CAREER: Advanced demand estimators for energy-efficiency in personal transportation

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1253475 (Daziano). The long-term career goal of the PI is to contribute significantly to both research and education in decision-making analysis to better understand consumer behavioral response to energy-efficient engineered technologies. In pursuit of this goal, the CAREER research objective is to exploit microeconometric discrete choice theory to better inform engineering of low emission vehicles. Aiming at the long-term goal of preparing engineers to create technically sound solutions that society is willing to adopt, the CAREER educational objective is to provide future engineers with a multidisciplinary vision of engineering decision-making informed by consumer demand. The research plan of this proposal seeks to: 1) generate new demand estimators of the structural parameters of a large-scale simultaneous-equations discrete choice system with heterogeneous consumers and decision rules for energy-efficient automobile technologies, 2) derive nonparametric Bayesian estimators of willingness-to-pay and consumer-surplus measures that account for behavioral uncertainties, 3) formulate a systematic Bayesian cost-benefit analysis of integrative counterfactual scenarios of low emission vehicle deployment for informing policy, technology, engineering, and infrastructure planning decisions. The three research tasks will be validated and tested using data on consumer adoption of low-emission vehicles from different sources. The education plan builds on and will contribute to the planned research, and comprises four steps: 1) collaboration with sustainability research centers at Cornell to foster multidisciplinary research and learning experiences for college students with different backgrounds but with common interests in energy sustainability, 2) extensive outreach on sustainable travel behavior to educate the public and to motivate socially-diverse future generations to pursue engineering careers, 3) enhancement of the curriculum at the senior undergraduate and graduate levels through implementing and continuously improving three courses aimed at integrating demand-side dynamics into engineering, and 4) mentoring graduate students at the PhD and MEng levels. The main research outcome will be a solution for the joint estimation problem of a complex system of structural equations based on random utility maximization that can be applied to formulate demand models for energy efficiency. Unsolved econometric challenges will be addressed for deriving flexible Bayesian parametric and nonparametric simulation-aided inference for identified reduced parameters. The simultaneous equations demand model will account for interactions of consumer response with the economic, environmental, energy, and transportation systems. The demand model will also incorporate social symbolic values such as pro-environmental preferences, energy security concerns, as well as consumers' awareness of emerging sustainable technologies and their readiness to adopt them. To represent choice among continuously evolving technologies, the demand system will also account for energy diversification, choice dynamics, and measurement of qualitative attributes. Access to data will be facilitated through collaborations with Ford Motors, UC Berkeley, the Centre for European Economic Research, and the University of Rome 3. The technical results will contribute to fields where decision-making under uncertainty is needed. Decision-making analysis tools derived from the demand estimators will serve to evaluate not only pricing and investment strategies for advanced energy-efficient propulsion technologies and infrastructure, but also public policies and incentives to best promote industry conversion to and consumer acceptance of low-emission vehicles. The results will be significant not only for US policymakers and transportation planners, but also for informing auto manufacturers to improve how industry engineers vehicles. Knowledge transfer will be achieved through multidisciplinary collaboration within and beyond Cornell, including international partnerships. Educational initiatives will be focused on disseminating the relevance of consumer response for successful engineering solutions. Cornell Engineering's Teaching Excellence Institute will assist in creating innovative active choice experiments using personal-response systems. Publicly discussed screenings of documentaries about electric vehicles and yearly participation at the NYS fair will support outreach plans on sustainable travel behavior to youth and college freshmen, with a special focus on underrepresented groups.