Irrefutable evidence shows that greater openness toward external partners enhances a firm's ability to solve innovation-related problems. To manage open innovation (OI) projects, firms use a variety of governance modes, including market-based contracts, platform intermediaries, and equity and non-equity partnerships. While innovation projects can be very diverse and characterized by various attributes, such as complexity and knowledge hiddenness, only a few conceptual studies have hitherto considered project attributes as drivers of OI governance mode selection. Using a sample of 85 OI projects and a set of illustrative cases, this paper explores empirically how project attributes influence OI governance mode selection. This empirical study advances previous conceptual work on OI governance. By accounting for project-level heterogeneity, we explore the micro-foundations of OI and provide more stable and fundamental insights into OI governance than previous industry-and firm-level analyses did. In addition, we suggest that effective OI management depends on matching project attributes with the benefits and costs of specific governance modes. Finally, we argue that this study enhances understanding and conceptualization of the relationship between project complexity and decomposability in the context of OI. MANAGERIAL RELEVANCE STATEMENT This study can help managers choose the appropriate governance mode for their OI projects by providing an empirically supported decision-making framework that accounts for the interplay between problem attributes and the costs and benefits of various OI governance modes. Our OI governance roadmap can in particular inform early stage decisions, which may have important implications for resource allocation during later stages of the project. Moreover, our findings can help managers decide whether to decompose complex problems into different sub-problems to which they can find solutions in collaboration with external partners. Our findings show that such decomposition does not only depend on problem complexity. Instead, problem complexity and knowledge hiddenness jointly drive problem decomposition decisions. More precisely, managers can think of complex problem decomposition only when the knowledge required for sub-problem solving exist, and they know which partners have the knowledge required to help them with their innovation projects.