Social Networks, Personalized Advertising, and Privacy Controls

This paper investigates how internet users' perception of control over their personal information affects how likely they are to click on online advertising. The paper uses data from a randomized field experiment that examined the relative effectiveness of personalizing ad copy to mesh with existing personal information on a social networking website. The website gave users more control over their personally identifiable information in the middle of the field test. The website did not change how advertisers used anonymous data to target ads. After this policy change, users were twice as likely to click on personalized ads. There was no comparable change in the effectiveness of ads that did not signal that they used private information when targeting. The increase in effectiveness was larger for ads that used less commonly available private information to personalize their message. This suggests that giving users the perception of more control over their private information can be an effective strategy for advertising-supported websites

Social Interactions, Network Fluidity and Network Effects

This paper asks how much the strength of network effects depends on the stability and structure of the underlying social network. I answer this using extensive microdata on all potential adopters of a firm's internal video-messaging system and their subsequent video-messaging. This firm's New York office had to be relocated due to the terrorist attacks of 2001 which lead to a physical re-organization of teams in that city but not in other comparable cities. I study the consequences of this disruption for adoption of video-messaging and the size of network effects. I find evidence that generally network effects are based on direct social interactions. Potential adopters react to adoption only by people they wish to communicate with: They are not affected by adoption by other people. However, when there is a disruption to the social network and communication patterns become less predictable, users become more responsive to adoption by a broader group of users

Heterogeneity and the Dynamics of Technology Adoption

This paper analyzes the role of heterogeneity and forward-looking expectations in the diffusion of network technologies. Using a detailed dataset on the adoption of a new videoconferencing technology within a firm, we estimate a structural model of technology adoption and communications choice. We allow for heterogeneity in network benefits and adoption costs across agents. We find that ignoring heterogeneity in the interplay between adoption costs and network effects will underpredict the size of the steady-state network size by almost 50 percent. We develop a new 'simulated sequence estimator' to measure the extent to which agents seek diversity in their calling behavior, and characterize the patterns of communication as a function of geography, job function, and rank within the firm. We find that agents have significant welfare gains from having access to a diverse network, and that a policy of strategically targeting the right subtype for initial adoption can lead to a faster-growing and larger network than a policy of uncoordinated or diffuse adoption

Search Engine Advertising: Pricing Ads to Context

Each search term put into a search engine produces a separate set of results. Correspondingly, each of the sets of ads displayed alongside the results is priced using a separate auction. We investigate how bids for these context-based ads depends on the difficulty of making a match. This contrasts with the existing literature that focuses on the effect of match quality. We examine advertising prices paid by lawyers for 139 Google search terms in 195 locations. Other things being equal, the fewer searches there are on a term, the higher the price. To identify a causal relationship between match-difficulty and prices paid, we exploit a natural experiment in 'ambulance-chaser' regulations across states. When lawyers cannot contact a client by mail and matching becomes more difficult, the relative price per ad click is $0.93 higher. We check the robustness of this result by performing a falsification test using a different ambulance-chaser regulation. Our results suggest that prices are higher for context-based ads when the difficulty of both online and off-line matching increases. This highlights that a major reason why search advertising is profitable is because its use of context can monetize the 'long tail' by reducing friction in the matching process

Decomposing the Congestion Effect and the Cross-Platform Effect in Two-Sided Networks: A Field Experiment

This paper highlights how the provision of information about user participation can serve as a strategic marketing tool for firms seeking to grow two-sided exchange networks. A two-sided exchange network is a business model (such as Ebay or Craiglist) where revenue is generated from persuading people to buy and sell items through that particular exchange. It is not immediately clear whether broadcasting information about the number of sellers will grow further seller participation. On the one hand, a strong rival presence may dissipate payoff (a 'congestion effect'). On the other hand, a large number of rivals may signal high buyer demand (a 'cross-platform effect'). We use field experiment data from a B2B web site that brings together buyers and sellers of used equipment and real estate. Before each seller made a posting request, the web site randomized whether to disclose the number of buyers and/or sellers, and the exact number to disclose. We find that when presented together with the number of buyers, a larger number of sellers makes sellers less likely to list their products, indicating a negative congestion effect. However, when the number of sellers is presented in isolation, its negative impact on entry is significantly reduced, indicating a positive cross-platform effect. Higher buyer search intensity amplifies the moderating role of demand uncertainty. The results suggest that information on the number of users can be an effective tool to grow two-sided networks but should be used strategically. A network can attract more users by advertising dense competition when demand is not transparent, especially in search-intensive markets

Heterogeneity and the Dynamics of Technology Adoption

This paper analyzes the role of heterogeneity and forward-looking expectations in the diffusion of network technologies. Using a detailed dataset on the adoption of a new videoconferencing technology within a firm, we estimate a structural model of technology adoption and communications choice. We allow for heterogeneity in network benefits and adoption costs across agents. We find that ignoring heterogeneity in the interplay between adoption costs and network effects will underpredict the size of the steady-state network size by almost 50 percent. We develop a new 'simulated sequence estimator' to measure the extent to which agents seek diversity in their calling behavior, and characterize the patterns of communication as a function of geography, job function, and rank within the firm. We find that agents have significant welfare gains from having access to a diverse network, and that a policy of strategically targeting the right subtype for initial adoption can lead to a faster-growing and larger network than a policy of uncoordinated or diffuse adoption

Social Networks, Personalized Advertising, and Privacy Controls

This paper investigates how internet users' perception of control over their personal information affects how likely they are to click on online advertising. The paper uses data from a randomized field experiment that examined the relative effectiveness of personalizing ad copy to mesh with existing personal information on a social networking website. The website gave users more control over their personally identifiable information in the middle of the field test. The website did not change how advertisers used anonymous data to target ads. After this policy change, users were twice as likely to click on personalized ads. There was no comparable change in the effectiveness of ads that did not signal that they used private information when targeting. The increase in effectiveness was larger for ads that used less commonly available private information to personalize their message. This suggests that giving users the perception of more control over their private information can be an effective strategy for advertising-supported websites

Days on Market and Home Sales

In April 2006, the real estate listing service in Massachusetts adopted a new policy that prohibits home sellers from resetting their property's 'days on market' to zero through relisting. We study the effect of this new policy on single-family home sales along the Massachusetts-Rhode Island border, using homes in Rhode Island, which did not change its policy, as the control group. We find that the policy change leads to a relative sale price reduction of around $11,000 for affected homes in Massachusetts. Homes caught in the middle of the policy change are the hardest hit; the sudden release of the cumulative days on market information lowers the average sale price by$21,500. Sellers respond to the new policy by reducing the listing price to shorten their property's days on market

Privacy Protection and Technology Diffusion: The Case of Electronic Medical Records

Some policymakers argue that consumers need legal protection of their privacy before they adopt interactive technologies. Others contend that privacy regulations impose costs that deter adoption. We contribute to this growing debate by quantifying the effect of state privacy regulation on the diffusion of Electronic Medical Record technology (EMR). EMR allows medical providers to store and exchange patient information using computers rather than paper records. Hospitals may not adopt EMR if patients feel their privacy is not safeguarded by regulation. Alternatively, privacy protection may inhibit adoption if hospitals cannot benefit from exchanging patient information with one another. In the US, medical privacy laws that restrict the ability of hospitals to disclose patient information vary across time and across states. We exploit this variation to explore how privacy laws affect whether hospitals adopt EMR. Our results suggest that inhibition of EMR's network benefits reduces hospital adoption by up to 25 percent. We find similar evidence when we control for the endogeneity of state laws using variation in signups to the 'Do Not Call' list

System Size, Lock-in and Network Effects for Patient Records

We examine empirically whether the size of a firm using a network affects the scope of its network usage, and consequently network effects and lock-in within the network. We use the example of hospital information exchange. We find that hospitals in larger hospital systems are more likely to exchange electronic patient information only within their system and less likely to exchange patient information externally. We show that hospitals are also more likely to exchange information externally if others hospitals also do so. This implies that the disinclination of large hospital systems to exchange data externally harms overall levels of network use. Our results highlight that makers of technology policy designed to encourage the optimal use of networks should consider regulating the behavior of network users as well as technology vendors