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The prioritization and verification of IT emerging technologies using an analytic hierarchy process and cluster analysis

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  • Lee, Sangjae
  • Kim, Wanki
  • Kim, Young Min
  • Lee, Hyoung Yong
  • Oh, Kyong Joo

Abstract

This study proposes a quantitative technology forecasting method for prioritizing investments using analytic hierarchy process (AHP) analysis and a verification process to evaluate the prioritization using factor analysis and cluster analysis of the factor scores.

Suggested Citation

  • Lee, Sangjae & Kim, Wanki & Kim, Young Min & Lee, Hyoung Yong & Oh, Kyong Joo, 2014. "The prioritization and verification of IT emerging technologies using an analytic hierarchy process and cluster analysis," Technological Forecasting and Social Change, Elsevier, vol. 87(C), pages 292-304.
    • Handle: RePEc:eee:tefoso:v:87:y:2014:i:c:p:292-304
    DOI: 10.1016/j.techfore.2013.12.029
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    References listed on IDEAS

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    1. Gunasekaran, A. & Ngai, E.W.T. & McGaughey, R.E., 2006. "Information technology and systems justification: A review for research and applications," European Journal of Operational Research, Elsevier, vol. 173(3), pages 957-983, September.
    2. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    3. Henry Kaiser, 1974. "An index of factorial simplicity," Psychometrika, Springer;The Psychometric Society, vol. 39(1), pages 31-36, March.
    4. Stewart, Jenny, 1995. "Models of priority-setting for public sector research," Research Policy, Elsevier, vol. 24(1), pages 115-126, January.
    5. Millet, Ido & Saaty, Thomas L., 2000. "On the relativity of relative measures - accommodating both rank preservation and rank reversals in the AHP," European Journal of Operational Research, Elsevier, vol. 121(1), pages 205-212, February.
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    Citations

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    Cited by:

    1. Eungchan Kim & Young Seok Ock & Seung-Jun Shin & Wonchul Seo, 2018. "An Approach to Generating Reference Information for Technology Evaluation," Sustainability, MDPI, vol. 10(9), pages 1-19, September.
    2. Lijie Feng & Yuxiang Niu & Zhenfeng Liu & Jinfeng Wang & Ke Zhang, 2019. "Discovering Technology Opportunity by Keyword-Based Patent Analysis: A Hybrid Approach of Morphology Analysis and USIT," Sustainability, MDPI, vol. 12(1), pages 1-35, December.
    3. Kiwon Lee & Suchul Lee, 2021. "Knowledge Structure of the Application of High-Performance Computing: A Co-Word Analysis," Sustainability, MDPI, vol. 13(20), pages 1-20, October.
    4. Yuan Zhou & Fang Dong & Yufei Liu & Liang Ran, 2021. "A deep learning framework to early identify emerging technologies in large-scale outlier patents: an empirical study of CNC machine tool," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 969-994, February.
    5. Song, Kisik & Kim, Karp Soo & Lee, Sungjoo, 2017. "Discovering new technology opportunities based on patents: Text-mining and F-term analysis," Technovation, Elsevier, vol. 60, pages 1-14.
    6. Noh, Heeyong & Seo, Ju-Hwan & Sun Yoo, Hyoung & Lee, Sungjoo, 2018. "How to improve a technology evaluation model: A data-driven approach," Technovation, Elsevier, vol. 72, pages 1-12.
    7. Song, Kisik & Kim, Kyuwoong & Lee, Sungjoo, 2018. "Identifying promising technologies using patents: A retrospective feature analysis and a prospective needs analysis on outlier patents," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 118-132.

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