Automated Author ProfileKussel, Gerhard
RWI – Leibniz Institute for Economic ResearchRuhr University Bochum
Kussel, Gerhard
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.3 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
With a share of 30% in total final energy consumption and around 20% in CO2 emissions, private households in Germany strongly affect the environment. At the same time private households are an important target group for policy interventions to fight climate change. Against this background, numerous policy measures that intend to decrease energy consumption and to support renewable energy technologies have been introduced. These policy measures call for accurate evaluation to avoid expensive redundancies due to overlapping policy instruments.The evaluation of energy and environmental policy measures requires comprehensive and reliable data. So far such data was unavailable in Germany, especially in the context of private households. Hence, the responsiveness of German households to climate protection policies was unknown.For this purpose, the Socio-Ecological Panel offers rich information on household’s energy consumption and environmental behavior. The data was gathered in four household surveys conducted in 2012, 2013, 2014 and 2015. The survey waves can be merged using the household ID. The data builds the basis for empirical analyses of households’ adaptation to climate change and the evaluation of environmental and climate policy measures.This data set comprises the information gathered in the 2013 survey wave.
Authors
- Frondel, Manuel ;
- Vance, Colin ;
- Andor, Mark ;
- Schmidt, Christoph M. ;
- Kussel, Gerhard ;
- Osberghaus, Daniel