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An assessment of technology forecasting: Revisiting earlier analyses on dye-sensitized solar cells (DSSCs)

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  • Huang, Ying
  • Porter, Alan L.
  • Zhang, Yi
  • Lian, Xiangpeng
  • Guo, Ying

Abstract

The increasingly uncertain dynamics of technological change pose special challenges to traditional technology forecasting tools, which facilitates future-oriented technology analysis (FTA) tools to support the policy processes in the fields of science, technology & innovation (ST&I) and the management of technology (MOT), rather than merely forecasting incremental advances via analyses of continuous trends. Dye-sensitized solar cells are a promising third-generation photovoltaic technology that can add functionality and lower costs to enhance the value proposition of solar power generation in the early years of the 21st century. Through a series of technological forecasting studies analyzing the R&D patterns and trends in Dye-sensitized solar cells technology over the past several years, we have come to realize that validating previous forecasts is useful for improving ST&I policy processes. Yet, rarely do we revisit forecasts or projections to ascertain how well they fared. Moreover, few studies pay much attention to assessing FTA techniques. In this paper, we compare recent technology activities with previous forecasts to reveal the influencing factors that led to differences between past predictions and actual performance. Beyond our main aim of checking accuracy, in this paper we also wish to gain some sense of how valid those studies were and whether they proved useful to others in some ways.

Suggested Citation

  • Huang, Ying & Porter, Alan L. & Zhang, Yi & Lian, Xiangpeng & Guo, Ying, 2019. "An assessment of technology forecasting: Revisiting earlier analyses on dye-sensitized solar cells (DSSCs)," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 831-843.
  • Handle: RePEc:eee:tefoso:v:146:y:2019:i:c:p:831-843
    DOI: 10.1016/j.techfore.2018.10.031
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    Cited by:

    1. Lidan Jiang & Jingyan Chen & Yuhan Bao & Fang Zou, 2022. "Exploring the patterns of international technology diffusion in AI from the perspective of patent citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5307-5323, September.
    2. Huang, Ying & Li, Ruinan & Zou, Fang & Jiang, Lidan & Porter, Alan L. & Zhang, Lin, 2022. "Technology life cycle analysis: From the dynamic perspective of patent citation networks," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    3. Sasikumar, Ragu & Thirumalaisamy, Suryaprabha & Kim, Byungki & Hwang, Byungil, 2024. "Dye-sensitized solar cells: Insights and research divergence towards alternatives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    4. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Zhang, Huiling & Pang, Hongshen, 2021. "Multidimensional Scientometric indicators for the detection of emerging research topics," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    5. Chia-Chi Sun & Shih-Chi Chang, 2021. "An Assessment Framework for Solar Cell Material Based on a Modified Fuzzy DEMATEL Approach," Energies, MDPI, vol. 14(18), pages 1-17, September.

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