Network platforms are increasingly important in current economic ecosystems. With industries, platforms and organizations integrating in many directions, the difficulties of defining the boundaries of organizational populations increase. Although population ecologists have frequently applied legitimation and competition mechanisms to analyze inside the organizational population, there is little understanding of the transition of such mechanisms across populations and whether competition mechanisms vary in mixed populations. This paper therefore builds on recent work in community ecology and proposes a Platform System Dependence Model, which involves a re-specification of these mechanisms and offers a theoretical framework that is suitable for heterogeneous organizational populations and sufficiently adapted to the dynamic nature of the network economy. Furthermore, in order to describe and analyze how different organizational populations interact within the ecosystem, we expand traditional population and community ecology models to time-related differential equations. This change makes it possible to perform a comprehensive density-trend analysis that can be applied within and across different categories of populations. We furthermore offer a simulation based on this framework, which supports the thesis that the density of a symbiotic organizational population and a competitive organizational population increases rapidly in the initial stage of organizational population growth, while, at the same time, the platform-based organizational population increases gradually. As the density of a symbiotic population decreases and the competitive population density remains stable, the density of the platform-based organizational population decreases after reaching its maximum. We discuss the implications of these findings for research on ecology and on the platform economy.

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Rotterdam School of Management (RSM), Erasmus University

Xu, J. (Jin), Peng, B. (Biyu), & Cornelissen, J. (2020). Modelling the network economy: A population ecology perspective on network dynamics. Technovation. doi:10.1016/j.technovation.2020.102212