Despite the omnipresence of platforms and the breadth of related re-search, predicting the outcomes of platforms remains challenging. To reach a critical mass of complementary partners innovating on their platform, platform owners must foster both generativity and profitability on their platform. The con-ditions under which these objectives may be achieved have yet to be delineated, however. The study at hand theorizes that the impact of platforms’ promised ca-pabilities is delineated by the conditions in the competitive environment. Through simulation, explicitly designed to understand system-level behavior, this theorization can be tested. The developed agent-based simulation model cap-tures a platform within its surrounding business ecosystem. It accounts for plat-forms’ value proposition to lower search costs and resource costs associated with innovation, as well as related governance decisions faced by platform owners. Importantly, conditions in the competitive environment, namely environmental complexity, may also be adjusted for experimental testing. The simulation model thereby enables a flexible investigation of platform governance decisions and broader environmental conditions. Experimentation results reveal platforms as ineffective at fostering generativity and profitability in low complexity environ-ments, implying platforms to not be uniformly promising or disruptive in all kinds of competitive environments. Thus, this study’s main contribution is an agent-based simulation model to help understand and predict outcomes of plat-forms as complex phenomena.

Marius Schmid

2022