Understanding the Evolution of Customer Motivations and Adoption Barriers in Residential Solar Markets: Survey Data

Sigrin, Ben; Dietz, Tom; Henry, Adam; Ingle, Aaron; Lutzenhiser, Loren; Moezzi, Mithra; Spielman, Seth; Stern, Paul; Todd, Annika; Tong, James; Wolske, Kim

doi:10.7799/1362095

Title: Understanding the Evolution of Customer Motivations and Adoption Barriers in Residential Solar Markets: Survey Data

Dataset
Other Related Research

Abstract

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 onmore »« less

Authors:: Sigrin, Ben; Dietz, Tom; Henry, Adam; Ingle, Aaron; Lutzenhiser, Loren; Moezzi, Mithra; Spielman, Seth; Stern, Paul; Todd, Annika; Tong, James; Wolske, Kim

Publication Date:: 2017-06-12

Other Number(s):: 68

DOE Contract Number:: EE0026154

Research Org.:: National Renewable Energy Laboratory - Data (NREL-DATA), Golden, CO (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office

Subject:: 14 SOLAR ENERGY

Keywords:: NREL; energy; data; Residential Solar; Surveys; SEEDS; Technology Adoption; Customer; solar photovoltaic; PV; solar adoption; rooftop; pv consideration; Arizona; California; New Jersey; New York; geographic consideration; USA

OSTI Identifier:: 1362095

DOI:: https://doi.org/10.7799/1362095

Citation Formats


                    Sigrin, Ben, Dietz, Tom, Henry, Adam, Ingle, Aaron, Lutzenhiser, Loren, Moezzi, Mithra, Spielman, Seth, Stern, Paul, Todd, Annika, Tong, James, and Wolske, Kim. Understanding the Evolution of Customer Motivations and Adoption Barriers in Residential Solar Markets: Survey Data.  United States: N. p., 2017. 
        Web.  doi:10.7799/1362095.

Copy to clipboard


                    Sigrin, Ben, Dietz, Tom, Henry, Adam, Ingle, Aaron, Lutzenhiser, Loren, Moezzi, Mithra, Spielman, Seth, Stern, Paul, Todd, Annika, Tong, James, & Wolske, Kim. Understanding the Evolution of Customer Motivations and Adoption Barriers in Residential Solar Markets: Survey Data.  United States.  doi:https://doi.org/10.7799/1362095

Copy to clipboard


                    Sigrin, Ben, Dietz, Tom, Henry, Adam, Ingle, Aaron, Lutzenhiser, Loren, Moezzi, Mithra, Spielman, Seth, Stern, Paul, Todd, Annika, Tong, James, and Wolske, Kim. 2017.  
"Understanding the Evolution of Customer Motivations and Adoption Barriers in Residential Solar Markets: Survey Data".  United States.  doi:https://doi.org/10.7799/1362095.  https://www.osti.gov/servlets/purl/1362095. Pub date:Mon Jun 12 00:00:00 EDT 2017

Copy to clipboard


                    
@article{osti_1362095,

  title        = {Understanding the Evolution of Customer Motivations and Adoption Barriers in Residential Solar Markets: Survey Data},

  author       = {Sigrin, Ben and Dietz, Tom and Henry, Adam and Ingle, Aaron and Lutzenhiser, Loren and Moezzi, Mithra and Spielman, Seth and Stern, Paul and Todd, Annika and Tong, James and Wolske, Kim},

  abstractNote = {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.},

  doi          = {10.7799/1362095},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {2017},

  month        = {6}

}

Copy to clipboard

Dataset:

View Dataset

DOI: https://doi.org/10.7799/1362095

Save / Share:

Export Metadata

Save to My Library

Similar records in DOE Data Explorer and OSTI.GOV collections:

UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency

Dataset Fuentes, Tracy L ; McCord, Kieren H ; Rackley, Adrienne LS ; ...

This work represents the largest and most comprehensive dataset to-date of responses surveyed from U.S. residents regarding home modifications and energy-related decision-making, including both objective measures describing the occupants and their homes and subjective measures describing the more unpredictable human factors behind residential decision-making. First, to develop the survey, we interviewed 121 individual decision-makers within their households regarding planned or completed projects. We used the insights of these interviews to design a survey that was distributed to 10,000 households across the U.S. The overarching topics approached in the survey include descriptive information about the respondent, their household, their home, homemore »« less
Data-Driven Understanding of Low-to-Moderate Income Customers’ Adoption and Financial Qualification in Community Solar (Final Technical Report)

Technical Report Speirs, Steph ; Murali, Sandhya

When Solstice began working in the community solar industry, it quickly became clear that there was a wide disparity along race and class lines in terms of what kind of household traditional solar offerings benefited. Solstice is an organization that aligns itself to the principles of a Just Transition, or the concept that a transition to a green economy should benefit and prioritize historically marginalized groups of people. Given that low-income communities are disproportionately burdened by our current polluting fossil fuel economy, Solstice set out to investigate the root causes of the exclusion of low to moderate income (LMI) householdsmore »« less
Using Machine Learning and Data Analysis to Improve Customer Acquisition and Marketing in Residential Solar

Program Document Sigrin, Benjamin O

High customer acquisition costs remain a persistent challenge in the U.S. residential solar industry. Effective customer acquisition in the residential solar market is increasingly achieved with the help of data analysis and machine learning, whether that means more targeted advertising, understanding customer motivations, or responding to competitors. New research by the National Renewable Energy Laboratory, Sandia National Laboratories, Vanderbilt University, University of Pennsylvania, and the California Center for Sustainable Energy and funded through the U.S. Department of Energy's Solar Energy Evolution and Diffusion (SEEDS) program demonstrates novel computational methods that can help drive down costs in the residential solar industry.
Screening Tool for Equitable Adoption and Deployment of Solar (STEADy Solar)

Dataset Ferrall-Wolf, Isa ; McLaren, Joyce

The Screening Tool for Equitable Adoption and DeploYment of Solar (STEADy Solar) is a database and mapping tool designed to promoting clean energy investments for low-income communities across the United States. The tool indicates locations that may be eligible for the Investment Tax Credit bonus adders defined in the 2022 Inflation Reduction Act (IRA) and combines this information with demographics, social vulnerability, solar technical potential, solar economics (modeled net present value), and building counts by use-type. It can be used by states, municipalities, community-based organizations, developers, and researchers to identify sites where solar projects may be economical and where federalmore »« less
DeepSolar++: Understanding residential solar adoption trajectories with computer vision and technology diffusion models

Journal Article Wang, Zhecheng ; Arlt, Marie-Louise ; Zanocco, Chad ; ... - Joule

Although the United States has generally experienced a rapid adoption of residential photovoltaics (PV), many communities are lagging behind. To investigate why, we developed a computer vision model that addresses the challenge of low image resolution to identify the installation year of PVs from historical aerial and satellite images. We used the model to construct a granular spatiotemporal dataset of PV deployment across 46 US states and analyzed these data from a technology adoption life cycle perspective. Our analysis of adoption curves and phases showed that low-income communities are not only delayed in their adoption onset but also saturate moremore »« less

Similar Records