Entrepreneurial Discovery and Information Complexity in Knowledge-Intensive Industries

Abstract

I investigate how the inherent complexity of the information associated with a newly introduced product affects the likelihood that the product is subsequently replicated, imitated, or both. Using information theory, I introduce a model and methods for quantifying the complexity of any product that is representable as an algorithm. I apply this methodology to construct and analyze a historical dataset of 91 digital signal processing firms and 853 product introductions (1974-2009). The empirical results support previously untested predictions from earlier simulation studies. The generalized model is extensible to many knowledge-intensive industries and has important implications for researchers, managers, and policymakers.