In recent years, sustainable mobility policy analysis has used Hybrid Choice Models (HCM) by incorporating latent variables in the mode choice models. However, the impact on policy analysis outcomes has not yet been determined with certainty. This paper aims to measure the effect of HCM on sustainable mobility policy analysis compared to traditional models without latent variables. To this end, we performed mode choice research in the city of Santander, Spain. We identified two latent variables—Safety and Comfort—and incorporated them as explanatory variables in the HCM. Later, we conducted a sensitivity study for sustainable mobility policy analysis by simulating different policy scenarios. We found that the HCM amplified the impact of sustainable mobility policies on the modal shares, and provided an excessive reaction in the individuals’ travel behavior. Thus, the HCM overrated the impact of sustainable mobility policies on the modal switch. Likewise, for all of the mode choice models, policies that promoted public transportation were more effective in increasing bus modal shares than those that penalized private vehicles. In short, we concluded that sustainable mobility policy analysis should use HCM prudently, and should not set them as the best models beforehand.

Best value has been used for more than two decades in the procurement of design-build highway projects in the United States. The question of whether this type of procurement selects best-value proposers has been raised by several authors. Considering procurement data from 128 projects procured between 2000 and 2022, this chapter aims to provide insights on the impact that different types of best-value award algorithms have in the selection of design-builders as well as answers to the question of whether or not best-value procurement is actually selecting the best-value proposers. Ultimately, the chapter will reflect on lessons learned that might help highway administrators plan to use or use the best value in procuring highway projects.