
Abstract The notion of ‘hype’ is widely used and represents a tempting way to characterize developments in technological fields. The term appears in business as well as in academic domains. Consultancy firms offer technological hype cycle models to determine the state of development of technological fields in order to facilitate strategic investment decisions. In Science, Technology and Innovation Studies the concept of hype is considered in studies on the dynamics of expectations in innovation processes, which focuses on the performative force of expectations. What is still lacking is a theory of hype patterns that is able to explain the different shapes of hype cycles in different contexts. In this paper we take a first step towards closing this gap by studying and comparing the results of case studies on three hypes in three different empirical domains: voice over internet protocol (VoIP), gene therapy and high-temperature superconductivity. The cases differ in terms of the type of technology and the characteristics of the application environment. We conclude that hype patterns indeed vary a lot, and that the interplay of expectations at different levels affects the ability of a field to cope with hype and disappointment.
Gene therapy, Milieukunde, VoIP, Expectation, High temperature superconductivity, Hype cycle
Gene therapy, Milieukunde, VoIP, Expectation, High temperature superconductivity, Hype cycle
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 251 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
