This dissertation presents two essays that explore the antecedents of consumer decision-making when choices or behaviors have significant environmental consequences. The first essay involves theoretical development and experimental testing of a conceptual model describing the process by which a car-buyer evaluates the choice between an electric vehicle (EV) and a gasoline vehicle, while the second essay consists of empirical analysis of a large panel dataset of household-level 15-minute interval electricity consumption data to identify the drivers of different behavioral response patterns to electric utility requests for energy conservation on hot summer afternoons.
The first essay is motivated by the observation that increased consumer adoption of battery-powered EVs is important for commercial and environmental reasons, but EV adoption is currently inhibited by both an up-front price disadvantage and the inconveniences associated with battery recharging. The research presented in the first essay leverages the Theory of Reasoned Action as well as the literature on identity signaling to develop a model on how consumers with interests in the environmental and/or technological implications of EV ownership evaluate the potential purchase of an EV versus a conventional automobile. The model generates ten pairs of hypotheses that are tested via estimation of a structural equation model using data from three online experiments. Bayesian pooling of the three sets of estimated path analysis coefficients finds considerable support for the conceptual model. These pooled results show that EV ownership signals the owner's concern about both environmental protection and technology advancement, but the effect of the environmental signal on EV purchase likelihood is positive whereas the effect of the technology signal on EV purchase likelihood is negative. Moreover, in addition to lowering EV purchase likelihood via a direct effect, the perceived inconveniences associated with EV ownership (e.g., needs for battery charging) offset the negative effect of technology signaling on EV purchase likelihood, while the corresponding interaction of inconvenience with environmental signaling value was found to be not significant. Meanwhile, a larger EV price premium had a direct negative effect on EV purchase likelihood but did not moderate the effects of either technology signaling value or environmental signaling value on EV purchase likelihood. Among other findings, specific knowledge about how EVs affect technological advancement has a direct positive influence on EV purchase likelihood. However, all downstream effects of specific knowledge about EVs effects on environmental protection are mediated by perceptions of EV effectiveness in benefitting the environment.
Meanwhile, the second essay investigates consumer behavior concerning household electricity consumption. Utilities use demand response (DR) programs to induce customers to reduce electricity consumption during selected hot summer afternoons when power generation supplies may be challenged to satisfy regional demand levels. The research presented in the second essay leverages panel data on electricity consumption from households in a community where an experimental pro-social DR program was conducted to explore drivers of household responses to utility requests to voluntarily reduce electricity consumption. Analysis of the panel data shows that, on average, households with solar rooftops respond differently to utility DR notifications than non-solar households: solar households reduce electricity consumption as requested by the utility, whereas non-solar households receiving the same request actually increase electricity consumption. However, although solar households respond favorably to DR notification, they also consume significantly more electricity than non-solar households during most hours. These empirical results – greater responsiveness to DR notifications, but otherwise higher levels of electricity consumption – beg reconciliation and explanation. An experimental research study is proposed for a future examination of alternative psychological explanations for the observed differences in behavioral responses between solar and non-solar households. / Doctor of Philosophy / This dissertation presents two essays that explore how and why individuals make decisions with environmental consequences. The first essay investigates how and why individuals choose to purchase a higher-cost big-ticket durable good (i.e., an electric vehicle) that results in substantially lower air emissions over the lifetime of the product, while the second essay investigates how and why individuals make environmentally-friendly behavioral decisions (i.e., conserving electricity on a hot summer afternoon) when the stakes are modest and transitory.
The first essay discusses the findings from three experiments in which on-line survey respondents were asked to imagine being in the market to buy a new car and then indicate how likely they would buy an electric vehicle (EV) rather than an otherwise identical gasoline automobile. Before indicating EV purchase likelihood, participants were informed to assume different levels of price premium and inconvenience (e.g., associated with battery recharging) resulting from EV ownership. Participants were also asked a series of questions to measure their attitudes about environmental protection and technology advancement, as well as the ability of EVs to help both of those dimensions of social progress. Of particular interest, participants were asked how much driving an EV sends a public signal of the owner's commitment to environmental and technology improvement. Among other findings, statistical analysis of the data collected from these experiments indicates that EV ownership sends a strong signal of the owner's commitment to both environmental protection and technology advancement. However, the environmental signal of EV ownership positively influences EV purchase likelihood, whereas the technology signal of EV ownership negatively influences EV purchase likelihood. Of further interest, this negative relationship between technology signaling value and EV purchase likelihood is offset by the perceived inconveniences associated with EV ownership (i.e., battery charging), such that the negative effect of technology signaling on EV purchase likelihood can be overcome if the prospective EV buyer also believes EV ownership is highly burdensome.
The second essay presents the findings from analysis of 15-minute interval electricity consumption data during the summer of 2021 from 307 households in a master-planned community that was the site of an experimental utility demand response (DR) program. In this community, at 2 pm on seven particularly hot weekday afternoons that summer, the local electric utility issued a DR text message to a randomly-selected subset of households, asking them to conserve energy between 4 and 8 pm in order to help alleviate tight supplies of power generation. Any difference in average electricity consumption patterns between households that were asked to reduce electricity consumption (i.e., "treatment" households) and those that were not asked (i.e., "control" households) can be considered a "DR effect": a change in behavior induced by the utility's request to reduce electricity consumption. While initial analysis of the electricity consumption data revealed no DR effects, subsequent identification and segmentation of solar households (I.e., households with rooftop solar electricity production systems) from non-solar households enabled discovery of statistically-significant DR effects for both solar and non-solar households. Of particular interest, while solar households responded to the utility's DR text message in the intended manner by reducing electricity consumption, non-solar households responded by increasing electricity consumption instead. Experimental research is planned to investigate why solar households and non-solar households respond so differently to the same message from the utility.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/119502 |
| Date | 25 June 2024 |
| Creators | Stuebi, Richard Theodore |
| Contributors | Business, Chakravarti, Dipankar, Herr, Paul Michael, Staelin, Richard, Jiang, Juncai, Bagchi, Rajesh |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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