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A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 0-9

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

Author: Ashish Sood and Gerard J. Tellis
Organisation: Marketing Science Institute
Publish Date: 2010
Country: Global
Sector: Technology
Type: Other publication
Language: English
Tags: Predicting Disruptive Technologies, Technology, Predictive models

For its many benefits to consumers and markets, technological change may be most notable for the challenge it presents to incumbent firms. From microcomputers to MP3 players, there are numerous examples of established firms misinterpreting the impact of new technology, leading to their own demise.

Why do firms fail when faced with technological change? Of several prominent theories, the theory of “disruptive technologies” has been dominant. This theory posits that disruption occurs when a technology that is superior on a new dimension that appeals to a niche, but inferior on a dimension that appeals to the mass market, improves on the latter dimension to meet the needs of the mass market. The theory suggests that such a lower attack is potentially “disruptive,” because managers of incumbent firms may ignore or belittle a seemingly inferior technology. However, this theory lacks precise definitions, suffers from tautologies, lacks adequate empirical testing, and has no predictive model.

Authors Sood and Tellis attempt to remedy these problems with a new schema, new empirical data, and a new predictive model. The proposed schema has clear definitions for types of technologies, types of attacks, and domains of disruption, and explains the dynamics of competition between new and dominant technologies. They derive seven testable hypotheses, which they test using historical data on 36 platform technologies from seven markets. Further, they carry out an out-of-sample predictive analysis that shows good to high sensitivity and specificity in predicting disruption.
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