From matchmakers to innovation machines: market generativity in the Bubble.io ecosystem

Firm-designed marketplaces are central to the business models of leading digital platforms, yet the dominant view in scholarship treats them primarily as matchmaking and allocation mechanisms. This view captures the dynamics of standardized marketplaces such as ride-sharing, but is incomplete for marketplaces in which value emerges from continuous innovation rather than from efficient allocation alone, including app stores, plugin marketplaces, and creator-content platforms. This study reconceptualizes such marketplaces as deliberately designed innovation systems and asks how they can be architected to optimize for generativity while maintaining necessary allocation and appropriation functions. Drawing on a revelatory case study of the Bubble.io ecosystem, including eight semi-structured interviews and extensive secondary data spanning more than 55,000 forum posts and 5500 marketplace listings, we operationalize marketplace generativity through seven empirically observable dimensions and develop a three-layer architectural framework comprising allocation, appropriation, and generation. We articulate five propositions about how the three layers interact, including an inverted-U relationship between appropriation and generativity that platform designers must calibrate. The framework distinguishes itself from adjacent perspectives, including two-sided market theory, market design theory, and platform ecosystem theory, by treating generation as a first-class design objective rather than as an emergent property of platform openness. We contribute actionable design principles for early-stage marketplace founders, maturing platform operators, and policymakers, and identify directions for extending the framework to data marketplaces, AI model marketplaces, and creator-content platforms.