Combining tech mining and semantic TRIZ for technology assessment: Dye-sensitized solar cell as a case (FULL-TEXT)

In a competitive business environment, an early understanding of the dynamics of technological change is crucial to help policymakers and managers make better-informed decisions. Bibliometric analyses help in studying trends and technological evolution. Tech mining (text analyses of science and technology information resources) enhances Bibliometric analyses. However, more often than not, such analyses focus on a specific technological area, and mainly result in incremental advance forecasts. An analysis of the interconnected dynamics of technology change warrants new approaches for identifying technology emergence, technological substitution, and the influences of vital socioeconomic forces. This paper introduces a unique combination that applies a tech mining and semantic TRIZ as a case study to Dye-Sensitized Solar Cell (DSSC) technology. This methodological combination brings broader insights to the emergence of DSSC in conjunction with related technologies that affect its progress, enriching the associated technological progression’s empirical characterization.

  • Techmining-semantic TRIZ helps to understand the competition influence among technologies.
  • The understanding of the architectural design, the system, helps to clearly understand the role of the different components.
  • Understanding the components’ role in the system helps to guide the techmining analysis and to understand the different trends.
  • Using the S-AO and not the SAO problem solving, the present work is able to find other competing or not, technologies that help to understand if that will support the emergence of the original or the competing technology.
  • This cross-tech-components have different role in other architectures. Perovskites, enhance silicon solar cells efficiency.

https://doi.org/10.1016/j.techfore.2021.120826 or download FULL-TEXT

Author(s):J.M. Vicente-Gomila, M.A. Artacho-Ramírez, Ma Ting, A.L.Porter
Organization(s):Universitat Politècnica de València, Beijing Institute of Technology, Search Technology
Source: Technological Forecasting and Social Change
Year: 2021

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