Automated Author ProfileIngle, Aaron
Ingle, Aaron
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: 7.2 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This research focused on accelerating solar photovoltaic (PV) diffusion by collecting new market data and developing predictive modeling frameworks to test and refine understandings of household level motivations for adopting solar. Three different household-level surveys were fielded: one for households who had installed PV on their current home or had signed a contract to do so (the Adopter survey), one for households that had seriously considered PV but had not installed it (the Considerer survey), and one for the general population who did not have PV on their current home (the general population survey or GPS). Survey respondents were from four U.S. states: New Jersey, New York, Arizona, and California. Details of recruiting and sampling are documented below. Research projects on residential PV adoption often collect data only from PV adopters or from the general population. One of the innovations of this project was the three-pronged household survey data collection. By collecting similar data from three fairly different "statuses" with respect to adoption, the surveys provide a basis for understanding how those who do not have rooftop PV differ from those who have, for how and why people do (or don't) transition from not having to having rooftop PV on their home, and for understanding the characteristics and viewpoints of households who have scarcely, or not at all, entered the "PV consideration" track. All three surveys covered single-family owner-occupied households in each of the four target states used in the project -- Arizona, California, New Jersey, and New York - allowing a comparative approach to understanding how the factors that affect PV adoption vary by geography and policy conditions. The General Population and Considerer surveys provide a basis for understanding opinions about and interest in solar, and how these relate to household demographics and other conditions. Paired with the Adopter survey, they also provide data for understanding how those who do not have rooftop PV differ from those who have, and for how and why people do (or don't) transition from not having to having rooftop PV on their home. The Adopter survey questions were designed to capture a broad range of information on what motivates and impedes households to install rooftop PV, as well as the details and timing of the decision and installation. Survey instrument development drew from existing PV adoption survey instruments, PV adoption literature, and research team experience, as well as from past work on household interest in energy efficiency, environmental attitudes, purchasing tendencies, and related knowledge. Early interviews and discussions with installers and others in the PV industry were also taken into consideration.
Authors
- Sigrin, Ben ;
- Dietz, Tom ;
- Henry, Adam ;
- Ingle, Aaron ;
- Lutzenhiser, Loren ;
- Moezzi, Mithra ;
- Spielman, Seth ;
- Stern, Paul ;
- Todd, Annika ;
- Tong, James ;
- Wolske, Kim