DEMATELab: A Python-based application for cause-and-effect analysis
SoftwareX, vol. 36, pp. 103172
Abstract
Cause-and-effect analysis is essential for understanding complex systems with interdependent factors and dynamic interactions. This analysis enables the identification of key drivers, feedback loops, and underlying structures that shape the behavior of a system. One of the well-known and established frameworks for modeling causal relationships in complex systems is the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. Experts and decision-makers are the main input sources for DEMATEL. This underscores the need for an accessible, user-friendly software package that can collect, manage, and integrate their evaluations. To this end, a Python-based application has been developed to support cause-and-effect analysis using DEMATEL and its extensions based on triangular fuzzy set, grey interval numbers, and Z-numbers. The software offers various useful options based on in-depth analyses using different threshold identification techniques, cluster analysis, and automated interpretation of results via large language models.
Authors 3
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Ali Ebadi Torkayesh corresponding Aachen Economics of Sustainability School of Business and Economics
RWTH Aachen University · Forschungszentrum Jülich
Affiliation as printed
Economics of Sustainability, School of Business and Economics, RWTH Aachen University, 52072 Aachen, Germany
Forschungszentrum Jülich GmbH, Institute of Climate and Energy Systems, Jülich Systems Analysis (ICE-2), 52425 Jülich, Germany
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Affiliation as printed
Independent Researcher, Aachen, Germany
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RWTH Aachen University · Forschungszentrum Jülich
Affiliation as printed
Economics of Sustainability, School of Business and Economics, RWTH Aachen University, 52072 Aachen, Germany
Forschungszentrum Jülich GmbH, Institute of Climate and Energy Systems, Jülich Systems Analysis (ICE-2), 52425 Jülich, Germany