Digital platforms have become central to modern economies, as consumers increasingly spend leisure time online and platform firms transform user engagement into economic value. This study develops a multi-country, multi-industry open economy general equilibrium model to analyze how web traffic—measured as visits to platform domains—can be converted into “data capital” through big data and AI algorithms and then used as a non-rival input for production and innovation.

To ground the analysis, we construct a new dataset that links domain-level web traffic to corporate ownership across countries. The evidence reveals sharp cross country differences in the geographic origin of users. U.S. platforms attract a strongly international audience, with domestic users accounting for less than one-third of visits on average. Chinese platforms are more domestically concentrated, though TikTok stands out as a global exception with a highly international user base. Korean platforms, by contrast, rely overwhelmingly on domestic users, with less than ten percent of traffic originating abroad. Comparing these patterns with international service trade statistics, we find that countries with higher shares of foreign users are systematically more active in exporting online services.

Qualitative analysis provides further insight into user behavior. Consumers allocate more time to a platform when they experience greater content satisfaction, which depends on both technological quality and country-specific content preferences. When the quality of foreign platform content improves, consumers reallocate time away from domestic platforms toward foreign ones. The extent of this shift is influenced by the elasticity of leisure demand, the substitutability across platforms, and the share of time already devoted to foreign platforms.

The general equilibrium model allows us to simulate counterfactual scenarios and evaluate policy-relevant outcomes. Reducing cross-border frictions to foreign content raises welfare in all countries, primarily through the expansion of content variety and the reallocation of consumer time, while leaving the broader industrial structure largely unchanged. Lowering barriers faced by foreign platforms, such as discriminatory digital services taxes, increases platform revenues, encourages consumers to spend more leisure time online, and strengthens investment incentives for domestic platforms. Although the immediate welfare gains are modest, the longer-run effects on intangible investment and innovation are more significant. Enhancing the productivity of platform R&D generates asymmetric effects by expanding platform activity in the innovating country and reducing it in the non innovating country, yet global welfare increases because users everywhere benefit from improved content quality and diversity.

Taken together, the findings highlight that the accumulation of web-traffic-based data capital is a central driver of platform growth. Policies that improve access to foreign content, the taxation of digital services, and foster innovation in platform R&D directly influence how consumer time is allocated and how platform firms invest in data-driven growth. For policymakers, the results suggest that lowering barriers to cross-border online activity can deliver substantial welfare gains, that digital taxation should be carefully designed to balance fiscal and innovation objectives, and that investment in platform R&D is essential for competitiveness in the global digital economy.

In sum, this study demonstrates that digital platforms thrive not only on technological progress but also on the ability to accumulate and deploy data capital derived from web traffic. Recognizing the economic role of data capital is crucial for designing effective policies in the digital era, where market access, taxation, and innovation shape the international competitiveness of platform industries.

Executive Summary

1. Introduction

2. Data

3. The Model

4. Qualitative properties

5. Numerical Simulation

6. Conclusion

Appendix

References