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

Money Walks: A Human-Centric Study on the Economics of Personal Mobile Data

In the context of a myriad of mobile apps which collect personally identifiable information (PII) and a prospective market place of personal data, we investigate a user-centric monetary valuation of mobile PII. During a 6-week long user study in a living lab deployment with 60 participants, we collected their daily valuations of 4 categories of mobile PII (communication, e.g. phonecalls made/received, applications, e.g. time spent on different apps, location and media, photos taken) at three levels of complexity (individual data points, aggregated statistics and processed, i.e. meaningful interpretations of the data). In order to obtain honest valuations, we employ a reverse second price auction mechanism. Our findings show that the most sensitive and valued category of personal information is location. We report statistically significant associations between actual mobile usage, personal dispositions, and bidding behavior. Finally, we outline key implications for the design of mobile services and future markets of personal data.Comment: 15 pages, 2 figures. To appear in ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp 2014

Competition Between Auctions

Even though auctions are capturing an increasing share of commerce, they are typically treated in the theoretical economics literature as isolated. That is, an auction is typically treated as a single seller facing multiple buyers or as a single buyer facing multiple sellers. In this paper, we review the state of the art of competition between auctions. We consider three different types of competition: competition between auctions, competition between formats, and competition between auctioneers vying for auction traffic. We highlight the newest experimental, statistical and analytical methods in the analysis of competition between auctions.auctions, bidding, competition, auction formats, auction houses

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

The Evolving Agricultural Marketplace: Selected Results and Implications for the West from the Laboratory

Marketing,

Country-Specific Effects of Reputation and Information: A Comparison of Online Auctions in Germany, the UK, and the US

Empirical studies on the effect of sellers’ reputation on closing prices in online auctions present mixed results. A large number of studies addresses reputational effects in one country, especially in the US. Only a small number of cross-country studies inspect the moderating role of institutional frameworks on bidder behavior. The purpose of this paper is to examine if country-specific differences in the formal and informal institutional framework influence the effects of reputation and information signals on final prices in online auctions. From the perspective of the New Institutional Economics, management decisions and individuals’ characteristics are affected by the institutional framework, which consists of cultural aspects as well as a set of social and legal rules and regulations. Therefore, bidders that are influenced by one institutional framework have different preferences, expectations, and perceptions about reputation and information in online auctions than individuals socialized by another institutional framework. In order to examine the effects of reputation and information on prices as well as to asses cross-country similarities and differences in these effects, a sample of 6,166 homogenous online auctions, conducted on the respective eBay websites in Germany, the UK, and the US, is analyzed. The results suggest that either the effects of reputation and product information variables vary significantly across countries or that different variables have an impact on prices in different countries. It can be concluded that country-specific institutional frameworks influence bidder behavior in international online auction markets.reputation, information, online auctions, cross-country studies

E-loyalty networks in online auctions

Creating a loyal customer base is one of the most important, and at the same time, most difficult tasks a company faces. Creating loyalty online (e-loyalty) is especially difficult since customers can ``switch'' to a competitor with the click of a mouse. In this paper we investigate e-loyalty in online auctions. Using a unique data set of over 30,000 auctions from one of the main consumer-to-consumer online auction houses, we propose a novel measure of e-loyalty via the associated network of transactions between bidders and sellers. Using a bipartite network of bidder and seller nodes, two nodes are linked when a bidder purchases from a seller and the number of repeat-purchases determines the strength of that link. We employ ideas from functional principal component analysis to derive, from this network, the loyalty distribution which measures the perceived loyalty of every individual seller, and associated loyalty scores which summarize this distribution in a parsimonious way. We then investigate the effect of loyalty on the outcome of an auction. In doing so, we are confronted with several statistical challenges in that standard statistical models lead to a misrepresentation of the data and a violation of the model assumptions. The reason is that loyalty networks result in an extreme clustering of the data, with few high-volume sellers accounting for most of the individual transactions. We investigate several remedies to the clustering problem and conclude that loyalty networks consist of very distinct segments that can best be understood individually.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS310 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Bidding Behavior in Competing Auctions: Evidence from eBay

Much of the existing auction literature treats auctions as running independently of one another, with each bidder choosing to participate in only one auction. However, in many online auctions, a number of substitutable goods are auctioned concurrently and bidders can bid on several auctions at the same time. Recent theoretical research shows how bidders can gain from the existence of competing auctions, the current paper providing the first empirical evidence in support of competing auctions theory using online auctions data from eBay. Our results indicate that a significant proportion of bidders do bid across competing auctions and that bidders tend to submit bids on auctions with the lowest standing bid, as the theory predicts. The paper also shows that winning bidders who cross-bid pay lower prices on average than winning bidders who do not.Competing Auction, Cross-Bidding, Auction Empirics

An Experimental Study of Information Revelation Policies in Sequential Auctions

Theoretical models of information asymmetry have identied a tradeoff between the desire to learn and the desire to prevent an opponent from learning private information. This paper reports a laboratory experiment that investigates if actual bidders account for this tradeoff, using a sequential procurement auction with private cost information and varying information revelation policies. Specically, the Complete Information Policy, where all submitted bids are revealed between auctions, is compared against the Incomplete Information Policy, where only the winning bid is revealed. The experimental results are largely consistent with the theoretical predictions. For example, bidders pool with other types to prevent an opponent from learning signicantly more often under a Complete Information Policy. Also as predicted, the procurer pays less when employing an Incomplete Information Policy only when the market is highly competitive. Bids are usually more aggressive than the risk neutral quantitative prediction, which is usually consistent with risk aversion.Complete and Incomplete Information Revelation Policies, Laboratory Study, Procurement Auction, Multistage Game

Engineering Trust - Reciprocity in the Production of Reputation Information

Reciprocity in feedback giving distorts the production and content of reputation information in a market, hampering trust and trade efficiency. Guided by feedback patterns observed on eBay and other platforms we run laboratory experiments to investigate how reciprocity can be managed by changes in the way feedback information flows through the system, leading to more accurate reputation information, more trust and more efficient trade. We discuss the implications for theory building and for managing the redesign of market trust systems.market design, reputation, trust, reciprocity, eBay