Parc Mediterrani de la Tecnologia
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CONSUMERS’ WINE PREFERENCES IN A
CHANGING SCENARIO: A GENERALIZED
MULTINOMIAL LOGIT APPROACH
Cristina ESCOBAR, Zein KALLAS & José María GIL
CREDA – UPC – IRTA
Centre for Agro-food Economy and Development
Castelldefels, Barcelona (SPAIN).
X CONGRESO NACIONAL DE ECONOMÍA AGRARIA “Alimentación y territorios sostenibles desde el sur de Europa”.
September 9th to 11th, 2015. Córdoba, Spain.
Table of contents
1. INTRODUCTION AND OBJECTIVES
1.1. Catalonia as a wine region
1.2. Socio-economic context in Catalonia
2. CONSUMERS’ PREFERENCES TOWARDS WINE
3. METHODOLOGY
4. EMPIRICAL APPLICATION
4.1. Sample
4.2. Attributes and levels
5. RESULTS AND DISCUSSION
6. CONCLUSIONS
1. INTRODUCTION: Catalonia as a wine region
Wine production in Spain > 42 millions Hectoliters
Catalonia
3,7 millions Hectoliters
300.000
ITALY;
44.900
250.000
200.000
Rest of Spain
1000 hl
Catalonia
FRANCE;
42.016
150.000
100.000
50.000
Source: OIV & DAAM, 2014
SPAIN;
42.700
REST OF
THE
WORLD;
148.984
0
2013
Source: OIV, 2014
1. INTRODUCTION: Catalonia as a wine region
WINE SECTOR KEY FACTORS (1): CONSUMPTION DECREASE
12
LITRES/CAPITA
10
8
6
4
2
0
2005
2006
TOTAL VINS (vins+escumosos)
2007
2.008
2.009
VI TRANQUIL (DO)
2.010
V.TAULA
2.011
2.012
ESCUMOSOS
2.013
ALTRES VINS
Source: MAGRAMA 2014
1. INTRODUCTION: Catalonia as a wine region
WINE SECTOR KEY FACTORS (2): LOW MARKET SHARE OF
CATALAN DO WINES IN CATALONIA respecto al vino con DO
% in volume
Catalan quality wines
Market share (11 DO)
2011
2012
2013
28,5%
28,9%
29,6%
Source: Nielsen panel, 2014
1. INTRODUCTION: Catalonia as a wine region
WINE SECTOR KEY FACTORS (3): EXPORTATION INCREASE
700
Milions d'euros
601
600
500
542
527
543
2010
2011
597
605
2012
2013
481
450
441
2005
2006
400
300
200
100
0
2007
2008
2009
Source: DATACOMEX 2014
1. INTRODUCTION: Socio economic context in Catalonia
 Market INSTABILITY (since 2007) and CRISIS
(Ortega &
Peñalosa, 2012)
 DEVASTATING IMPACT on the EMPLOYMENT IN SPAIN: 6.2
million people unemployed in 2011 (INE, 2014)
 SHARP DROP in consumption and in fixed capital investment
(Carballo-Cruz, 2011)
 Also consequences for the AGRO FOOD MARKET (Nielsen
market trends)
1. INTRODUCTION: Socio economic context in Catalonia
 POLITICAL CHANGES have also occurred in Catalonia
 Members of Parliament strongly in favor of an INDEPENDENT
CATALONIA increased 7,4% (elections of 2012)
 Massive POPULAR MOBILIZATIONS in Catalonia after the long
awaited decision of the Constitutional Court about the new
Statute of Autonomy
 Plus, the MAIN NATIONALIST PARTY in Catalonia (CIU), has
SHIFTED
from
nationalism
to
(Guibernau, M., 2013, amongst others)
Catalan
independentism
1. INTRODUCTION
 Thus, the OBJECTIVE of this paper is:

To determine CONSUMERS’ RED WINE PREFERENCES for a
special occasion and,

More specifically, their CHANGES regarding the newer
economic and political scenario
 We applied 2 DISCRETE CHOICE EXPERIMENTS (DCE), BEFORE
and DURING the economic crisis (1TBefore vs.3TDuring)
2. CONSUMERS- PREFERENCES TOWARDS WINE
 Wine is a DIFFICULT AND CONFUSING product for consumers to
choose  IMMENSE NUMBER OF CUES
COO
White
Red
ROO
DO
BRAND
Rosé
Liquored
TYPE
PRICE
AWARDS
Sparkling
Others...
PACKAGING
TASTE
GRAPES
VINTAGE
ALCOHOL
CONTENT
2. CONSUMERS- PREFERENCES TOWARDS WINE
BRAND
 Are capable of acting as a SURROGATE for a number
of attributes (including quality) and might help
address RISK while providing product cues
 Consumers may use a SMALL REPERTOIRE, which may well be a
collection of true brands and GENERIC TYPES
ROO
DO
GRAPE
GENERIC TYPES
VARIETY
2. CONSUMERS- PREFERENCES TOWARDS WINE
COUNTRY
OF ORIGIN
 Plays a KEY ROLE in the consumers’ decision
making
process,
specially
in
wine
producing
countries
When consumers do not have information about the
PRICE
product, it generally performs as a PROXY to infer the
quality of the product when:
 The product cannot be evaluated
 The RISK of making a wrong choice is high
2. CONSUMERS- PREFERENCES TOWARDS WINE
RISK REDUCTION STRATEGIES
Compilation of the main RRS in wine choice (Rawbone-Viljoen, 2012)
 INFORMATION SEARCH [assistants, waiters, wine editorials,
tasting notes, packaging, word-of-mouth, family and friends and
opinion leaders]
 SEEKING REASSURANCE [mainly through tastings, information
seeking behaviour and prior experience]
 BRAND loyalty and Well-known brands
 PRICE
 STORE IMAGE
3. METHODOLOGY: The DCE: Econometric model
U jn  V jn ( X j , Sn )   jn
 The basic model is THE MULTINOMIAL LOGIT MODEL (MNL).
U njt   xnjt   njt  n
n  1, , N
j  1, , J
t  1, , T
 It imposes homogeneity in preferences for observed attribute
 The IIA property seldom hold.
3. METHODOLOGY: The DCE: Econometric model
 The Mixed Logit Model (MIXL)
U njt   n xnjt   njt  n n  1, , N j  1, , J t  1, , T
 Extend the MNL introducing for unobserved heterogeneity by
allowing random coefficients on attributes .
 Recent
studies
argued
that
much
of
the
PREFERENCE
HETEROGENEITY captured by random parameters in MIXL can be
better captured by the scale term; and thus known as “SCALE
HETEROGENEITY”.
 The MIXL turns to be likely a POOR APPROXIMATION to stated
data if scale heterogeneity is not accounted for
3. METHODOLOGY: The DCE: Econometric model

The Generalized Multinomial Logit Model (GMNL)
U njt  [ n   γn  (1  γ) nn ] X njt   njt
 Known also as Generalized Mixed Logit Model (G-MXL).
 n is a scaling factor that proportionately scales the  up or down
for each individual n.
  is a mixing parameter, and its value determines the level of
mixing or interaction between the scale heterogeneity coefficient
and the parameter heterogeneity coefficient .
4. EMPIRICAL APPLICATION: Sample
 2 IDENTICAL SURVEYS performed in 2 DIFFERENT TIMES:
BEFORE & DURING the ECONOMIC CRISIS.
Before
Population
Sample Design
Field
Sample Size
Confidence
interval
Confidence level
Control measure
During
Consumers over 18 years who purchase regularly food
and are residents in the metropolitan area of Barcelona.
Stratified sample by age and postal districts using
proportional affixation to the number of persons by
stratum.
Metropolitan area of Barcelona
400
401
 4.9
± 4,9%
95.5% (k=2)
95.5% (k=2)
Pilot survey (25 questionnaires)
4. EMPIRICAL APPLICATION: Attributes and levels
 To reduce wine choice complexity we delimited our wine selection
by focusing on a RED WINE purchased for a SPECIAL OCCASION
such as Christmas.
 Based on the literature and discussion groups we identified the
following attributes and levels:
 ORIGIN: Catalonia (regional), Spain (national), Imported
(international)
 WINE REFERENCES: Own Experience, Recommendation,
Prestige
 GRAPE VARIETY: Cabernet Sauvignon, Grenache, Merlot
 PRICE: €6, €10, €14
4. EMPIRICAL APPLICATION: Attributes and levels
 We followed the DUAL RESPONSE CHOICE EXPERIMENT design.
 From the FULL FACTORIAL DESIGN using the total number of
attributes and levels which led to a total of 81 hypothetical
products. In a choice set of 2 alternatives we have 6,561 possible
combinations.
 The orthogonal fractional factorial design with only 9 CHOICE
SETS.
4. EMPIRICAL APPLICATION
4. EMPIRICAL APPLICATION: Attributes and levels
 All attributes, including the price, were coded with EFFECT
CODING as discrete variables
 To avoid the base levels being CONFOUNDED WITH THE
INTERCEPT  Effects of all levels can be estimated
 All models were estimated by using 500 Halton draws.
 Both models are statistically significant and exhibited a good fit with
highly significant likelihood ratios.
5. RESULTS AND DISCUSSION

Before
During
Random parameter estimates
2.03293***
.27705
Spanish
3.80717***
.73884***
Catalan
-.80762**
-.20509***
Recommended
-1.06844***
.09827
Prestigious
-1.52072***
-.25125
Grenache
1.58843***
.29349**
Cabernet sauvignon
.90290**
.01346
Price-10€
-1.96268***
-1.19805***
Price-14€
Practically all
-2.52462***
2.86293***
No choice
SIGNIFICANT
-3955.00
-3964.89
Log-Likelihood (0)
947.73 (0.000)
3650.00 (.000)
LL ratio test
Consumers’
preferences
are
higher
for
the
CATALAN
ORIGIN of
.1198152
.4602901
Pseudo R2
1.965
1.217 and,
AIC/N for the grape variety CABERNET
product,
SAUVIGNON
Variance parameter tau in scale
2.05073***
.05930
parameter
(τ) been PREVIOUSLY EXPERIENCED
wines
that have
.02924*
.10052
Weighting parameter Gamma (γ)
the
for
5. RESULTS AND DISCUSSION
Before
During
SomeRandom
levelsparameter estimates
2.03293***
.27705
Spanish
turn into NON3.80717***
.73884***
Catalan
SIGNIFICANT
-.80762**
-.20509***
Recommended
-1.06844***
.09827
Prestigious
-1.52072***
-.25125
Grenache
1.58843***
.29349**
Cabernet sauvignon
.90290**
.01346
Price-10€
-1.96268***
-1.19805***
Price-14€
-2.52462***
2.86293***
No choice
A change
into positive utility for the
No choice intercept
might
-3964.89
Log-Likelihood (0)
explain it-3955.00
947.73 (0.000)
3650.00 (.000)
LL ratio test
.1198152
Pseudo
R2
In During
consumers
show a greater preference
for not.4602901
taking the
1.217
AIC/N
product,
indicating PERSISTENCE 1.965
IN THE UNOBSERVED
Variance parameter tau in scale
2.05073***
.05930
ATTRIBUTES
parameter (τ)
.02924*
.10052
Weighting parameter Gamma (γ)
5. RESULTS AND DISCUSSION
Before
During
Random parameter estimates
 In “During”
the VARIATION
OF
2.03293***
.27705
Spanish model it becomes NON-SIGNIFICANT:
3.80717***
.73884***
Catalan
THE DEGREE of RANDOMNESS in their final decision and hence their
-.80762**
-.20509***
Recommended
-1.06844*** significantly.
.09827
Prestigious
degree of UNCERTAINTY DECREASED
-1.52072***
-.25125
Grenache
1.58843***
.29349**
Cabernetsauvignon
Tau parameter (KEY PARAMETER)
.90290**
.01346
Price-10€
captures the SCALE HETEROGENEITY
-1.96268***
-1.19805***
Price-14€
-2.52462***
2.86293***
No choice
-3955.00
-3964.89
Log-Likelihood (0)
Common circumstances may have had a
947.73 (0.000)
3650.00 (.000)
LL ratio test
HOMOGENISING INFLUENCE
.1198152
.4602901
Pseudo R2
1.965
1.217
AIC/N
Variance parameter tau in scale
2.05073***
.05930
parameter (τ)
.02924*
.10052
Weighting parameter Gamma (γ)
5. RESULTS AND DISCUSSION
Before
During
 GAMMA in both models
is SIGNIFICANTLY
DIFFERENT from ZERO.
Random
parameter estimates
2.03293***
.27705
Spanish
 TASTE
heterogeneity is PARTIALLY
CONDITIONED
to SCALE

Catalan
heterogeneity.
Recommended
Prestigious
In “During”
model, however,
Grenache
Cabernet
sauvignonfrom 0.10 to
(Gamma
increases
Price-10€
Price-14€
No choice
Log-Likelihood (0)
LL ratio test
Pseudo R2
AIC/N
Variance parameter tau in scale
parameter (τ)
Weighting parameter Gamma (γ)
3.80717***
-.80762**
-1.06844***
they-1.52072***
become
1.58843***
0.57)
.90290**
-1.96268***
-2.52462***
-3955.00
947.73 (0.000)
.1198152
1.965
.73884***
-.20509***
.09827
more INDEPENDENT
-.25125
.29349**
.01346
-1.19805***
2.86293***
-3964.89
3650.00 (.000)
.4602901
1.217
2.05073***
.05930
.02924*
.10052
5. RESULTS AND DISCUSSION
Before
Spanish
3.12735***
.25613
Catalan
5.09622***
.59020**
.23246
.08569
Prestigious
1.65080***
.11011
Grenache
1.81875***
.67845
Cabernet sauvignon
2.74603***
.21026
Price-10€
Practically all
Price-14€
SIGNIFICANT
3.05442***
.38428
4.86483***
.97643**
No choice
7.34722***
.52561
Recommended
Standard deviations of
parameter distributions
 Regarding
During
the
UNOBSERVED
TASTE
(PREFERENCE)
HETEROGENEITY, it is captured by the standard deviation of the
random parameters.
5. RESULTS AND DISCUSSION
Before
Spanish
3.12735***
.25613
Catalan
5.09622***
.59020**
.23246
.08569
Prestigious
1.65080***
.11011
Grenache
1.81875***
.67845
Cabernet sauvignon
2.74603***
.21026
Price-10€
3.05442***
.38428
Price-14€
4.86483***
.97643**
No choice
7.34722***
.52561
Recommended
Standard deviations of
parameter distributions
During
Some levels
turn into NONSIGNIFICANT
5. RESULTS AND DISCUSSION
In the During model,
 Spanish wine’s show a NOT SIGNIFICANT UTILITY but its TASTE
HETEROGENEITY TURNS SIGNIFICANT
 Catalan wines show again a SIGNIFICANTLY POSITIVE UTILITY
and its TASTE HETEROGENEITY TURNS NOT SIGNIFICANT
 Furthermore,
the
SCALE
HETEROGENEITY
=
ZERO

CONSUMERS’ PREFERENCES TOWARDS CATALAN wines have
become CLEAR
6. CONCLUSIONS
 Consumers’ preferences are higher for the CATALAN ORIGIN of
the product, for the grape variety CABERNET SAUVIGNON and
for wines that have been PREVIOUSLY EXPERIENCED
 The CATALAN ORIGIN of the wine shows a SIGNIFICANTLY
POSITIVE UTILITY IN BOTH SURVEYS, which reveals the
importance of the Catalonian identity in the consumer behaviour.
 However, During the crisis, this quality is HOMOGENEOUS
ACROSS CONSUMERS (does not show any unobservable
heterogeneity).
 This
finding
ENVIRONMENT
is
in
ACCORDANCE
with
the
POLITICAL
6. CONCLUSIONS
 SPANISH WINES shows a NON-SIGNIFICANT UTILITY During the
crisis, this occurs in spite of gathering the highest market share in
Catalonia, which suggests an influence of the political changes
6. CONCLUSIONS
 The GMNL model has shown to be appropriated to DECOUPLE
both UNOBSERVED HETEROGENEITIES
 Has provided us with more information about the SOURCE OF
CONSUMERS’ HETEROGENEITY
 In
the
“During”
model:
the
results
for
the
SCALE
HETEROGENEITY indicate that the degree of uncertainty in the
decision-making process has DECREASED SIGNIFICANTLY.
 This finding might show an IMPACT OF SOCIO ECONOMIC
CHANGES in the environment of consumers’ decision-making
towards wine. In this sense, external common circumstances may
have had a HOMOGENIZING INFLUENCE.