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Abstract:
Peer-to-peer file sharing networks are becoming an important medium for the distribution of information goods. However, there is little academic research into the optimal design of these networks under real-world conditions. Our research represents an initial effort to analyze the impact of positive and negative network externalities on the optimal size of these P2P networks. Our analysis uses a unique dataset collected from the six most popular OpenNap peer-to-peer networks between December 19, 2000 and April 22, 2001.

We find that users contribute value to the network in terms of additional content and additional replicas of content at a diminishing rate, while they impose costs on the network in terms of congestion on shared resources at an increasing rate. Together these results suggest that the optimal size of peer-to-peer networks is bounded — at some point the costs a marginal user imposes on the network will exceed the value they provide.

peer-to-peer, file sharing, empirical, network externalities, network size

Abstract:
Peer-to-Peer (P2P) networks have emerged as a significant social phenomenon for the distribution of information goods and may become an important alternative to traditional client-server network architectures for knowledge sharing within enterprises. This paper reviews and synthesizes the relevant computer science and economics literatures as they relate to P2P networks, and raises important questions for researchers interested in studying the behavior of these networks from the perspective of the economics of information technology.

With regard to the economic characteristics of these networks, we show that while the characteristics of services provided over P2P networks are similar to public goods and club goods, they have many important differences and hence there is a need for new theoretical models as well as empirical and experimental analysis to understand P2P user behavior. We then identify several important areas for study with regard to the economics of P2P networks and review recent academic papers in each area.

Peer-to-peer, club goods, public goods, network externalities

Abstract:
Peer-to-peer networks have emerged as a popular alternative to traditional client-server architectures for the distribution of information goods. Recent academic studies have observed high levels of free-riding in various peer-to-peer networks, leading some to suggest the imminent collapse of these communities as a viable information sharing mechanism.

Our research develops both static and dynamic analytic models to analyze the behavior of peer-to-peer networks in the presence of free-riding. In contrast to previous predictions we find that free-riding is sustainable in equilibrium and in some cases occurs as part of the socially optimal outcome. However, we also show that without external incentives, the level of freeriding in peer-to-peer networks will be higher than the socially optimal level. Finally, we show that quality of service tied to the contribution of content can be used as a lever to induce users to share and thereby achieve the socially optimal outcome for the network.

peer-to-peer, free-riding, public goods, club goods, incentives

Abstract:
Content Delivery Networks (CDNs) are a vital component of the Internet's content delivery value chain, servicing nearly a third of the Internet's most popular content sites. However, in spite of their strategic importance little is known about the optimal pricing policies or adoption drivers of CDNs. We address these questions using analytic models of CDN pricing and adoption under Markovian traffic and extend the results to bursty traffic using numerical simulations.

When traffic is Markovian, we find that CDNs should provide volume discounts to content providers. In addition, the optimal pricing policy entails lower emphasis on value-based pricing and greater emphasis on cost-based pricing as the relative density of content providers with high outsourcing costs increases. However, when traffic is bursty and content providers have varying levels of traffic burstiness, as ex-pected in reality, volume discounts may be suboptimal and may even be replaced by volume taxes. Fi-nally, a pricing policy that accounts for both the mean and variance in traffic such as percentile-based pricing is more profitable than pure volume-based pricing when there is heterogeneity in burstiness across content providers. This finding is in contrast to the current practices of many CDN firms that use pure volume-based pricing.

Content delivery networks, internet, pricing, bursty traffic, web hosting, media delivery

Abstract:
Improving the information retrieval (IR) performance of P2P networks is an important and challenging problem. Recently, the computer science literature has tried to address this problem by improving the efficiency of search algorithms. However, little attention has been paid to improving performance through the design of incentives for encouraging users to share content and, mechanisms for enabling peers to form communities based on shared interests.

Our work draws on the club goods economics literature and the computer science IR literature to propose a next generation file sharing architecture addressing these issues. Using the popular Gnutella 0.6 architecture as context, we conceptualize a Gnutella ultrapeer and its local network of leaf nodes as a club (in economic terms). We specify an IR-based utility model for a peer to determine which clubs to join, for a club to manage its membership, and for a club to determine to which other clubs they should connect.

We simulate the performance of our model using a unique real-world dataset collected from the Gnutella 0.6 network. These simulations show that our club model accomplishes both performance goals. First, peers are self-organized into communities of interest - in our club model peers are 85% more likely to be able to obtain content from their local club than they are in the current Gnutella 0.6 architecture. Second, peers have increased incentives to share content - our model shows that peers who share can increase their recall performance by nearly five times over the performance offered to free-riders. We also show that the benefits provided by our club model outweigh the added protocol overhead imposed on the network, that our results are stronger in larger simulated networks, and that our results are robust to dynamic networks with typical levels of user entry and exit.

Peer-to-peer, club economics, dynamic network, empirical

Abstract:
Improving the information retrieval (IR) performance of P2P networks is an important and challenging problem. Recently, the computer science literature has tried to address this problem by improving the efficiency of search algorithms. However, little attention has been paid to improving performance through the design of incentives for encouraging users to share content and, mechanisms for enabling peers to form communities based on shared interests.

Our work draws on the club goods economics literature and the computer science IR literature to propose a next generation file sharing architecture addressing these issues. Using the popular Gnutella 0.6 architecture as context, we conceptualize a Gnutella ultrapeer and its local network of leaf nodes as a club (in economic terms). We specify an IR-based utility model for a peer to determine which clubs to join, for a club to manage its membership, and for a club to determine to which other clubs they should connect.

We simulate the performance of our model using a unique real-world dataset collected from the Gnutella 0.6 network. These simulations show that our club model accomplishes both performance goals. First, peers are self-organized into communities of interest - in our club model peers are 85% more likely to be able to obtain content from their local club than they are in the current Gnutella 0.6 architecture. Second, peers have increased incentives to share content - our model shows that peers who share can increase their recall performance by nearly five times over the performance offered to free-riders. We also show that the benefits provided by our club model outweigh the added protocol overhead imposed on the network, that our results are stronger in larger simulated networks, and that our results are robust to dynamic networks with typical levels of user entry and exit.

Peer-to-peer, club economics, dynamic network, empirical

Abstract:
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. Concerns about such P2P file sharing were highlighted by content owners' recent lawsuits against individual users and P2P network operators.

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.

Peer-to-peer networks, digital business models, public goods, club goods, free riding

Abstract:
In addition to the wireless telephony boom, a similar exponential increasing trend in wireless data service - short message service (SMS) - is visible as technology advances. We develop a structural model to understand how mobile users behave, especially how they consume voice, and services. Specifically, we measure the own- and the cross-price elasticities of these services. The cross-price elasticity is of significant importance because marketing activities are critically influenced by whether the goods are substitutes or complements. The research context poses significant econometric challenges due to three-part tariff, sequential discrete plan choice and continuous quantity choices. Using detailed individual consumption data, we find that SMS and voice services are small substitutes. 10% increase in the price of voice minutes will induce about 0.8% increase in the demand for SMS. Younger users' demand is far more inelastic than that of older users. Finally, we discuss practical implications, conducting policy experiments that capture the effects of change in the strategic pricing scheme on firm revenues.

Mobile Demand, A Discrete/Continuous Choice Model, Structural Model, Wireless Communication, substitutes, elasticity

Abstract:
The increasing dependence on information networks for business operations has focused managerial attention on managing risks posed by failure of these networks. In this paper, we develop models to assess the risk of failure of an information network due to attacks that exploits known software vulnerabilities. Software vulnerabilities arise from software installed on the nodes of the network. When the same software stack is installed on multiple nodes on the network, software vulnerabilities are shared among them. These shared vulnerabilities can result in correlated failure of multiple nodes resulting in longer repair times and greater loss of availability of the network. We show that considering positive network effects (e.g., compatibility) alone without taking the risks of correlated failure and the resulting costs due to lack of availability into account leads to over-investment in homogeneous software installations. The notion of using diversity to limit correlated failure is a widely accepted risk management strategy in many fields e.g. insurance and portfolio management. However, these approaches are advantageous only for risk-averse agents as the expected loss remains unchanged. Using software diversification as a managerial lever, we show that the expected loss under homogeneous software deployment is higher than the expected loss under diverse software deployment, making diversification appealing to even risk-neutral firms. Our analysis suggests that security risk is a cost that firms should take into consideration in developing their IT infrastructure. Exploiting characteristics unique to information systems, we present an analytical framework that allows us to quantify security loss faced by a firm as a function of investment in security technologies to avert attacks, software diversification to limit correlated failure under attacks and IT resources to repair failures due to attacks. We analyze the effectiveness of diversification strategy under different operating conditions.

Abstract:
Software vulnerability disclosure refers to the publication of vulnerability information before a patch to address the vulnerability has been issued by the software vendor. It has generated intense interest and debate. In particular, there have been arguments made both in opposition to and in favor of alternatives such as full and instant disclosure and limited or no disclosure. An important consideration in this debate is the behavior of the software vendor. Does vulnerability disclosure policy have an effect on patch release behavior of software vendors? This paper compiles a unique data set from CERT/CC and SecurityFocus to answer this question. Our results suggest that disclosure policy has a significant positive impact on the vendor patching speed. Vendors are 137% more likely to patch due to disclosure. In particular, instant disclosure hastens the patch delivery by almost 29 days. Open source vendors patch more quickly than closed source vendors and severe vulnerabilities are patched faster. We also find that vendors respond more slowly to vulnerabilities not handled by CERT/CC. This might reflect unmeasured differences in the severity and importance of vulnerabilities. It might also reflect the stronger lines of communication between CERT/CC and vendors, and the value of the vulnerability analysis by CERT/CC.

Security vulnerability, disclosure policy, patching speed, open source, hazard functions

Abstract:
Network caches are the storage centers in the supply chain for content delivery - the digital equivalent of warehouses. Operated by access networks and other operators, they provide benefits to content publishers in the forms of bandwidth cost reduction, response time improvement, and handling of flash crowds. Yet, caching has not been fully embraced by publishers, since its use can interfere with site personalization strategies and/or collection of visitor information for business intelligence purposes. While recent work has focused on technological solutions to these issues, this paper provides the first study of the managerial issues related to the design and provisioning of incentive compatible caching services. Starting with a single class of caching service, we find conditions under which the profit maximizing cache operator should offer the service for free. This occurs when the access networks' bandwidth costs are high and a large fraction of content publishers value personalization and business intelligence. Yet, some publishers will still opt out of the service, i.e., cache-bust, as observed in practice. We next derive the conditions under which the profit-maximizing cache operator should provision two vertically differentiated service classes, namely premium and best-effort. Interestingly, caching service differentiation is different from traditional vertical differentiation models, in that the premium and best effort market segments do not abut. Thus, optimal prices for the two service classes can be set independently, and cannibalization does not occur. It is possible for the cache operator to continue to offer the best-effort service for free while charging for the premium service. Furthermore, consumers are better off because more content is cached and delivered faster to them. Finally, we find that declining bandwidth costs will put negative pressure on cache operator profits, unless consumer adoption of broadband connectivity and the availability of multimedia content provide the necessary increase in traffic volume for the caches.

Web caching, dontent delivery, pricing, quality of service

Abstract:
Using data collected between August 1999 and January 2000 covering 399 books, including New York Times bestsellers, computer bestsellers, and random books, we examine pricing by thirty-two online bookstores. One common prediction is that the reduction in search costs on the Internet relative to the physical channel would cause both price and price dispersion to fall. Over the sample period, we find no change in either price or price dispersion. Another prediction of the search literature is that the prices and price dispersion of advertised items or items that are purchased repeatedly will be lower than for unadvertised or infrequently purchased items. Prices across categories of books appear to conform to this prediction, with New York Times bestsellers having the lowest prices as a fraction of the publisher's suggested price and random books having the highest prices. Interestingly, price dispersion does not conform with this prediction, apparently for reasons related to stores' decisions to carry particular books. One reason why we may not observe convergence in prices is because stores have succeeded in differentiating themselves even though they are selling a commodity product. We observe differentiation (or attempted differentiation) by a significant number of firms.

Abstract:
Two conflicting predictions have emerged regarding the effect of low-cost information on price. The first states that all Internet retailers will charge the same low price for mass produced goods. The second states that Internet retailers will differentiate to avoid intense price competition. Using data collected in April 1999 on the prices of 107 books in thirteen online and two physical bookstores, we find similar average prices online and in physical stores and substantial price dispersion online. Analysis of product differentiation yields no clear results. The substantial premium charged by Amazon provides indirect evidence of product differentiation.