What is the scope of data-sharing across firms, and what are the economic implications? In her co-authored study “Data as a Networked Asset,” supported by the Stevens Center for Innovation in Finance, Huan Tang, professor of finance at Wharton, uncovers a hidden network of inter-firm data flows — revealing that companies are connected not only by products or supply chains, but also by the information they exchange. The research shows that this data network influences how firms perform, how they respond to shocks, and how they are valued in the market. Tang explains the financial and economic implications of data as a networked asset in the conversation below.
What is the relevance of your research for investors, companies, and policymakers?
Huan Tang: Our paper is motivated by the unprecedented scale of the data economy. With smartphones in every pocket and tracking technologies like cookies embedded in websites and apps, companies today can collect and exchange data on users in real time — at massive scale.
This shift is exemplified by the rise of data aggregators like Oracle and Acxiom, who’ve quietly built detailed profiles on billions of individuals by pulling data from a wide range of sources — what we browse and buy, where we go, and even who we interact with.
As firms become increasingly connected through data sharing, it’s important to understand how they use data, how they exchange it, and what the broader consequences of this sharing are. Our research sheds light on this by uncovering the data-sharing network among firms, offering insights for companies seeking data-driven growth, for investors evaluating firm value, and for policymakers designing data privacy laws that could reshape the structure of the data economy in ways we don’t yet fully grasp.
Your research identifies data sharing as an economic linkage between firms. How does data link firms, and how does this differ from other industry linkages?
Tang: We show that data-based connections between firms are largely distinct from traditional linkages like supply-chain relationships or product-market overlap. For example, Amazon’s top data-connected peers include General Motors, American Express, Vodafone, and Morgan Stanley — firms that span very different industries.
This suggests that we’ve uncovered a novel type of economic linkage. Rather than being connected by physical inputs or shared markets, these firms are linked by the way they use and benefit from each other’s data. This opens a new lens for thinking about how firms interact and create value in the digital economy.
What is the scope of data-sharing across firms, and what are the economic implications? In her co-authored study “Data as a Networked Asset,” supported by the Stevens Center for Innovation in Finance, Huan Tang, professor of finance at Wharton, uncovers a hidden network of inter-firm data flows — revealing that companies are connected not only by products or supply chains, but also by the information they exchange. The research shows that this data network influences how firms perform, how they respond to shocks, and how they are valued in the market. Tang explains the financial and economic implications of data as a networked asset in the conversation below.
What is the relevance of your research for investors, companies, and policymakers?
Huan Tang: Our paper is motivated by the unprecedented scale of the data economy. With smartphones in every pocket and tracking technologies like cookies embedded in websites and apps, companies today can collect and exchange data on users in real time — at massive scale.
This shift is exemplified by the rise of data aggregators like Oracle and Acxiom, who’ve quietly built detailed profiles on billions of individuals by pulling data from a wide range of sources — what we browse and buy, where we go, and even who we interact with.
As firms become increasingly connected through data sharing, it’s important to understand how they use data, how they exchange it, and what the broader consequences of this sharing are. Our research sheds light on this by uncovering the data-sharing network among firms, offering insights for companies seeking data-driven growth, for investors evaluating firm value, and for policymakers designing data privacy laws that could reshape the structure of the data economy in ways we don’t yet fully grasp.
Your research identifies data sharing as an economic linkage between firms. How does data link firms, and how does this differ from other industry linkages?
Tang: We show that data-based connections between firms are largely distinct from traditional linkages like supply-chain relationships or product-market overlap. For example, Amazon’s top data-connected peers include General Motors, American Express, Vodafone, and Morgan Stanley — firms that span very different industries.
This suggests that we’ve uncovered a novel type of economic linkage. Rather than being connected by physical inputs or shared markets, these firms are linked by the way they use and benefit from each other’s data. This opens a new lens for thinking about how firms interact and create value in the digital economy.
