Residual Value Analysis
Andreas Jost
DaimlerChrysler Research and Technology
IT for Engineering and Processes - Digital Engineering Competence Center
Wilhelm-Runge-Strasse 11 - 89013 Ulm - Germany
phone: + 49 731 505 2364 - fax: + 49 731 505 4400
mail: andreas.jost@daimlerchrysler.com
Alexander Franke
Collége des Ingénieurs (CDI)
49 rue de l'Université - 75007 Paris - France
phone: +49 179 964 1081
mail: afranke@cdi.fr
ABSTRACT
Residual values are considered of major importance for an automotive product/brand in
various aspects. They are believed to have a major influence on attributes such as: new car
sales, pricing options, buyback risk, and image perception. The presented paper refers to a
work in progress model developed for the analysis of residual values in the automotive
industry. It is designed to analyze how an automotive company can support and take
advantage of residual values. Among others, the following questions are addressed:
= Which leverages/policies effect residual values?
= Which leverages/policies are particularly effective/sensitive?
= What effects/consequences regarding the new car business are to expect
by changes in residual values?
Although the model is designed and developed for practical use in the automotive industry
and can not be revealed in detail, it provides important aspects that are worthy of discussion
with experts in the field of System Dynamics. It represents a new approach to the subject of
residual values and connects to previous work such as Sterman (2002). The developed
model reproduces the course of residual values in relation to specified market cycles as well
as the given exogenous factors realistically and has proven valuable for important questions
of the automotive industry regarding effective leverages and policies to residual values.
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INTRODUCTION
Residual values are considered of major importance for an automotive product/brand in
many aspects. They are believed to support new car sales, to influence pricing options and
reduce buyback risks. Furthermore residual values significantly influence brand image.
Classical approaches to the subject of residual values include statistical regression analysis
and maximum likelihood estimates based on available market data. Automotive market
analysts also offer product oriented multipoint checklists and various forecast models.
Nevertheless the identified, classical approaches did not provide sufficient support to
address the aforementioned questions (see abstract) and to develop strategic policies
accordingly. Therefore a System Dynamics approach was taken in order to explore
leverages and effects to residual values from a perspective of an automotive manufacturer.
Also the System Dynamic modeling process was considered to be of remarkable value for
the formulation of a common perspective and the generation of additional insights to the
subject.
LITERATURE REVIEW
Little previous work was found focusing on the analysis of residual values. Most related
publications concentrate on more general questions associated with the market of used cars.
A milestone towards a better understanding of the relevant market mechanisms was
introduced by Akerloff (1970). According to this model a potential buyer has disadvantages
as he cannot access the quality of a used car individually. This leads to decisions purely
based on price and the association of lower prices with lower qualities accordingly. A
reinforcing cycle may therefore lead to a reduction in the average quality of goods and
result in a “market of lemons”. Akerloff’s hypothesis were repeatedly tested (more recently
by Emons/Sheldon (2002)) but have not been empirically confirmed. Nevertheless they are
considered to be highly significant and believed to have led to higher transparency in
market of used cars.
With focus on the car market in Germany Dudenhdffer/Borscheid (2004) describe available
forecast models for residual values and highlight the advantages of explicative time series.
Also with regard to the German market Beyer (1997) proposes the introduction of a used
car price index as a basis to reduce car lessor’s risks in the instability of residual values
through the utilization of options and derivatives.
Applying System Dynamics as a method in the context of used car markets Barraba/Pudar
(1997) analyze long-term effects of leasing strategies with General Motors. Along this
System Dynamic initiative GM’s Dialogue Decision Process was developed and
introduced. An important aspect for the work presented in this paper is the connection to
the physical vehicle flow model presented by Sterman (2002). Its model section simulates
volume flows of cars on the automotive market. Sterman related his analysis to the
interaction of the new and used car market and investigated the impact of a substitute
market (of younger used cars) as an option for new cars triggered by leasing. Whereas
Sterman (2002) focuses on the physical flow of cars form production to today’s
recycling phase within the presented model. This flow is extended to include orders
and most importantly buyback volumes.
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A. Jost, A. Franke (2005) Residual Value Analysis
MODEL STRUCTURE AND ASPECTS
In the following an overview of the model structure is provided and selected model sections
are briefly introduced.
MODEL OVERVIEW
In the developed model four sections can be distinguished: Vehicle Flow and Buyback
Volume, Model Cycles and Vehicle Attractiveness, Residual Value Formation and
Exogenous Factors (see Figure 1). The last sector is concerned with the integration of
exogenous factors and basic demand volumes and will not be described in detail.
Vehicle Flow
and “Exogenous
Buyback Volume Factors
Model Cycles and
Vehicle Attractiveness
&
Residual Value
Formation
Fig 1: Overview model structure
VEHICLE FLOW AND BUYBACK VOLUME
The vehicle flow is modeled similar to Sterman (2002). It simulates volume flows of
vehicles from production to today’s recycling phase. Compared to the model introduced by
Sterman the vehicle flow was extended to include orders and most importantly buyback
volumes (see Figure 2).
Orders are distinguished between base orders and additional orders generated by short-term
initiatives (including market initiatives as well as production oriented activities).
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Buyback volumes explicate the number of buyback cars on the road and introduce a virtual
used car inventory generated by the commitments to buybacks and the available number of
younger used cars on the road.
orders Qo
generated
short term| Bate Oars
initiatives
Order Inventory
Production
New Car Inventory
Buyback
Volume
New Ca
Sales Buyback Volume
(delayed)
Buyback Cars On Road
Lp} Younger Used Cars On Road |} ——fm| Used Car Inventory
Cars Availiable
f for Trade |
TradelNs
Aging Rate
Y
Older Used Cars
Recycling Rate
Fig 2: Vehicle Flow and Buyback Volume
MODEL CYCLES AND VEHICLE ATTRACTIVENESS
The Vehicle Attractiveness distinguishes between new and used car attractiveness. Both
parameters counteract in relation to the model cycles. New product launches frequently
start a new model cycle and significantly influence the respective residual values. The
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A. Jost, A. Franke (2005) Residual Value Analysis
effects of model upgrades are less sensitive in their influence on the formation of residual
values. Central parameters are intervals between model cycles and age (time since
production) of a respective model.
RESIDUAL VALUE FORMATION
The residual value is formed through a competing approach between the demand for
younger used cars and the respective supply combined with the identified dynamics
(derivatives). Supply pressure is believed to be a major factor in the formation of residual
values. The strategies employed by car manufacturers can have significant effects on the
supply side as well as on the demand side. The model takes different strategic levers into
account that are directly and indirectly controlled by OEMs. Examples are product life
cycles, leasing strategies and market initiatives.
MODEL CHARACTERISTICS
Figure 3 shows the qualitative course of the residual value in relation to a given model
cycle. The attractiveness of new and used vehicles is shown in parallel in order to
emphasize significant points within a model. The graph is not shown in scale and with no
hierarchical order on the vertical axis.
tu to: te fe te
Attractiveness New Vehicle
Attractiveness Used Vehicle
Residual Value (generic used vehicle)
Fig 3: Residual Value and Model Attractiveness
At ty; a new car model enters the marked for new vehicles. In the used car market its
respective predecessor car model is in a mature life cycle phase. The residual value of a
given car model is low. At tg; a new car model becomes available in the market for used
cars and the residual value rises significantly. At tno the highest level of the residual value
is reached. Further on residual values decrease until at tg. an upgrade of the current car
model becomes available on the used car market. tga marks the presentation of the new
(successor) car model in advance to the planned market introduction (tni).
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CONCLUSIONS AND FURTHER RESEARCH
The developed model is able to address important questions of the automotive industry
regarding effective leverages and policies to residual values. It is able to realistically
reproduce the course of residual values in relation to specified market cycles and the given
exogenous factors.
Nevertheless, certain effects have been left out in the first step which are worthy of
consideration in a second step. All above, the model is designed to support the decision of
an automotive company and focuses on leverages that are in direct or indirect control of
that company. In the first step the market cycles of competing car models (of other
manufactures) have been omitted. The integration of competitor model cycles is believed to
be a significant factor which can further improve the value of the developed model.
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REFERENCES
Akerlof GA. 1970. The Market for Lemons: Quality Uncertainty and the Market Mechanism.
Quarterly Journal of Economy 89: 488-500.
Beyer S. 1997. A Used Car Price Index as Underlying to Reduce Car Lessor’s Residual Value Risk
with Options. Geld, Finanzwirtschaft, Banken und Versicherungen. Verlag _ fiir
Versicherungswissenschaft: Karlsruhe.
Barraba V, Pudar N. 1997. Communication for action: GM’s Dialogue Decision Process. Strategic
Communication Management 1 (1): 24-29.
Dudenhéffer F, Borscheid D. 2004. Automobilmarkt-Prognosen: Modelle und Methoden.
Automotive Management. Strategie und Marketing in der Automobilwirtschaft. B.Ebel:
Heidelberg:.
Emons W, Sheldon G. 2002. The Market for Used Cars: A New Test of the Lemons Model.
Universitat Bern, Department of Economics: Discussion Paper 02.02.
Sterman J. 2000. Business Dynamics. McGraw Hill: Boston Massachusetts.
Sterman J. 2002. System Dynamics: Systems Thinking and Modelling for a Complex World.
Massachusetts Institute of Technology. Engineering Systems Division. Working Paper Series.
ESD-WP-2003-01.13-ESD Internal Symposium.
WT
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