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Multi-sided platforms must make decisions on both pricing and engineering investment and must continually adjust them as the platform scales over its lifecycle. Engineering investments can be allocated to features that improve a platform’s standalone value, social features to take advantage of same-side network effects, or integration tools and boundary resources to facilitate third-party content creation. Guidance in the academic or practitioner literature is not granular. Moreover, relevant normative economic models that consider externalities are rarely dynamic. Hence, there is a gap in knowledge about how to best balance tradeoffs between different strategic decisions throughout the entire platform lifecycle. To begin to address this gap, we explore normative strategies for coordinating pricing and engineering investment decisions on a continuous basis under different ecosystem conditions. We build a simulation model informed by economics and marketing theory and perform extensive sensitivity analyses on key parameters in different ecosystem scenarios over a multi-period lifecycle. We find that pricing and investment strategies must continuously change to perform optimally. In particular, strategies that are most effective at launch often differ from those that are most effective during scaling as well as those most effective at maturity. We also find that the optimal strategy depends strongly on the monetization model and market aversion to price changes. Lastly, we specifically examine four different industry segments: mobile platforms, social media, the sharing economy, and business-to-business. The results provide evidence that the trajectory of platform pricing and investment strategies should greatly differ depending on industrial context.

Strategic Investments for Platform Launch and Ecosystem Growth: A Dynamic Analysis