Internet auctions in marketing: The consumer perspective

Internet auctions for consumer are among the most popular and most successful business models in electronic commerce. Research so far, however, has focused on prerequisites and consequences of auctions as a marketing intstrument of suppliers. Even though it is a key success factor from a marketing perspective, the demand side has not inspired similar attention. This paper focuses on the attitudes, motives, and behavior of auction customers. It shows why ccurrent beliefs about bidder characteristics are myths. Taking these misconceptions as a starting point, the existence of an experiential and a pragmatic type of auction customer is proposed. An explorative empirical study looking for the characteristics of both types of auction customers is described. Results indicate that less than half of auction shoppers in the sudy are experiential oriented. Except substantial additional demand concerning technological and emotional qualities of auctions these shoppers do not differ dramatically from pragmatic oriented shoppers. Both types are open-minded towards further development of consumer auctions to commercial marketplaces. Business models of auctioneers and suppliers should concentrate on the basic utility of the auction algorithm by facilitating individual matchmaking instead of pursuing costly additional utility by promoting the entertainment value of auctions. --

Trust and Experience in Online Auctions

This paper aims to shed light on the complexities and difficulties in predicting the effects of trust and the experience of online auction participants on bid levels in online auctions. To provide some insights into learning by bidders, a field study was conducted first to examine auction and bidder characteristics from eBay auctions of rare coins. We proposed that such learning is partly because of institutional-based trust. Data were then gathered from 453 participants in an online experiment and survey, and a structural equation model was used to analyze the results. This paper reveals that experience has a nonmonotonic effect on the levels of online auction bids. Contrary to previous research on traditional auctions, as online auction bidders gain more experience, their level of institutional-based trust increases and leads to higher bid levels. Data also show that both a bidder’s selling and bidding experiences increase bid levels, with the selling experience having a somewhat stronger effect. This paper offers an in-depth study that examines the effects of experience and learning and bid levels in online auctions. We postulate this learning is because of institutional-based trust. Although personal trust in sellers has received a significant amount of research attention, this paper addresses an important gap in the literature by focusing on institutional-based trust

Internet Auctions: Description, Bidders' Profiles and Implications

The increasing quantity of items bough and sold over the internet led to the success of internet auctions, to the introduction of new auction rules and the creation of new businesses and merger among existing ones. In this paper, we present a description of existing internet auction rules and typical profile of consumers who use them. We found that bidders are most likely located in the U.S., have some internet experience and skills and that they belong to the 26-50 years old age group. We also discuss the implication of online auctions on resource allocation.Internet Auctions, Online Auctions

Market-based Recommendation: Agents that Compete for Consumer Attention

The amount of attention space available for recommending suppliers to consumers on e-commerce sites is typically limited. We present a competitive distributed recommendation mechanism based on adaptive software agents for efficiently allocating the 'consumer attention space', or banners. In the example of an electronic shopping mall, the task is delegated to the individual shops, each of which evaluates the information that is available about the consumer and his or her interests (e.g. keywords, product queries, and available parts of a profile). Shops make a monetary bid in an auction where a limited amount of 'consumer attention space' for the arriving consumer is sold. Each shop is represented by a software agent that bids for each consumer. This allows shops to rapidly adapt their bidding strategy to focus on consumers interested in their offerings. For various basic and simple models for on-line consumers, shops, and profiles, we demonstrate the feasibility of our system by evolutionary simulations as in the field of agent-based computational economics (ACE). We also develop adaptive software agents that learn bidding strategies, based on neural networks and strategy exploration heuristics. Furthermore, we address the commercial and technological advantages of this distributed market-based approach. The mechanism we describe is not limited to the example of the electronic shopping mall, but can easily be extended to other domains

Moving from Data-Constrained to Data-Enabled Research: Experiences and Challenges in Collecting, Validating and Analyzing Large-Scale e-Commerce Data

Widespread e-commerce activity on the Internet has led to new opportunities to collect vast amounts of micro-level market and nonmarket data. In this paper we share our experiences in collecting, validating, storing and analyzing large Internet-based data sets in the area of online auctions, music file sharing and online retailer pricing. We demonstrate how such data can advance knowledge by facilitating sharper and more extensive tests of existing theories and by offering observational underpinnings for the development of new theories. Just as experimental economics pushed the frontiers of economic thought by enabling the testing of numerous theories of economic behavior in the environment of a controlled laboratory, we believe that observing, often over extended periods of time, real-world agents participating in market and nonmarket activity on the Internet can lead us to develop and test a variety of new theories. Internet data gathering is not controlled experimentation. We cannot randomly assign participants to treatments or determine event orderings. Internet data gathering does offer potentially large data sets with repeated observation of individual choices and action. In addition, the automated data collection holds promise for greatly reduced cost per observation. Our methods rely on technological advances in automated data collection agents. Significant challenges remain in developing appropriate sampling techniques integrating data from heterogeneous sources in a variety of formats, constructing generalizable processes and understanding legal constraints. Despite these challenges, the early evidence from those who have harvested and analyzed large amounts of e-commerce data points toward a significant leap in our ability to understand the functioning of electronic commerce.Comment: Published at http://dx.doi.org/10.1214/088342306000000231 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

A proposed marketing strategy for GO2HK.COM

Within these few years, the Internet becomes popular in the world. There are many well-known websites, such as the eBay, Amazon and Yahoo, etc.. In foreign countries, Web auction is very famous for the Internet users in foreign countries, while it is a new kind of electronic business in Hong Kong. The trend of web auction has penetrated into Hong Kong in this few years, but it is still at a growth stage of the industry life cycle. Web auction seems to be a new type of business in electronic commerce, thus it can attract the people to participate it in future. The potential market for web auction is quite large. In Hong Kong, there are four major companies that work on the business of web auction. They are the (1) Red-dots, (2) Go2hk, (3) Yahoo and (4) Clubciti. Whereas, go2hk is the smallest company in terms of company size, it is the second in terms of the number of registered users. The industry is growing rapidly and facing a keen competition. Therefore, the company needs to have good marketing mix strategies to establish its brand name. This project aims to purpose an appropriate marketing strategy of GO2HK.COM, which can allow the company to match the consumer needs with marketing strategy. Interviews are conducted and questionnaire surveys are initiated to look into the most preferable strategy for GO2HK. Before doing the questionnaire survey, we have interviewed the company, in order to identify the current marketing mix first. After that, questionnaire surveys are used to access the information about the procedure of non-users, sellers and bidders. Based on the findings, a proposed marketing strategy is recommended for go2hk. To conclude, security is the most critical aspect that both users and non-users are highly concerned

Lowest Unique Bid Auctions

We consider a class of auctions (Lowest Unique Bid Auctions) that have achieved a considerable success on the Internet. Bids are made in cents (of euro) and every bidder can bid as many numbers as she wants. The lowest unique bid wins the auction. Every bid has a fixed cost, and once a participant makes a bid, she gets to know whether her bid was unique and whether it was the lowest unique. Information is updated in real time, but every bidder sees only what's relevant to the bids she made. We show that the observed behavior in these auctions differs considerably from what theory would prescribe if all bidders were fully rational. We show that the seller makes money, which would not be the case with rational bidders, and some bidders win the auctions quite often. We describe a possible strategy for these bidders

Online Auctions

The economic literature on online auctions is rapidly growing because of the enormous amount of freely available field data. Moreover, numerous innovations in auction-design features on platforms such as eBay have created excellent research opportunities. In this article, we survey the theoretical, empirical, and experimental research on bidder strategies (including the timing of bids and winner's-curse effects) and seller strategies (including reserve-price policies and the use of buy-now options) in online auctions, as well as some of the literature dealing with online-auction design (including stopping rules and multi-object pricing rules).

The Economics of Internet Markets

The internet has facilitated the creation of new markets characterized by large scale, increased customization, rapid innovation and the collection and use of detailed consumer and market data. I describe these changes and some of the economic theory that has been useful for thinking about online advertising markets, retail and business-to-business e-commerce, internet job matching and financial exchanges, and other internet platforms. I also discuss the empirical evidence on competition and consumer behavior in internet markets and some directions for future research.internet, market, innovation, advertising, retail, e-commerce, financial exchanges