Panel:
Consumer Behavior and Sustainability Policy: Understanding Decision-Making and Response to Policy Changes
(Natural Resource, Energy, and Environmental Policy)
*Names in bold indicate Presenter
Many policy interventions either directly or indirectly impact consumers’ decision-making. It is critical for policy makers to understand consumer behaviors, in order to design optimal policy interventions and evaluate program effectiveness. Policy makers may choose to address externalities or behavioral failures via promotion of certain new technologies or practices. In these cases, policy makers need to understand behavioral factors in order to efficiently promote the adoption of these technologies and practices. This includes identifying factors influencing consumers’ decisions, understanding consumer attitudes towards new technologies or programs, and detecting behavioral failures in a timely manner. In terms of consumer welfare, even when consumers are fully rational and adjust their behaviors to mitigate the impact from any negative externalities, such rational behavioral changes can create unintended consequences that increase negative externalities. Policy makers need to be aware of the magnitudes of such unintended consequences. Lastly, after policy interventions are implemented, rigorous methods are needed to conduct unbiased evaluation of the response to policy changes. Recent development of big data opportunities makes such unbiased evaluation more feasible without conducting expensive and time-consuming randomized control trials. This panel addresses these crucial roles of consumer behavior in public policy analysis in the context of sustainability policy.
Our panel fits the theme of the 2019 APPAM conference and draws diverse perspectives and methods from several different disciplines, including environmental economics, computational science and engineering, consumer research, policy analysis, and big data analytics. Our panel participants also have diverse backgrounds including scholars from academia as well as practitioners from a government agency (Department of Energy) and an electric utility company.
The first paper identifies key factors influencing consumers’ adoption of battery electric vehicles (BEVs), a key technology to address climate change. Survey data collected from a sample of over 1000 potential vehicle purchasers are used to understand the extent to which daily and occasional perceived mobility necessity limits BEV adoption intentions and how such influence interacts with environmentalist status. The second paper analyzes consumer behavioral failures and attitudes towards BEV charging stations. Real time large-scale social data from a popular BEV driver app and machine learning algorithms to process consumer reviews are used to analyze the quality of charging services in the emerging BEV charging infrastructure in the United States. The third paper examines unintended consequences of consumers’ avoidance behaviors in response to air pollution; these avoidance behaviors can generate further co-damages from air pollution. Using customer-level daily electricity data in Arizona, results show that the interactions of consumer avoidance behaviors, clean technology performance, and particulate air pollution generate extra-damage due to increased electricity consumption and reduced solar panel electricity generation. The last paper evaluates consumers’ response to energy conservation nudging interventions. Monthly billing data of 3000 households in Florida are used to estimate the impact of actively using a messaging package about electricity conservation behavior. Results show that consumers respond to nudging messages on energy saving tips in different ways, based on their social economic characteristics.
