Research Summary: Entrepreneurial ecosystems command increasing attention from policy makers, academics, and practitioners, yet the phenomenon itself remains under‐theorized. Specifically, the conceptual similarities and differences of entrepreneurial ecosystems relative to, for instance, clusters, “knowledge clusters,” regional systems of innovation, and “innovative milieus” remain unclear. Drawing on research on industrial districts and agglomerations, clusters, and systems of innovation, we suggest that entrepreneurial ecosystems differ from traditional clusters by their emphasis on the exploitation of digital affordances; by their organization around entrepreneurial opportunity discovery and pursuit; by their emphasis on business model innovation; by voluntary horizontal knowledge spillovers; and by cluster‐external locus of entrepreneurial opportunities. We highlight how these distinctive characteristics set entrepreneurial ecosystems apart from other cluster types, propose a structural model of entrepreneurial ecosystems, summarize the articles in this special issue, and suggest promising avenues for future research. Managerial Summary: Entrepreneurial ecosystems command increasing attention from policy makers, academics, and practitioners. We suggest that entrepreneurial ecosystems differ from traditional clusters by their emphasis on the exploitation of digital affordances; by their organization around entrepreneurial opportunity discovery and pursuit; by their emphasis on business model innovation; by voluntary horizontal knowledge spillovers; and by cluster‐external locus of entrepreneurial opportunities. We highlight how these distinctive characteristics set entrepreneurial ecosystems apart from regional cluster phenomena discussed in received economic geography and innovation literatures. We suggest policy makers need to adopt novel approaches to stimulate entrepreneurial ecosystems that differ from those in place to develop industrial clusters or support already established small‐ and medium‐sized companies.

The use of the term platform has proliferated in management research. However, theoretical work on the concept has lagged behind. We present a systematic review of the platform literature, identifying four distinct streams: organizational platforms, product family platforms, market intermediary platforms, and platform ecosystems. Each of these streams is characterized by a distinctive, although usually implied, theoretical logic. We elaborate on the theoretical logics of leverage and architectural openness, both of which underpin all four streams of platform research. We further discuss three distinctive leverage rationales exhibited in different platform variants—production, innovation, and transaction—and illustrate how platform ecosystems combine aspects of all three. We explain the meta-logic of architectural leverage to facilitate the purposive manipulation of platforms, providing a link between platform design features and sources of leverage. This provides a model that allows the different platform types to be placed into context with others. Finally, we outline how the concept of architectural leverage can be used to understand platform evolution.

Ecosystems—communities of interdependent yet hierarchically independent heterogeneous participants who collectively generate an ecosystem value proposition—often emerge through collective action, where ecosystem participants interact with each other and the external environment. When such organizational forms are emerging, they require legitimacy to overcome the “liability of newness.” Adopting a collective action lens and taking a legitimacy-as-process approach, we propose a process model of ecosystem collective action, where an orchestrator, complementors, users, and external actors together drive ecosystem legitimacy. We identify three key legitimation processes—discursive legitimation, performative legitimation, and ecosystem identity construction—and demonstrate how these three processes together facilitate the emergence of ecosystem legitimacy and reduce the liability of newness of emerging ecosystems.

Based on a longitudinal case study, this paper presents an ecosystem‐level process model of the interlocking key activities of the business model disruptor, other ecosystem participants (customers, partners, media, analysts), and the incumbent. Together these constitute a strategic process of ecosystem evolution from incumbent‐centred to disruptor‐centred. We identify the phenomenon of a ‘disruptor's gambit’, where the disruptor reveals its intentions early on through effective framing, followed by rapid adaptation of its business model to satisfy ecosystem needs. These processes generate a virtuous framing‐adaptation cycle, where feed‐forward and feedback enable rapid response to customers and partners, while engaging them as force multipliers during new ecosystem creation. Our findings suggest that framing constitutes a dynamic strategic process enabling disruptors to reduce uncertainty, dislodge powerful incumbents, and shape new ecosystems through business model innovation.

This article considers how the innovation ecosystem concept has been defined to date and then reviews the extant ecosystem literature from two perspectives. First, it provides insights with regard to ecosystem boundaries, structure, and coordination, drawing on ecosystem research as carried out in different empirical contexts. Second, it outlines three theoretical perspectives that can be applied to ecosystem research—notably, the value creation perspective, the network embeddedness perspective, and the network management perspective. Building upon these perspectives the ecosystem concept is then applied to innovation strategy analysis, design, and implementation.

With increasing interest in how digital technology impacts innovation, the constructs “digitization” and “digitalization” have become popular. However, different conceptualizations have emerged resulting in conceptual overlap and little definitional consensus. To understand how these two constructs have been used within innovation management, we systematically review both constructs and identify 26 different definitions used for both, underscoring the need for greater precision. Building from our systematic review, we synthesize and integrate these findings to derive clear and parsimonious definitions of digitization and digitalization and propose a conceptual framework that systematically links both constructs with existing innovation scholarship. We then discuss the implications of our framework on theories of the process of innovation and digital transformation. We recommend future research into digital design principles, digital product life cycle, knowledge accumulation, generativity, and the feedback dynamics within our framework. We also provide practitioner implications and limitations.