• ISSN: 2148-2225 (online)

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alphanumeric journal

The Journal of Operations Research, Statistics, Econometrics and Management Information Systems

Data-Driven Insights into Climate Change and Technological Levels: Data Mining Visualization and TOPSIS Approach

Merve Doğruel, Ph.D.


Abstract

The 2024 Global Risks Report identifies misinformation and disinformation under the technology category as the foremost short-term global risk, followed closely by the risk of extreme weather events categorized under environmental concerns. In a longer-term perspective, the prominence of extreme weather events escalates to the top position, with misinformation and disinformation remaining significant, and adverse outcomes from AI technologies emerging as the seventh most critical risk. This delineation underscores the preeminent challenges posed by environmental and technological factors to global stability. These risks are not confined to the realm of environmental scientists or technologists; rather, they impact humanity as a whole. Recognizing that each individual holds inherent responsibilities, it is crucial to approach these issues through a multidisciplinary academic lens. This study, therefore, concurrently addresses climate change and technological impacts, investigating the interconnections and sub-indicators of these issues on a national scale. Countries were assessed based on these dimensions, compared, and visually represented, culminating in a comprehensive ranking. To facilitate these analyses, methodologies such as exploratory data analysis, principal component analysis, multidimensional scaling, and the TOPSIS were employed. The findings reveal a negative correlation between energy consumption and technology metrics, and a positive correlation between renewable energy indicators and technology. This study provides a nuanced understanding of how countries align with these global risks, offering a ranked evaluation starting from the most to the least affected.

Keywords: Cliamte change, Data Mining, TOPSIS, Technology level, Visualization

Jel Classification: C38, C44, C63

Suggested citation

Doğruel, M. (). Data-Driven Insights into Climate Change and Technological Levels: Data Mining Visualization and TOPSIS Approach. Alphanumeric Journal, 13(1), 13-35. https://doi.org/10.17093/alphanumeric.1647858

bibtex

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Volume 13, Issue 1, 2025

2025.13.01.OR.02

alphanumeric journal

Volume 13, Issue 1, 2025

Pages 13-35

Received: Feb. 27, 2025

Accepted: May 6, 2025

Published: June 30, 2025

Full Text [3.4 MB]

2025 Doğruel, M.

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