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The hype cycle model: A review and future directions

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  • Dedehayir, Ozgur
  • Steinert, Martin

Abstract

The hype cycle model traces the evolution of technological innovations as they pass through successive stages pronounced by the peak, disappointment, and recovery of expectations. Since its introduction by Gartner nearly two decades ago, the model has received growing interest from practitioners, and more recently from scholars. Given the model's proclaimed capacity to forecast technological development, an important consideration for organizations in formulating marketing strategies, this paper provides a critical review of the hype cycle model by seeking evidence from Gartner's own technology databases for the manifestation of hype cycles. The results of our empirical work show incongruences connected with the reports of Gartner, which motivates us to consider possible future directions, whereby the notion of hype or hyped dynamics (though not necessarily the hype cycle model itself) can be captured in existing life cycle models through the identification of peak, disappointment, and recovery patterns.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:tefoso:v:108:y:2016:i:c:p:28-41
    DOI: 10.1016/j.techfore.2016.04.005
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    1. Konrad, Kornelia & Markard, Jochen & Ruef, Annette & Truffer, Bernhard, 2012. "Strategic responses to fuel cell hype and disappointment," Technological Forecasting and Social Change, Elsevier, vol. 79(6), pages 1084-1098.
    2. Schmoch, Ulrich, 2007. "Double-boom cycles and the comeback of science-push and market-pull," Research Policy, Elsevier, vol. 36(7), pages 1000-1015, September.
    3. Hariolf Grupp, 1998. "Foundations of the Economics of Innovation," Books, Edward Elgar Publishing, number 1390.
    4. 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.
    5. Klepper, Steven, 1996. "Entry, Exit, Growth, and Innovation over the Product Life Cycle," American Economic Review, American Economic Association, vol. 86(3), pages 562-583, June.
    6. Gao, Lidan & Porter, Alan L. & Wang, Jing & Fang, Shu & Zhang, Xian & Ma, Tingting & Wang, Wenping & Huang, Lu, 2013. "Technology life cycle analysis method based on patent documents," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 398-407.
    7. Seung-Pyo Jun, 2012. "An empirical study of users’ hype cycle based on search traffic: the case study on hybrid cars," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 81-99, April.
    8. Ron Martin & Peter Sunley, 2011. "Conceptualizing Cluster Evolution: Beyond the Life Cycle Model?," Regional Studies, Taylor & Francis Journals, vol. 45(10), pages 1299-1318, November.
    9. Routley, Michèle & Phaal, Robert & Probert, David, 2013. "Exploring industry dynamics and interactions," Technological Forecasting and Social Change, Elsevier, vol. 80(6), pages 1147-1161.
    10. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    11. Birgitte Andersen, 1999. "The hunt for S-shaped growth paths in technological innovation: a patent study," Journal of Evolutionary Economics, Springer, vol. 9(4), pages 487-526.
    12. Geels, Frank W., 2004. "From sectoral systems of innovation to socio-technical systems: Insights about dynamics and change from sociology and institutional theory," Research Policy, Elsevier, vol. 33(6-7), pages 897-920, September.
    13. Jun, Seung-Pyo & Yeom, Jaeho & Son, Jong-Ku, 2014. "A study of the method using search traffic to analyze new technology adoption," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 82-95.
    14. Alkemade, Floortje & Suurs, Roald A.A., 2012. "Patterns of expectations for emerging sustainable technologies," Technological Forecasting and Social Change, Elsevier, vol. 79(3), pages 448-456.
    15. Jun, Seung-Pyo, 2012. "A comparative study of hype cycles among actors within the socio-technical system: With a focus on the case study of hybrid cars," Technological Forecasting and Social Change, Elsevier, vol. 79(8), pages 1413-1430.
    16. Feng, Guangchao Charles, 2015. "Determinants of Internet diffusion: A focus on China," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 176-185.
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