Abstract
The multisided platform (MSP) is an essential business construct in the digital economy. Some of the largest companies in the world—including Google, Amazon, and eBay—exploit the MSP in their business models. Fundamental insights into the MSP are crucial to understand the business operations of the digital economy and how new innovative digital services are adopted in the market. The MSP ecosystem is complex and dynamic, and involves heterogeneous stakeholders with different business motivations. This paper classifies the various types of MSPs, distinguished by the network effect between user groups. Moreover, this paper shows how the original diffusion model of Frank Bass can be extended to analyze the temporal evolution of multisided platforms. Analytical models using coupled sets of ordinary differential equations are developed for several examples of two-sided platforms. For some of these examples, analytical solutions are found.
Highlights
Fundamental strategic questions in market analysis are related to how the market for new innovations evolves as a function of time
This paper presents a comprehensive overview of the different types of multisided platforms, distinguished by network effects within and between user groups
The purpose of the models presented in the paper is to study the temporal evolution of user adoption of each service the platform is offering based on interactions between the user groups
Summary
Fundamental strategic questions in market analysis are related to how the market for new innovations evolves as a function of time. The purpose of this paper is to fill this gap by developing new mathematical models for how network effects within (same-side) and between (cross-side) different market segments—or user groups—make the market segments interact and grow. This analysis is by no means complete, but it provides some insight into strategic issues related to the different classes, in particular the “chicken and egg”.
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