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Method For Forecasting Di Based On Triz Technology System Evolution Theory

Author

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  • JIANGUANG SUN

    (Hebei University of Technology, Institute of Design for Innovation, No. 8 Dingzigu Yihao Road Hongqiao District, Tianjin, P. R. China)

  • RUNHUA TAN

    (Hebei University of Technology, Institute of Design for Innovation, No. 8 Dingzigu Yihao Road Hongqiao District, Tianjin, P. R. China)

Abstract

Disruptive Innovation (DI) is an effective method for a new firm to enter mature market. According to the composing analysis of the technical system for the product, six kinds of typical state in the technical system process can be detected. In accordance with technology system evolution analysis, two kinds of evolutionary technologies — mainstream evolutionary technologies and laggard evolutionary technologies — can be detected. Then, the conditions for forecasting DI technologies are established. Based on evolution path lines of TRIZ, the potential DI can be forecasted. As a case study, the video game console system is investigated. The study shows that the adoption of TRIZ evolution theory in forecasting disruptive technologies of product is feasible.

Suggested Citation

  • Jianguang Sun & Runhua Tan, 2012. "Method For Forecasting Di Based On Triz Technology System Evolution Theory," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 1-20.
    • Handle: RePEc:wsi:ijitmx:v:09:y:2012:i:02:n:s0219877012500101
    DOI: 10.1142/S0219877012500101
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    References listed on IDEAS

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    1. Fey,Victor & Rivin,Eugene, 2005. "Innovation on Demand," Cambridge Books, Cambridge University Press, number 9780521826204.
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    Cited by:

    1. Lantano, Francesco & Petruzzelli, Antonio Messeni & Panniello, Umberto, 2022. "Business model innovation in video-game consoles to face the threats of mobile gaming: Evidence from the case of Sony PlayStation," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    2. Sowmini Sengupta & Jisun Kim & Seong Dae Kim, 2018. "Forecasting New Features and Market Adoption of Wearable Devices Using TRIZ and Growth Curves: Case of Fitness Tracking Products," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 15(01), pages 1-19, February.
    3. Ping Qiao & Xiaoman Zhu & Yangzhi Guo & Ying Sun & Chuan Qin, 2021. "The Development and Adoption of Online Learning in Pre- and Post-COVID-19: Combination of Technological System Evolution Theory and Unified Theory of Acceptance and Use of Technology," JRFM, MDPI, vol. 14(4), pages 1-17, April.

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