Integrated Modelling of Consumer Choice, Producer Decisions, and Policy Design in the Automotive Market

In this thesis, I explored and investigated consumer choice modeling, optimal engineering design, and technology-specific policy simulation in three studies. In the first study (Chapter 2), “On the Implications of Using Composite Vehicles in Choice Model Prediction,” I investigated the issues of choice set representation in choice modeling methodology. I derived composite correction factors for logit-class models that can help reconcile differences in modeling results in composite-level and elemental-level models. I then demonstrated cases where correction factors may be useful. This contributed to an improved understanding of how competitor representation affects choice predictions. In the second study (Chapter 3), “Implications of Competitor Representation on Optimal Engineering Design ,” I investigated profit-maximizing engineering design models that integrate choice models for demand. Specifically, I studied how competitor representation can affect the trade-off between cost and benefit of design change. I derived a closed-form expression for the marginal cost and benefit relationship for the level of an attribute under optimal design assuming a latent-class or mixed logit (random-coefficients logit) demand model. I used this to characterize the impact of competitor representation in a case study of optimal automotive design. In the third study (Chapter 4), “The dynamic costs and benefits of a technology-forcing policy nested in a broader performance standard: the case of ZEV and CAFE,” I addressed the complexity of dynamic effects and nested policy interaction in automotive energy and environmental policy. I focus on two policies: Zero-Emission Vehicle (ZEV) mandates and Corporate Average Fuel Economy / Greenhouse Gas (CAFE/GHG) standards. I simulated consumer, producer, and government decisions in a model with explicit technological change, dynamic learning-by-doing spillover effects, policy interaction effects, and endogenous fleet standard setting via cost-benefit analysis. I demonstrated the potential impacts of ZEV mandates: potential net social benefit or net social cost, depending on key factors and parameters. I identified these key factors and quantified the trade-offs that may inform ZEV and CAFE/GHG fleet standard policy-making.