1. Branding an Emerging Wine Region:
Do Appellation or Sub-Appellation matter?
Isabelle Lesschaeve and Nicolas Mathieu,
Vineland Research and Innovation Centre,
Vineland Station, Ontario Canada
2. Outline
Background
Factors affecting wine choice and purchase
Importance of origin
Research questions and
methodology
Results and Discussion
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3. Wine purchase decision making
“Taste” is one of the most important factors cited by
consumers for choosing wine (Thompson and Vourvachis,
1995; Charters, 2003)
Tasting wine prior purchase is not common practice
Purchasing wine is a risky endeavour, because of taste
uncertainty (Mitchell and Greatorec, 1988)
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4. Retail experience
The retail experience is changing with the market
globalization
Extreme confusion wine consumers
could feel entering a retail store
Confusing factors (Casini et al.)
Unprecedented levels of product
proliferation
Available access to increasing
amounts of information
Increasing use of imitation strategies
Consumers shopping in new or unfamiliar environments
Need for confusion reducing strategies
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5. Risk reducing strategies
Consumers tend to use these extrinsic cues to minimize risk:
Price
Awards
Front label attributes
Brand name Dependent on
Region of origin, Appellation of Origin product involvement
Design
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6. Product involvement
Product involvement has been conceptualized as the interest,
enthusiasm and excitement that consumers exhibit towards a
product (Mittal, 1989; Bloch and Richins, 1983)
“Higher involvement consumers utilise more information and
are interested in learning more, while low involvement
consumers tend to simplify their choices and use risk
reduction strategies”. (Lockshin, 2006)
Highly involved Australian consumers conceptualized wine
quality more objectively, by using more cognitive dimensions
(interest or complexity) (Charters and Pettigrew, 2006)
Highly involved consumers in New Zealand tended to use
extrinsic quality cues other than price to lead their choice
(Hollebeek et al. 2007)
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7. Branding wine origin
Linking a product to its place of origin is an innovative way of
differentiating the product for involved consumers (Johnson
and Bruwer, 2007)
Although not that new…
Creation of INAO in 1935 in France contributed to the
contemporary acceptance of ‘terroir’ and its allied ‘quality’ and
‘typicality’ (Vaudour, 2002)
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8. Branding wine origin
Impact of label of origin on wine choice
Low to moderate impact for Australian consumers (Veale, 2008;
Australian Wine and Brandy Corporation, 2008)
For US consumers, wine region was the most important cue for
quality (Johnson and Bruwer, 2007).
Wine region (e.g. Sonoma) was a stronger brand than sub‐region
(e.g. Dry Creek)
Impact of label of origin is moderated by wine involvement and
expertise
A strong regional brand is critical when most wines
consumed in the local market are imported (Vrontis and
Papasolomou, 2007)
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9. The case of Niagara
The Niagara Peninsula accounts
for over 90% of Ontario’s grape
growing volume
7,500 ha in Ontario, 6,800 ha in the Niagara Peninsula
(VQAO, 2009)
71 wineries producing 998434 (9L cases)
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10. Niagara
In 2006, the Niagara Peninsula was divided into 10 sub-
appellations and 2 regional appellations
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11. Research question
A large scope project has been undertaken to determine if
these sub-appellations were distinct terroirs for grape and
wine quality (Willwerth and Reynolds)
Application to Riesling wines
The representation of these new sub-appellations in the
consumer mindset and its impact on purchase decision are
unknown
Do consumers reading the sub-appellation name on the wine
label generate quality expectations? Are those confirmed or
disconfirmed after sampling the wine?
Hypothesis: Mature drinkers who drink regularly premium
wines will use regional branding as a quality cue when buying
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Vineland Research and Innovation Centre
12. Experimental design
77 white wine involved consumers (49 women and 28 men),
were recruited from the Niagara Peninsula region.
Screening questionnaire
Riesling drinker
Involved consumers (questionnaire from Lockshin et al., 1997)
Participated in two one-hour sessions one week apart.
Session 1:
Effect of extrinsic cues incl. Origin on wine quality expectation
Session 2:
Relative importance of origin, price, and taste cues on wine quality
experienced
Compensated $10/hour
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13. Extrinsic cues Levels
Cork
Closure type
Session 1 Label style
Screw cap
Intermediate
Traditional
Modern
Capsule
Logo VQA Absent
Front label
None
Geographical indication Niagara Peninsula
Ontario
Creek Shores
None
Sub-appellation indication
Niagara-on-the-lake
Beamsville Bench
8
Font of regional indications
9
(Times New Roman)
10
Estate vineyard
Reserve indication Reserve
Absent
38 concepts created systematically Vintage
2005
2006
using a factorial design 2007
10-12
Price range ($) 13-15
16-20
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14. Session 1
How much do you expect to like the wine described by
this concept?
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15. Session 2
Determine the impact of the origin on the overall wine
experience
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16. Session 2
Selection of 4 wines with similar sensory profiles (short
supply)
8
7
6
5 Reif
Myers
4
Flat rock
3 Cave Spring
2
1
0
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17. Extrinsic cues Levels
Cork
Closure type
Session 2
Screw cap
Intermediate
Label style Traditional
Modern
Selection of 6 visual concepts Capsule
Logo VQA Absent
where 3 cues were varied, the Front label
None
other remaining constant Geographical indication Niagara Peninsula
Ontario
Creek Shores
Sub-appellation indication None
Niagara-on-the-lake
Beamsville Bench
8
Font of regional
9
indication(Times New Roman)
10
Estate vineyard
Reserve indication Reserve
Absent
2005
Vintage 2006
2007
10-12
Price range ($) 13-15
16-20
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18. Session 2
Four groups of consumers tested 4 different wines
Within one group, consumers tested 6 times the same wine
(coded differently) presented with 6 different concepts
Group of
consumers Vineyard Number of consumers per group
Group 1 Flat Rock 20
Group 2 Myers 20
Group 3 Cave Spring 22
Group 4 Reif 15
Consumers were presented with one wine sample at a time
and the computerized questionnaire displayed at the same
time the corresponded visual concept.
They were asked to look at the concept and to taste the wine ,
and then to rate how much they liked the wine on a 10 point
scale anchored from ‘Not at all’ to `Very much'.
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19. Data analysis
Results from session 2
Data analysis conducted using SPSS v.16.0 (SPSS Inc.,
Chicago) and XLStat 2007.1 (Addinsoft, Paris).
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20. Effect of wine versus extrinsic cues
Source F Sig.
Intercept 935.59 0.000
Wine .849 0.471
Subject(Wine) 5.682 0.000
Appellation .563 0.453
Sub-appellation 1.183 0.277
Price 2.951 0.087
Wine * Price .768 0.512
Wine * Appellation 1.316 0.269
Wine * Sub-appellation .632 0.594
Appellation * Price .006 0.936
Sub-appellation * Price .003 0.957
No wine effect data from 4 subgroups are merged
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21. Effect of extrinsic cues on liking
differential
Dependent variable: Experienced Liking – Expected Liking
Source F Sig.
Intercept 8.028 0.006
Appellation 2.656 0.107
Sub-appellation 0.659 0.419
Price 4.069 0.046
Subject 3.97 0.000
Appellation * Price 0.15 0.699
Appellation * Subject 1.06 0.376
Sub-appellation * Price 0.309 0.579
Price * Subject 1.74 0.002
Sub-appellation * Subject 1.344 0.063
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23. Existence of Segmentation
Dependent variable: Experienced Liking – Expected Liking
Source F Sig.
Intercept 3.342 0.071
Cluster 1.072 0.347
Subject(Cluster) 10.138 0.000
Appellation 1.71 0.192
Sub-appellation 3.323 0.069
Price 0.253 0.615
Cluster * Price 22.342 0.000
Cluster * Appellation 3.312 0.038
Cluster * Sub-appellation 6.024 0.003
Appellation * Price 0.139 0.709
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Subappellation * Price 0.273 0.602
24. Effect of extrinsic cues on liking
differential between clusters
2
1.5
1
0.5
*** *
(*)
0
Cluster 1 Cluster 2 Cluster 3
-0.5
-1
Niagara P. None Beamsville None $13-15 $16-20
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25. Cluster description
2
1.5
1
0.5
0
Cluster 1 Cluster 2 Cluster 3
-0.5
-1
Niagara P. None Beamsville None $13-15 $16-20
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26. Clusters’ description
Demographic and attitudinal data were collected
Few variables explain the difference between clusters
Cluster 3 tend to purchase less often wine (monthly rather than
weekly)
Cluster 3 tend to drink more white wines whereas Cluster 1
and 2 tend to drink equally white and red wines
Cluster 1 tend to drink wine less frequently (once a week or
less) whereas cluster2 and 3 tend to drink wine several times a
week
Cluster 1 tend to store less wines at once (1-10 vs. >10)
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27. Discussion
Do consumers reading the sub-appellation name on
the wine label generate quality expectations? Are
those confirmed or disconfirmed after sampling the
wine?
Majority of involved wine consumers were sensitive to the
presence of a sub-appellation when tasting the wines
Encouraging for the Ontario wine industry
Controversial because of the lack of sensory differentiation
Other clusters were more price driven
Cluster 3 seems more sensitive to the wine quality/price ratio
Wine quality needs to match the expectations created
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28. Discussion
Our results confirmed that the 3 extrinsic cues tested were
strong quality signals, although the wine intrinsic quality
remained similar.
Prevalence of extrinsic cues over the sensory experience has
already been shown by Lange (2000) on Burgundy wines and
Lange et al. (2002) on Champagne wines. Wines were
different.
D’ Hauteville et al. (2007) showed that the region effect on
perceived quality could vary with the type of wines and the
level of respondent expertise.
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29. Discussion
Price also moderated the quality experienced by consumers
when tasting similar wines
Positively for Cluster 1, negatively for Clusters 2-3
Almenberg and Dreber (2009) reported that disclosing the
high price of a wine before tasting increased quality rating by
women
Demographics and attitudinal data failed to explain the
behavioural differences between clusters.
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30. Acknowledgements
This project was funded by the OMAFRA/University of
Guelph program #26480
It has been reviewed and received ethics clearance through
the Research Ethics Board at Brock University (File # 07-
286), where the data collection took place.
Jim Willwerth and Dr. Andrew Reynolds, Brock University
for providing the experimental Riesling wines
Dr. Johan Bruwer, University of Adelaide and Senior
Research Fellow - VRIC
Erika Neudorf, Research Analyst - VRIC
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