Digital Privacy
March 23, 2022 Itay P. Fainmesser

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Speakers:

Itay P. Fainmesser (JHU)

Itay P. Fainmesser is an Associate Professor at Johns Hopkins Carey Business School. Prof. Fainmesser studies how social networks and social media affect and are affected by market activities and market rules. His current work studies the pricing of network goods, the role of intermediaries in markets, the shape and evolution of trust networks, the market for online influence, and user privacy in online platforms. Prof. Fainmesser holds a PhD in Business Economics from Harvard University.


Recap:

Professor Fainmesser talked about his recent paper coauthored with professor Andrea Galeotti (London Business School) and professor Ruslan Momot (HEC Paris). He mainly addressed how platform firms' data strategy may impact the consumer surplus and social welfare, and the corresponding implications for data regulation policies. The two important elements of a data strategy, professor Fainmesser emphasizes, are how much data to be collected and how much protection to be imposed on the collected data. They both depend on the business model, particularly whether the collected data is used to improve services, or just gather information for sale. Business models relying more on information collection tend to collect more data and impose better data protection. Due to the complexity brought by the interactions among business model, data collection, and data protection, he points out that, it is not easy to tell whether firms' choices of data collection and data protection deviate from the socially optimal. In particular, for business models with a middle level of reliance on information collection, a minimum data protection policy might hurt the consumers and decrease the overall welfare. Therefore, he suggests that the data protection policy has to work together with regulations on data collection. For example, if a minimum data protection is imposed, it probably needs to be accompanied by a liability fine upon damage or an information tax on data collection.



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