from making unreasonable reserve prices compared with the previous methods.

• Advances in robotics research
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• v.2 no.3
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• pp.247-257
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• 2018

Various studies have been performed to coordinate robots in transporting objects and different artificial intelligence algorithms have been considered in this field. In this paper, we investigate and solve Multi-Robot Transportation problem by using a combined auction algorithm. In this algorithm each robot, as an agent, can perform the auction and allocate tasks. This agent tries to clear the auction by studying different states to increase payoff function. The algorithm presented in this paper has been applied to a multi-robot system where robots are responsible for transporting objects. Using this algorithm, robots are able to improve their actions and decisions. To show the excellence of the proposed algorithm, its performance is compared with three heuristic algorithms by statistical simulation approach.

• Industrial Engineering and Management Systems
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• v.14 no.1
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• pp.32-43
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• 2015

This study suggests an electronic brokerage system that has the capability of efficiently matching dispatching delivery tasks with trucks. In the brokerage system, individual truck drivers and shippers are allowed to participate in the dispatching process through the internet or wireless communication. An auction-based dispatching method for the electronic brokerage system is suggested. The basic rationale of the auction-based dispatching method-which is a distributed decision-making process-is discussed. The performance of the suggested algorithms is evaluated by a simulation study.

• The Journal of Society for e-Business Studies
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• v.11 no.2
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• pp.31-48
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• 2006

Commercial internet auction systems have been successfully used recently. In those systems, because auction prices of auction items are given by sellers only, the success bid rate can be decreased due to the large difference between the reserve price and the normal price. In this paper, we propose an agent that generates auction prices to sellers based on past auction data and item prices gathered from the web Through performance experiments, we show that the successful bid rate increases by preventing sellers from making unreasonable reserve prices. Using the pricing agent, we design and implement an XML-based auction system on the web.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.955-962
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• 2002

Commercial internet auction systems have been successfully used recently. In those systems, because reserve prices of auction items are given by sellers only, the success bid rate can be decreased due to the large difference between the reserve price and the normal price. In this paper, we propose an agent that generates reserve prices to sellers based on past auction data and item prices gathered from the web. Through performance experiments, we show that the successful bid rate increases by preventing sellers from making unreasonable reserve prices. Using the pricing agent, we design and implement an XML-based auction system on the web.

• The Journal of Society for e-Business Studies
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• v.9 no.2
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• pp.17-31
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• 2004

It is very important that sellers provide reasonable reserve prices for auction items in internet auction systems. Recently, an agent has been proposed to generate reserve prices automatically based on the case similarity of information retrieval theory. However, one of its drawbacks is that the recent trend of auction prices is not reflected in the generated reserve prices, because it suggests the bid price of the most similar item from the past auction data. In this paper, in order to overcome the problem, we propose a new method that generates reserve prices based on the moving average of time series analysis, in which more weight is provided to the recent bid prices. Through performance experiments, we show that the successful bid rate can be increased by preventing sellers from making unreasonable reserve prices.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.48 no.1
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• pp.72-81
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• 2012

Using artificial neural network (ANN) technique, auction prices for common mackerel were forecasted with the daily total sale and auction price data at the Busan Cooperative Fish Market before introducing Total Allowable Catch (TAC) system, when catch data had no limit in Korea. Virtual input data produced from actual data were used to improve the accuracy of prediction and the suitable neural network was induced for the prediction. We tested 35 networks to be retained 10, and found good performance network with regression ratio of 0.904 and determination coefficient of 0.695. There were significant variations between training and verification errors in this network. Ideally, it should require more training cases to avoid over-learning, which leads to improve performance and makes the results more reliable. And the precision of prediction was improved when environmental factors including physical and biological variables were added. This network for prediction of price and catch was considered to be applicable for other fishes.