A Framework for Predicting Emerging Technology Adoption

Abstract

Blockchain, big data, and internet of things are just a few of the over 200 technologies introduced in the last 15 years. Technology adoption/diffusion has significant implications for adopting firms, suppliers of these technologies, and investors. Approaching technology adoption from a strategic standpoint (i.e., a potential source of competitive advantage); the objective of this study is to develop a framework for predicting technology diffusion using publicly available data. The proposed framework integrates elements from the technology diffusion cycle, hype cycles of emerging technologies, and resource-based view (RBV). We apply the methodology on cloud computing and ERP, using the following four sources of data: Google Trends for web search interest, LexisNexis for news stories, Gartner Hype Cycles for emerging technologies, and number of book titles. All sources produce comparable results. For ERP, we rely on prior literature on IT business value to show that diffusion related predictions are consistent with evidence from empirical studies. In addition to the contribution to the literatures on technology diffusion and RBV; one of the main practical contributions of this study is that the proposed methodology is relatively easy to implement. Stakeholders can use readily available data to make their own predictions

Keywords: Technology adoption, competitive advantage, duration, RBV, hype cycle, ERP, cloud computing

JEL Classification: O3, L1