Business Information Through Choice-Based Conjoint Analysis: The Case of Electric Vehicle Home Charging

Abstract

Information and data fuel businesses and markets; thus, provision, generation, and interpretation of information and data are crucial to support managerial decisions. We demonstrate the generation of information through choice-based conjoint analysis using the example of electric vehicle charging. There are several alternatives for electric vehicle charging, with home charging being the main charging point for most of today’s electric and plug-in hybrid electric vehicles. Therefore, a large number of consumers consider home charging as mandatory when buying a car. Before blindly investing in the construction of charging stations close to citizens’ homes, decision makers (e.g., policy makers) need to learn about the impact of possible measures. This paper examines whether performance improvements in alternative vehicles (e.g., in terms of range or charging time) or governmental incentives (e.g., price subsidies) could compensate consumers for not having home charging stations. Findings reveal that, in general, both electric and plug-in hybrid electric vehicles profit from the construction of home charging stations, but its perceived benefit decreases continuously with faster charging times at public charging stations. However, at the present time, when the technological progress of electric vehicles remains low, monetary subsidies for environmentally friendly vehicles appear to mainly support only sales of plug-in hybrid electric vehicles.