Conference Agenda

The transition to electric mobility plays a crucial role in achieving Germany’s ambitious climate goals, with the Vehicle-to-Grid (V2G) technology offering a promising solution for stabilizing the energy grid and enhancing the integration of renewable energy. This study empirically examines individuals’ preferences for V2G energy tariffs using a stated choice experiment conducted with 6,198 citizens in Germany. Respondents chose between three different V2G tariffs and an opt-out choice option, with tariffs varying in attributes such as minimum monthly plug-in hours, fixed and variable remuneration, and guaranteed minimum range. Using mixed logit models estimated in willingness-to-accept (WTA) space, the results reveal a strong preference for the opt-out option, suggesting general skepticism toward V2G. However, respondents exhibit clear trade-offs: They are willing to forgo €2.35 in fixed remuneration for an additional kilometer of guaranteed range, but require €1.32 in compensation for an extra hour of minimum plug-in time. Our empirical analysis also highlights the presence of strong heterogeneity in preferences based on individual characteristics. Higher annual mileage and being female increase the likelihood of opting out, while owning a wallbox or having a larger household size reduces it. Additionally, wallbox owners are more flexible with plug-in time but demand higher compensation for reduced range, whereas PV system owners show the opposite pattern. These findings provide valuable insights for policymakers aiming to design effective and widely accepted V2G tariffs, emphasizing the importance of financial incentives, flexible tariff structures, and targeted awareness campaigns to foster participation in V2G programs.

Smart charging (also known as V1G) programs adjust the time of day of electric vehicle charging to reduce congestion in the grid, reduce the cost of electricity and/or maximize the use of renewable energy sources. As General Motors (GM) partners with electric utilities to design and implement these programs, it is important to understand customers' preferences and motivations for enrolling. GM executed a conjoint study to quantify how customers make trade-offs among program characteristics and incentives when deciding whether to enroll in a V1G program. We fit several different discrete choice models to the survey data, including benchmark models (conditional logit and mixed logit) and hybrid choice models (latent class logit and integrated choice and latent variable models). Each model provides different behavioral insights and supports different use cases. The latent variable models reveal that environmental concern is a key latent factor for customers, and a useful dimension for differentiating customers. These findings enable GM to implement targeted marketing efforts that promote the environmental benefits of V1G programs to the customer groups who are most likely to be environmentally conscious.

As part of the energy transition, the electricity grid often needs to be reinforced. These investments are not only associated with public benefits but also give rise to private concerns such as the impact on property values. However, it is challenging to determine the value loss associated with an HV-line crossing a real estate property as other characteristics such as age, size and location of the property also matter. In the Belgian context, compensation for property value losses caused by the public utility easement is legally required. Only the amount of compensation is subject to debate. Thus, the research question we address in this study is how the compensation should be determined and how this should depend on property characteristics. To provide a market and a citizen perspective, we assess the points of view of real estate experts and Belgian citizens, which we then compare with the current compensation scheme.

This pioneering study employs stated preference methods, specifically discrete choice experiments, to evaluate public preferences for the protection of diverse cultural heritage assets in Victoria, Australia. By analyzing responses to a series of hypothetical policy scenarios, we uncover the economic values the public assigns to various heritage attributes, including condition, accessibility, and protection measures. Our findings emphasize the importance of both use and non-use values in shaping willingness to pay for heritage conservation. These insights are critical for developing more effective, community-aligned heritage policies that reflect the public's valuation of cultural heritage. This research marks a significant advancement in the application of discrete choice experiments for general heritage valuation, offering a robust framework for future studies and policy development in cultural heritage preservation.