Data analytics, big data, cloud computing, and internet of things are just a few of the recent technological innovations. A total of 236 emerging technologies were identified by Gartner Inc., over the period 2003 to 2015. The rate of adoption of new technologies has significant implications for adopting firms, suppliers of these technologies, and investors. Some of these new technologies have the potential to disrupt the competitive landscape and provide firms that adopt with a sustained competitive advantage. In the paper "Emerging Technology Adoption and Expected Duration of Competitive Advantage," I have developed a framework for predicting the expected duration of a competitive advantage due to adoption of an emerging technology, and suggest a process for generating technology specific predictions of expected duration.
The framework integrates elements from the technology adoption (diffusion) cycle, hype cycles of emerging technologies, and the resource based view conceptualization of number of firms associated with a perfectly competitive market equilibrium. The objective of this synthesis is to generate a framework for estimating average technology diffusion time and standard deviation. Given the prevailing assumption that technology diffusion follows an approximate bell shaped distribution, we can use these two values to estimate the duration of a technology adoption related competitive advantage. The paper demonstrates the empirical estimation of the mean and standard deviation, as well as expected duration of competitive advantage for a specific emerging technology (i.e., cloud computing) using three methods: Google Trends to capture web search interest, LexisNexis to capture news stories with focus in cloud computing, and Gartner Hype Cycles for emerging technologies. All three methods produce comparable results.
The paper is available from the following URL: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2695858
