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1. Residents’ Perceptions of Behavioral Reference Groups for Personalized Normative Messaging Interventions

   Song, K. ( November 2020 , Construction Research Congress)

   Reporting normative feedback to residential energy consumers has been found effective at reducing residential energy consumption. Upon receiving normative feedback households tend to modify their use to become in line with group norms. The effect of normative messages is partially moderated by how personally relevant normative reference groups are to the individual. Advanced energy metering technologies capture households’ energy use patterns, making it possible to generate highly similar and relevant normative reference groups in a non-invasive manner. Unfortunately, it is not well understood how similar individuals are to other group members. It also remains unknown how much individuals identify with behavioral reference groups. Therefore, this research aims to investigate how households perceive behavioral reference groups used in normative comparisons. Survey questionnaires are collected from 2,008 participants using Amazon Mechanical Turk. It is found that while households’ behaviors are more similar when grouped based on energy use profiles than based on geographic proximity, they identify more closely with proximity-based groups. Also, members’ group identification increases as individuals have higher similarity in energy use behaviors with other group members. This implies that enhancing the identity of profile-based behavioral reference groups will lead to an increase in norm adherence, and in turn reductions in household energy use. 

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2. Non-Invasive Behavioral Reference Group Categorization Considering Temporal Granularity and Aggregation Level of Energy Use Data

   https://doi.org/10.3390/en13143678  

   Song, Kwonsik ; Anderson, Kyle ; Lee, SangHyun ; Raimi, Kaitlin T. ; Hart, P. Sol ( July 2020 , Energies)

   Within residences, normative messaging interventions have been gaining interest as a cost-effective way to promote energy-saving behaviors. Behavioral reference groups are one important factor in determining the effectiveness of normative messages. More personally relevant and meaningful groups are likely to promote behavior change. Using readily available energy-use profiles in a non-invasive manner permits the creation of highly personalized reference groups. Unfortunately, how data granularity (e.g., minute and hour) and aggregation (e.g., one week and one month) affect the performance of energy profile-based reference group categorization is not well understood. This research evaluates reference group categorization performance across different levels of data granularity and aggregation. We conduct a clustering analysis using one-year of energy use data from 2248 households in Holland, Michigan USA. The clustering analysis reveals that using six-hour intervals results in more personalized energy profile-based reference groups compared to using more granular data (e.g., 15 min). This also minimizes computational burdens. Further, aggregating energy-use data over all days of twelve weeks increases the group similarity compared to less aggregated data (e.g., weekdays of twelve weeks). The proposed categorization framework enables interveners to create personalized and scalable normative feedback messages. 

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3. Resilient and Sustainable Urban and Energy Systems

   https://doi.org/10.1061/9780784482445.062  

   Song, K. ; Anderson, K. ; Lee, S. ; Raimi, K. T. ; Hart, P. S. ( June 2019 , "Exploring the Effect of Data Granularity on Personalized Normative Messaging Interventions for Reducing Household Energy Consumption)

   Normative messaging interventions have proven to be a cost-effective strategy for promoting pro-environmental behaviors. The effectiveness of normative messages is partially determined by how personally relevant the comparison groups are as well as the lag of feedback. Using readily available energy use data has created opportunities to generate highly personalized reference groups based on households’ behavioral patterns. Unfortunately, it is not well understood how data granularity (e.g., minute, hour) affects the performance of behavioral reference group categorization. This is important because different levels of data granularity can produce conflicting results in terms of group similarity and vary in computational time. Therefore, this research aims to evaluate the performance of clustering methods across different levels of temporal granularity of energy use data. A clustering analysis is conducted using one-year of energy use data from 3,000 households in Holland, Michigan. The clustering results show that behavioral reference groups become the most similar when representing households’ energy use behaviors at a six-hour interval. Computationally, less granular data (i.e., six and twelve hours) takes less time than highly granular data which increases exponentially with more households. Considering the enormous scale that normative messaging interventions need to be applied at, using less granular data (six-hour intervals) will permit interveners to maximize the effectiveness of highly personalized normative feedback messages while minimizing computation burdens. 

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4. Ingroup love, outgroup hate, and the gateway group effect: Comparing the direct and indirect impact of dual versus single identification

   https://doi.org/10.1371/journal.pone.0287631  

   Levy, Aharon ; Galinsky, Adam ; Nguyen, Christine Q. ; Saguy, Tamar ; Ikizer, Elif G. ; Dovidio, John F. ( August 2023 , PLOS ONE)

   Windmann, Sabine (Ed.)

   Decades of research in social identity have shown that people instinctively hold positive attitudes towards ingroup members and negative attitudes towards outgroup members. However, it remains unclear how people respond to individuals explicitly identified with both one’s ingroup and outgroup. We propose that when people are exposed to dual-identified individuals and groups (e.g., Muslim-Americans explicitly identifying with both their Muslim and American identities), intergroup attitudes will improve, driven more by the ingroup component (American), despite the presence of the outgroup component (Muslim). Moreover, we suggest exposure to dual-identification can also improve attitudes toward the broader outgroup (Muslims more generally), a phenomenon called the gateway-group effect. To test these hypotheses, we created a new measure of dual-identification and conducted three studies involving both Muslim-Americans and Mexican-Americans. Results confirmed that exposure to explicitly dual-identified groups improved attitudes towards the dual-identified group (e.g., Mexican-Americans) as well as toward the respective outgroup (e.g., Mexicans).

    

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5. Characterizing Student Identities in Engineering: Attitudinal Profiles of Engineering Majors

   Benson, L. ; Potvin, G. ; Kirn, A. ; Godwin, A. ; Doyle, J. ; Rohde, J.A. ; Verdín, D. ; Boone, H. ( June 2017 , ASEE annual conference & exposition)

   https://peer.asee.org/27950 This paper presents results of work completed on our project, Intersectionality of Non-normative Identities in the Cultures of Engineering (InIce). The overarching focus of this project is on how students who hold non-normative identities position themselves, grow through their education, and navigate the cultures of engineering they experience in college. Our goal is to investigate ways to engage students who hold non-normative identities to become more active and lifelong participants in engineering disciplines. Our work is proceeding in three phases: 1) Identify, through a quantitative instrument, the attitudinal profiles of normative and non-normative students in engineering; 2) Characterize students’ normative and non-normative identities through in-depth interviews and analysis of differences between students with normative and non-normative identities in engineering; and 3) Drawing from our findings, develop a workshop and set of courses to incorporate diversity topics into engineering programs to enhance the culture of engineering to be more responsive towards, and inclusive of, a diverse range of student identities. We have completed the first phase of the project in which we quantitatively measured and characterized student groups with normative and non-normative identities in engineering. Our definitions of normative and non-normative for this project are developed through Topological Data Analysis (TDA) of a set of multi-institution survey data (n = 2916). TDA allows identification of groups without imposing a priori hypotheses on how the attitudes of students may group together (nor how they may distinguish between demographic groups). This approach allows the underlying structure of the data to emerge rather than imposing pre-defined definitions of normative attitudes or identities. Our TDA results revealed one group that contains a relatively large number of students (the “normative” group) and a total of seven other distinct, but relatively populated, groups (the “non-normative” groups). We have compiled a summary of the most salient attitudinal constructs in terms of characterizing and distinguishing between all these groups including: motivation (value, goal orientation, future time perspective), engineering and physics identities (performance/competence and recognition beliefs for each), personality traits (neuroticism, extraversion, belongingness) and grit (consistency of interest). We are currently in Phase 2 of our study in which we are conducting a series of qualitative, longitudinal interviews with students selected from normative and non-normative groups to understand how they navigate their engineering experiences and define their educational trajectories over the first two years of college. This data will be deductively analyzed based on our existing attitudinal frameworks as well as inductively coded for emerging themes on how students feel belongingness within engineering culture. This project promises to move traditional measures of demographic data beyond socially constructed perceptions of others and allows for the representation of student diversity from the perspective of each participant. This more accurate reflection of diversity provides novel insight into the experiences of students who might otherwise be ignored or unjustifiably lumped in with other students with whom they share some demographic indicator and how residing at the intersection of multiple measures of diversity can influence students’ experiences in engineering culture. 

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