Gartner's Hype Cycle diagram attracted increasing attention in the business world and, more recently, also in academia (see Ozgur and Steinert, 2016). The initial idea of a five-phased hype cycle over usually “five to eight years” is based on two equations, the bell-curve-shaped hype expectations model arising from initial overenthusiasm, and the technological maturity S-curve model (Fenn & Raskino, 2008). Empirically, however, the cycle appears, if at all, only with strong deviations and there is a lack of theory “able to explain the different shapes of hype cycles in different contexts” (van Lente et al., 2013, p. 1615). Explaining such variance, regarding the shape of the peak, depth of the trough, and the overall length or duration of a hype, by their “specificity of the envisioned application, and the nature of the environment in which the expectations surrounding the envisioned applications where created, shared and refined,” motivates the authors to three case studies (p. 1626). For the Voice over Internet Protocol (VoIP), Gene Therapy, and High-Temperature Superconductivity (HTS) the authors present storylines about technological promises in their regulatory and economic environments, sentiment-focused discourse analyses of the expectations at different phases, and quantifications of attention as represented by the annual numbers of regarding articles in the New York Times. The authors find that the attention over time only represents the hype pattern in the case of superconductivity, while, in the other two cases, hype reveals itself primarily in the discourse analysis (p. 1624). Focusing on how emerging technologies can best survive the so-called “Trough of Disillusionment” (Fenn & Raskino, 2007), the authors conclude that “a good mix of different expectations at different levels is a potential predictor for a productive recovery after disappointment” (p. 1627). Accordingly, an analysis fruitful for dealing with hypes requires both considered quantifications and a more substantive examination of visions and their social contexts of emergence and contestation.

References: Fenn, Jackie, and Mark Raskino. Mastering the Hype Cycle: How to Choose the Right Innovation at the Right Time. Boston, Mass: Harvard Business School Press, 2008. Dedehayir, Ozgur, and Martin Steinert. The Hype Cycle Model: A Review and Future Directions. Technological Forecasting and Social Change 108 (July 2016): 28–41. https://doi.org/10.1016/j.techfore.2016.04.005.