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General morphological analysis as a basic scientific modelling method

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  • Ritchey, Tom

Abstract

General Morphological Analysis (GMA) is a method for structuring a conceptual problem space – called a morphospace – and, through a process of existential combinatorics, synthesising a solution space. As such, it is a basic modelling method, on a par with other scientific modelling methods including System Dynamics Modelling, Bayesian Networks and various types graph-based “influence diagrams”. The purpose of this article is 1) to present the theoretical and methodology basics of morphological modelling; 2) to situate GMA within a broader modelling theoretical framework by developing a (morphological) model representing different modelling methods, and 3) to demonstrate some of the basic modelling techniques that can be carried out with GMA using dedicated computer support.

Suggested Citation

  • Ritchey, Tom, 2018. "General morphological analysis as a basic scientific modelling method," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 81-91.
    • Handle: RePEc:eee:tefoso:v:126:y:2018:i:c:p:81-91
    DOI: 10.1016/j.techfore.2017.05.027
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    Cited by:

    1. Kemp-Benedict, Eric & Carlsen, Henrik & Kartha, Sivan, 2019. "Large-scale scenarios as ‘boundary conditions’: A cross-impact balance simulated annealing (CIBSA) approach," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 55-63.
    2. Pereverza, Kateryna & Pasichnyi, Oleksii & Kordas, Olga, 2019. "Modular participatory backcasting: A unifying framework for strategic planning in the heating sector," Energy Policy, Elsevier, vol. 124(C), pages 123-134.
    3. Pawel Gromek & Grzegorz Sobolewski, 2020. "Risk-Based Approach for Informing Sustainable Infrastructure Resilience Enhancement and Potential Resilience Implication in Terms of Emergency Service Perspective," Sustainability, MDPI, vol. 12(11), pages 1-30, June.
    4. Vanessa J. Schweizer, 2020. "Reflections on cross-impact balances, a systematic method constructing global socio-technical scenarios for climate change research," Climatic Change, Springer, vol. 162(4), pages 1705-1722, October.
    5. Gustavo Ezequiel Martinez & Roel Degens & Gabriela Espadas-Aldana & Daniele Costa & Giuseppe Cardellini, 2024. "Prospective Life Cycle Assessment of Hydrogen: A Systematic Review of Methodological Choices," Energies, MDPI, vol. 17(17), pages 1-15, August.

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