TY - JOUR
T1 - Forecasting of potential impacts of disruptive technology in promising technological areas
T2 - Elaborating the SIRS epidemic model in RFID technology
AU - Cheng, Yu
AU - Huang, Lucheng
AU - Ramlogan, Ronnie
AU - Li, Xin
PY - 2017/4/1
Y1 - 2017/4/1
N2 - 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.
AB - 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.
KW - Application areas forecasting
KW - Disruptive technology
KW - Industrial disruption
KW - SIRS epidemic model
KW - Technological disruption
KW - Technology forecasting
UR - http://www.scopus.com/inward/record.url?scp=85009461559&partnerID=8YFLogxK
U2 - 10.1016/j.techfore.2016.12.003
DO - 10.1016/j.techfore.2016.12.003
M3 - Article
AN - SCOPUS:85009461559
SN - 0040-1625
VL - 117
SP - 170
EP - 183
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
IS - 0
ER -