Innovation, Openness, and Platform Control

Consider that a firm in charge of a business platform is a firm in charge of a micro economy. To achieve the highest growth rate, how open should that platform economy be? To encourage third party developers, how long should their proprietary interests last? To address these questions, we develop a sequential innovation model that balances two trade-offs. (i) Closing the platform increases the sponsor's ability to charge for access while opening the platform increases developer ability to build upon it. (ii) The longer developers retain proprietary interest in their innovations, the higher the royalties they and the sponsor earn. In contrast, the sooner developers' proprietary interests expire, the sooner their innovations become a public good, bundled into the open platform, upon which other ecosystem developers can further build. Our model allows us to characterize the optimal levels of openness and of IP duration in a business ecosystem. Based on innovation profits, this model can also characterize the firm's decision to vertically integrate into downstream production as a closed hierarchy or to offer an open contract to an innovation ecosystem. We use standard tools of Cobb-Douglas production and two-sided networks to derive these results. Findings can inform innovation strategy, choice of organizational form, intellectual property law, and management of competition.

Biography
Professor Van Alstyne received a BA from Yale, and MS & PhD degrees from MIT. He is an Associate Professor at Boston University and a Visiting Professor at MIT. His work concerns information economics. In designing information goods, this research concerns competitive strategy and network effects. In control over information, it concerns who has access to what information, when, and at what price. Work also balances open source principles against those that generate profits and stimulate innovation.
Professor Van Alstyne was among the first to document productivity effects of IT and communications at the individual desktop level. His work has received an NSF Career Award, two best paper awards, and has appeared in Science, Management Science, Harvard Business Review, and the popular press.