Professor Helveston is interested in understanding the factors that shape technological change, with a particular focus on transitioning to more sustainable and energy-saving technologies. Within this broader category, he studies consumer preferences and market demand for new technologies as well as relationships between innovation, industry structure, and technology policy. He has explored these themes in the context of China’s rapidly developing electric vehicle industry. He applies an interdisciplinary approach to research, with expertise in discrete choice modeling and conjoint analysis as well as interview-based case studies.
Professor Helveston has written the logitr package to support flexible estimation of multinomial logit models with preference space and willingness-to-pay (WTP) space utility specifications. The package supports homogeneous multinomial logit (MNL) and heterogeneous mixed logit (MXL) models, including support for normal and log-normal parameter distributions. Since MXL models and models with WTP space utility specifications are non-convex, an option is included to run a multi-start optimization loop with random starting points in each iteration. The package also includes a simulation function to estimate the expected market shares of a set of alternatives based on an estimated model.