计量经济分析 = Econometric analysis

1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

On robust estimation of the location parameter

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The Theory of Industrial Organization

Online feedback mechanisms harness the bidirectional communication capabilities of the Internet to engineer large-scale, word-of-mouth networks. Best known so far as a technology for building trust and fostering cooperation in online marketplaces, such as eBay, these mechanisms are poised to have a much wider impact on organizations. Their growing popularity has potentially important implications for a wide range of management activities such as brand building, customer acquisition and retention, product development, and quality assurance. This paper surveys our progress in understanding the new possibilities and challenges that these mechanisms represent. It discusses some important dimensions in which Internet-based feedback mechanisms differ from traditional word-of-mouth networks and surveys the most important issues related to their design, evaluation, and use. It provides an overview of relevant work in game theory and economics on the topic of reputation. It discusses how this body of work is being extended and combined with insights from computer science, management science, sociology, and psychology to take into consideration the special properties of online environments. Finally, it identifies opportunities that this new area presents for operations research/management science (OR/MS) research.

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The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms

Most online feedback mechanisms rely on voluntary reporting of privately observed outcomes. This introduces the potential for reporting bias, a situation where traders exhibit different propensities to report different outcome types to the system. Unless properly accounted for, reporting bias may severely distort the distribution of public feedback relative to the underlying distribution of private transaction outcomes and, thus, hamper the reliability of feedback mechanisms. This study offers a method that allows users of feedback mechanisms where both partners of a bilateral exchange are allowed to report their satisfaction to “see through” the distortions introduced by reporting bias and derive unbiased estimates of the underlying distribution of privately observed outcomes. A key aspect of our method lies in extracting information from the number of transactions where one or both trading partners choose to remain silent. We apply our method to a large data set of eBay feedback. Our results support the widespread belief that eBay traders are more likely to post feedback when satisfied than when dissatisfied and are consistent with the presence of positive and negative reciprocation among eBay traders. Most importantly, our analysis derives unbiased estimates of the risks that are associated with trading on eBay that, we believe, are more realistic than those suggested by a naive interpretation of the unusually high (>99%) levels of positive feedback currently found on that system.

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The Sound of Silence in Online Feedback: Estimating Trading Risks in the Presence of Reporting Bias

What factors make individual bidders pay more or less for the same item in online auctions? We use data on over 55,000 bids over a three-year period collected by a customized Internet software agent. These data are used to perform a within-bidders quasi-experiment, testing bidders who bid on the exact same item at different times during a 30-day period in online auctions. With theories from information systems and consumer behavior as our theoretical lens, we then examine factors that make individuals pay more for the exact same item in online auctions. We find that the same individual will tend to pay more for items sold on a weekend, for items with a picture, and for items sold by experienced sellers. We also find that the same individual is willing to pay more for the same item if others express an interest in that item, exhibiting a type of herd effect. Our results are generalizable to other auctions, and shed light on electronic commerce sales in general, where firms try to sell products for the highest possible price.

Doing their bidding: An empirical examination of factors that affect a buyer's utility in Internet auctions

Reputation systems are emerging as an increasingly important component of online communities, helping elicit good behavior and cooperation among loosely connected and geographically dispersed economic agents A deeper understanding of the factors that drive voluntary online feedback contribution is crucial to the long-term viability of such systems and of the online communities that rely on them This paper contributes in this direction by offering what we believe to be the first in-depth study of the motivations of trader participation in eBay's reputation system To examine these questions, we analyze data from 51,452 eBay rare coin auctions We find evidence suggesting that the high levels (50-70%) of voluntary online feedback contribution on eBay are not strongly driven by pure altruism Rather, we analytically and empirically demonstrate that the expectation of reciprocal behavior from partners increases reputation system participation from self-interested eBay buyers and sellers We develop a random effects probit model that sheds light on the drivers of feedback submission in individual transactions, and find that participation levels rise, then decline as users accumulate experience within the eBay community

Self-Interest, Reciprocity, and Participation in Online Reputation Systems

https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=3141&context=sis_research

The effects of shilling on final bid prices in online auctions

Although the Internet is great for transferring information, transactions in Internet auctions have a greater information asymmetry than corresponding transactions in traditional environments because current auction market mechanisms allow the seller to remain anonymous and to easily change identities. Buyers must rely on the seller's description of a product and ability to deliver the product as promised. Internet auction environments make opportunistic behavior more attractive to sellers because the chance of detection and punishment is decreased. In this research, we examine auction data to see the effect of opportunism in the online auction environment. Introduction E-commerce (EC) offers a variety of new business models, such as long-lasting auctions or 24-hour per day automated order taking. These new models are designed to generate and sustain revenue by taking advantage of the unique characteristics of the World Wide Web. Though the trade media has viewed EC as "the next big thing," its growth has been below expectations. Most companies have Web sites to provide information, but only 4% of organizations currently generate revenue using EC technology, up from 3% in 1998 (Littlewood 1999), implying low customer demand for EC services from most customers. Many media analysts attribute the lower-than-expected EC growth to low levels of trust among consumers (Rankin 1999). Many observers have written about how EC benefits the consumer because of reduced search costs (Bakos 1997; Choudhury 1998). However, what needs to be better recognized by the research literature is how EC opportunism is facilitated by an increase in information asymmetry between the online buyer and the online seller. Economics defines information asymmetries as instances in which there is knowledge that one party has and that another other party lacks in a variety of decisionmaking settings (e.g., production, investment, resource allocation, contracting, and so on). Information asymmetries often lead to various kinds of problems in these settings, including inappropriate decisions and outcomes, unfair exchanges of value, and loss of social welfare. They also can occur in sales transactions, where buyers and sellers are involved. The asymmetry in information can occur with respect to knowledge about product quality or knowledge about behavior that may occur even after the sale. As a result, information asymmetries can lead to transactions in which only one side benefits. They can also lead to fraud, cheating, misrepresentation of self or product, or other moral hazards benefiting one party in a transaction at the expense of another (Tirole 1988). Although EC buyer behavior has been investigated (Lee 1998), less work has been done to investigate changes in seller behavior, especially in Internet auctions. In this research, we propose and test a model that shows how sellers in Internet auctions behave in the absence of identification, personal contact, and a higher uncertainty on the part of the buyer about the product. We explore the following research questions: • Why and how does the increase in information asymmetry brought about by Internet auction transactions change seller behavior? • How does the buyer in an Internet auction respond to this increase in information asymmetry? • How does information asymmetry affect prices in online auctions, and social welfare, more generally? We employ a software agent to gather data from online auctions, extending prior work by Kauffman, March, and Wood (1999). We analyze this data to show how Internet auction sellers react to the customer when information asymmetry increases.

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Charles A. Wood

Papers

The Sound of Silence in Online Feedback: Estimating Trading Risks in the Presence of Reporting Bias

Doing their bidding: An empirical examination of factors that affect a buyer's utility in Internet auctions

Self-Interest, Reciprocity, and Participation in Online Reputation Systems

The effects of shilling on final bid prices in online auctions

Running up the Bid: Modeling Seller Opportunism in Internet Auctions