Zhulei Tang

The impact of free-riding on peer-to-peer networks

Peer-to-peer networking is gaining popularity as a architecture for sharing information goods and other computing resources. However, these networks suffer from a high level of free-riding, whereby some users consume network resources without providing any network resources. The high levels of free-riding observed by several recent studies have led some to suggest the imminent collapse of these communities as a viable information sharing mechanism. Our research develops analytic models to analyze the behavior of P2P networks in the presence of free-riding. In contrast to previous predictions, we find that P2P networks can operate effectively in the presence of significant free-riding. However, we also show that without external incentives, the level of free-riding in P2P networks is higher than socially optimal. Our research also explores the implications of these findings for entrepreneurs, network designers, and copyright holders.

Digital Business Models for Peer-to-Peer Networks: Analysis and Economic Issue

Peer-to-peer (P2P) services allow users to share networked resources, notably bandwidth and content, from the edges of the network. These services have been popularized because of file sharing particularly the sharing of unlicensed copyrighted files. However, content owners are increasingly exploring the ability of peer-to-peer networks to accommodate legitimate content distribution and promotion. In this article, we review the economic characteristics of P2P networks and outline the implications of these characteristics on efforts to counteract illegal piracy and on potential uses of P2P networks in a commercial media distribution strategy.

Incentive Problems in Performance-Based Online Advertising Pricing: Cost per Click vs. Cost per Action

The multibillion-dollar online advertising industry continues to debate whether to use the cost per click (CPC) or cost per action (CPA) pricing model as an industry standard. This paper applies the economic framework of incentive contracts to study how these pricing models can lead to risk sharing between the publisher and the advertiser and incentivize them to make efforts that improve the performance of online ads. We find that, compared with the CPC model, the CPA model can better incentivize the publisher to make efforts that can improve the purchase rate. However, the CPA model can cause an adverse selection problem: the winning advertiser tends to have a lower profit margin under the CPA model than under the CPC model. We identify the conditions under which the CPA model leads to higher publisher (or advertiser) payoffs than the CPC model. Whether publishers (or advertisers) prefer the CPA model over the CPC model depends on the advertisers’ risk aversion, uncertainty in the product market, and the...

Pricing of Online Advertising: Cost-Per-Click-Through Vs. Cost-Per-Action

Todays online advertising contracts tie online advertising payments directly to campaign measurement data such as click-throughs and purchases. This paper applies the economic theory of incentive contracts to the study of these pricing models and provides potential explanations as to when and how CPC (cost-per-click-through) and CPA (cost-per-action) pricing models should be used. We argue that using CPC and CPA models appropriately can give both the publisher and the advertiser proper incentives to make non-contractible efforts that may improve the effectiveness of advertising campaigns. It also allows the publisher and the advertiser to share the risk caused by uncertainty in the product market. Our research discovers various factors that can influence the usage of CPC and CPA models.