The Impact of Data Cross-Border Flow Policies on Cross-Border Digital M&As: Evidence from Chinese Firms

In the era of the digital economy, cross-border business activities are increasingly reliant on large-scale data flows, making the governance of cross-border data a central policy issue worldwide. Many countries have introduced varying degrees of data cross-border flow restrictions, raising the question of how such policies affect firms' international operations. Using the OECD's Digital Services Trade Restrictiveness Index (DSTRI) as a data source, this paper applies the entropy-weight method to construct a Cross-Border Data Flow Restriction Index (CDFRI) for major economies from 2014 to 2022, and then empirically examines how such restrictions reshape the cross-border digital merger and acquisition (M&A) activity of Chinese firms by employing negative binomial regression models, Probit models, and moderated regression analysis. The results reveal that higher levels of data cross-border flow restrictions significantly inhibit digital M&A in two ways: on the cost side, stricter restrictions increase transaction and compliance costs, leading to fewer completed deals, lower completion rates, and longer deal durations; on the benefit side, they reduce the expected value of digital M&A, resulting in fewer initiated deals and a higher propensity for joint ventures over wholly-owned ones. Further evidence shows that this inhibitory effect is amplified when the target firm is more data-sensitive, due to higher exposure to localization, audit, and liability risks, and when the target is more knowledge-intensive, because restrictions hinder algorithm transfer and post-merger knowledge integration. These findings indicate that data cross-border flow restrictions do not merely increase the costs of doing business, but fundamentally reshape the feasibility and governance structure of digital M&A.