Internationalization of Digital Platform Firms: An Exploration of Resource Orchestration, Platform Accessibility, and Cultural Distance

Abstract

Digital platforms constitute strategic applications that utilize a core technology with a prescribed interface that enable external third parties to build complementary products to expand value capture capabilities (Ceccagnoli et al., 2012; Cusumano et al., 2019; Gawer & Cusumano, 2015; Van Alstyne et al., 2016b). The “boundary resources” that span the firm’s internal and external environment can influence a platform’s success by affecting a complementor’s choice (Cennamo et al., 2018; X. Shi et al., 2024). While platforms have been acknowledged as a market entry strategy (Brouthers et al., 2022; Teece et al., 2022), little research has explored how resource orchestration choices lead to different international performance outcomes (Coviello et al., 2017). This dissertation uses a novel AI-powered qualitative content analysis to analyze developer portal data from 230 global platforms in 57 countries and identifies the suppressive effects of a proposed new construct of “platform accessibility” (PA), measured by investment in a variety of natural language and programming language customization for the host market. Moderated by cultural distance, PA negatively predicts international performance, despite evidence that platform resources strongly increase PA. I examine the differing effects by each platform boundary resource category and identify five new configurations of resource bundle patterns that demonstrate good empirical model fit and differ from prior theory. Investments in core platform infrastructure and AI resources drive performance outcomes. An emergent strategic resource investment pattern in AI agentic solutions is identified, alongside a nuanced view of 3 discrete social resource patterns. Four clusters of platform firm resource orchestration behaviors are identified, and the effects of poor language-market fit are also explored with cultural distance.