Abstract

The government’s aim of one million environmentally friendly electric vehicles (EVs) on German roads by 2020 has been withdrawn due to the low demand for such vehicles. The rea- sons are different and range from unfavorable price-performance ratios to the actual battery of EVs itself. Against this background, successful industrial and policy measures are necessary in order to offer customer-oriented solutions for EVs in Germany. This dissertation contributes to the evaluation of battery electric vehicles (BEVs) from a consumer-oriented total cost of ownership (TCOC) and a behavioral decision making (vehicle choice) perspective, using three re- search approaches to derive potential industrial and policy measures for Germany. These three approaches are described below in detail and are interconnected as follows: (1) modeling of the TCOC followed by (2) analyzing of the TCOC information disclosure under a risk situation and (3) optimizing of the TCOC using an optimal cost package for BEVs. The first research paper to be published formed the basis for this cumulative dissertation. In the paper, a TCOC model was developed to identify the profitability, including potential cost risks, of selected passenger vehicles. This approach was achieved by extending existing TCOC models with often ignored ownership costs, such as the resale value for the battery second use and second life. We identified the profitability for the ten most frequently registered BEVs in Germany in 2014 and compared them with similar internal combustion engine vehicles (ICEVs) fueled with gasoline (ICEV-SI) or diesel (ICEV-CI). Here, we also considered full hybrid electric vehicles (HEVs), as they play an important role in the transformation phase between BEVs and ICEVs. We analyzed the results under various assumptions, including a Monte Carlo simulation with 500,000 draws per simulation for 2016 and 2021. Results show that four BEVs – BMWi3, TeslaS, Mercedes B250e, and TeslaX – and five HEVs – Honda Jazz, Toyota Auris, LexusIS, Mercedes E300h, and Mercedes S400h – are profitable despite cost risks in the elec- tricity/fuel and battery price compared to their equivalent ICEVs in 2016. The purchase-based incentive in the form of a subsidy shows a positive effect on the actual TCOC but not for all selected BEVs. The second research paper analyzed two potential use-based incentive measures in the form of TCOC information disclosure and a driving ban on ICEVs with regard to the purchasing decision for a BEV in order to determine the effectiveness of both influential factors. This approach was achieved by asking 379 potential consumers via an online experiment, including a post-experimental questionnaire throughout Germany. We analyzed the choice decision for a BEV by using a logistic regression with a linear generalized estimating equation (GEE) method. Results show that these two potential use-based incentives can have a positive impact on the choice decision for BEVs, as the threat of a driving ban on ICEVs and the TCOC information weighted with the TCOC value difference have a significant positive effect on the decision of whether to buy a BEV (p < 0.001). In addition, control variables with costs (purchase price, range), hedonic benefits (awareness, experience), and some demographics (education, annual mileage) show a significant impact on the choice decision for a BEV. Moreover, the three well known BEV attributes – range, infrastructure, and price – remain a problem. In a further step, we calculated the planned TCOC to make a clear statement about the financial consequences for ICEVs. The risk-related policy measure also has a positive impact on the planned TCOC, as the already profitable four BEVs become even more favorable. With the subsidy, in total the five BEVs (same as with actual TCOC) are favored over their ICEVs. The last research paper analyzed potential cost-benefit improvements for BEVs with regard to the purchasing decision in order to identify the optimum price-performance ratio when calculating the target TCOC. This approach was achieved by asking 86 early adopters via a discrete choice experiment, including a questionnaire throughout Germany. We analyzed the cost-benefit related attributes with regard to the choice decision for a BEV by using a mixed logit (MXL) regression. Results show that the selected vehicle-based attributes can have a significant impact on BEVs choice, as the monetary costs (initial purchasing price (IPP), battery payment option (BC), yearly maintenance and repair costs (MR) and electricity costs per 100 km for fast charging (EC): p < 0.001) have a significantly negative impact and non-monetary costs (range (R): p < 0.001) have a significantly positive impact on the choice decision for a BEV. On this basis, we determined the optimal cost package comprising a 15 % lower MR and 10 % lower IPP, including a battery purchase with an actual consumption of 17 kilowatt hour (kWh) and an actual range of 700 km. Following that, we calculated the target TCOC to identify the optimum price-performance ratio for BEVs. The identified cost-benefit improvements lead to roughly ten percent saving potential of specific BEVs. The already profitable four BEVs (same as with actual TCOC) become even more economical. Besides the Renault Zoe Z.E., with the subsidy the German key vehicle segment (medium segment) becomes profitable for BEVs (VW e-Golf and Nissan Leaf) over ICEVs. Consequently, determined cost-benefit improvements seem to be successful, as the results can have an essential impact on the German mass-market. In summary, we established with our overall research approach that all selected BEV segments, with the exception of the mini vehicle segment (e.g. Smart), can become profitable. Consequently, this dissertation provides valuable insights for research and for practice (industry and government) to enable the further development of BEVs in Germany.

Abstract

Providing a sufficiently appropriate route environment is crucial to ensuring fair and safe biking, thus encouraging cycling as a sustainable mode of transport. At the same time, better understanding of cyclists&rsquo preferences regarding the features of their routes and their infrastructure requirements is fundamental to evaluating improvement of the current infrastructure or the development of new infrastructure. The present study has two objectives. The first is to investigate cyclists&rsquo route preferences by means of a choice experiment based on a stated preference survey. Subsequently, the second objective is to compare cyclist preferences in two countries with different cycling characteristics (both in infrastructure as well as cyclists&rsquo behavior). For this purpose, a graphical online stated preferences survey was conducted in Greece and Germany. Within the framework of statistical analyses, multinomial mixed logit discrete choice models were developed that allow us to quantify the trade-offs of interest, while distinguishing between the preferences of different user groups. In addition, user requirements in Greece, as a country with a low cycling share and very little dedicated bike infrastructure, were compared to the requirements in Germany, where cycling is popular and the infrastructure is well developed. The results over the whole sample indicate that subgroups value infrastructure differently according to their specific needs. When looking at country specifics, users from Greece are significantly more willing to accept longer travel times in return for higher-quality facilities. The utility of low speed limits in mixed traffic is also different. In Germany, low speed limits offset the disturbance caused by motorized traffic, but in Greece they do not. Consequently, the results help to asses which types of infrastructure are most sustainable from a user perspective and help to set priorities when the aim is to adapt the road infrastructure efficiently in a stable strategy. Document type: Article