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Author:

Cheng, Yu (Cheng, Yu.) | Huang, Lucheng (Huang, Lucheng.) (Scholars:黄鲁成) | Ramlogan, Ronnie (Ramlogan, Ronnie.) | Li, Xin (Li, Xin.) (Scholars:李欣)

Indexed by:

SSCI EI Scopus

Abstract:

Disruptive technology introduces new competitive platforms, possesses the ability of initiating new markets, and changes firms' technological competition status. Early identification of candidate application areas will allow for timely adjustment of technology innovation strategies and minimization of risks at firm level. This paper proposes a framework of application areas forecasting process for disruptive technology based on patent data. SIRS epidemic model is analogically introduced by measuring transition velocity of all the entities in the technology diffusion system respectively. We implement the model deterministically to forecast the potential of industrial and technological disruption in the short run, and stochastically to forecast the disruptive technology's major outbreak in candidate application areas in the long run. Radio-frequency identification technology is selected as case study. We conclude by discussing the major outbreak probabilities and potential disruptions of RFID in three different application areas. The results will provide practical suggestion to firms and other stakeholders to facilitate their strategy making when faced with disruptive technologies. (C) 2016 Elsevier Inc. All rights reserved.

Keyword:

Technology forecasting SIRS epidemic model Application areas forecasting Industrial disruption Technological disruption Disruptive technology

Author Community:

  • [ 1 ] [Cheng, Yu]Beijing Univ Technol, Coll Econ & Management, Res Base Beijing Modern Mfg Dev, Beijing, Peoples R China
  • [ 2 ] [Huang, Lucheng]Beijing Univ Technol, Coll Econ & Management, Res Base Beijing Modern Mfg Dev, Beijing, Peoples R China
  • [ 3 ] [Li, Xin]Beijing Univ Technol, Coll Econ & Management, Res Base Beijing Modern Mfg Dev, Beijing, Peoples R China
  • [ 4 ] [Ramlogan, Ronnie]Univ Manchester, Alliance Manchester Business Sch, Manchester Inst Innovat Res, Manchester, Lancs, England

Reprint Author's Address:

  • [Ramlogan, Ronnie]Univ Manchester, Alliance Manchester Business Sch, Manchester Inst Innovat Res, Manchester, Lancs, England

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Source :

TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE

ISSN: 0040-1625

Year: 2017

Volume: 117

Page: 170-183

ESI Discipline: SOCIAL SCIENCES, GENERAL;

ESI HC Threshold:116

Cited Count:

WoS CC Cited Count: 36

SCOPUS Cited Count: 58

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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