Third-party providers as entrepreneurs boost technology platforms. Yet, despite increasing interest in technological platforms, existing research offers little predictive insight into how firms can identify individuals who are likely to become entrepreneurs. We take the strategic perspective of a platform owning company, asking how to pinpoint those individuals who transition into entrepreneurship in the near future. We base our analysis on automatically registered behavioral data, such as the complete sales history of all applications related to a technological platform, and the complete history of communications in communities related to the platform. We employ logistic regression models to predict: (a) the transition from registered platform user to third-party developer (i.e. entrepreneurial intent) and (b) the launch of a first platform application (i.e. commercialization). We control for individuals’ social network positions, their communication behaviors, exposure to input from other entrepreneurs (i.e social contagion), and their early adoption and lead- user traits. We show that even after inclusion of these controls volume-wise “bulk” consumption still adds significantly to the predictional power on each step towards entrepreneurship. The impact of simple measures for bulk consumption on entrepreneurship is often ignored in the entrepreneurship literature. Our study contributes to the strategic management literature on the dynamics of innovation on technological platforms, by explicitly linking the production and consumption sides of two-sided markets. It also adds to the entrepreneurship literature by showing how the entrepreneurial process manifests itself in the context of technological platforms
