Economics at your fingertips  

Decision Support for the Automotive Industry

Christoph Gleue (), Dennis Eilers (), Hans-Jörg Mettenheim () and Michael Breitner ()
Additional contact information
Christoph Gleue: Leibniz Universität Hannover
Dennis Eilers: Leibniz Universität Hannover
Hans-Jörg Mettenheim: Leibniz Universität Hannover

Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, 2019, vol. 61, issue 4, No 2, 385-397

Abstract: Abstract In the automotive industry, it is very common for new vehicles to be leased rather than sold. This implies forecasting an accurate residual value for the vehicles, which is a major factor for determining monthly leasing rates. Either a systematic overestimation or underestimation of future residual values can incur large potential losses in resale value or, respectively, competitive disadvantages. For the purpose of facilitating residual value related management decisions, an operative decision support system is introduced with emphasis on its forecasting capabilities. In the paper, the use of artificial neural networks for this application is demonstrated in a case study based on more than 250,000 data sets of leasing contracts from a major German car manufacturer, completed between 2011 and 2017. The importance of determining price factors and the effect of different time horizons on forecasting accuracy are investigated and practical implications are discussed. In addition, the authors neither found a significant explanatory nor predictive power of external economic factors, which underlines the importance of collecting and taking advantage of vehicle-specific data or, in more general terms, the exclusive data of corporations, which is often only available internally.

Keywords: Decision support systems; Business intelligence; Artificial neural networks; Residual value forecasts; Car leasing (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link) Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from

DOI: 10.1007/s12599-018-0527-3

Access Statistics for this article

Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK is currently edited by Martin Bichler

More articles in Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK from Springer, Gesellschaft für Informatik e.V. (GI)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

Page updated 2023-05-18
Handle: RePEc:spr:binfse:v:61:y:2019:i:4:d:10.1007_s12599-018-0527-3