Philosophy

Extant taxon

Biology

Economics

Computer science

Schema (genetic algorithms)

Empirical evidence

Business

Evolutionary biology

Epistemology

Emerging technologies

Data science

Artificial intelligence

Industrial organization

Machine learning

Marketing Science

The failure of firms in the face of technological change has been a topic of intense research and debate, spawning the theory (among others) of disruptive technologies. However, the theory suffers from circular definitions, inadequate empirical evidence, and lack of a predictive model. We develop a new schema to address these limitations. The schema generates seven hypotheses and a testable model relating to platform technologies. We test this model and hypotheses with data on 36 technologies from seven markets. Contrary to extant theory, technologies that adopt a lower attack (“potentially disruptive technologies”) (1) are introduced as frequently by incumbents as by entrants, (2) are not cheaper than older technologies, and (3) rarely disrupt firms; and (4) both entrants and lower attacks significantly reduce the hazard of disruption. Moreover, technology disruption is not permanent because of multiple crossings in technology performance and numerous rival technologies coexisting without one disrupting the other. The proposed predictive model of disruption shows good out-of-sample predictive accuracy. We discuss the implications of these findings.

Demystifying Disruption: A New Model for Understanding and Predicting Disruptive Technologies