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Abstract:
Online feedback mechanisms harness the bi-directional communication capabilities of the Internet in order 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 in order to take into consideration the special properties of online environments. Finally, it identifies opportunities that this new area presents for OR/MS research.

Online Feedback Mechanisms, Reputation Systems, E-commerce, Internet, Game Theory, Management Science, Operations Research

Abstract:
Over the past decade, the rise of the Internet has enabled the emergence of surprising new forms of collective intelligence. Examples include Google, Wikipedia, Threadless, and many others. To take advantage of the possibilities these new systems represent, it is necessary to go beyond just seeing them as a fuzzy collection of "cool" ideas. What is needed is a deeper understanding of how these systems work.

This article offers a new framework to help provide that understanding. It identifies the underlying building blocks - to use a biological metaphor, the "genes" - at the heart of collective intelligence systems. These genes are defined by the answers to two pairs of key questions:

- Who is performing the task? Why are they doing it? - What is being accomplished? How is it being done?

The paper goes on to list the genes of collective intelligence - the possible answers to these key questions - and shows how combinations of genes comprise a "genome" that characterizes each collective intelligence system. In addition, the paper describes the conditions under which each gene is useful and the possibilities for combining and re-combining these genes to harness crowds effectively.

Using this framework, managers can systematically consider many possible combinations of genes as they seek to develop new collective intelligence systems.

crowd courcing, wisdom of crowds, collective intelligence

Abstract:
This paper offers a systematic exploration of reputation mechanism design in trading environments with opportunistic sellers, imperfect monitoring of a seller's actions and two possible seller effort levels, one of which has no value to buyers. The objective of reputation mechanisms in such settings is to induce sellers to exert high effort as often as possible. I study the impact of various mechanism parameters (such as the granularity of solicited feedback, the format of the public reputation profile, the policy regarding missing feedback, and the rules for admitting new sellers) on the resulting market efficiency. I find that the maximum efficiency that is attainable through reputation mechanisms is bounded away from the hypothetical first-best case where sellers could credibly pre-commit to full cooperation by a factor that is related to the probability that cooperating sellers may receive "unfair" bad ratings. Furthermore, the maximum efficiency is independent of the length of past history summarized in a seller's public reputation profile. I apply my framework to a model of eBay's feedback mechanism and conclude that eBay's simple mechanism is capable of inducing the maximum theoretical efficiency independently of the number of recent ratings that are being summarized in a seller's profile. I also derive optimal policies for dealing with missing feedback and easy online identity changes.

Reputation Mechanisms, E-commerce, Moral Hazard, Game Theory, Electronic Markets, Internet

Abstract:
Online reputation mechanisms are emerging as a promising alternative to more established mechanisms for promoting trust and cooperative behavior, such as legally enforceable contracts. As information technology dramatically reduces the cost of accumulating, processing and disseminating consumer feedback, it is plausible to ask whether such mechanisms can provide an economically more efficient solution to a wide range of moral hazard settings where societies currently rely on the threat of litigation in order to induce cooperation. In this paper we compare online reputation to legal enforcement as institutional mechanisms in terms of their ability to induce cooperative behavior. Furthermore, we explore the impact of information technology on their relative economic efficiency. We find that although both mechanisms result in losses relative to the maximum possible social surplus, under certain conditions online reputation outperforms litigation in terms of maximizing the total surplus, and thus the resulting social welfare.

Online Reputation Mechanisms, Quality Assurance, Litigation, Internet, Game Theory, E-commerce, Information Technology

Abstract:
Several properties of online interaction are challenging the accumulated wisdom of trading communities on how to produce and manage trust. Online reputation reporting systems have emerged as a promising trust management mechanism in such settings. The objective of this paper is to contribute to the construction of online reputation reporting systems that are robust in the presence of unfair and deceitful raters. The paper sets the stage by providing a critical overview of the current state of the art in this area. Following that, it identifies a number of important ways in which the reliability of the current generation of reputation reporting systems can be severely compromised by unfair buyers and sellers. The central contribution of the paper is a number of novel "immunization mechanisms" for effectively countering the undesirable effects of such fraudulent behavior. The paper describes the mechanisms, proves their properties and explains how various parameters of the marketplace microstructure, most notably the anonymity and authentication regimes, can influence their effectiveness. Finally, it concludes by discussing the implications of the findings for the managers and users of current and future electronic marketplaces and identifies some important open issues for future research.

Abstract:
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.

Online Community, Reputation Systems, Altruism, Reciprocity, Self-interest

Abstract:
Despite the widespread popularity of online opinion forums among consumers, the business value that such systems bring to organizations has, so far, remained an unanswered question. This paper addresses this question by studying the value of online movie ratings in forecasting motion picture revenues. First, we conduct a survey where a nationally representative sample of subjects who do not rate movies online is asked to rate a number of recent movies. Their ratings exhibit high correlation with online ratings for the same movies. We, thus, provide evidence for the claim that online ratings can be considered as a useful proxy for word-of-mouth about movies. Inspired by the Bass model of product diffusion, we then develop a motion picture revenue-forecasting model that incorporates the impact of both publicity and word of mouth on a movie's revenue trajectory. Using our model, we derive notably accurate predictions of a movie's total revenues from statistics of user reviews posted on Yahoo! Movies during the first week of a new movie's release. The results of our work provide encouraging evidence for the value of publicly available online forum information to firms for real-time forecasting and competitive analysis.

Online reviews, motion pictures, revenue forecasting, diffusion models

Abstract:
This paper introduces a model for analyzing marketplaces, such as eBay, which rely on binary reputation mechanisms for quality signaling and quality control. In our model sellers keep their actual quality private and choose what quality to advertise. The reputation mechanism is primarily used to induce sellers to advertise truthfully. Buyers base their ratings on the difference between expected and actual quality. Furthermore, raters are lenient and do not post negative ratings unless transactions end up exceptionally bad. It is shown that, in such a setting, the fairness of the market outcome is determined by the relationship between rating leniency and corresponding strictness when assessing a seller's feedback profile. If buyers judge sellers too strictly (relative to how leniently they rate) then, at steady state, sellers will be forced to understate their true quality. On the other hand, if buyers judge too leniently then sellers can get away with consistently overstating their true quality. An optimal judgment rule, which results in outcomes where, at steady state, buyers accurately predict the true quality of sellers, is theoretically possible to derive for all leniency levels. Furthermore, if buyers judge sellers using that rule, then the more lenient buyers are when rating sellers, the more likely it is that sellers will find it optimal to settle down to steady-state quality levels, as opposed to oscillating between good quality and bad quality. However, it is argued that this optimal rule depends on several parameters, which are difficult to estimate from the information that eBay currently makes available to its members. It is therefore questionable to what extent unsophisticated buyers are currently using eBay feedback information in an optimal way.

Abstract:
There is growing evidence that consumers are influenced by Internet-based opinion forums before making a variety of purchase decisions. Firms whose products are being discussed in such forums are, therefore, tempted to try to manipulate consumer perceptions by posting costly anonymous messages that praise their products or by offering incentives to consumers to do so. This paper offers a theoretical analysis of the impact of such behavior on firm profits and consumer surplus. We examine a setting where two firms simultaneously introduce imperfect substitute experience goods of different qualities and consumers obtain quality information from an online forum. The most striking result of our analysis is that strategic manipulation can either decrease or increase the information value of online forums to consumers relative to the case where no manipulation takes place. Specifically, there exist settings where the presence of honest consumer opinions induces firms to reveal their own, more precise, knowledge of product qualities by manipulating the forums at relative intensities that are proportional to their actual qualities. However, if a sufficiently large number of consumers post honest opinions online forum manipulation is harmful to firms because its cost outweighs its benefits. The social overhead of online manipulation can be reduced by developing technologies that increase the unit cost of manipulation and by encouraging higher participation of honest consumers.

Internet-based opinion forums, Strategic Manipulation

Abstract:
There is growing evidence that consumers are influenced by Internet-based opinion forums before making a variety of purchase decisions. Firms whose products are being discussed in such forums are, therefore, tempted to try to manipulate consumer perceptions by posting costly anonymous messages that praise their products or by offering incentives to consumers to do so. This paper offers a theoretical analysis of the impact of such behavior on firm profits and consumer surplus. We examine a setting where two firms simultaneously introduce imperfect substitute experience goods of different qualities and consumers obtain quality information from an online forum. The most striking result of our analysis is that strategic manipulation can either decrease or increase the information value of online forums to consumers relative to the case where no manipulation takes place. Specifically, there exist settings where the presence of honest consumer opinions induces firms to reveal their own, more precise, knowledge of product qualities by manipulating the forums at relative intensities that are proportional to their actual qualities. However, if a sufficiently large number of consumers post honest opinions online forum manipulation is harmful to firms because its cost outweighs its benefits. The social overhead of online manipulation can be reduced by developing technologies that increase the unit cost of manipulation and by encouraging higher participation of honest consumers.

Internet-based opinion forums, Strategic Manipulation

Abstract:
Online "feedback mechanisms" - also known as "reputation systems" - have been implemented in the most important private e-markets, such as eBay, Yahoo!, Amazon to foster trust and cooperation among trading partners. In this paper we discuss the main issues relevant for the optimal design of such mechanisms, providing practical indications for public and private e-platforms.

Procurement, reputation, feedback mechanisms

Abstract:
By providing a platform where consumers can discuss obscure products not covered by mainstream media, user-centered media, such as online product review forums, are expected by many to reduce the informational inequality between hit and niche products and thus help shift demand towards the long tail of less popular products. Some researchers have challenged this viewpoint, arguing that other aspects of the Internet, such as the prevalence of prominently displayed statistics about the actions of prior consumers, end up reinforcing consumer attention on already popular products. In this paper, we empirically test the merits of these two hypotheses by investigating how a population's propensity to contribute post-purchase online reviews for different products of the same category (motion pictures) relates to offline and online indicators of those products' popularity. We discover the presence of an interesting tension between the population's preference to review products that are lesser known in the offline domain and its simultaneous attraction to discussing products that many other people have already commented on online. Overall, it appears that the latter effect dominates: A Gini coefficient analysis reveals that the weekly volumes of user-contributed movie reviews in our sample are even more skewed towards popular movies than the corresponding weekly box office revenues. Our findings have implications for online forum designers and for ongoing research on the long tail theory.

user-generated content, online product reviews, word-of-mouth, long tail, motion pictures, event count modeling, Gini coefficient

Abstract:
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 confirm the widespread belief that eBay traders are more likely to post feedback when satisfied than when dissatisfied. Furthermore, we provide rigorous evidence for 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 naïve interpretation of the unusually high (>99%) levels of positive feedback currently found on that system.

electronic markets, feedback mechanisms, reputation, reporting bias, maximum likelihood

Abstract:
This paper studies settings where a number of sellers of different reputations for honesty simultaneously offer sealed-bid, second-price, single-unit auctions for imperfect substitute goods to unit-demand buyers. Among other applications, these settings can serve as an abstraction of large scale decentralized Internet auction marketplaces, such as eBay. I characterize the form of the bidding equilibria and derive expressions for the corresponding allocative efficiency and expected seller revenue. When bidders are restricted to submit at most one bid there exists a unique Bayes-Nash equilibrium that has the following form: Auctions are ranked according to their expected valuation, taking into account both the quality of the good and the seller's reputation. Buyers self-separate into a finite number of zones, according to their types. Buyers whose types fall in the k-th zone randomize between the top k auctions, assigning increasingly higher probability to selecting lower auctions. In such equilibria auction revenue is an increasing convex function of seller reputation. Allowing unit-demand bidders to place an arbitrary number of bids induces complex mixed strategy profiles where bidders place positive bids in all available auctions. The probabilistic nature of the bidding equilibria introduces allocative inefficiencies that are most severe when the number of bidders is roughly equal to the number of sellers.

simultaneous auctions, imperfect substitutes, reputation, Internet, eBay

Abstract:
An important current trend in advertising is the replacement of traditional pay-per-exposure (aka pay-per-impression) pricing models with performance based mechanisms in which advertisers pay only for measurable actions by consumers. Such pay-per-action mechanisms are becoming the predominant method of selling advertising on the Internet. Well-known examples include pay-per-click, pay-per-call and pay-per-sale. This work highlights an important, and hitherto unrecognized, side-effect of pay-per-action advertising. I find that, if the prices of advertised goods are endogenously determined by advertisers to maximize profits net of advertising expenses, pay-per-action mechanisms induce firms to distort the prices of their goods (usually upwards) relative to the prices that would maximize profits in settings where advertising is sold under pay-per-exposure methods. Upward price distortions reduce consumer surplus and one or both of advertiser profits and publisher revenues, leading to a net reduction in social welfare. They persist in current quality-weighted pay-per-action schemes, such as the ones used by Google and Yahoo. In the latter settings they always reduce publisher revenues relative to pay-per-exposure methods. I propose enhancements to today’s quality-weighted pay-per-action schemes that resolve these problems and show that the steady state limit of my enhanced mechanisms has identical allocation and revenue properties to those of an optimal pay-per-exposure mechanism.

online advertising, pay-per-action, keyword auctions, game theory.

Abstract:
Reputation mechanisms have become an important component of electronic markets, helping to build trust and elicit cooperation among loosely connected and geographically dispersed economic agents. Understanding the impact of different reputation mechanism design parameters on the resulting market efficiency has, thus, emerged as a question of theoretical and practical interest. Along these lines, this note studies the impact of the frequency of reputation profile updates on cooperation and efficiency. The principal finding is that, in trading settings with pure moral hazard and noisy ratings, if the per-period profit margin of cooperating sellers is sufficiently high, a mechanism that does not publish every single rating it receives but rather, only updates a trader's public reputation profile every k transactions with a summary statistic of a trader's most recent k ratings, can induce higher average levels of cooperation and market efficiency than a mechanism that publishes all ratings as soon as they are posted. The note derives expressions for calculating the optimal profile updating interval k, discusses the implications of this finding for existing systems, such as eBay, and proposes alternative reputation mechanism architectures that attain higher maximum efficiency than the, currently popular, reputation mechanisms that publish summaries of a trader's recent ratings.

electronic markets, reputation mechanisms, game theory