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A proactive technology selection model for new technology: The case of 3D IC TSV

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  • Hung, Chih-Young
  • Lee, Wen-Yi

Abstract

Many studies have addressed the issues of the evaluation and the selection of new technology. In this paper, we add to this literature by formulating a more general model that incorporates the evaluation, the selection and the improvement of new technology. The improvement of new technology refers to the modification of the development of the underlying technology. We accomplish this by combining an Importance-Score Report for each of the factors of the new technology to the adopting firm and a Performance-Score Report of the alternative new technologies' performance on each of the factors into a two-dimensional graph. This graph helps to reveal the specific factors of the new technology for the adopting firm to work on improving. Processes such as this will be an informative and powerful planning tool for decision maker when choosing among competing new technologies. We then use a case of selecting a 3D IC TSV technology for a Taiwanese IC manufacturer to illustrate the application of the PTSM. Three critical factors of the 3D IC TSV technology were then identified for improvement.

Suggested Citation

  • Hung, Chih-Young & Lee, Wen-Yi, 2016. "A proactive technology selection model for new technology: The case of 3D IC TSV," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 191-202.
    • Handle: RePEc:eee:tefoso:v:103:y:2016:i:c:p:191-202
    DOI: 10.1016/j.techfore.2015.11.009
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    References listed on IDEAS

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    Cited by:

    1. Lizarralde, Rafael & Ganzarain, Jaione & Zubizarreta, Mikel, 2022. "Adaptation of the MIVES method for the strategic selection of new technologies at an R&D centre. Focus on the manufacturing sector," Technovation, Elsevier, vol. 115(C).
    2. Rafael Lizarralde & Jaione Ganzarain & Mikel Zubizarreta, 2020. "Assessment and Selection of Technologies for the Sustainable Development of an R&D Center," Sustainability, MDPI, vol. 12(23), pages 1-23, December.
    3. Cheng, Yu & Huang, Lucheng & Ramlogan, Ronnie & Li, Xin, 2017. "Forecasting of potential impacts of disruptive technology in promising technological areas: Elaborating the SIRS epidemic model in RFID technology," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 170-183.
    4. Guo, Jianfeng & Pan, Jiaofeng & Guo, Jianxin & Gu, Fu & Kuusisto, Jari, 2019. "Measurement framework for assessing disruptive innovations," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 250-265.

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