Green Building, Green Behavior? An Analysis of Building Characteristics that Support Environmentally Responsible Behaviors

This study examines the environmentally responsible behaviors (ERBs) of undergraduates ( n = 575). ERBs were measured in an online survey and the influence of situational context on behavior was explored at two scales: 1) green versus non-green building and 2) building characteristics. The Positive Sustainable Built Environments model was used to analyze three building characteristics: Prime, Permit, and Invite. Prime refers to characteristics that prepare occupants to adopt ERBs via communicating a sustainable ethos or restoring attentional capacity (e.g., use of natural materials and views to nature). Permit refers to features that allow occupants to conserve resources (e.g., operable light switches). Invite pertains to features that explicitly encourage ERBs (e.g., signage prompting occupants to turn off lights). Regression results demonstrated that living in a green building had no significant impact on ERBs. However, the Prime and Invite building characteristics significantly predicted improved Energy, Water, and Materials conservation. Results yield implications for designers seeking to create sustainable buildings that promote ERBs.

Sets of Environmentally Responsible Behaviors Among Residents of New Jersey

There are many challenges facing humanity and the degradation of resources and natural spaces. One avenue for approaching these issues is through attempting to change human behaviors. Drawing on Stern’s Value-Behavior-Norm theory, we sought out to test the idea that these Environmentally Responsible Behaviors (ERBs) fell into well-established sets. In this research, we developed questionnaire that surveyed 290 residents on Central New Jersey. The questions included demographic information, as well as items gauging the type and extent of respondents’ engagement in ERBs. We used generalized canonical correlation analysis in order to sort the types of behaviors that respondents engaged in to distinct groups. The ERBs sorted into 3 canonical correlation variables that account for 53.7% of the variation in the data. Twenty-five ERBs that loaded highly on at least one of the three canonical correlation variables. The ERBs sorted into 3 groups that did not follow the expected pattern based on Stern’s research. Instead into three other groups suggesting alternative ways of conceptualizing pro-environmental behavior in this population. We found that ERBs tended to sort into those related to energy expenditures, identity as an environmentalist, and impact-oriented ERBs. This research helps to foster a greater understanding of individuals’ engagement in Environmentally Responsible Behaviors.

Framing and Feeling Fuel Environmentally Responsible Behaviors of Black Residents in the United States

Scholars have long investigated factors contributing to enactment of environmentally responsible behaviors (ERBs), largely among white populations. Although research has debunked the myth that black people express less environmental concern, few studies examine what influences their pro-environmental behavior. We focus on how the cognitively oriented cultural frames of environmentalism and environmental justice combine with overlooked emotions to shape ERBs reported by a nationally representative sample of 988 black residents in the United States. Results indicate that the environmentalism frame, indicated by environmental identity but not attitudes, enhances all the behaviors examined: general conservation, cost-saving conservation, recycling, and advocacy. Effects of environmental justice, however, are more limited. Passion for environmental protection likewise positively affects all pro-environmental actions, and moral outrage over the condition of the environment exerts strong positive effects on conservation and advocacy. In highlighting the role of emotions in conjunction with cultural frames on ERBs, new avenues for research emerge.

Can a Green School Building Teach? A Pre- and Post-Occupancy Evaluation of a Teaching Green School Building

Amid increasing interests in social metrics within green buildings, this work focuses on buildings designed to enhance environmental education, here called “Teaching Green Buildings” (TGBs). This study examines one school building at three points in time before and after the move into a new construction TGB. Middle school students here and at a local, comparison Non-Green School ( N = 264) took a survey measuring outcomes of green building knowledge (GBK) and environmentally responsible behaviors (ERBs). Regression results showed that GBK is significantly higher for students in the Green School compared with the Non-Green School, but is not increasing over time for students at the Green School. No differences were detected in ERBs across schools or time, and it was found that school practices, more than the green building itself, were pivotal in student choices to conduct ERBs at school.

An Investigation of Links between Environmentally Responsible Behaviors and Built and Natural Features of Landscape in Central New Jersey

Responses from Central New Jersey residents (n = 290) to nine survey items about pro-environmental behaviors were analyzed for their connection to survey respondents’ local built and natural landscape characteristics. These nine survey items were of interest due to their clustering in three groups in earlier dimension reduction analysis. Nine logistic regression models (one for each of these items) were built using a suite of built and natural features of landscape at the municipal level—including land use, population density, and access to parks. The logistic regression models using the landscape variables failed to provide effective explanations of engagement in pro-environmental behavior. In total, only ten landscape feature variables—out of a possible thirty-eight -were used in any of the most effective models. The logistic regression model of proper appliance disposal performed best and could correctly classify responses of whether respondents had disposed of an appliance correctly 84% of the time. The rest of the models were of little use. This suggests that there may not be a connection between these built and natural landscape features and these behaviors, or that the study did not look at location at a level that was granular enough to detect any patterns.