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Abstract: With the proliferation of online user review systems, there has been a growing interest in understanding how they influence consumers' purchase decisions. In this paper, we explore the dynamic process of online user reviews for motion pictures, and its relationship with movies' daily box office performance. We characterize online user reviews through a dynamic simultaneous system, in which we separate the effects of online user reviews as both a precursor to and an outcome of box office revenues. First, in contrast to the common wisdom that better user reviews lead to more sales, we showed that the rating of online user reviews has no significant impact on movies' box office revenues. Second, we found that box office sales are significantly influenced by the number of online postings. Our findings suggest that it is the underlying word-of-mouth effect that plays a dominant role rather than the user ratings. Online user review sites help reveal the underlying word-of-mouth process, but the sites themselves may not play as significant a role in influencing sales as commonly expected.
Online User Review; Word-of-Mouth; Product Sale; Motion Picture
Abstract: There are growing interests in understanding how word-of-mouth (WOM) on the Internet is generated and how it influences consumers' purchase decisions at retail outlets. A unique aspect of the WOM effect is the presence of a positive feedback mechanism between WOM and retail sales. We characterize the process through a dynamic simultaneous equation system, in which we separate the effect of online WOM as both a precursor to and an outcome of retail sales. We apply our approach to the movie industry, showing that both a movie's box office revenue and WOM valence significantly influence WOM volume. WOM volume in turn leads to higher box office performance. This positive feedback mechanism highlights the importance of WOM in generating and sustaining retail revenue.
Online user reviews, Word-of-mouth, e-Commerce, Motion picture, Simultaneous equations
Abstract: This paper aims to answer three major questions related to the unexplored role of organic listing in online search advertising: (1) Should advertisers who are already placed at top slots in the organic list bid actively for sponsored positions? (2) Does organic listing benefit or harm search engine revenue, social welfare, and overall sales diversity? (3) How can organic ranking be improved? We set up a game-theoretic model in which firms bid for sponsored advertising slots and compete for consumers in the product market. Firms are asymmetrically differentiated in terms of market preference and are placed at different organic slots with different prominence based on their relative popularity. We identify two major incentives for sponsored bidding when advertisers face the two competing lists: the promotive and predatory incentives. We investigate the interaction between the two forces across firms within different market structures and derive the equilibrium bidding outcome. We analyze the effects of the organic listing on equilibrium outcomes by comparing it with a benchmark case in which there is only a sponsored list. We find that, in general, organic listing may hurt search engine revenue, yet it could induce higher social welfare and sales diversity. To overcome the shortcomings of the organic listing that arise in the presence of huge competence differences among advertisers, we propose a mixed organic ranking mechanism in place of the typical popularity-based ranking rule. We show that the proposed organic ranking may improve equilibrium outcomes such that revenue, welfare, and diversity increase concurrently.
organic listing, sponsored bidding, price advertising
Abstract: Keyword auctions are another multi-billion dollar application of auctions after the celebrated eBay-like business-to-consumer auctions in electronic commerce. Inevitably, keyword auctions have recently gained attention among researchers. Questions regarding what (is keyword auction), why (we should use keyword auctions), and how (to design keyword auctions), have been raised. While some of these issues has become clearer over time, many are still open. The purpose of this paper is to summarize the current efforts to address these questions, focusing mainly on the third, that is, how to design effective keyword auctions. We also point out several issues for future research.
keyword auctions, google, yahoo, online advertising
Abstract: Online users often need to make adoption decisions without accurate information about the product values. An informational cascade occurs when it is optimal for an online user, having observed others' actions, to follow the adoption decision of the preceding individual without regard to his own information. Informational cascades are often rational for individual decision making; however, it may lead to adoption of inferior products. With easy availability of information about other users' choices, the Internet offers an ideal environment for informational cascades. In this paper, we empirically examine informational cascades in the context of online software adoption. We find user behavior in adopting software products is consistent with the predictions of the informational cascades literature. Our results demonstrate that online users' choices of software products exhibit distinct jumps and drops with changes in download ranking, as predicted by informational cascades theory. Furthermore, we find that user reviews have no impact on user adoption of the most popular product, while having an increasingly positive impact on the adoption of lower ranking products. The phenomenon persists after controlling for alternative explanations such as network effects, word-of-mouth (WOM) effects, and product diffusion. Our results validate informational cascades as an important driver for decision making on the Internet. The finding also offers an explanation for the mixed results reported in prior studies with regard to the influence of online user reviews on product sales. We show that the mixed results could be due to the moderating effect of informational cascades.
E-commerce, herding, informational cascades, decision making, network effects, word-of-mouth, software download, online communities, online user review
Abstract: Recently, user-oriented online sharing communities (e.g., YouTube, Flickr) have seen explosive growth. In these communities, social norms are relatively weak compared to many message-based online communities, as users' attention is on content and communication among them is limited. Under this setting, it is crucial to understand the factors that affect a user's choice to share. We propose a three-factor decision framework to study users' choice of sharing, which we then empirically test using a five-year dataset collected in an IRC music sharing community. We find that a user is more likely to continue sharing if he receives more benefit directly from the community; if he has more social connections; and if he has a high recognized value to the community. We also test the validity of the results by controlling the impacts of aggregated community activities, individual characteristics, users' life span, and legal events.
Online sharing community, implicit community, IRC, voluntary contribution, music sharing
Abstract: We consider an integrated game-theoretic model in which firms compete for advertising positions and then compete in price for customers in a product market. Positions are differentiated in their prominence and firms differ in their competence. We use this framework to endogenously evaluate the value of a prominent advertising position, and examine the competition outcome and the resulting price dispersion patterns. We find that a prominent advertising position may or may not be desirable for a firm with competitive advantage, depending on market structure and consumers' search pattern. When it values the prominent position, the advantaged firm should bid aggressively to win only if either its relative competitive strength or the location prominence difference is significant. Interestingly, the expected price in the prominent position may or may not be higher. It is lower when firms' competence difference is salient and not dwarfed by the location prominence difference.
Pricing, Price Advertising, Consumer Search
Abstract: Online peer-to-peer communities and online social networks have become increasingly popular. In particular, the recent boost of online peer-to-peer communities leads to exponential growth in sharing of user-contributed content which have brought profound changes to business and economic practices. Understanding the formation and sustainability of such peer-to-peer communities has important implications for businesses. We develop a dynamic two-sided network model that relates growth of communities to interactions between contribution and consumption of resources in online sharing activities. Using online music sharing data collected from a popular IRC music sharing service over five years, we empirically apply the model to identify dynamics in the music sharing community. We find that the music sharing community demonstrates distinctive characteristics of a two-sided network. Contribution in the community leads to more consumption and consumption leads to more contribution, creating positive network effects in the community. Moreover, we find significant negative externalities among consumption activities and among contribution activities. The combination of the positive and negative externalities drives the underlying dynamics and growth of online sharing communities. Using the dynamic model, we quantify equilibrium growth rate of the community. We find that the equilibrium growth rate changes over time, possibly as a result of legal actions taken by the music industry. Our study provides a first glimpse into the mechanism through which peer-to-peer communities sustain and thrive in a constantly changing environment.
online communities, two-sided networks, IRC channel, P2P music sharing, evolutionary games, digital piracy
Abstract: Shifts to more distributed forms of organizations and the prevalence of interorganizational relationships have lead to increasing needs for knowledge transfers between entities with asymmetric and incomplete information. Due to such information asymmetry and incompleteness, parties seeking knowledge may not be able to identify qualified knowledge providers, and the appropriate experts may fail to be motivated to engage in knowledge transfers. In this paper, we propose a sender-receiver framework for studying knowledge transfers under asymmetric and/or incomplete information. We outline four types of information structures for knowledge transfers, and focus on the sender-advantage asymmetric information structure and the symmetric incomplete information structure. We develop formal game-theoretical models, show how information incompleteness and asymmetry may negatively influence knowledge transfers, and propose solutions to alleviate these negative impacts. Implications for knowledge transfer research and practice are also discussed.
knowledge transfer, knowledge management, incomplete information, asymmetric information, sender-receiver game, game theory
Abstract: Procurement auctions are sometimes plagued with a chosen supplier's failing to accomplish a project successfully. The risk of project failure is considerable, especially when the buyer has inadequate information about suppliers ex ante and the project can only be evaluated at the end. To manage such uncertainty, a model of competitive procurement and contracting for a project is presented in this paper. We study a setting in which suppliers differ in both the costs to fulfill the project and the types reflecting their success probabilities. To screen suppliers, the buyer invites suppliers to specify a two-dimensional bid composed of the proposed cost and a penalty payment if the delivered project fails to meet the requirements. We find that a quasi-linear scoring rule can effectively separate suppliers regarding their types. We then study the efficient and optimal design of the scoring rule. The efficient design internalizes the inferred information on suppliers' type and essentially ranks suppliers based on the expected total cost to the buyer. In the optimal design, the buyer may or may not under-reward suppliers' high success probability, depending on the balance between suppliers' success probabilities and the associated cost distributions. Interestingly, it is always optimal for the buyer to possibly award the project to suppliers with low success probability in order to promote the competition, even when the difference in suppliers' success probabilities is huge. We show that, compared to standard auctions, the procurement auctions with contingent contracts can significantly improve both social welfare and the buyer's payoff.
Procurement auctions, Contingent contract, Scoring rule
Abstract: This paper discusses a class of auctions, weighted unit-price auctions (WUPAs), which capture key features of keyword auctions, a novel mechanism behind the multi-billion-dollar keyword advertising industry. We analyze the equilibrium bidding strategy in the WUPA class and study its two main design parameters - weighting factors and minimum bids - both of which make use of the auctioneer's ex-ante information on bidders' ability to generate outcomes. Our results indicate equilibrium bidding functions in WUPAs may have kinks and jumps. WUPAs can be efficient when an auctioneer weights unit-price bids by bidders' expected yield and imposes the same minimum score (but not the same minimum bid-price) across all bidders. Optimally weighted WUPAs can generate more revenue than generalized first-price auctions, and optimal minimum bids generally differ from those prescribed in the mechanism design literature.
keyword advertising, weighted unit-price auctions, ex-ante information, score rule, Google and Yahoo
Abstract: Recently user-oriented online sharing communities have seen explosive growth. Two characteristics of these communities set them apart from traditional online message-based communities such as online forums. First, users have no social ties before joining the community. Second, there is little or no "verbal" communication between users. This research investigates the structure and dynamics of online sharing communities using data collected from an IRC music channel from 2001 to 2006, covering all five years of the post-Napster age. We have collected more than three hundred million individual activities, capturing 0.05% of the global music sharing volume. We find that sharers are an essential part of the community and their activities have a dominant impact on the growth of the community. By contrast, free riders have two opposite impacts on sharer retention. More free riders in number make it more likely for a sharer to keep sharing, while more free rider activities discourage sharers from contributing. That is, the existence of free riders, despite the congestion caused by their download activities, does to some degree stabilize the community. Most previous literature examines the online community only from the aggregate level. Our study, nevertheless, distinguish the influence and behavior of different members in the community. Instead of paying only attention to the total number of users, our results suggest that understanding the impact of their core members is critical in investigating the dynamics and the sustainability of online sharing communities.
sharing community, sustainability, network externality, free-riding
Abstract: The convenience of wireless networking and lightweight handheld devices has led to a large-scale adoption of wireless technologies. Corporations, universities, hospitals, homes, and public places are deploying these networks at a remarkable rate. In a wireless mesh network, a few Internet transmit access points (ITAPs), serving as gateways to the Internet, are deployed across the neighborhood. Wireless nodes (e.g., houses) are equipped with low-cost antennas, and serve as routers to send traffic for both itself and its neighbors. In this way, a multihop wireless network is formed among wireless nodes to cooperatively route traffic to the Internet through the ITAPs. Such a multihop structure dramatically reduces the number of ITAPs, which is a major cost in deployment. The promise of wireless mesh networks has attracted lots of research work in the area, ranging from designing MAC protocols to developing routing protocols and routing metrics, to studying interactions with TCP, to controlling topology via power control, channel assignment, and directional antennas. In addition to network technologies, another major factor that determines the success of wireless mesh networks is whether there exist viable business models. There is limited research on this problem. In wireless mesh networks, wireless nodes are required to forward traffic for both itself and its neighbors. If the nodes are controlled by self-interested users, they may not efficiently share their capacity to route traffic for other nodes. Such possibility undermines the performance and feasibility of wireless mesh networks. Therefore effective pricing mechanisms need to be developed before the mesh technologies are commercialized. Motivated by the observations, we develop two pricing mechanisms for non-cooperative wireless mesh networks: a centralized pricing mechanism and a decentralized one. In the centralized pricing mechanism, the service provider needs to monitor and price the traffic originated from every node, while the decentralized scheme leaves the traffic monitoring and pricing to each router. We describe algorithms a service provider uses to efficiently place the ITAPs, and determine the prices. We evaluate the profitability and overall efficiency of the wireless mesh network under the centralized and decentralized pricing mechanisms. As a comparison, we also analyze an alternative structure based on a single-hop wireless network. In such a network, each user can directly communicate with an ITAP, and does not rely on other users for its communication. On the other hand, the singlehop wireless network requires more Internet access points to be deployed, thereby increasing the infrastructure cost. Our analysis has important practical implications to wireless service providers and the future of wireless mesh technologies.
Wireless Mesh Network, Pricing Mechanism, Business Model
Abstract: Indirect reciprocity is an important factor that motivates individual contributions in social networks. However, prior studies of indirect reciprocity are often limited to a snapshot view of individual interactions in social environments. This paper analyzes indirect reciprocity from a dynamic perspective in the context of a peer-to-peer music sharing network. We have two main findings. First, we reveal that indirect reciprocity is a dynamic social force. An individual's likelihood of contribution changes with the social environment, particularly with others' contribution levels in the network. The individual increases her contribution probability when she observes an increase in the number of contributors while decreases her contribution probability when she observes an increase in the number of free riders. Second, we find that indirect reciprocity is a social norm that is voluntarily enforced by contributors in the network. They do so through the setting of servers to discriminate downloaders. When the number of free riders increases, a contributor is more likely to change the server settings to provide preferential services to other contributors and lesser services to free riders. Our results indicate that indirect reciprocity plays a key role in sustaining private contributions to social networks.
indirect reciprocity, social norm, social enforcement, social networks, peer-to-peer networks, public goods, incentive provisions, music sharing
Abstract: Online communities provide a social sphere for people to share information and knowledge. While information sharing is becoming a ubiquitous online phenomenon, how to ensure information quality or induce quality content, however, remains a challenge due to the anonymity of commentators. This paper introduces moderation into reputation systems. We show that moderation directly impacts strategic commentators' incentive to generate useful information, and moderation is generally desirable to improve information quality. Interestingly, we find that when being moderated with different probabilities based on their reputations, commentators may display a pattern of reputation oscillation, in which they generate useful content to build up high reputation and then exploit their reputation. As a result, the expected performance from high-reputation commentators can be inferior to that from low-reputation ones (reversed reputation). We finally investigate the optimal moderation resource allocation, and conclude that the seemingly abnormal reversed reputation could arise as an optimal result.
Moderation, reputation, online community, knowledge management
Abstract: There has been an extensive research literature on auctions, but recent developments in technology have resulted in new interest in auction mechanisms as a practical way of allocating resources. This paper presents a new double-auction mechanism to handle resource allocation for public goods when complementarity exists. The mechanism is placed in the context of an organization's internal knowledge investment. Knowledge goods have two distinct characteristics. First, knowledge within an organization can be considered a public good, so it is subject to the free-rider problem. Second, knowledge is interrelated and interdependent; that is, there is complementarity among knowledge components. The value of knowledge often derives from a bundle of knowledge components, rather than from its individual pieces. These two characteristics present a serious challenge to allocating organizational resources for knowledge goods. We introduce an internal market in which knowledge providers offer knowledge projects and knowledge consumers place bids to acquire them. The mechanism is a Groves-Clarke type double auction that allows bundled knowledge goods to be traded so as to recognize complementarities between knowledge projects. The market mechanism we propose is incentive compatible; i.e., it induces people to reveal their true valuation. In addition, it allows trades of knowledge bundles to determine which knowledge components are most valuable from the organization's viewpoint. Under mild assumptions, the mechanism is a computationally tractable solution to operating a market of bundled public goods. We further show how imputed prices can be calculated for subsets of knowledge components and prove that a market mechanism that does not allow bundle orders or does not address the freerider problem yields a systematic underinvestment in knowledge.
Mechanism design, knowledge sharing, incentive compatibility, public goods, combinatorial aution, bundle auction, knowledge investment
Abstract: The qualitative reasoning (QR) field has developed various representation and reasoning methods for the modeling with incomplete information or incomplete knowledge. While most uncertain reasoning approaches describe uncertain or imprecisely known information as probability distribution functions, qualitative reasoning bases its model specification on qualitative descriptions that are derived from known qualitative system properties. Problems are formulated as sets of qualitative constraints and their analysis is performed by applying a qualitative calculus. This paper presents a general, unifying theory of the various existing qualitative reasoning systems that includes, as special cases, reasoning methods that use representations of qualitative differential equations and qualitative difference equations. Based on set theory, our QR framework describes fundamental concepts such as qualitative models and solutions, and relates them to the quantitative analogues of its underlying quantitative reference system. Our motivation arises from the types of models found in the management sciences. Thus we emphasize the significance of discrete, dynamic models and optimization models in the business management and economics fields, both of which have received less attention in current QR research. Finally, we extend our theoretical framework to include an approach to qualitative optimization.
qualitative reasoning, qualitative modeling, incomplete information, simulation, epistemology
Abstract: With the rapid growth of rich-media content over the Internet, content and service providers (SP) are increasingly facing the problem of managing their service resources cost-effectively while ensuring a high Quality of Service (QoS) delivery at the same time. To address this problem, we consider a model where infrastructure resources are traded, cooperatively shared and accessed through coordination mechanisms. In this research, we conceptualize and model an economy of Internet based storage provisioning for rich-media content delivery. This is modeled as a Capacity Provision Network (CPN) where participants possess service infrastructures and leverage their topographies to effectively serve specific customer segments. A CPN is a network of SPs coordinated through an allocation hub. We first develop the notion of discounted QoS capabilities of storage resources. We then develop a market maker mechanism for optimal multilateral allocation in a network. The proposed CPN is closely tied to two fundamental properties of Internet service technology: positive network externality among cooperating SPs and the convexity property of capacity allocation with geographically distributed service sites. In conclusion, this study demonstrates the practical business viability of a cooperative CPN market.
Capacity Provision Network, Quality of Service, Market Maker mechanism, Optimization
Abstract: Motivated by the enormous growth of keyword advertising, this paper explores the design of unit-price contract auctions, in which bidders bid their unit prices, and the winner is chosen based on both their bids and performance levels. The previous literature in unit-price contract auctions usually considers a static case where bidders' performance levels are fixed, and suggests giving preferential treatment to those bidders with low performance levels in order to promote competition. This paper extends such research by allowing bidders with lower performance levels to improve their performance at a certain cost. We examine the impact of the preferential policy on overall bidder performance, the auction efficiency, and the auctioneer's revenue, and derive the revenue-maximizing and efficient policy accordingly. Moreover, the possible upgrade in bidders' performance levels gives the auctioneer an incentive to modify the auction rules over time, as is confirmed by the practice of Yahoo! and Google. We thus compare the auctioneer's revenue-maximizing policies when she is fully committed to the auction rule and when not, and show that she should give less preferential treatment to low-performance advertisers when she is fully committed.
Performance-base pricing, Unit-price auctions, Keyword auctions, Commitment
Abstract: In this chapter, we present a conceptual model and a web-based architecture for implementing an enterprise-wide modeling system for decision support. It describes a framework and a method that is aimed at effectively organizing, integrating, and reusing knowledge and model components from various sources across an organization in order to provide better knowledge access to decision makers. It is a useful tool for operational and strategic corporate decision-making.
Decision Support Systems, Enterprise Modeling, Compositional Modeling, Model Integration, Organizational Knowledge Base Design, Knowledge Components
Abstract: Because uncertainties around innovative technologies resolve over time, investments in such technologies are often made in stages so that organizations can use the knowledge gained from earlier stages to decide the next step. Previous studies usually assume that once some uncertainty is resolved, it becomes common knowledge within the investing organization. We develop a game-theoretical model to study how different parties within an organization gain and transfer knowledge about new technologies while investing in these technologies, and how the learning process may affect the investment decisions. We show that managers with incentives misaligned with the organization may transfer their knowledge untruthfully and distort the learning process of decision makers. Such behavior may lead to inefficient investment decisions. We also study the impact of uncertainty on the misreporting problem and the investment decisions. Mechanisms to mitigate or prevent untruthful knowledge transfer are also proposed. In particular, powerful incentive schemes may alleviate, but not prevent, the misreporting problem; punishing managers who are caught misreporting may deter the misreporting behavior, but in practice, such mechanisms are difficult to implement.
economic analysis, game theory, investment under uncertainty, knowledge transfer, organizational learning, signal jamming
Abstract: We study reputations with imperfect audit and a reputation market. The main result shows the existence of a separating equilibrium in the reputation market, which contrasts with Tadelis [Tadelis, S., 2002, The market for reputations as an incentive mechanism, Journal of Political Economy 110(4), 854-882].
Reputation, Audit, Infinitely repeated game
Abstract: Online anonymity has posed a significant threat on online reputation mechanisms and online identity management. How to improve the reliability and effectiveness of online reputation has thus become an important question of theoretical and practical interest. We examine a reputation market in an infinite repeated game setting, where agents sell online services and trade their online reputations. Agents exert effort to provide services and high type agents have a lower cost of effort than low types. An auditor performs random checks on services and determines agents' reputations. Our analysis depicts a full equilibrium in the reputation system with audit, including separating, partial separating, and pooling equilibrium under different conditions. In particular, we show that full separation can arise as an equilibrium such that high-type agents can be sorted out from low-type agents by their reputations, which is in contrast to Tadelis (2002). In a separating equilibrium, reputations become a perfect indicator of agents' types, effort levels, and quality of the services. By proposing online reputations as an asset, our paper generates implications for establishing reliable online environments and promoting online interactions.
reputation, online community, audit, identity management, electronic market
Abstract: Current knowledge management (KM) technologies and strategies advocate two different approaches: knowledge codification and knowledge sharing networks. However, the extant literature has paid limited attention to the interaction between them. This research draws upon the literature on formal modeling of networks to examine the interaction between knowledge codification and knowledge sharing networks. The analysis suggests that an increase in codification may damage existing network-sharing ties. Anticipating that, individuals may hoard their knowledge to protect their network ties, even when there are nontrivial rewards for codification. We find that despite the aforementioned tension between the codification and the network approach, a firm may still benefit from combining the two approaches. Specifically, when the future sharing potential between knowledge workers is high, a combination of the two approaches may outperform a codification-only or a network-only approach as the codification reward causes fewer network ties to break down and the benefit from increased codification can offset the loss of some network ties. However, when the future sharing potential is low an increase in codification reward can quickly break down the whole network, thus firms may be better off by pursuing a codification-only or a network-only strategy.
Knowledge Management, Codification, Knowledge Sharing Network, Sharing Potential
Abstract: We examine a reputation market in an infinite repeated game setting, where agents operate firms and trade firms' reputations. Agents exert effort to produce homogeneous products, which ex post may be of different qualities. High-type agents have a lower cost of effort than low types. An auditor performs random checks on products and determines agents' reputations. Our analysis depicts a full equilibrium in the reputation system with audit, including separating, partial separating, and pooling equilibrium under different conditions. In particular, we show that in separation, agents' types can be sorted by their reputations, which is in contrast to Tadelis (2002).
Abstract: Online communities provide a social sphere for people to share information and knowledge. While information sharing is becoming a ubiquitous online phenomenon, how to ensure information quality or induce quality content, however, remains a challenge due to the anonymity of commentators. This paper introduces moderation into reputation systems. We show that moderation directly impacts strategic commentators incentive to generate useful information, and moderation is generally desirable to improve information quality. Interestingly, we find that when being moderated with different probabilities based on their reputations, commentators may display a pattern of reputation oscillation, in which they generate useful content to build up high reputation and then exploit their reputation. As a result, the expected performance from high-reputation commentators can be inferior to that from low-reputation ones (reversed reputation). We then investigate the optimal moderation resource allocation, and conclude that the seemingly abnormal reversed reputation could arise as an optimal result. The paper concludes with a discussion of the development of a scientific moderation system with application to academic publishing.
moderation, reputation, online community, knowledge management
Abstract: A consumer contest is a sales promotion technique that requires participants to apply certain skills as they compete for prizes or awards. This article is the first to employ a game-theoretical approach to investigate consumer contest design issues, including prize structure, segmentation, and handicapping. First, the authors find that both skill distribution and the number of contestants play an important role in determining the optimal prize structure in consumer contests. Specifically, if the skill distribution has the increasing hazard-rate property, it is optimal for a marketer to use a winner-take-all design. In large contests, for the winner-take-all approach to be optimal, it suffices to have the increasing hazard-rate property only at the high end of the skill distribution. Second, increasing contest size is beneficial to the marketer. Third, a less dispersive skill distribution leads to higher consumption by consumers at all skill levels and thus is beneficial to the marketer. The marketer may achieve less dispersive skill distributions by (1) segmenting or screening contestants according to their skill levels and (2) adopting a performance evaluation scheme that handicaps high-skilled contestants.
consumer contests, prize structure, segmentation, handicapping, entry fee
Abstract: Keyword advertising, or "sponsored links" that appear alongside online search results or other online content, has grown into a multibillion-dollar market. Providers of keyword advertising, such as Google and Yahoo!, profit by auctioning keywords to advertisers. One issue of increasing importance for advertising providers is the "share structure" problem; that is, out of the total available resources for each keyword (in terms of exposure), how large a share should be set aside for the highest bidder, for the second highest bidder, and so on. We study this problem under a general specification and characterize the optimal share structures that maximize advertising providers' revenues. We also derive results on how the optimal share structure should change with advertisers' price elasticity of demand for exposure, their valuation distribution, total resources, and minimum bids. We draw implications for keyword auctions and other applications.
keyword advertising, sponsored links, share structures, search engine, Internet auctions, divisible goods, Google, Yahoo!
Abstract: Online users often need to make adoption decisions without accurate information about the product values. Herding is common in such situations where users infer values from other customers' choices and incorporate that information into their own decision-making process. Herding is often rational for individual decision-making; however, it may lead to adoption of inferior products. The Internet affects the herding phenomenon in adoption decisions in two ways. On the one hand, it provides more information about other users' choices, therefore making herding more feasible. On the other hand, the Internet provides more details about product values, thus making herding less desirable. In this paper, we empirically examine herd behavior in the context of online software adoption. Consistent with the predictions of the informational cascades literature, we find that online users engage in significant herd behavior in choosing software programs, and professional product reviews and user reviews have little impact on the popularity of software programs. We also find that, while product reviews do not directly affect software popularity, their availability mitigates the herd behavior. Our results validate informational cascades as an important driver for decision-making on the Internet.
E-commerce, herding, informational cascades, decision-making, network externalities, software download, online communities, online user review
Abstract: A consumer contest is a sales promotion technique that requires participants to apply certain skills as they compete for prizes or awards. Consumer contests are increasingly used in such markets as the fast-growing mobile entertainment industry. We study a one-period model of consumer contest in which consumers' performance is a multiplicative function of their skill and consumption, and the marketer maximizes profits from the aggregate consumption. This paper is the first to employ a game-theoretical approach to investigate consumer contest design issues. We find that the optimal (profit-maximizing) prize structure is either for the winner to take all or for multiple winners to take equal prizes. A winner-take-all prize structure is optimal when the hazard rate of the skill distribution increases. Intuitively, increasing hazard rate implies fiercer competition (thus more consumption) at high-skill levels, and the first prize is most effective in inducing aggregate consumption by high-skilled consumers. Furthermore, when there are many contestants, an increasing (and higher) hazard-rate at high-skill levels is sufficient for winner-take-all prize structure to be optimal. We also find that, as consumers' skill levels become less dispersive, meaning they have more equal skill levels, they will compete more aggressively - to the marketer's benefit. This provides a rationale for the marketer to handicap high-skilled consumers and to segment consumers based on their skill levels. Yet, we do not find segmenting based on non-skill factors, such as geographic regions, to increase the marketer's profits. Finally, when consumers derive little intrinsic value from consumption, the marketer can benefit from charging an entry fee.
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