To Hunt or to Scavenge: Optimal Investment Strategies in the Presence of Indirect Network Effects

What determines optimal R&D investment in a market with indirect network effects? We analyze this question in a hardware-software framework, where software firms strategically invest in quality upgrades. We find that a firm’s optimal investment depends predominantly on (1) the quality level of its software relative to its competitors on the same hardware and on (2) the quality levels of all software firms on the same platform relative to those on competing hardware platforms. Using a dynamic model we examine firms’ investment responses to changes in their own quality levels as well as changes in competitors’ quality levels. We show that intense competition across platforms stimulates investment across firms on the same platform, regardless of their current quality level. However, when competition across platforms is weak, firms may find it optimal to increase or reduce their investment in response to their own or their competitors’ quality upgrades. This gives rise to a matrix of optimal investment strategies. Since these strategies depend on market structure, we can map each firm’s optimal strategy into its position within the market. We would like to thank David Besanko, Ulrich Doraszelski, and Shane Greenstein, as well as seminar participants at Harvard University, Northwestern University and the ZEW conference in Mannheim for very helpful comments. Angela Malakhov, Ami Navon and Veronica Tong provided excellent research assistance. All remaining errors are ours. * Arison School of Management, Hertzliya, Israel, [email protected] ** School of Business, Redlands, Ca-92373-0999, Tel.: (909) 748-8779, [email protected]