Online Reputation Systems

SSRN Electronic Journal, 2000

We analyze how different dimensions of a seller's reputation affect pricing power in electronic markets. We do so by using text mining techniques to identify and structure dimensions of importance from feedback posted on reputation systems, by aggregating and scoring these dimensions based on the sentiment they contain, and using them to estimate a series of econometric models associating reputation with price premiums. We find that different dimensions do indeed affect pricing power differentially, and that a negative reputation hurts more than a positive one helps on some dimensions but not on others. We provide the first evidence that sellers of identical products in electronic markets differentiate themselves based on a distinguishing dimension of strength, and that buyers vary in the relative importance they place on different fulfilment characteristics. We highlight the importance of textual reputation feedback further by demonstrating it substantially improves the performance of a classifier we have trained to predict future sales. This paper is the first study that integrates econometric, text mining and predictive modeling techniques toward a more complete analysis of the information captured by reputation systems, and it presents new evidence of the importance of their effective and judicious design.

Experimental Economics, 2006

We conducted the first randomized controlled field experiment of an Internet reputation mechanism. A high-reputation, established eBay dealer sold matched pairs of lotsbatches of vintage postcards-under his regular identity and under new seller identities (also operated by him). As predicted, the established identity fared better. The difference in buyers' willingness-to-pay was 8.1% of the selling price. A subsidiary experiment followed the same format, but compared sales by relatively new sellers with and without negative feedback. Surprisingly, one or two negative feedbacks for our new sellers did not affect buyers' willingness-to-pay.

Journal of Organizational Computing and Electronic Commerce, 2014

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Proceeding of the 2005 ACM SIGCOMM workshop on Economics of peer-to-peer systems - P2PECON '05, 2005

Web-based systems that establish reputation are central to the viability of many electronic markets. We present theory that identifies the different dimensions of online reputation and characterizes their influence on the pricing power of sellers. We provide evidence that existing, numeric reputation scores conceal important seller-specific dimensions of reputation and we validate our theory further by proposing a new text mining technique that identifies and quantitatively evaluates further dimensions of importance in reputation profiles. We also suggest that the buyer-seller network contains critical reputation information that we can further exploit to improve the design of a reputation mechanism. Our experimental evaluation validates the predictions of our model using a new data set containing over 12,000 transactions for consumer software on Amazon.com's online secondary marketplace. This paper is the first attempt to integrate econometric methods and text and link mining techniques towards a more complete analysis of the information captured by reputation systems, and it presents new evidence of the importance of their effective and judicious design.

ACM Transactions on the Web, 2010

Reputation in on-line economic systems is typically quantified using counters that specify positive and negative feedback from past transactions and/or some form of transaction network analysis that aims to quantify the likelihood that a network user will commit a fraudulent transaction. These approaches can be deceiving to honest users from numerous perspectives. We take a radically different approach with a goal to guarantee to a buyer that a seller cannot disappear from the system with profit following a set of transactions that total a certain monetary limit. Even in the case of stolen identity, an adversary cannot produce illegal profit unless a buyer decides to pay over the suggested sales limit.

Review of Economics and Statistics, 2005

On the online auction site eBay, by convention, sellers do not ship goods to winning bidders until after they have received payment, so there is an opportunity for sellers to take advantage of bidders' trust. Realizing this, the designers of eBay created a system that relies on self-enforcement using reputation. Several recent studies have found that bidders give little or no reward to sellers who have better reputations. I show that in fact, sellers are strongly rewarded for the first few reports that they have behaved honestly, but marginal returns to additional reports are severely decreasing.

Analyse & Kritik, 2004

Each day, a countless number of items is sold through online auction sites such as eBay and Ricardo. Though abuse is being reported more and more, transactions seem to be relatively hassle free. A possible explanation for this phenomenon is that the sites' reputation mechanisms prevent opportunistic behavior. To analyze this issue, we first summarize and extend the mechanisms that affect the probability of sale of an item and its price. We then try to replicate the results as found in four recent papers on online auctions. Our analyses reveal that (1) it makes sense to differentiate between 'power sellers' and the less regular users, (2) there are variables that have an effect on sales that are often not controlled for, (3) one should carefully consider how reputation is operationalized, (4) neglecting heteroscedasticity in the data can have serious consequences, and there is some support indicating that effects differ across auction sites.

Electronic Commerce Research, 2010

Many studies have examined how various factors affect prices in online auctions. These studies assume that the relationship between price and the seller's reputation take a variety of functional forms, most frequently linear or linear-log. Others divide the sellers into categories by their reputations, and control for dummy variables indicating the seller's category. Identifying the correct functional form is a critical issue for research on any topic involving online auctions. Studies that assume the wrong functional form run the risk of generating biased and inconsistent estimates of the effect of their variables of interest. In this study, the price-reputation relationship is estimated under each of these functional forms using data from auctions of three different products. The estimated effect of reputation on price is substantially larger when using a categorical specification. The models are then subjected to specification tests which suggest that the categorical model is the most appropriate choice.

Applied Economics, 2012

Feedback systems are claimed to be a crucial component of the success of electronic marketplaces like eBay or Amazon Marketplace. This article aims to examine the efficiency of various feedback systems on trust between anonymous traders, through a set of experiments based on the trust game. Our results indicate that trust is significantly improved by the introduction of a reputation feedback system. However such mechanisms are far from being perfect and are especially vulnerable to strategic ratings and reciprocation. Our findings indicate that some changes in rating rules may significantly improve the efficiency of feedback systems, by avoiding strategic rating or reciprocation, and hence stimulate trust and trustworthiness among traders. In particular, a system in which individuals are not informed of the other trader's decision before taking their own decision provides better results both in terms of trust and earnings. JEL classification: C92, C72, L14, L86. * CREM, CNRS, Université de Rennes 1, Marsouin and CIRANO (Montreal). [email protected] † CREM, CNRS, Université de Rennes 1, Marsouin. [email protected]

Information & Management, 2016

Reputation profiles, based on customer feedback ratings, are important for achieving above average sales prices in online auctions. However, contradictory results in past research suggest that reputation effects may depend on information alternatives to customer feedback that sellers can provide to buyers. By explicitly modeling the competing assumptions of classical and contemporary approaches to buyer decision-making and using hierarchical linear modeling to analyse data from 363 online auctions, we found that sellers may benefit from carefully evaluating what information alternatives they combine with reputation profile to realize higher sales prices. 2016 Elsevier B.V. All rights reserved.