Evaluating Emerging Technologies on the Gartner Hype Cycle by Network Analysis : A Display Technology Case Study

Gartner’s Technology Hype Cycle (THC) is widely used as a method for evaluating new technologies. Gartner positions each technology concept in consideration of various factors such as the maturity of complementary technologies, social acceptability, and development of technological infrastructure. However, since THC is a snapshot-like prediction made once a year, there is a lack of time information. Thus, it is not easy to judge the best timing for resource investment. Based on the above awareness of the problem, this study conducted a network analysis of the time concept missing in THC. A new indicator is incorporated to evaluate the speed of dynamic and continuous technology growth. We focused on the number of clusters in the network to consider the calculation of speed and examined two cases to compare two display technologies, OLED and QD. In a previous study, we found that a fast-changing QD dataset could be difficult to predict. This graph network analysis made it possible to understand the status of each display R&D and to compare both technologies by acceleration. This research will contribute to the development of tools for resource allocation at appropriate times.