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Comparing technological hype cycles: Towards a theory


  • van Lente, Harro
  • Spitters, Charlotte
  • Peine, Alexander


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.

Suggested Citation

  • van Lente, Harro & Spitters, Charlotte & Peine, Alexander, 2013. "Comparing technological hype cycles: Towards a theory," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1615-1628.
  • Handle: RePEc:eee:tefoso:v:80:y:2013:i:8:p:1615-1628
    DOI: 10.1016/j.techfore.2012.12.004

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    3. Wilson, Charlie & Hargreaves, Tom & Hauxwell-Baldwin, Richard, 2017. "Benefits and risks of smart home technologies," Energy Policy, Elsevier, vol. 103(C), pages 72-83.
    4. repec:eee:tefoso:v:129:y:2018:i:c:p:76-87 is not listed on IDEAS
    5. Dedehayir, Ozgur & Steinert, Martin, 2016. "The hype cycle model: A review and future directions," Technological Forecasting and Social Change, Elsevier, vol. 108(C), pages 28-41.
    6. Jun, Seung-Pyo & Sung, Tae-Eung & Park, Hyun-Woo, 2017. "Forecasting by analogy using the web search traffic," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 37-51.
    7. Boon, Wouter P.C. & Aarden, Erik & Broerse, Jacqueline E.W., 2015. "Path creation by public agencies — The case of desirable futures of genomics," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 67-76.
    8. repec:gam:jsusta:v:10:y:2018:i:9:p:3125-:d:167199 is not listed on IDEAS
    9. Garud, Raghu & Gehman, Joel & Giuliani, Antonio Paco, 2014. "Contextualizing entrepreneurial innovation: A narrative perspective," Research Policy, Elsevier, vol. 43(7), pages 1177-1188.
    10. Hansen, Ulrich Elmer & Nygaard, Ivan, 2014. "Sustainable energy transitions in emerging economies: The formation of a palm oil biomass waste-to-energy niche in Malaysia 1990–2011," Energy Policy, Elsevier, vol. 66(C), pages 666-676.
    11. Silvestrini, Paolo & Amato, Umberto & Vettoliere, Antonio & Silvestrini, Stefano & Ruggiero, Berardo, 2017. "Rate equation leading to hype-type evolution curves: A mathematical approach in view of analysing technology development," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 1-12.
    12. Lyons, Glenn & Davidson, Cody, 2016. "Guidance for transport planning and policymaking in the face of an uncertain future," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 104-116.
    13. repec:eee:infome:v:12:y:2018:i:1:p:113-132 is not listed on IDEAS
    14. repec:eee:tefoso:v:130:y:2018:i:c:p:69-87 is not listed on IDEAS


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