Nonlinear Trend Analysis

Nonlinear Trend Analysis is a methodological framework within technology forecasting that models the non-constant rate of performance improvement over time by capturing S-shaped dynamics through nonlinear mathematical functions, distinguishing it from linear or polynomial trend models by explicitly representing phases of slow initial progress, rapid acceleration, and eventual saturation.

131

Publications

9.5K

Citations

409

Authors

234

Institutions

Publications per year

2017–2026

45

Authors

409

  1. JC
    Juan Carlos Cuestas

    University of Sheffield, United Kingdom

    4 publications · 155 citations

    4

    h-index

  2. WL
    Weihong Li

    Xinjiang Institute of Ecology and Geography, China

    3 publications · 173 citations

    3

    h-index

  3. PP
    Pierre Perrón

    Boston University, United States

    3 publications · 79 citations

    3

    h-index

  4. ZC
    Zhongsheng Chen

    Xinjiang Institute of Ecology and Geography, China

    3 publications · 106 citations

    3

    h-index

  5. YC
    Yaning Chen

    Xinjiang Institute of Ecology and Geography, China

    3 publications · 161 citations

    3

    h-index

1–5 of 409

Venues

  1. International Journal of Climatology

    5 publications · 466 citations

    5

    h-index

  2. Applied Economics

    3 publications · 81 citations

    3

    h-index

  3. Applied Economics Letters

    3 publications · 91 citations

    3

    h-index

  4. Heliyon

    2 publications · 41 citations

    2

    h-index

  5. 2

    h-index

1–5