Refine
Year of publication
- 2024 (2) (remove)
Document Type
- Article (2)
Institute
- Forschungszentrum Business Informatics (2) (remove)
Language
- English (2) (remove)
Has Fulltext
- no (2) (remove)
Is part of the Bibliography
- yes (2)
Keywords
- Application (1)
- Constrained Optimization (1)
- Evolution Strategies (1)
- Self-Adaptation (1)
- Sustainability (1)
- discourse network analysis (1)
- socio-political acceptance (1)
- technology legitimacy (1)
- wind energy (1)
Why do some countries assign a major role to wind energy in decarbonizing their electricity systems, while others are much less committed to this technology? We argue that processes of (de-)legitimation, driven by discourse coalitions who strategically employ certain storylines in public debates, provide part of the answer. To illustrate our approach, we comparatively investigate public discourses surrounding wind energy in Austria and Switzerland, two countries that differ strongly in wind energy deployment. By combining a qualitative content analysis and a discourse network analysis of 808 newspaper articles published 2010–2020, we identify four distinct sets of storylines used to either delegitimize or legitimize the technology. Our study indicates that low deployment rates in Switzerland can be related to the prominence of delegitimizing storylines in the public discourse, which result in a rather low socio-political acceptance of wind energy. In Austria, by contrast, there is more consistent support for wind energy by discourse coalitions using a broad set of legitimizing storylines. By bridging the related but separate literatures of technology legitimacy and social acceptance, our study contributes to a better understanding of socio-political conflict and divergence in low-carbon technological pathways.
In this paper, we consider the question of data aggregation using the practical example of emissions data for economic activities for the sustainability assessment of regional bank clients. Given the current scarcity of company-specific emission data, an approximation relies on using available public data. These data are reported in different standards in different sources. To determine a mapping between the different standards, an adaptation to the Covariance Matrix Self-Adaptation Evolution Strategy is proposed. The obtained results show that high-quality mappings are found. Nevertheless, our approach is transferable to other data compatibility problems. These can be found in the merging of emissions data for other countries, or in bridging the gap between completely different data sets.