Some pay much but many don’t: Vehicle TCO imputation in travel surveys

Eisenmann, Christine; Kuhnimhof, Tobias

doi:10.1016/j.trpro.2018.10.056

Cited by 8 publications

(5 citation statements)

References 3 publications

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“…Dividing this by the number of cars with private registration in Germany in 2016 (41.183 million: (Kraftfahrt-Bundesamt 2017)) gave us the expenditure per vehicle covering these cost items (€231/month). To complete the picture, we added expenditures for vehicle tax (€12/month) and insurance (€36/month) per vehicle as measured in the 2013 German income and expenditure survey (Eisenmann and Kuhnimhof 2018). In this way we arrived at €279/month per vehicle as our average.…”

Section: Discussionmentioning

confidence: 99%

“…The MOP-FCOR questionnaire elicits vehicle details such as make, model, year of construction, engine size, propulsion technology and type of fuel. In one of our previous studies (Eisenmann and Kuhnimhof 2018), we used this information in combination with the vehicle mileage to impute vehicle costs, broken down by cost component (depreciation, tax, insurance, fuel and other). This imputation procedure was carried out for the MOP-FCOR vehicle samples from 2015 and 2016, which totalled 2977 cars.…”

Section: Data: Travel Survey Data With Imputed Vehicle Cost Informationmentioning

confidence: 99%

“…The procedure was validated against results from the German income and expenditure survey and found to deliver plausible results. For details see (Eisenmann and Kuhnimhof 2018).…”

Section: Data: Travel Survey Data With Imputed Vehicle Cost Informationmentioning

confidence: 99%

“…Andor et al also list surprisingly high costs for insurance and tax. We believe that this is an artefact of their methodology of imputing insurance costs on the basis of the ADAC database, which fails to account for insurance discounts despite the fact that they are in actual fact very common (for a detailed discussion of this, see (Eisenmann and Kuhnimhof 2018)).…”

Section: Costs Of Running Private Carsmentioning

confidence: 99%

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Mobility-on-demand pricing versus private vehicle TCO: how cost structures hinder the dethroning of the car

Kuhnimhof

Eisenmann

2021

Transportation

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This study uses a unique dataset on the cost of motoring in Germany to analyse cost competitiveness of emerging mobility-on-demand (MOD) services. Previous studies have focused on comparing current and projected MOD prices with the average cost of private motoring. This study quantifies which proportion of private car travel would actually turn out to be costlier than MOD given that MOD costs drop below certain levels relative to the cost of private motoring. In this context, not the average but the distribution of the costs of motoring are the key issue. These costs are strongly skewed across the cars in private households when including new and old vehicles: a large proportion of private car kilometres are driven at relatively low cost. The study uses simplified scenario settings with MOD price levels ranging from 0.1 €/km to 1.5 €/km to make predictions of hypothetical modal shifts under the assumption that car user switch to the most economic mode of travel. These modal shifts serve as an indicator of MOD cost competitiveness. The results indicate that MOD prices would have to drop to 0.5 €/km or lower to have a notable impact on use of the private car if cost was the key mode choice criterion. Only if MOD prices drop down to a level of about 0.3 €/km—quite possibly a lower boundary for automated MOD—MOD-enabled mobility packages would be the less costly alternative to the private car for a substantial proportion of mileage. However, even at that MOD price level, the private car would still be the most economic option for the majority of today’s car user kilometres. Our findings illustrate that the skewed distribution of the cost of owning and running private cars—where many of those who drive much drive inexpensively—substantially dampens the disruptive potential of MOD. While we use data from Germany to illustrate this, many of our findings are more widely applicable.

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Section: Discussionmentioning

confidence: 99%

Section: Data: Travel Survey Data With Imputed Vehicle Cost Informationmentioning

confidence: 99%

“…The procedure was validated against results from the German income and expenditure survey and found to deliver plausible results. For details see (Eisenmann and Kuhnimhof 2018).…”

Section: Data: Travel Survey Data With Imputed Vehicle Cost Informationmentioning

confidence: 99%

Section: Costs Of Running Private Carsmentioning

confidence: 99%

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Mobility-on-demand pricing versus private vehicle TCO: how cost structures hinder the dethroning of the car

Kuhnimhof

Eisenmann

2021

Transportation

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“…It is convenient for vehicle 88 buyers to leave the car shop with a fully registered vehicle with permanent number plates and stickers (Kiesel, 2005). About one third of transport costs are fuel, another third is depreciation, and the rest are mainly fixed costs (insurance, taxes, repairs and maintenance), but the distribution of costs is different, with most motorists paying less than average for private vehicles, while few pay more and apparently some pay much more (Eisenmann, Kuhnimhof, 2018). One of the main problems in the vehicle registration industry is that Latvian citizens are often dissatisfied with the high prices of vehicle registration, suggesting that the costs of vehicle registration in the neighbouring countries -Lithuania and Estonia -are lower.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Vehicle Registration Services in the Baltic States

Romaņuka

Puzule

2021

JRESD

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The problem of the study is that Latvian citizens often express dissatisfaction with vehicle registration prices, speculating that these services are available at lower prices in the neighbouring countries – Lithuania and Estonia. The aim of the research: to compare and analyse vehicle registration services in the Baltic States in order to provide suggestions for the improvement of the services. The research uses general scientific research methods: the monographic and descriptive methods, the document analysis method, the comparative analysis method, the horizontal analysis, the ranking method, the logical construction method and the graphical method. Based on the cases analysed, the authors conclude that vehicle registration costs are the lowest in Lithuania, yet these costs may depend on factors such as vehicle age and technical parameters, so not always the cheapest price is reported in Lithuania. Vehicle registration costs in Estonia, regardless of any parameters, for all light vehicles are the same at 192,00 euro. The authors compared and analysed vehicle registration services in the Baltic States, evaluated the price of services and the elements included in them. The study shows that when receiving vehicle registration services in the Baltic States, the conditions and price for receiving them differ. It is mainly influenced by the tax policies and pricing strategies of each country.

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