De Liu

Auctioning Keywords in Online Search

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. An issue of increasing importance for advertising providers is the “share structure” problem—that is, 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. The authors study this problem under a general specification and characterize the optimal share structures that maximize advertising providers’ revenues. They 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. The authors draw implications for keyword auctions and other applications.

Designing online auctions with past performance information

We investigate the value of past performance information in the context of keyword advertising auctions, where advertisers differ both in valuation-per-click and in the numbers of clicks they can generate (their performance). We focus on weighted unit-price-contract (UPC) auctions, in which bidders bid unit prices and pay accordingly if they win, and their bids are weighted by factors based on their own past performance. We characterize the efficient and the revenue-maximizing weighting factors and apply our framework to study Yahoo!s and Googles auction designs, each of which can be viewed as a special case of weighted UPC auctions.

Optimal Design of Consumer Contests

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.

The Interaction Between Knowledge Codification and Knowledge-Sharing Networks

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 on 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 because 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.

Information Asymmetry and Hybrid Advertising

Pay-for-performance (P4P) pricing schemes such as pay per click and pay per action have increased in popularity in Internet advertising. Meanwhile, pay-per-impression (PPI) schemes persist, and several publishers have begun to offer a hybrid mix of PPI and P4P schemes. Given the proliferation of pricing schemes, this study examines the optimal choices for publishers. The authors highlight two-sided information asymmetries in online advertising markets and the consequent trade-offs faced by a high-quality publisher using P4P schemes. Pay-for-performance schemes enable a high-quality publisher to reveal its superior quality; however, such schemes may incur allocative inefficiencies stemming from inaccurate estimates of advertiser qualities. The authors identify conditions under which a publisher may opt for a PPI, P4P, or hybrid scheme and, in doing so, provide theoretical explanations for the observed variations in the pricing schemes and the increasing popularity of hybrid schemes. Using a new “uncompromised” equilibrium refinement, the authors find that the hybrid scheme can emerge as an equilibrium choice in a variety of conditions. In addition, they provide prescriptive guidelines for firms choosing between different pricing schemes.

Toward meaningful engagement: a framework for design and research of gamified information systems

Gamification, an emerging idea for using game design elements and principles to make everyday tasks more engaging, is permeating many different types of information systems. Excitement surrounding gamification results from its many potential organizational benefits. However, few research and design guidelines exist regarding gamified information systems. We therefore write this commentary to call upon information systems scholars to investigate the design and use of gamified information systems from a variety of disciplinary perspectives and theories, including behavioral economics, psychology, social psychology, information systems, etc. We first explicate the idea of gamified information systems, provide real-world examples of successful and unsuccessful systems, and, based on a synthesis of the available literature, present a taxonomy of gamification design elements. We then develop a framework for research and design: its main theme is to create meaningful engagement for users; that is, gamified information systems should be designed to address the dual goals of instrumental and experiential outcomes. Using this framework, we develop a set of design principles and research questions, using a running case to illustrate some of our ideas. We conclude with a summary of opportunities for IS researchers to extend our knowledge of gamified information systems, and, at the same time, advance existing theories.

Research Note Gamification of Technology-Mediated Training: Not All Competitions Are the Same

Gamification, an application of game design elements to non-gaming contexts, is proposed as a way to add engagement in technology-mediated training programs. Yet there is hardly any information on how to adapt game design elements to improve learning outcomes and promote learner engagement. To address this issue, we focus on a popular game design element, competition, and specifically examine the effects of different competitive structures, i.e., whether a person faces a higher-skilled, lower-skilled or equally-skilled competitor, on learning and engagement. We study a gamified training design for databases, where trainees play a trivia-based mini-game with a competitor after each e-training module. Trainees who faced a lower-skilled competitor reported higher self-efficacy beliefs and better learning outcomes, supporting the effect of peer appraisal, a less examined aspect of social cognitive theory. Yet trainees who faced equally-skilled competitors reported higher levels of engagement, supporting the b...

Influence and conditional influence-new interestingness measures in association rule mining

Discusses the issues of interestingness in association rule mining. First, a rule is possibly redundant or misleading even if it possesses high degrees of confidence and support. Second, association rules do not reflect the effect of negatively influential facts. Such problems are related to confidence deviation. In the paper, therefore, two new measures of interestingness, namely influence and conditional influence, are introduced to represent the effect of the antecedent on the consequent. Furthermore, the mining algorithms are extended accordingly such that certain redundant rules can be eliminated and negatively influential rules may be discovered.

Peer-to-Peer Enterprise Knowledge Management

Organizations recognize the importance of enterprise knowledge management, but what has not been realized is the enormous potential offered by peer-to-peer (P2P) networking in managing organizational knowledge. This chapter explores how P2P can confer superior knowledge management capabilities by improved search capabilities, content sensitive addressing, and the community aspect of knowledge transfer in a P2P network. While P2P offers tremendous potential, it should be recognized that this technology is severely limited by the holdup problem. This article explores the free rider problem and suggests ways to align the incentives of participants in a P2P network.

Current Issues in Keyword Auctions (Book Chapter)

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.