Rate equation leading to hype-type evolution curves: A mathematical approach in view of analysing technology development

The theoretical understanding of Gartner's “hype curve” is an interesting open question in deciding the strategic actions to adopt in presence of an incoming technology. In order to describe the hype behaviour quantitatively, we propose a mathematical approach based on a rate equation, similar to that used to describe quantum level transitions. The model is able to describe the hype curve evolution in many relevant conditions, which can be associated to various market parameters. Different hype curves, describing the time evolution of a new technology market penetration, are then obtained within a single coherent mathematical approach. We have also used our theoretical model to describe the time evolution of the number of scientific publications in different fields of scientific research. Data are well described by our model, so we present a statistical analysis and forecasting potentiality of our approach. We note that the hype peak of inflated expectations is very smooth in the case of scientific publications, probably due to the high level of awareness and the deep preliminary understanding which is necessary to carry on a research project. Our model is anyway flexible enough to describe many patterns of increasing interest on a new idea, leading to a hype behaviour or other time evolution.

[1]  Carlos Castillo-Chavez,et al.  Population modeling of the emergence and development of scientific fields , 2008, Scientometrics.

[2]  F. Bass A new product growth model for consumer durables , 1976 .

[3]  L. Petti,et al.  Performance of High-Sensitivity Nano-SQUIDs Based on Niobium Dayem Bridges , 2009, IEEE Transactions on Applied Superconductivity.

[4]  V. Mahajan,et al.  Timing, Diffusion, and Substitution of Successive Generations of Technological Innovations: The IBM Mainframe Case , 1996 .

[5]  des lettres et des beaux-arts de Belgique.,et al.  Nouveaux mémoires de l'Académie royale des sciences et belles-lettres de Bruxelles. , 1827 .

[6]  P. Silvestrini,et al.  Measurement of the effective dissipation in an rf SQUID system , 2003 .

[7]  A. Dobson An introduction to generalized linear models , 1990 .

[8]  Nano Superconducting Quantum Interference device: a powerful tool for nanoscale investigations , 2015, 1505.06887.

[9]  P. Silvestrini,et al.  Tunable Josephson Devices for Quantum Computation , 2007, IEEE Transactions on Applied Superconductivity.

[10]  Jacob Goldenberg,et al.  Riding the Saddle: How Cross-Market Communications Can Create a Major Slump in Sales , 2002 .

[11]  Marc S. Lavine What Would A. G. Bell Say Now? , 2010, Science.

[12]  P. Silvestrini,et al.  Supercurrent decay in underdamped Josephson junctions: Nonstationary case , 1985 .

[13]  Alexander Peine,et al.  Comparing technological hype cycles: Towards a theory , 2013 .

[14]  E. Rogers Diffusion of Innovations , 1962 .

[15]  Topology-induced critical current enhancement in Josephson networks , 2005, cond-mat/0512478.

[16]  Yogesh V. Joshi,et al.  New Product Diffusion with Influentials and Imitators , 2007 .

[17]  Paolo Silvestrini,et al.  OBSERVATION OF ENERGY LEVELS QUANTIZATION IN UNDERDAMPED JOSEPHSON JUNCTIONS ABOVE THE CLASSICAL-QUANTUM REGIME CROSSOVER TEMPERATURE , 1997 .

[18]  Gila E. Fruchter,et al.  A utility-based dynamic model used to predict abnormalities in diffusion over time , 2017 .

[19]  Seung-Jun Yeon,et al.  A dynamic diffusion model for managing customer's expectation and satisfaction , 2006 .

[20]  S. Kalish A New Product Adoption Model with Price, Advertising, and Uncertainty , 1985 .

[21]  Inhomogeneous superconductivity in comb-shaped Josephson junction networks , 2006, cond-mat/0609639.

[22]  Marco Campani,et al.  A simple interpretation of the growth of scientific/technological research impact leading to hype-type evolution curves , 2015, Scientometrics.