Growth-System Transferability across Digital Ecosystems: Evidence from the United States, China and Ukraine

Dmytro Skrynskyi

Citation: Dmytro Skrynskyi, "Growth-System Transferability across Digital Ecosystems: Evidence from the United States, China and Ukraine", Universal Library of Business and Economics, Volume 02, Issue 01.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Digital growth systems developed in mature ecosystems are increasingly applied across international markets, yet the conditions under which their underlying logic transfers remain insufficiently theorized. This paper examines the transferability of growth-marketing frameworks across three structurally distinct digital ecosystems: the United States, China, and Ukraine. Applying a comparative case-study design supported by systematic literature review and secondary data analysis of digital advertising expenditure (2021-2023), the study introduces the Growth-System Transferability Framework and a companion Behavioral Alignment Index, which together operationalize the concept of contextual fit between a source market’s growth levers and a target market’s structural characteristics. Results indicate that transferability follows a continuum shaped by platform concentration, regulatory environment, AI adoption rate, and consumer behavior maturity, rather than a binary adopt-or-reject logic. The findings offer practitioners and marketing associations a calibrated decision tool for cross-market strategy deployment, particularly for evidence-based digital marketing operations and AI-enabled campaign management. The findings are of value to researchers, practitioners, and professional associations engaged in cross-market knowledge exchange and digital marketing standards.


Keywords: Growth Hacking, Digital Ecosystems, Marketing Transferability, Cross-Market Strategy, Behavioral Alignment, AI-Enabled Marketing, Data-Driven Marketing, Performance Measurement, Digital Advertising, Evidence-Based Marketing.

Download doi https://doi.org/10.70315/uloap.ulbec.2025.0201013