Invisible Engines
David S. Evans, Andrei Hagiu, Richard Schmalensee
Harnessing the power of software platforms: what executives and entrepreneurs must know about how to use this technology to transform industries and how to develop the strategies that will create value and drive profits.Software platforms are the invisible engines that have created, touched, or transformed nearly every major industry for the past quarter century. They power everything from mobile phones and automobile navigation systems to search engines and web portals. They have been the source of enormous value to consumers and helped some entrepreneurs build great fortunes. And they are likely to drive change that will dwarf the business and technology revolution we have seen to this point. Invisible Engines examines the business dynamics and strategies used by firms that recognize the transformative power unleashed by this new revolution?a revolution that will change both new and old industries.The authors argue that in order to understand the successes of software platforms, we must first understand their role as a technological meeting ground where application developers and end users converge.
Award History
1 wins · 1 total
| Award | Year | Result | Category / Notes |
|---|---|---|---|
| PROSE Award for Business, Finance, and Management | 2006 | Winner | Official source |
Experimental book profileGenerated by GPT-5.4 nano · may contain inaccuracies
This is an unverified interpretation of the catalog description, offered as an opt-in discovery experiment—not as bibliographic fact.
01 Central figures
None extracted with sufficient confidence.
02 Central places
None extracted with sufficient confidence.
03 Suggested argument
Software platforms act as a technological meeting ground where application developers and end users converge, and understanding this role is necessary to explain firms’ successes with platform strategies.
Model confidence 78%
04 Reading orientation
65 / 100 academicAcademic
An estimate of intended readership and scholarly apparatus—not quality or importance.
Confidence percentages are the model's own estimates. Profile confidence: 72%.