Innovation Patterns in the History of Web Technology: A Patent-Based Approach.

This thesis explores the evidence behind popular narratives regarding the development of the Web industry over time. Topics such as the rate of technological growth, generations in Web technology and the emergence of novel technological species are conceptualised here using theoretical perspectives from the fields of economic history, innovation studies and cultural evolution. These fields share an interest in applying the evolutionary principles of variation, selection andtransmission to technological change. Each principle is investigated here by means of empirical investigations into the temporal patterns of Web innovation, adoption of technical standards and transmission of knowledge through time. The methodological approach is based on an original longitudinal dataset of 20,493 US patents related specifically to the Web to trace the history of this industry between the years of 1990 through 2013. Quantitative analyses revealed thatinnovation in the Web industry in some ways conformed, and in other ways deviated from theoretical models of technology growth. Areas of consistency include an initial S-shaped trajectory of corporate innovation that aligned with stock market movements. Associations like this have previously been observed in other technological revolutions. The unique aspects of Web evolution relate mainly to its continued growth beyond the expected ceiling of the S-curve. It was found that this extension can be partly attributed to firms who adopted interactive Web 2.0applications such as social networks, blogs, wikis and RSS feeds. Moreover, Web 2.0 firms werecontinuing to adopt core Web standards that had been established earlier. It appears that standardisation played a role in the long-term evolution of the Web industry by providing a meansfor knowledge to be conserved, transmitted and combined in new ways. The thesis concludes with implications for researchers, managers and policy makers with a view to understanding and fostering sustainable long-term innovation. Specific recommendations are also provided to support the future expansion of Web technology into the emerging fields of data science and AI