Angela Sanguinetti

Home energy management (HEM) database: A list with coded attributes of 308 devices commercially available in the US

Policymakers worldwide are currently discussing whether to include home energy management (HEM) products in their portfolio of technologies to reduce carbon emissions and improve grid reliability. However, very little data is available about these products. Here we present the results of an extensive review including 308 HEM products available on the US market in 2015–2016. We gathered these data from publicly available sources such as vendor websites, online marketplaces and other vendor documents. A coding guide was developed iteratively during the data collection and utilized to classify the devices. Each product was coded based on 96 distinct attributes, grouped into 11 categories: Identifying information, Product components, Hardware, Communication, Software, Information - feedback, Information - feedforward, Control, Utility interaction, Additional benefits and Usability. The codes describe product features and functionalities, user interaction and interoperability with other devices. A mix of binary attributes and more descriptive codes allow to sort and group data without losing important qualitative information. The information is stored in a large spreadsheet included with this article, along with an explanatory coding guide. This dataset is analyzed and described in a research article entitled “Categories and functionality of smart home technology for energy management” (Ford et al., 2017) [1].

A Typology of In-Vehicle Eco-Driving Feedback

Eco-driving is a promising strategy for reductions in fossil fuel consumption and carbon emissions. Eco-driving is most frequently promoted via in-vehicle feedback. Eco-driving feedback studies demonstrate fuel economy improvements up to 18 %, but results are widely variable—partly due to the wide variation in feedback design. This paper addresses the need for a greater understanding of how variations in eco-driving feedback design are related to its effectiveness. We identified characteristics of feedback with implications for behavior change based on behavioral theory and evaluation of a large sample of in-vehicle eco-driving feedback interfaces. We developed a typology of in-vehicle eco-driving feedback interfaces based on these characteristics. We identified 15 distinct types of in-vehicle eco-driving feedback interfaces. We describe each feedback type and discuss implications for feedback design. Our typology provides a foundation for subsequent research to determine most effective feedback types for particular behaviors, drivers, and driving conditions.

More room for cohousing in the United States: Understanding diffusion potential by exploring who knows about, who likes, and who would consider living in cohousing

ABSTRACT Early adopters of cohousing have been relatively homogenous in many regards. For example, most are white, politically liberal, Democrat, and have a post-graduate education; females are also overrepresented compared to the general population. Little is known about the degree to which this lack of diversity is due to lack of broader appeal, lack of awareness or access, or other factors. The present study sought to further understanding of this issue. Through a diffusion of innovations lens, we explored a wide range of potential demographic, socioeconomic, and attitudinal predictors of knowledge of and interest in cohousing among the general US population, via an online survey of 157 individuals. Regression analysis revealed that being older, not heterosexual, more educated, and voting in the 2012 presidential election predicted greater knowledge of cohousing, and being liberal and a working woman predicted interest in cohousing. Findings are discussed in terms of implications for understanding the profile of cohousing early adopters and potential for the movement to expand to broader segments of the US population.

Electric Vehicle Explorer

Most HCI research related to electric vehicle adoption has focused on mitigating barriers related to vehicle range and charging infrastructure, while relatively less attention has been given to helping consumers recognize the benefits of electric vehicles. A significant benefit is reduced energy costs; however, the complexity of comparing gasoline and electricity prices makes it difficult for consumers to quantify. This paper describes and evaluates an online tool called EV Explorer that enables users to compare personalized estimates of annual energy costs for multiple vehicles. We assessed the tool through an online experiment, gauging users’ perceptions—before and after using the tool—of their current energy costs, potential savings with electric vehicles, attitude toward electric vehicle charging, and intention to buy or lease an electric vehicle in the future. Statistically significant changes in each of these variables validate the tool as an educational and persuasive strategy to promote electric vehicle adoption.

Energy UX: Leveraging Multiple Methods to See the Big Picture

Engaging the public to decrease their carbon footprint via energy feedback has become a significant topic of both study and practice and understanding how to best leverage technology for this purpose is an ideal question for the field of HCI to address. One common example is Home Energy Reports (HERs) and Business energy reports (BERs), which are paper or electronic reports that display a consumer’s energy use alongside various benchmarks and “tips” to help (and persuade) them to save energy. While HERs and BERs show great promise, average savings hover around 1–3% with the potential savings in the average home and/or business closer to 15–20%, leaving potential room for improvement. This paper presents a mixed-methods research framework that is being used to improve BER user experience and energy savings. It blends inductive research methods from the fields of design and HCI with deductive methods drawn from psychology and behavioral economics to develop and test hypotheses and translate findings into real-world application. After introducing the framework, a case study is presented in which these steps are followed over two years of research with one BER product across multiple utility pilots. Implications for both energy feedback specifically as well as suggestions on how this framework can be applied across the broader field of usability are discussed.