Data-Driven Decision-Making Model for Overseas Market Growth of U.S. Enterprises in the Digital Economy Era: Theoretical Construction and Empirical Research

Abstract

The global digital economy reached a scale of 55.3 trillion US dollars in 2024, accounting for 47.6% of the global GDP. The proportion of overseas revenue of U.S. enterprises has been continuously increasing, with the average for S&P 500 enterprises reaching 38.2% in 2023. Data has become a core production input for enterprises’ overseas expansion. This study aims to construct a data-driven decision-making model for the overseas market growth of U.S. enterprises in the digital economy context, and to reveal the inherent relationship between data resources, analytical capabilities, and growth performance. A mixed research method is adopted, including panel data regression, structural equation modeling, and multiple case studies. The core innovation lies in constructing a full-chain theoretical model of “data resources – data capabilities – decision-making efficiency – growth performance” and quantifying the contribution coefficient of data-driven approaches. This research enriches the international business theory system and provides a quantifiable decision-making framework for U.S. enterprises in formulating overseas strategies.