Daniel Steichen* *IUT de l

How taste and reputation affect the champagne market
January 2005
Christophe Terrien* – Daniel Steichen*
*I.U.T. de l’Aisne, 2 place Pierre Curie, 02000 LAON
*Université de Reims Champagne-Ardenne
EA 2065, Laboratoire OMI-EDJ,
christophe.terrien@u-picardie.fr
daniel.steichen@u-picardie.fr
Key words: dynamic model, vertical differentiation, myopia parameter, champagne
wines, taste, target quality, consumer behaviour, quality, goodwill
ABSTRACT
This paper presents a dynamic model of sales on the champagne wine market. It
is assumed that goods are vertically differentiated on this market with the result that, for
a given price, there is a generally accepted rank order.
Three categories of actors operate on this market. Wine merchants are few in
number but propose large volumes of a high-quality product they alone can provide.
Wine growers are numerous, each proposing a small quantity (compared to merchants)
of a low-quality product they alone can provide. Buyers are defined by the income
available to them to purchase champagne and by their own individual target quality.
This target quality (individual taste for product of a given quality) can be interpreted as
a personal (not shared) preference relation based on qualities observed on the market
and on the purchaser’s consumer habits. The importance of this behaviour is modulated
by what is termed here a ‘myopia parameter’.
The consumer’s choice (to buy or not to buy) depends on the surplus derived
from four factors: product quality, product price, willingness to pay and target quality.
These factors are modulated by the vertical differentiation parameter and the myopia
parameter.
The model is made dynamic by having the actors make adjustments over time.
As bargaining advances, buyers adjust their target quality while sellers adjust their price
depending on previous sales.
Various simulations were carried out based on different pairings of the myopia
and differentiation parameters. The results show that excessive product differentiation
combined with a weak myopia parameter make the market unstable.
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1. Introduction
Our model is original in that it provides a form of consumer interpretation of
uncertainty about quality on the champagne wine market. Because of the problems
individuals have in appraising the product’s characteristics, they measure quality on the
basis of a signal which is a matter of common knowledge such as a particular
champagne’s reputation. Their initial choices are based on this signal. Repeated
experience then allows individuals to make their own judgements about the product,
which then relativises their faith in its reputation.
1.1 Observable and non-observable quality
Quality is regarded here as the economic variable that determines how the
market operates, alongside price and income (Stiglitz 1987), in particular with regard to
its non-observable content. If, at the time of exchange, the price is visible, we consider,
following Arrow (1963) and Akerlof (1970), that consumers have insufficient
information about this product in contrast to the omniscient seller. Champagne can be
considered a heterogeneous good with a multitude of characteristics relating to research
(Nelson, 1970), experience (Nelson 1970), and belief (Darby and Karni, 1973). Perfect
knowledge of the product is compromised by limited rationality.
These various categories of characteristics can be observed to a greater or lesser
extent. The A.O.C, for example, as a guarantee of product characteristics is, a priori,
fully observable. It relates to objective, measurable characteristics and is guaranteed by
a trustworthy third party — government. However, the effectiveness of this signal is
attenuated by the complexity of its content 1 which is accessible only in part because of
the consumer’s limited rationality. 2 Accordingly the A.O.C is interpreted as a
characteristic of belief. Lastly, the A.O.C, as a common frame of reference for
producers, forces them to differentiate their products in terms of non-observable
characteristics guaranteed by a brand name.
Having product characteristics or guarantees that are unobservable raises a
problem of moral hazard, because the producer may take advantage of the consumer’s
ignorance of how reliable the product is (Cooper and Ross 1985). In addition, as
Spence (1977) emphasises, consumers may be misled by there being a guarantee, as
mentioned for the A.O.C. guarantee. Spence assumes consumers systematically
overestimate the probability that a product is reliable. Producers who anticipate
rationally can then make a profit by offering a weaker guarantee at a lower price.
1
2
The A.O.C. is extremely complex for the uninitiated, involving characteristics of grape variety,
cliping, yield, etc.
According to a survey by Sylvander (1995), consumers associated ‘label rouge’ chicken with
farmhouse or free-range chicken. Yet such farming characteristics are not included in the ‘label rouge’
specifications.
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1.2. Reputation and its limits
Because it is unobservable or inaccessible (there being such a mass of it),
information generates excessive access costs for individuals. Consumers then seek
synthetic guarantee signals either from independent third parties (INAO for A.O.Cs) or
from interested parties (branding), which are far less expensive as it is government or
the seller who foot the bill. Reputation, 3 as a system of guarantee based on common
knowledge 4 and shared values about a product, an individual or a firm, serves this
purpose. However, it has been seen that these guarantees may involve varying degrees
of moral hazard. This more or less strong feeling of moral hazard is reflected by the
consumer’s varying level of confidence 5 in the guarantee given, which may depend on
the type of institution underwriting it or on sellers fulfilling their commitments. 6
Fulfilment of commitments and so a reliable reputation are tested by past
experiences of consumption. 7 The relative trust in reputation depends on the gap
between the consumer’s personal judgement, which is in turn built up through positive
and negative confrontations with products, and the values bestowed on products through
reputation. If consumers have faith in the self-reinforcing quality process, they expect
firms to maintain their reputation and this is just what firms do. A balanced reputation is
obtained corresponding to sustained product quality over time, thus meeting consumers’
expectations.
In reputation models, 8 the firm will be forced to provide high quality if
purchasers learn the quality of goods rapidly enough (this is the role of reputation as a
synthetic signal) and if repeat purchases are made often enough. 9 In our model stability
is only achieved after a large number of purchase confrontations.
3
4
5
6
7
8
9
This may also be defined as the goodwill value attributed to a firm (Shapiro, 1983, p. 659).
For reputation to act as a signal it must be common knowledge (Shapiro, 1983, p. 663).
We argue that relative trust varies with the discrepancy between the consumer’s own judgement and
the credit afforded to the brand by its reputation. See below.
Furubotn and Richter (1997) claim reputation forges a self-reinforcing agreement about product
quality. This agreement presupposes that government or other third parties cannot determine whether
or not the agreement has been observed and cannot check whether agents have met their
commitments. It is the parties involved who judge whether commitments have been met, which is
reinforced by the explicit or implicit threat of breaking off the contract (Telser 1980).
Shapiro (1983) and Klein and Leffler (1981) show that reputation acts as an incentive for sellers to act
honestly. At each period, a firm can change the quality of the good, but the consumer at time t knows
the quality of the product at time t-1. If purchases are repeated (infinite horizon), consumers can base
their estimates of quality on the firm’s reputation. The quality of goods produced by the firm in the
past is used as an indicator of present and future quality.
Kreps and Wilson (1982) and Milgrom and Roberts ,
Tirole (1993) p. 224.
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2. The simulation model
2.1. Initial conditions
2.1.1. Sellers
We consider the champagne market comprises two main suppliers, wine
merchants and wine growers. In this model the number of sellers does not vary. There is
no way out of the market even if sales are poor. The characteristics of merchants vary
from those of growers. Merchants own reputed brands. This does not mean growers do
not use brands but that theirs are not as well known and are not crucial sales factors.
There are few merchants compared with growers. Wine merchants represent about 87%
of all shipments and the leading six groups have more than 60% of the total sales.
Consequently merchants’ production volumes are high. There is also a marked contrast
in prices with a ratio of 2 to 1 between merchants and growers. This can be attributed to
reputation. High spending on communication in brand capital implies high sales prices
(reputation cost 10 ), which consumers associate with higher quality. Merchants have
greater capacities for blending wines purchased from growers and it is the blending that
confers (stable) taste characteristics on the product.
The characteristics of merchants and growers are summarised below (Table 1).
Table 1
Number Sales potential Reputation Price
Merchants Low High High High
Growers High Low Low Low
In the model
Ng is the number of growers
Nm is the number of merchants
These parameters are set in line with the relative numerical importance of each category
of seller.
Qmaxg: Growers’ maximum sales potential in units.
Qmaxm: Merchants’ maximum sales potential in units.
Km: merchants’ reputation index considered as common knowledge
Kg: growers’ reputation index considered as common knowledge
10
Shapiro specifies under what circumstances reputation is an incentive for firms. Firms must enjoy
higher takings than they would by lowering quality. Reputation for high quality entails a cost through
the production of a quality good. This investment in reputation is recouped at equilibrium: high
quality goods are sold for more than they cost to produce. This price difference corresponds to income
from the investment in reputation (Shapiro, 1983, p. 660). The premium must be high enough for the
cost associated with the loss of future sales to exceed current cost savings from a reduction in quality
(Tirole, 1993). Without quality premiums firms would be tempted to increase their short term profits
by lowering their product quality (Klein and Leffler, 1981).
- 4 -

For the sake of simplicity, each seller proposes a single product associated with
a certain reputation. The range of reputations equals the number of suppliers.
Reputations are distributed randomly between a minimum and an intermediate value for
growers and an intermediate and a maximum value for merchants. To maintain a
quality-price relation that is consistent with our assumptions and with the real world,
prices are distributed in the same way. Reputation brings about vertical differentiation
among products so that, other things (income, price, etc.) being equal, a bottle of high
repute is unanimously preferred to a bottle of mediocre repute.
A product can be now identified by 6 parameters in the model (Table 2).
Table 2
Index Description Example Type*
1 Bottle number corresponding to a {9,0.462205,30,0.45138,0,5} P
producer (each producer
proposing a unique product)
2 Reputation associated with the {9,0.462205,30,0.45138,0,5} P
product
3 Maximum quantity associated {9,0.462205,30,0.45138,0,5} P
with producer
4 Price associated with product. {9,0.462205,30,0.45138,0,5} V
This price changes with the sales
results of each cycle, that is
when the last consumer has made
his choice.
5 Flag: 0 = no purchase
{9,0.462205,30,0.45138,0,5} P
1 = purchase
6 Aggregate sales for this product. {9,0.462205,30,0.45138,0,5} V
* P = parameter (fixed, static). V = variable (dynamic).
- 5 -

2.1.2. Buyers
2.1.2.1. Characteristics
Buyers characteristics are summarised below:
Table 3
Index Description Example Type*
1 Buyer identifier {362,1.60112,0.536961,1,51} P
2 Income associated with {362,1.60112,0.536961,1,51} P
buyer
3 Taste for product
{362,1.60112,0.536961,1,51} V
associated with buyer
4 Flag : 0 = no purchase {362,1.60112,0.536961,1,51} P
1 = purchase
5 Aggregate purchases {362,1.60112,0.536961,1,51} V
As for the distribution of prices and reputations, consumer incomes and tastes
are distributed uniformly between a minimum and maximum value.
In the model
Rmax is a buyer’s maximum income; R Є [0, Rmax]
θmax is a buyer’s maximum taste; θ Є [0, θmax]
Taste (θ):
‘Taste’, in the model, means a given consumer’s personal predisposition to purchase a
given product. It can also be interpreted as a personal evaluation of a product’s
reputation formed through experience, habit and the level of individual trust in
reputation as mentioned before.
2.1.2.2. Surplus function
In our model, buyers seek to maximise their satisfaction by choosing the bottle
that brings them the greatest available surplus. Several criteria describe the purchasing
process:
‣ budget constraint is taken into account by the relation between income and price,
‣ reputation k;
‣ deviation between the common appreciation of quality through reputation and
the personal appreciation of quality summarised by the taste variable;
- 6 -

The consumer’s utility corresponds to the surplus S(R,p,k,θ)
S (R, p, k, θ ) =
R
p
*( Γ(
k,
θ ))
α
−1
Where:
k
Γ ( k,
θ ) =
2
(1 + ( θ − k)
)
β
Γ ( k,
θ ) is the quality of a bottle of reputation k (0 ≤ k ≤ 1) perceived by a consumer
with taste θ (0 ≤ θ ≤ 1).
R is income, (in the model 0 ≤ R ≤ 2),
p is the price of the product,
k is reputation (0 ≤ k ≤ 1),
θ is the consumer’s personal taste for champagne ( 0 ≤ θ ≤ 1),
α is a parameter for modulating the budget constraint ( p
R ) relative to quality perceived
in the surplus function,
β is a parameter for modulating the impact of taste relative to reputation in the
perceived quality function ( Г(k ,θ) ).
A purchase is made if S ≥ 0.
The diagram below (Fig. 1) depicts the influence of β on reputation for a given θ
(θ=0.5). Г(k ,θ) is defined as the quality actually perceived by the consumer taking
account of his personal allowance for reputation.
Perceived quality Г(θ,k)
1
0.8
Fig. 1
k
Γ(
k,
θ ) =
2
(1 + ( θ − k)
)
β
β=0
β=1
0.6
0.4
0.2
β=5
β=10
0.2 0.4 0.6 0.8 1
k
A high β expresses a high personal relativisation of reputation. Consumers have
a distorted picture of high quality and have difficulty in clearly observing products
remote from their own taste, hence the term ‘myopia’ parameter. These conclusions are
found in Figure 2 which takes up the distortion of reputation for a high β but for
different values of θ representing low, medium and high factors of personal taste.
- 7 -

Г(θ,k)
1
0.8
β=10
θ=0,9
0.6
0.4
θ=0,5
0.2
θ=0,1
0.2 0.4 0.6 0.8 1
k
Notice that consumers with high taste levels appreciate highly-reputed products
more. Conversely, they underestimate products with poor reputations.
2. Dynamics of the model
2.2.1. Changes in sale price
It is assumed that suppliers aim to improve their turnover relative to the previous
period. Remember a period ends when every consumer has made his choice (to buy or
not to buy). At this point, each supplier knows the quantities sold. Each supplier has to
estimate the sales trend from the previous period and the one just ended. Suppliers’
memory is therefore limited to two periods. Suppose that p 0 and q 0 are respectively the
price and quantity of sales (in bottles) for the preceding period and p 1 and q 1 the price
and quantity sold for the period just ended. Let us consider that the other agents (sellers
and buyers alike) change nothing. Each supplier may decide either to maintain his
earlier decision to raise or lower prices (depending on the trend) or to revise that
decision. Any of the following situations may therefore arise.
‣ S1: A price increase has brought about a rise in turnover. In this event, the seller
maintains the strategy of price increases. The size of the increase is controlled
by a random variable determined from a given standard deviation σ and a mean
µ.
‣ S2: After a price reduction, if turnover increases, the seller continues to lower
prices (controlled to some extent by the parameters of the random variable).
‣ S3: After a price rise entailing a fall in sales, the seller changes strategy and
cuts 11 prices in the next period.
‣ S4: After a price fall entailing a fall in turnover the seller changes strategy and
raises 12 prices.
‣ S5: If turnover is stable from one period to the next, chance introduces a rise or
fall in prices the size of which is set by the random variable.
11
12
The size of the cut is set so as not to stay the same side of p 0
The size of the rise is set so as not to go beyond p 0
- 8 -

‣ S6: This special situation arises at the beginning of the simulation when both q 1
and q 0 are zero (no sales yet). The seller opts for a random price cut.
As a final point, a price floor is allowed for, corresponding to production cost. It
is assumed that no seller will accept to sell at a loss. This provision also precludes any
collapse of the market.
2.2.2. Changes in buyer’s taste
Consumer expectations change with the results of the latest market confrontation
(purchase or non-purchase). Should the bottle meet expectations, the purchaser moves
closer to the expected quality. In this way allowance can be made for the buyer’s
experience.
δ ( k −θ
0
)
θ1
= θ
0
+
1+
( k −θ
)
The parameter “δ” is used to weight the rate of change in taste. We set δ = 1/5.
The higher parameter δ , the more readily the consumer changes his taste.
2.3. General operation of the simulation
The standard starting factors of the model are supply represented by two agents
(growers and merchants) and demand represented by purchasers. A cycle is completed
when all the individuals making up the demand side, characterised by their own income
and their own taste, etc., have managed to choose from the available supply of bottles
proposed by growers and dealers. Each buyer has full information about the supply,
particularly about the full set of prices and reputations.
During a cycle, a buyer is taken at random and chooses from the available
supply the product giving him the greatest positive surplus. If no bottle provides a
positive surplus, then no purchase is made. Otherwise, a purchase is recorded by
deducting the chosen bottle from the relevant seller’s available stock of products
Another purchaser is chosen at random and the process is reiterated. The cycle ends
when the last buyer has made a decision. There are as many supply-demand
confrontations as there are buyers. 13 At the end of the cycle just set out, sellers adjust
their prices in line with sales which determine a trend in relation to the previous cycle.
At the same time, buyers may adjust their taste depending on the purchase made.
Consequently, there are three stages in the operation. The first is to draw up a table of
buyers and bottles (or sellers since a seller produces only one type of product, which is
an acceptable simplification in the case of champagne). Each product’s reputation
remains constant. 14 The second stage is an initial supply-demand confrontation whose
0
2
13
14
For the simulation the number of purchasers is greater than the number of sellers. There is, in fact, a
chronic deficit of supply on the champagne market.
Again this matches the historical reality of the champagne market. The reputation of the great
champagne houses has been sustained since they were formed in the 18th and 19th centuries (Henriot
1808, Perrier-Jouët 1811, Laurent Perrier 1812, Mumm 1827, Bollinger 1829). Cuvée Dom Pérignon
dates from 1921. Packaging is identical to Cuvée du centenaire from Simon Brothers, Moët’s UK
brokers. Until 1947, cuvée Dom Pérignon was reserved for the UK. Moët et Chandon work to
maintain its reputation. The brand was served at royal weddings. Edward VII in 1902 with the 1898
year, when Prince Rainier acceded in 1949, at his wedding in 1956, at the wedding of King Baudouin
in 1967.
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outcome influences the purchaser’s taste. However, sellers cannot yet change their
prices as two results are needed to identify a trend. This problem is solved at the third
stage illustrated by a second confrontation changing tastes and prices. The first two
stages are all that is needed to start the simulation. The iterations bring about the third
stage. In our model, the buyer is in a purchase situation one thousand times.
3. Results
Calculations were made with the following parameters:
Number of cycles = 1000
To allow for disruption in the starting conditions, the first 200 cycles were ignored.
Tests were also made on a very large number of cycles without radical differences in
results.
Price floor = 0.1
Ng = 20
Qmaxg = 25
Ng = 5
Qmaxg = 400
Na = 5000 (buyers number)
These parameters are set in line with the real situation on the champagne market,
particularly the representative character of categories of sellers and their market shares.
Buyer’s taste = 3/4
Income: max. = 2
δ=1/5 (weighting for rate of change of taste)
3.1. Results removing the effects of reputation and taste (α = 0 , β = 0 , δ = 0)
Fig. 3
Total quantities sold (Growers and merchants)
600
500
400
300
200
100
Q vendues neg+vig
200 400 600 800 1000
Figure 3 shows the change in total quantities sold over time eliminating the
influence of reputation and taste on consumer choice (α = 0 , β = 0 , δ = 0). Values
change in a ratio of 1 to 6. The market is highly unstable, swinging between extremely
profitable situations and situations of virtually no sales. The market does not seem to
operate without signals for reducing uncertainty about quality.
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3.2. Results influenced by reputation and taste (α ≠ 0 and β ≠ 0)
All other parameters are unchanged. The market is identical to the previous one.
The distribution of buyers (income, taste, etc.) and suppliers (initial price, reputation,
etc.) is identical.
Compared with the results of Figure 3, the market is very stable as can be seen
from Figure 4 showing the change in sales by growers over 10,000 cycles (for α=1 and
β=5)
360
Fig. 4
Grower’s sales
Q vendues vig
350
340
330
320
310
2000 4000 6000 8000 10000
Fig. 5
Merchant’s sales
Q vendues neg
1500
1400
1300
1200
1100
1000
2000 4000 6000 8000 10000
The same stability is observed for quantities sold by merchants. The range over
which sales change is much more limited (10–50%). In accordance with the starting
equations, consumer taste changes markedly upmarket (Fig. 6). Prices change little (Fig.
7).
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Fig. 6
Average taste evolution
Evol. gout moyen de la population
0.525
0.52
0.515
0.51
0.505
2000 4000 6000 8000 10000
Fig. 7
Growers’ average price
Prix moy. marché vig.
0.62
0.61
0.59
2000 4000 6000 8000 10000
0.58
0.57
0.56
Fig. 8
Merchants’ average price
Prix moy. neg.
1.3
1.2
1.1
2000 4000 6000 8000 10000
Merchants’ average price is consistent with the change in sales. As the results as
a whole are consistent, we examined the effects of different values of α and β on market
stability. It can be seen that when α increases, stability, expressed by the variation
coefficient, decreases.
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3.3. Impacts of qualitative interpretation on the market
Two snapshots of the market depict the impact of the consumers’ interpretation
of quality. Figure 9 shows consumers’ positive surpluses in the initial state.
Computations are therefore made from tables of consumers and initial products. Figure
10 shows consumers’ positive surpluses at the end of the last cycle of choice. The tables
used allow for changes in taste and prices at the end of the simulation.
Fig. 9. Initial market (S 1 )
No purchase zone
Positive surplus
1.5
1
0.5
0.6
0
0
0.4
0.5
R [0 , 2]
1
1.5
2 0 0.2
θ [0 , 3/4]
α = 1
β = 5
Fig. 10. Final market (S 2 )
Distortion
1.5
1
0.5
0.6
0
0
0.4
Market expansion
0.5
R [0 , 2]
1
1.5
2 0 0.2
θ [0 , 3/4]
- 13 -

The market is distorted for high reputations between Figures 9 and 10 because of
the influence of taste. In addition, the market broadens towards lower income segments.
Figure 11 shows the differences in positive surpluses between the initial and final states.
It brings out the distortion zones seen in Figure 10.
Fig. 11.
S 2 - S 1
R [0 , 2]
0.1
0.05
0
0.6
0
0.5
0.4
θ [0 , 3/4]
1
1.5
2 0 0.2
4. Conclusion
In the absence of signals consumers can interpret, the champagne market is
extremely unstable. Sales vary by chance encounters between more or less demanding
and wealthy individuals and products of greater or lesser repute and price, without
achieving any equilibrium. Reputation as a common reference framework organises
consumer decisions. It provides the system with a provisional point of equilibrium.
However, in the long term, a situation of equilibrium should logically be reached which
gives precedence to products of high repute. As reputation governs the preference order
of all consumers, each consumer will choose the product with the highest reputation he
can afford. The distribution of sales would then be calculated from the decreasing order
of reputation as a function of available income. Now, this situation does not arise as
high-income consumers may prefer products of lower reputation than they could in fact
afford. The role of reputation must therefore be specified to explain the operation of the
champagne market. As sales are not correlated with reputation, it is accepted that
consumers interpret the signal in a way that relativises its effect. We suggest individuals
relativise the reputation effect through their own interpretation of that reputation in line
with their experience and their own taste. Simulations allowing for these two parameters
of taste and reputation, to varying extents, lead to stable and realistic markets. The
possibility that the market would be cornered by merchants does not occur even if the
weight attributed to reputation favours their sales. The model therefore proposes a good
dynamic representation of how the champagne market operates.
For the needs of our study, the champagne wine market allows a number of
useful simplifications. Supply is mostly reduced to two actors with very limited product
ranges. It is based traditionally on reputation as a signal of market standard and as a
factor of product differentiation. This model might be transposed to other markets
where reputation effects are important, such as the automobile market.
- 14 -

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