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This article examines how an online auction of a preannounced product, the Microsoft Xbox 360, proceeds and performs before its official launch on eBay. Data from the eBay marketplace is examined after the date of the preannouncement in May 2005 until the launch in November 2005. Specifically, the authors look to see if auction success rates from one day affect the success rates on the following day. They also examine if the winning bid prices of one day affect the winning bids on the following day. The results show that auction success rates on one day do not have a significant impact on the following day's success rates. Regarding winning bid prices, there is strong evidence that the winning price series is a nonstationary process, and daily prices show a reverse trending pattern. The authors discuss the managerial implications of their findings.

This article compares four data mining models (discriminant analysis, logistic regression, decision tree, and multilayer neural networks) for online auction transaction predictions. It aims to choose the best model in terms of prediction accuracy and to identify determinants significant for auction transactions. By using datasets from eBay, the authors find that the best data mining model for auction transactions is multilayer neural networks. Logistic regression and decision tree models can be used to identify determinants significant for auction transaction such as seller's feedback profile, listing picture, listing files size, return policies, and others. By adjusting these listing options, sellers could increase the auction transaction likelihood. This study will help sellers improve their auction listings by constructing effective selling strategies so that they can enhance the likelihood of online auction transactions. All these efforts will help improve their online auction performances and finally lead to a more efficient electronic marketplace.

In recent decades, internet auctions have become the most significant e-commerce business model worldwide. With the rapid rise of cloud computing over the last few years, the legacy online auction platform is gradually being replaced using service-oriented cloud computing in real time. This chapter describes the design and implementation of a state and high-performance online auction system over cloud and proposes the methodology to provide persistent state records during the auction process so that we are able to ensure the reliability of submitted bid price and guarantee the security of price message in the delivery process. The authors employ actor-based applications to achieve stateful, parallel, and distributed architecture. Meanwhile, utilizing distributed databases provides secure and efficient data storage. To the best of the authors' knowledge, this is the first time that the actor framework has been applied to the online auction. The preliminary result is for implementation of high-performance and real-time bidding online auction.

Online auction is one of the most successful internet business models. However, auction fraud has become the highest threat and hazard to the future of this business model. The blockchain provides a new perspective to resolve this problem. It can be used for current financial services, certificates, remittances, and online payments; meanwhile it also provides several crucial services such as smart contract, smart property, trust system, and security services. This chapter discusses how to apply blockchain to a cloud-based online auction and the principle of operation. The purpose is to fundamentally solve the problem of online fraud caused by information asymmetry of electronic transactions. To the best of the authors' knowledge, this is the first time that the blockchain has been applied to authentication of online auction. The preliminary contribution is for preventing auction fraud from the aspects of smart properties and smart contract.

Trust between partners is a precondition for business transactions. The perceptions of trust were studied among the users of a popular Finnish online auction site, ‘Huuto.net’. Results are based on interview and survey data collected from 358 users. According to the interviews, a reputation system that is based on user feedback is essential for the evaluation of other users and their reliability, but the more experienced users had also adopted more advanced strategies for looking for additional reliability cues. The results of the survey indicate that experienced users with a longer transaction history often tend to establish regular contacts, and, partly for this reason, perceive online transacting as reliable. The experienced users were also more positive about the system and its administration than less experienced users. As a practical result, in this paper, the authors examine which kinds of design elements of the service support the experience of trust.

Research into the determinants of online auction prices has tended to group them into buyer factors, seller factors and site factors. A case is presented which records how a $30 handbag was sold for $ 22,750 in an online auction shortly after a national sport final. Analysis of the case indicates additional factors which can exert a considerable influence on the final auction price. A model is proposed which depicts five groups of factors impacting the final price: buyer factors, seller factors, site factors which are expanded to include timing of the “action”, and site brand strength; product factors which include product features, brand strength, and brand extension/association; and promotion, which includes media publicity. While not all factors will impact on every auction, due consideration should be accorded each of them.

Online auctions are becoming extremely popular because of the convenience that it offers to the consumers. Much work has been done in designing bidding strategy that can be utilized by bidders who want to participate in online auctions. However, very little work has been done on the seller’s strategy for online auctions. In any online auction, the final selling price of the item is unknown until the auction closes. This price is dependent on several factors such as the number of bidders participating in the auction, how much each bidder is willing to pay for the product, how many online auctions are selling the same item as well as the duration of each auction. Each item to be auctioned off has a reserved price set by the seller. Setting the reserved price too high for the item will result in the item not being sold and setting the price too low may result in profit reduction or even loss. Deciding on the reserved price of an item to be auctioned off is not a straightforward decision. This paper reports on a preliminary implementation of a seller agent that recommends a reserved price for a given item to be auctioned off by the seller. The seller agent’s objective is to suggest a reservation price that guarantees the sale of the item within a given period (as required by the seller) with a profit.

Escrow is an emerging trust service in online consumer-to-consumer auction markets in preventing Internet fraud. This chapter studies the effect of traders’ perceived risk on the adoption of online escrow service (OES). This research establishes decision-making models for both the honest trader and the monopolist OES provider. Perceived risk rate (PRR), a dynamic measure of perceived risk for online traders, is introduced to link the two decision-making models together. A calculative model for PRR is proposed, and the primary outcomes from the computer simulation for PRR measurement are presented. This chapter reveals that OES adoption is positively correlated to the estimated level of traders’ PRR. A higher PRR definitely leads to a higher OES adoption rate and hence reduces the Internet fraud in the auction markets. In addition, an overestimate of PRR leads to higher adoption rate, lower defrauding rate, and higher fraud blocking rate.

The most cited and researched example of C2C e-commerce is through online auctions such as eBay. However, there are many other venues for conducting C2C e-commerce that should be explored that may not necessarily be apparent. As demonstrated by existing research in C2C e-commerce, researchers have focused their studies on venues in which C2C e-commerce is the specified purpose of a site. In addition to these venues, C2C e-commerce can be facilitated in places such as online communities, Web-based discussion forums, consumer blogs, and chat rooms. Each of these venues needs to be explored before a complete representation of C2C e-commerce can be made. Differences in how a consumer views each of the C2C e-commerce venues may be expected to alter the factors affecting his/her determination to participate in C2C e-commerce in the various venues. To help researchers in structuring the potential venues and classifying factors affecting participation, this article presents a taxonomy of the C2C e-commerce venues and a description of the types of venues found in the categories. The next section provides a background discussion of each venue discussed in the taxonomy. Following that will be the presentation of the taxonomy. Future trends and conclusions are provided at the end of the article.

Online auctions are one of the most popular and effective ways of trading goods over the Internet (Bapna, Goes, & Gupta, 2001). Thousands of items are sold on online auctions everyday including books, toys, computers, antiques, and even services. As an example, eBay (http://www.ebay. com), the largest online auction house, has more than 241 million registered users today, and in the year 2006 alone, eBay recorded consolidated net revenue of $6 billion (eBay, 2007). On any given day, there are more than 78 million items listed on eBay, and approximately 6 million listings are added per day. It has also spread its wings to other countries outside the USA, and to date it is present in 24 countries. In addition to eBay, there are more than 2,600 auction houses that conduct online auctions (common sites include Amazon. com, http://www.amazon.com; Yahoo! Auctions, http://auctions. shopping.yahoo.com; priceline.com, http://www.priceline. com; and uBid, http://www.ubid.com). These auction houses conduct many different types of auctions according to a variety of rules and protocols.

Electronic commerce (e-commerce) refers generally to all forms of buying, selling, transforing, exchanging products, services, or information over computer networks (Carter, 2002). Business activities such as communication, business transactions, and data transfer, including both organizations and individual, are conducted online. The “electronic” or “e” in e-commerce or e-business refers to the technology/systems; the “commerce” refers to the traditional business models. Things like funds transfer, order booking, data interchange, automated inventory management, and online marketing all come under the purview of e-commerce (Erber, Klaus, & Voigt, 2001). For instance, people and organizations can shop around the Web to find the products, prices, and services that suit them best and order and pay for items without a physical presence of either the shopper or the merchandise.

The online auction has become an important form of e-commerce. Although using a different mode for conducting auction activities, online auctions should abide by the same code of ethics outlined in the face-to-face auction environment. Yet, ethics-related issues for online auctions have not been fully discussed in the current literature. The unique features of online auctions present an opportunity to address how ethical conduct could be supported, monitored, and enforced in an online auction environment. With technology being the backbone of online auction, information systems appear to be a useful tool in facilitating ethics enforcement. This article summarizes ethics-related issues that are particularly relevant in online auctions, and recommends a code of ethics that could be applied to online auctions. Based on this set of ethics, this article proposes a model for an information system that will support and enhance ethical conduct in an online auction environment.

In this chapter, we introduce a generic Internet trading framework for online auctions. We present the requirements and service of the framework. A generic OR/XOR bidding language that can express different OR/XOR combinations is adopted for Web interfaces. The framework is implemented with free open-source technologies already successfully tested in industries. Researchers can use the platform to implement different electronic-market mechanisms, simulate the market behavior of their interests, and experiment with it. We also provide future directions for the framework design.

Reputation is an important organization asset, particularly in the era of e-commerce. In an online consumer-to-consumer (C2C) auction market, a trader’s reputation sends an important signal to his/her trading partners in their decision-making on C2C transactions, due to the nature of the anonymous transaction process. While prior research has shown that reputation systems, such as eBay’s Feedback Forum, facilitated buyer-seller transactions, several fundamental issues with the transaction mechanism remained unclear. Based on the empirical reputation data directly collected from eBay.com, we find that the distribution of reputation scores can be approximated in a geometric function. We analyze the formation of the distribution with a stochastic process model. The computer simulation using the Monte Carlo approach further validates the findings of the empirical study.