WINE TOURISM CONSUMERS: WHO ARE
THEY AND WHAT MOTIVATES THEM?
A FIELD WORK APPLIED TO PORTO, RIOJA AND
BORDEAUX
CAROLINA AFONSO
"The real voyage of discovery consists not in seeking new landscapes, but in
having new eyes" –
Marcel Proust.
ACKNOWLEDGMENTS
This GWC Research has been shaped by many people, to whom I am forever grateful. Some
influenced my intellectual approach, providing support, insight and inspiration. Others have
been always by my side, giving me the energy to pursuit my dreams, no matter what.
A special thank you to Great Wine Capitals and Porto, Rioja and Bordeaux wine region’s
people to have selected me and to have trusted and supported during this year. Specially to
Fernando Urdaniz, Maria do Carmo Costa, Jacques-Olivier Pesme, Cristina Quintero, Susana
Ribeiro and Catherine Leparmentier Dayot.
To Carmo's Boutique Hotel, Monverde Wine Experience Hotel, Quinta da Boeira, Quinta das
Escomoeiras, Quinta da Pacheca, Quinta do Vallado, Turismo de Portugal and all partners that
helped to promote the survey and provided support along the way, also a big thank you!
A number of friends, colleagues, and family members have supported me along this wine
tourism journey and for that I’m extremely thankful.
Thank you! Obrigado! Muchas Gracias!Merci!
ABSTRACT
This research aims to explore wine tourism consumer profile and propose a conceptual
framework that enables to understand the consumer’s motivations as a predictor of the
intention to opt for a wine tourism program. More specifically, the objective is to present a
research model proposal about wine tourism consumers’ behavior, taking into account their
motivations and return intention At the end, the aim is to provide insights about ‘who’ are
potential wine tourism segments of consumer and what are their motivations.
The focus of this study is the wine tourism consumer’s profiling and behavior, based on socio-
demographic variables and psychographic variables. The objective is to understand the
relevance of those variables to explain wine tourism consumer’s behavior and also to propose
motivations as determinants of return intention.
In order to assess to wine tourism consumers’ profile and motivation, the motivational
approach developed by ALEBAKI et al. (2015) was adapted and used in this study applied to
Porto, Rioja and Bordeaux wine regions.
Results have shown that Porto, Rioja and Bordeaux consumers have similar sociodemographic
profile. Their main motivations to visit these wine regions are educational experiences, the
existence of core wine activities and the desire for escape and socialization. When we have
analyzed the motivations that mostly influence visitors to return to the wine region,
educational experiences and product involvement are the ones that significantly contribute to
consumer’s loyalty. These findings pose a great emphasis on the need to understand deeper
wine tourism consumer motivations. At the end, there are four distinct segments of these
consumers: the “wine curious”, the “wine interest” and “the wine lovers”.
The theoretical framework proposed might help to support organizations to better understand
the wine tourism consumer behavior. It also enables managers and marketers to target and
develop better market strategies for these segments.
KEYWORDS: Wine tourism, wine marketing, consumer behavior, consumer segmentation,
innovation.
TABLE OF CONTENTS
ABSTRACT ................................................................................................................................. IV
1 | LITERATURE REVIEW ..........................................................................................................9
1.1| WINE TOURISM ......................................................................................................................... 10
1.2 | WINE TOURISM IN MEDITERRANEAN .............................................................................. 11
1.2.1 | PORTO, RIOJA AND BORDEAUX .................................................................................. 11
1.3 | WINE TOURISM BEHAVIOUR AND MOTIVATIONS ...................................................... 14
1.4 | WINE TOURISM CONSUMERS SEGMENTATION ........................................................... 17
1.5 | WINE TOURISM OFFERS IN PORTO, RIOJA AND BORDEAUX ................................... 18
1.6 | VISIT RETURN INTENTION .................................................................................................... 21
1.7 | CONCLUSIONS AND HYPOTHESES .................................................................................... 22
2 | METHODOLOGY ............................................................................................................... 23
2.1 | RESEARCH INSTRUMENT ...................................................................................................... 24
2.1.1 | THE QUESTIONNAIRE ..................................................................................................... 24
2.1.2 | THE MEASURES ................................................................................................................ 24
2.1.3.| SAMPLE AND PROCEDURE ............................................................................................ 29
3 | RESULTS ANALYSIS .......................................................................................................... 32
3.1| MISSING DATA ........................................................................................................................... 33
3.2 | NORMALITY OF DATA ............................................................................................................ 34
3.3 | DESCRIPTIVE STATISTICS ANALYSIS ................................................................................. 35
3.4 | DESCRIPTIVE STATISTICS OF EACH DIMENSION .......................................................... 36
3.5 | RESPONDENTS’ SOCIAL-DEMOGRAPHICS ...................................................................... 44
3.6| INTERNAL CONSISTENCY AND RELIABILITY .................................................................... 49
3.7 | WINE TOURISM CONSUMERS: SOCIO-DEMOGRAPHIC PROFILE ............................ 50
3.7.1 | PORTO WINE TOURISM PROFILE ................................................................................ 50
3.7.2 | RIOJA WINE TOURISM PROFILE................................................................................... 59
3.7.3 | BORDEAUX WINE TOURISM PROFILE ...................................................................... 67
3.8 | EXPLORATORY FACTOR ANALYSIS ................................................................................... 76
3.9 | MULTIVARIATE DATA ANALYSIS ........................................................................................ 81
3.9.1 | CLUSTER ANALYSIS .......................................................................................................... 84
3.10| HYPOTHESES VALIDATION ................................................................................................. 91
4 | DISCUSSION & CONCLUSIONS ..................................................................................... 92
LIMITATIONS AND FUTURE RESEARCH .......................................................................... 97
BIBLIOGRAPHY ................................................................................................................................... 98
APPENDIX ........................................................................................................................................... 102
TABLE OF FIGURES
Figure 1 - Guided visits to wine yards at Monverde ......................................................................... 18
Figure 2 - Educational Experience at Wine Workshops provided at Carmo’s Boutique Hotel
(Porto wine region) ............................................................................................................... 19
Figure 3 - Cultural and traditional immersive experiences at Viña Tondonia, R. Lopez de
Heredia (Rioja Wine Region) ............................................................................... 19
Figure 4 - Gastronomy and Wine experiences at Marqués de Murrieta’s restaurant (Rioja
wine region) ............................................................................................................................ 20
Figure 5 - Wine event at Bordeaux (Bordeaux wine region) ........................................................... 20
Figure 6 - eBook produced delivered at the end of the survey ..................................................... 30
Figure 7 - Posts on Facebook promoting the survey ........................................................................ 31
Figure 8 - Gender ..................................................................................................................................... 44
Figure 9 - Age ........................................................................................................................................... 45
Figure 10 - Educational Level ................................................................................................................ 46
Figure 11 - Monthly Income (gross) in relation to average in your country ................................ 47
Figure 12 - Country of Origin ................................................................................................................ 48
Figure 13 - Visit Frequency by Gender – Porto ................................................................................ 51
Figure 14 - Visit Return Intention by Gender – Porto ...................................................................... 52
Figure 15 - Visit Frequency by Age - Porto ........................................................................................ 53
Figure 16 - Visit Return Intention by Age - Porto ............................................................................. 54
Figure 17 - Visit Frequency by Education Level - Porto .................................................................. 55
Figure 18 - Visit Return Intention by Education Level - Porto ....................................................... 56
Figure 19 - Visit Frequency by Income - Porto.................................................................................. 57
Figure 20 - Visit Return Intention by Income – Porto ...................................................................... 58
Figure 21 - Visit Frequency by Gender – Rioja .................................................................................. 59
Figure 22 - Visit Return Intention by Gender - Rioja ........................................................................ 60
Figure 23 - Visit Frequency by Age - Rioja ......................................................................................... 61
Figure 24 - Visit Return Intention by Age - Rioja .............................................................................. 62
Figure 25 - Visit Frequency by Education Level - Rioja ................................................................... 63
Figure 26 - Visit Return Intention by Education Level - Rioja ........................................................ 64
Figure 27 - Visit Frequency by Income - Rioja ................................................................................... 65
Figure 28 - Visit Return Intention by Income – Rioja ....................................................................... 66
Figure 29 - Visit Frequency by Gender - Bordeaux .......................................................................... 67
Figure 30 - Visit Return Intention by Gender – Bordeaux .............................................................. 68
Figure 31 - Visit Frequency by Age - Bordeaux ................................................................................ 69
Figure 32 - Visit Return Intention by Age - Bordeaux ...................................................................... 70
Figure 33 - Visit Frequency by Education Level – Bordeaux .......................................................... 71
Figure 34 - Visit Return Intention by Education Level - Bordeaux ................................................ 72
Figure 35- Visit Frequency by Income - Bordeaux ........................................................................... 73
Figure 36 - Visit Return Intention by Income - Bordeaux ............................................................... 74
Figure 37 – Causal Relations ................................................................................................................. 81
Figure 38 - Model Summary & Cluster Quality ................................................................................. 84
TABLE OF TABLES
Table 1 - Review sum-up of the motivations that influence potential wine tourists' destination
choice ....................................................................................................................................... 16
Table 2 - Core Wine (CW). Author: Adapted from ALEBAKI ET AL. (2015). ............................... 25
Table 3 - Educational Experience (EE). Author: Adapted from ALEBAKI et al. (2015). ............. 26
Table 4 - Escape & Socialization (ES). Author: Adapted from ALEBAKI et al. (2015). ............... 27
Table 5 - Awareness and Reputation (AR). Author: Adapted from ALEBAKI et al. (2015). ...... 27
Table 6 - Product Involvement (PI). Author: Adapted from ALEBAKI et al. (2015). ................... 28
Table 7 - Visit Frequecy (VF). ................................................................................................................ 28
Table 8 - Return Intention (RI). .............................................................................................................. 29
Table 9 - Skewness and Kurtosis. ......................................................................................................... 34
Table 10 - Descriptive Statistics for each variable. ........................................................................... 35
Table 11 - Descriptive Analysis – Educational Experience ............................................................ 36
Table 12 - Descriptive Analysis – Core Wine .................................................................................... 37
Table 13 - Descriptive Analysis – Escape & Socialization ............................................................... 38
Table 14 - Descriptive Analysis – Awareness & Reputation ........................................................... 39
Table 15 - Descriptive Analysis – Product Involvement .................................................................. 40
Table 16 - Descriptive Analysis – Visit Frequency (Porto) .............................................................. 40
Table 17 - Descriptive Analysis – Visit Frequency (Rioja) ............................................................... 41
Table 18 - Descriptive Analysis – Visit Frequency (Bordeaux) ....................................................... 41
Table 19 - Descriptive Analysis – Visit Return Intention (Porto) ................................................... 42
Table 20 - Descriptive Analysis – Visit Return Intention (Rioja) .................................................... 42
Table 21 - Descriptive Analysis – Visit Return Intention (Bordeaux) ............................................ 43
Table 22 - Reliability ................................................................................................................................ 49
Table 23 –Pearson Chi-Square – Frequency and Gender ............................................................... 51
Table 24 - Pearson Chi-Square – Visit Return and Gender ............................................................. 52
Table 25 - Pearson Chi-Square – Frequency and Age ..................................................................... 53
Table 26 - Pearson Chi-Square – Visit Return and Age ................................................................... 54
Table 27 - Pearson Chi-Square – Frequency and Education .......................................................... 55
Table 28 - Pearson Chi-Square – Visit Return and Education ........................................................ 56
Table 29 - Pearson Chi-Square – Frequency and Income ............................................................... 57
Table 30 - Pearson Chi-Square – Visit Return and Income ............................................................. 58
Table 31 - Pearson Chi-Square – Frequency and Gender ............................................................... 59
Table 32 - Pearson Chi-Square – Return Intention and Gender .................................................... 60
Table 33 - Pearson Chi-Square – Frequency and Age ..................................................................... 61
Table 34 -Return Intention and Age .................................................................................................... 62
Table 35 - Pearson Chi-Square – Frequency and Education .......................................................... 63
Table 36 - Pearson Chi-Square – Return Intention and Education ............................................... 64
Table 37 - Pearson Chi-Square – Frequency and Income ............................................................... 65
Table 38 - Pearson Chi-Square – Visit Return and Income ............................................................. 66
Table 39 - Pearson Chi-Square – Frequency and Gender ............................................................... 67
Table 40 - Pearson Chi-Square – Visit Return and Gender ............................................................. 68
Table 41 - Pearson Chi-Square – Frequency and Age ..................................................................... 69
Table 42 - Pearson Chi-Square – Visit Return and Age ................................................................... 70
Table 43 - Pearson Chi-Square – Frequency and Education .......................................................... 71
Table 44 - Pearson Chi-Square – Visit Return and Education ........................................................ 72
Table 45 - Pearson Chi-Square – Frequency and Income ............................................................... 73
Table 46 - Pearson Chi-Square – Return Intention and Income .................................................... 74
Table 47 - The KMO and Bartlett’s Test ................................................................................................ 77
Table 48 - Total Variance Explained .................................................................................................... 78
Table 49 - Rotated Component Matrixa .............................................................................................. 79
Table 50 - Regression – Model Summary ........................................................................................... 82
Table 51 - ANOVA ................................................................................................................................... 82
Table 52 – Regression Coefficients ...................................................................................................... 83
Table 53 - Cluster 1 – The “Wine Curious” Characterization ......................................................... 85
Table 54 - Cluster 2 – The “Wine Interested” Characterization ..................................................... 87
Table 55 - Cluster 3 – The “Wine Lovers” Characterization ........................................................... 89
Table 56 - Hypotheses Validation ........................................................................................................ 91
Wine tourism is an emerged form of alternative tourism that combines both the wine and tourism industries. It is becoming increasingly important for wine-growing regions.
Wine marketers are faced with insufficient empirical data when examining wine tourism consumers’ profile and behaviour. This issue is a critical success factor for marketers to implement more effective strategies to target consumers and also for managers that aim to promote excellence and innovation in wine tourism market.
Although identifying the wine tourist has been an important dimension in previous studies, information about wine tourism consumer behaviour is rather limited (ALONSO AND ALANT, 2007). Much of the information about wine tourists has been inferred from the suppliers’ perspective rather than from the consumers (MITCHELL et al., 2000). Empirical evidence coming directly from consumer’s side is needed to develop a more attractive and innovative wine tourism targeted products.
What are the main motivations to visit wine regions? Which relation exist between motivations and the visit return by existing customers? Are wine tourism motivations the same for all wine tourism visitants or there are different segments? What are the main socio-demographic profile of the wine tourism consumers from Porto, Rioja and Bordeaux?
The objectives of the present paper are to introduce a theoretical framework that could support organizations to better understand the wine tourism consumer behaviour and to present a model that help marketers to better understand how consumer thinks and acts and enable them to target and develop better market strategies for these segments.
LITERATURE REVIEW
10
LITERATURE REVIEW
1.1| WINE TOURISM
Wine tourism is becoming increasingly important for wine-growing regions and it has been
recognized as part of agricultural tourism, rural tourism, cultural tourism, industrial tourism and
special-interest tourism.
According to GETZ AND BROWN (2006), wine tourism is based on the desire to visit wine
producing regions or in which travelers are induced to visit wine producing regions, and
wineries in particular, while travelling for other reasons.
Wine tourism can be defined as visitation to vineyards, wineries, wine festivals and wine shows
for which grape wine tasting and/or experiencing the attributes of a grape wine region are the
main motivating factors for wine tourism consumers (HALL, 1996). MACIONIS (1996)
proposed a model of wine tourism based around wine motivations to visit a wine region, to
enroll in an activity (wine tasting, for example) or both.
Much of the literature concentrates on the supply side of wine tourism, while knowledge of
the attributes of wine tourists, their purchasing behavior and demographic, behavioral and
attitudinal characteristics is sparse. This tourism activity is “simultaneously a form of consumer
behaviour, a strategy by which destinations develop and market wine-related attractions and
imagery, and a marketing opportunity for wineries to educate and to sell their products directly
to consumers’’ (GETZ AND BROWN, 2006). From consumers’ perspective, wine tourism is
defined as: ‘‘visitation to vineyards, wineries, wine festivals and wine shows for which grape
wine tasting and/or experiencing the attributes of a grape wine region are the prime motivating
factors for visitors’’ (HALL et al., 2000).
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LITERATURE REVIEW
1.2 | WINE TOURISM IN MEDITERRANEAN
Mediterranean countries have long been associated with wine production. Nevertheless, only
recently, as regions come to face the implications of global rural restructuring, have wine and
tourism been utilized for regional development (HALL AND MITCHELL, 2000). Wine was
traded by the ancient Greeks and Phoenicians while, more recently, wine production has
developed into one of the main areas of agricultural production of the region. However, wine
is more than just a farming activity. Wine is part of the way of life for many countries on the
Mediterranean shore and is an essential element in expressing the regional cuisine not only
within the Mediterranean but throughout the world.
1.2.1 | PORTO, RIOJA AND BORDEAUX
Portugal is a country which by virtue of its long trade links with Britain has long used wine as
a means to link wine regions with tourism. The city of Porto in northern Portugal uses the port
wine connection extensively in its promotion as well as in the hosting of events and festivals.
From the perspective of local politicians and government officials such relationships create the
opportunity for long term loyalty from visitors to the region in terms of their wine purchasing
behavior. Market awareness of port has provided an opportunity for Portugal to promote its
other red and white wines, particularly from the Douro valley, which is the site of the port
grape vineyards.
The Alto Minho region in northern Portugal which is best known in wine terms as producers
of Vinho Verde has also been attempting to develop linkages between wine and tourism. The
Vinho Verde DOC region is Portugal’s largest demarcated wine region. Wine tourism related
development has included the development of wine routes, homestay accommodation and
guides to the gastronomic opportunities in the region.
Spain is also increasingly utilizing the large number of tourists it receives as a means to promote
its wine regions and wine types. For, example sherry is undergoing a revival while regions such
as the Rioja in northern Spain have established an export department which coordinates the
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LITERATURE REVIEW
activities of the various bodegas in the area and which utilizes the links between wine and
tourism as a major promotional tool.
Rioja wine region has a “Denominación de Origen Calificada” (D.O.Ca., "Qualified Designation
of Origin"). The wine from Rioja is made from grapes grown in the autonomous communities
of La Rioja and Navarre, and the Basque province of Álava. Rioja is further subdivided into
three zones: Rioja Alta, Rioja Baja and Rioja Alavesa. Many wines have traditionally blended
fruit from all three regions, though there is a slow growth in single-zone wines.
For quite some time, the Rioja wine industry has been dominated by local family vineyards and
co-operatives that have bought the grapes and make the wine. Some bodegas would buy
fermented wine from the co-ops and age the wine to sell under their own label. In recent times
there has been more emphasis on securing vineyard land and making estate bottled wines from
the bodegas.
Investment in modernizing the Spanish wine industry has come from the private sector rather
than through the conservative cooperative system. Interestingly, it is also the private sector
which has also been the most enthusiastic about wine tourism, although some government and
EU funding has been put into rural tourism development in the wine regions.
Bordeaux is the largest French wine region (with 120 000ha of vineyards). By definition,
Bordeaux wine is any wine produced in the Bordeaux region of France, centered on the city of
Bordeaux and covering the whole area of the Gironde. Average vintages produce over 700
million bottles of Bordeaux wine, ranging from large quantities of everyday table wine, to some
of the most expensive and prestigious wines in the world. The vast majority of wine produced
in Bordeaux is red with sweet white wines (most notably Sauternes), dry whites, and (in much
smaller quantities) rosé and sparkling wines (Crémant de Bordeaux) collectively making up the
remainder. Bordeaux wine is made by more than 8,500 producers or châteaux.
In Bordeaux, wine tourism is booming with the development of popular wineries with some
chateaux in the Medoc region opening all year round and welcoming as many as 70000 visitors
annually. Major Bordeaux producers provide tasting rooms and trained personnel in an effort
to attract more visitors to their chateaux.
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LITERATURE REVIEW
Of all French regions, Bordeaux, with its world-known chateaux is one of the most popular
destinations for wine travelers because of the reputation of its wines and its close proximity to
the sandy beaches.
To sum up, wine tourism is defined as tourism in which the opportunity for wine related
experiences contributes significantly to the reason for travel to the destination or to itinerary
planning while at the destination.
Wine tourism has been identified as sector that could be drivers for increased tourism in the
Mediterranean region.
The importance of wine tourism is growing and it becomes relevant for the industry to
understand more deeply consumer behavior so that offers can be more attractive and
innovative. Most part of the information regarding wine tourists has been obtained from the
suppliers’ perspective rather than from the consumers’ side (MITCHELL et al., 2000).
Therefore, empirical evidence coming directly from consumers is in great need to develop a
more accurate strategy. Although identifying the wine tourist has been an important dimension
in previous studies, information about wine tourism consumer behavior is rather limited
(ALONSO et al., 2007). Wine marketers are faced with insufficient empirical data when
examining wine tourists’ characteristics and behavior. This issue is a critical success factor for
marketers to implement more effective strategies to target consumers and also for managers
that aim to promote excellence and innovation in wine tourism market, specially focusing in
Porto, Rioja and Bordeaux wine regions. The general purpose of this research is to undertake
a review of existing wine tourism activities, profile the wine tourist by understanding their
motivations in order to identify areas for growth and make recommendations with respect to
an action plan that will develop wine, tourism and expand tourism growth.
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LITERATURE REVIEW
1.3 | WINE TOURISM BEHAVIOUR AND MOTIVATIONS
MITCHELL et al. (2000) proposed a framework that integrates demand and supply of the wine
tourism experience. The main focus of this framework is the wine tourism experience that the
consumer faces when getting into contact with the elements comprising the wine tourism
product (wines, wineries, festivals, wine hotels, etc). Wine tourist's demand comprises their
motivations, perceptions, past experiences, preferences, information and expectations. The
selection of destinations and visits to wine regions' attractions are affected by past experiences
and the degree of enjoyment with these experiences.
MITCHELL et al. (2000) presented a three-dimensional model to provide a more holistic view
of the winery experience. The framework combines the spatial (setting) and the temporal (stage
of travel time) dimensions of the wine tourism experience (the spatial-temporal model). A pre-
visit experience in a familiar setting, for example, drinking wine from the host region at home
before the winery visit, is placed at the familiar/past/real end of each dimension. At the other
end might be the recollection of the winery experience that takes place at another location
(post-visit/imagined/remote).
CHARTERS AND ALI-KNIGHT (2002) proposed a three-dimensional model incorporating
motivation, intention and integration of travel activities (the motivation-intention-activity
model). Intention is the relationship of the tourist's general level of interest in wine to their
immediate purpose of visiting a specific winery and the reasons for their overall presence in
the region. Travel activities vary from focusing entirely on the winery experience to winery
visits forming a small part of a mix of attractions. The relationship of the winery to other
tourism activities increases in this later situation.
DODD (2000) proposed a model to winery visitors' behavior that incorporates socio-
demographic, psychographic and behavioral variables, information search, perceptions and the
outcomes of the visits (the wine purchasing model). The visitor's demographic and
psychographic characteristics such as attitudes, knowledge and behavioral consumption may
have a relationship with purchases at wineries. Differences were found in the perceptions of
winery and service attributes between groups differing in age and income.
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LITERATURE REVIEW
Market segmentation is based on a mix between socio-demographic and psychographic
variables. According to BRUWER et al. (2002) visitors with similar demographics may present
considerable differences concerning their attitudes, lifestyle and wine consumption behaviour.
Therefore, in combination with psychographic variables, such as motivations, lifestyle,
interests, values, personality, should also be used as criteria for segmentation and provide a
better insight into ‘who’ exactly the wine tourist is (GALLOWAY et al., 2008).
Some researchers have identified the primary motivations of wine tourists being ‘wine tasting
and purchasing’ (HALL et al., 2000; ALANT AND BRUWER, 2004), and secondary motivations
such as ‘socializing’, ‘learning about wine’, ‘entertainment’, ‘rural setting’, ‘relaxation’ (HALL et
al., 2000; CARMICHAEL, 2005; BRUWER AND ALANT, 2009).
The wine tourism experience is more than drinking wine (ROBERTS AND SPARKS, 2006). The
Push–Pull Theory (CROMPTON, 1979), push factors include the benefits of wine (GETZ et al.,
2008), which are linked with pull factors, namely particular attributes. The combination of push
and pull factor are the driving forces that enable the decision of the consumer to visit the wine
region or the winery (MITCHELL et al., 2000) and, as consequence, help to shape the
attractiveness of each destination.
MITCHELL et al. (2000) have made a distinction between ‘primary’ (for example, wine tasting
and purchasing) and ‘secondary’ wine tourism motivations (attending to food and wine events).
According to ALANT AND BRUWER (2004), motivation has three sub-dimensions of
motivation, namely: the visitor; the wine region; and the visit dynamic.
Similarly, GETZ AND BROWN (2006) suggest critical features of wine tourism experiences for
consumers include three core dimensions: “core wine product”, “core destination appeal”, and
“the cultural product”. Several studies examined the relative importance of motivations in
influencing potential wine tourists' destination choice. Table 1 presents a summary of findings.
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LITERATURE REVIEW
Table 1 - Review sum-up of the motivations that influence potential wine tourists' destination choice
AUTHOR PARTICIPANTS MOTIVATIONAL FACTORS
YUAN et al. (2005) Wine Festival Attendees Wine; Festival and Escape; Family
Togetherness; Socialization.
GETZ AND BROWN
(2006) Potential Wine Tourists
Core Wine Product: Core Destination
Appeal; The Cultural Product; Variety;
Tourist oriented.
SPARKS (2007) Potential Wine Tourists Destination Experience; Personal
Development; Core Wine Experience;
GALLOWAY et al.
(2008) Actual Wine Tourists Wine and winery related features;
Reputation; Learning; Value for
money; Staff knowledge;
COHEN AND BEN-NUN
(2009) Potential Wine Tourists Winery Atmosphere; Cultural
Activities; Family Activities.
CLEMENTE-RICOLFE et
al. (20012) Potential Wine Tourists Interest in Wine; Leisure; Cultural
Heritage.
MARZO-NAVVARO and
PEDRAJA-IGLESIAS
(2012)
Potential Wine Tourists Winery Services, Extra Activities; Core
Destination Appeal; Touristic
Development; Cultural Product
ALEBAKI et al. (2015) Winery Visitors
Core Wine Product; Vineyard
Aesthetics;Educational Experience;
Familiarity;Reputation and Novelty;
Socialization.
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LITERATURE REVIEW
1.4 | WINE TOURISM CONSUMERS SEGMENTATION
CHARTERS AND ALIKNIGHT (2002), HALL AND MITCHELL (2008) found that wine tourists
tend to fall into three categories based on their motivation and involvement with wine
(CHARTERS AND ALI-KNIGHT, 2002; HALL AND MITCHELL, 2008). These have been
described as: wine lover (who is an experienced winery visitor, mature with high income and
education, and will purchase wine at a winery), wine interested (likely to have visited other
wine regions but wine is not the sole purpose of the visit to the destination, moderate to high
income and university educated and will purchase wine from the winery) and the curious
tourist (moderate interest in wine, and wineries are as seen ‘just another attraction’, moderate
income and education and may purchase wine).
ALEBAKI AND IAKOVIDOU (2010) reveal that there are four types of visitors who engage in
wine tourism in Northern Greece: the wine lovers, who are usually highly educated with high
income and whose prime objectives for visiting the area are: visiting the winery, meeting the
winemaker and learning more about wine and wine making; the “neophytes”, who are mainly
low income students with a special interest in wine and visiting the winery is their major
incentive; the “occasional visitors”, who are not interested about wine, but are interested on
exploring gastronomy; and the “hangers-on”, whose motivations for visiting the wine region
are not focused on wine, they are not wine consumers in general and they consider the
vineyard or the winery as just another tourism attraction.
To sum up, researchers feel that there is not a stereotypical wine tourist (CHARTERS AND ALI-
KNIGHT, 2002, MITCHELL AND HALL, 2006).
A number of methods of segmenting and profiling winery visitors highlight the complexity of
making generalizations about winery visitors (ALONSO ET AL., 2007), however, some of these
studies tend to analyze wine tourists as a homogenous target market.
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LITERATURE REVIEW
1.5 | WINE TOURISM OFFERS IN PORTO, RIOJA AND BORDEAUX
The wine regions of Porto, Rioja and Bordeaux offer a wide range of different experiences, as
we can see on Figures 1, 2, 3, 4, 5. Guided or self-guided wine tours to wine regions, short
gastronomic getaways, a road trip or long vacations with cultural content. These experiences
are incorporated motivations to enroll on wine tourism activities.
Figure 1 - Guided visits to wine yards at Monverde
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LITERATURE REVIEW
Figure 2 - Educational Experience at Wine Workshops provided at Carmo’s Boutique Hotel
(Porto wine region)
Figure 3 - Cultural and traditional immersive experiences at Viña Tondonia, R. Lopez de Heredia
(Rioja Wine Region)
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LITERATURE REVIEW
Figure 4 - Gastronomy and Wine experiences at Marqués de Murrieta’s restaurant (Rioja wine region)
Figure 5 - Wine event at Bordeaux (Bordeaux wine region)
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LITERATURE REVIEW
1.6 | VISIT RETURN INTENTION
In order to understand wine tourism customers’ intention to return to a wine region it is
important to determine the key attributes of the wine tourism experience that drives the
behavior. Some researchers mentioned previously (CHARTERS AND ALI-KNIGHT, 2002;
GETZ & BROWN, 2006) have investigated the attributes that are important to consumers in
the domain of wine tourism. However, this has seldom been researched using existing
customers. GETZ (1999) argues that attributes of a wine region, such as the scenery and open
spaces, also provide an incentive to return to the region. Likewise, HALL ET AL. (2000) have
asserted that visitation to a wine region is frequently motivated by ‘the attributes of a grape
wine region’, referred to as the winescape (see, Peters, 1997). Winescapes are characterized
by three main elements: the presence of vineyards, the winemaking activity and the wineries
where the wine is produced and stored (TELFER, 2001). HALL AND MITCHELL (2002) discuss
the concept of tourist terroir, which they define in terms of the “unique combination of the
physical, cultural and natural environment (that) gives each region its distinctive tourist appeal”.
Thus, this concept expands the notion of winescapes to encompass more of the feeling of
region, which is a culmination of all of its physical and cultural parts. Importantly, and not
unrelated to the tourist terroir, for some tourists, it is the ‘experience of the visit’ that can be
an important factor when considering visitation to a wine region. For others, who might be
more serious wine tourists, purchasing wine is of utmost importance (DODD AND BIGOTTE,
1997). It is argued that the demand for wine tourism is driven by a desire to purchase wine, an
interest in learning more about wine, opportunities for social interaction, and, possibly, health
reasons (HALL et al. 2000; MITCHELL, HALL AND MCINTOSH, 2000).
22
LITERATURE REVIEW
1.7 | CONCLUSIONS AND HYPOTHESES
Literature review suggests that a number of motivations can be used as predictors for the
consumer’s return visit intention to a wine region.
Based on review of the literature, each motivator (core wine, educational experience, escape
and socialization, awareness and reputation and wine involvement) is proposed to have a
positive effect on visitors return intention to a wine region. Then, the wine tourism motivations
are proposed to be ascertain as a multidimensional concept (ALEBAKI et al., 2015) so that we
can have an overall perception of the magnitude of concept to visitor’s return intention.
The motivation multidimensional approach is based on ALEBAKI et al. (2015) study that has
revealed that core wine product, vineyard aesthetics, educational experience are primary
motivations whereas familiarity, reputation and novelty and socialization are considered
secondary.
The hypotheses of the present research are as follows:
H1. There are similarities between Porto, Rioja and Bordeaux wine tourism consumers in terms
of their socio-demographic and psychographic profile (gender, age, income, education level,
frequency of visit and return intention).
H2. Core wine products, product involvement and educational experience are primary
motivations to visit Porto, Rioja and Bordeaux wine regions.
H3: There is a positive relation between motivations and visit return intention on existing
customers.
H4. There are different segments of wine tourism consumers.
The purposes of this chapter are (1) to present the research methodology of this study, (2) to
describe the procedure used in designing the instrument and collecting the data, (3) to explain the
sample selection, and (4) to provide an explanation of the statistical procedures used to analyze the
data.
METHODOLOGY
24
METHODOLOGY METHODOLOGY
2.1 | RESEARCH INSTRUMENT
2.1.1 | THE QUESTIONNAIRE
This research used a structured questionnaire that took into account the information needs
and the data collection method chosen, that was an online questionnaire (see Appendix 1).
Smith (1999) notes that it should give special attention to biases due to the response style. So,
the construction of the questionnaire was carefully designed to motivate the answer and
minimize possible errors and misunderstandings.
Efforts were made so to assure that the questions were as clear and uniform as possible, to
prevent that different meanings could create some confusion among respondents, yielding
fewer correct answers.
Though, an attempt was made to make sure that wordings of the attributes were clear,
objective and not very long, following some authors’ recommendations (MALHOTRA, 1999;
DEVELLIS, 1991). It should be noted that the final part of the questionnaire consisted of socio-
demographic characterization data. The questionnaire was subjected to a pre-test before the
launch.
2.1.2 | THE MEASURES
The measures were adapted from previous studies. In this questionnaire the Likert scale was
used, so that the respondents could classify their position on each one of the questions.
According to MALHOTRA (2006), this scale, widely used, requires respondents to indicate a
degree of agreement or disagreement with each of a series of statements. All of the items
related to motivations were measured on a 5-point scale, where 1 represents “not at all
important” and 5 represents “extremely important”. Visit Freqency was measured on a 5-point
scale, where 1 represents “Strongly disagree” and 5 represents “strongly agree” and Return
Intention was measured on a 5-point scale, where 1 represents “Nor Probably” and 5
represents “For sure”
25
METHODOLOGY METHODOLOGY
The English questionnaire was translated and then reviewed into Spanish, Portuguese and
French. In order to ensure the questionnaire captured the same meanings across languages,
considerable effort was undertaken to ensure conceptual comparability.
The professional questionnaire service, Qualtrics (www.qualtrics.com), was used to create an
online survey and to ensure data protection.
Core Wine scale was measured by eight items (Table 2) adapted from ALEBAKI et al. (2015).
Table 2 - Core Wine (CW). Author: Adapted from ALEBAKI ET AL. (2015).
CODE ITEM
CW_1 To taste the winery’s products
CW_2 To increase my knowledge about wine and viticulture
CW_3 To learn about the winemaking process
CW_4 To learn how to appreciate wine
CW_5 To taste rare/fine wines
CW_6 To have a tour through the vineyards
CW_7 To purchase wines
CW_8 To meet the winemaker
26
METHODOLOGY METHODOLOGY
Educational Experience scale was measured by eight items (Table 3) adapted from ALEBAKI et
al.. (2015).
Table 3 - Educational Experience (EE). Author: Adapted from ALEBAKI et al. (2015).
CODE ITEM
EE_1 Visit to Wineries and Vineyards
EE_2 Participation in Wine Tastings
EE_3 Participation in Wine Courses/Workshops
EE_4 Visit to Wine Bars
EE_5 Stay in Wine Hotels & Spas
EE_6 Visit to Wine Festivals
EE_7 Visit to Cellars
EE_8 Wine Tours (by bus, by cruise, etc)
27
METHODOLOGY METHODOLOGY
Escape and Socialization scale was measured by six items (Table 4) adapted from ALEBAKI et
al. (2015).
Table 4 - Escape & Socialization (ES). Author: Adapted from ALEBAKI et al. (2015).
CODE ITEM
ES_1 To escape routine
ES_2 To enjoy the rural landscape and scenary
ES_3 To relax
ES_4 To be with friends/family
ES_5 To participate in a new and different activity
ES_6 To socialize
Awareness & Reputation scale was measured by five items (Table 5) adapted from ALEBAKI et
al. (2015).
Table 5 - Awareness and Reputation (AR). Author: Adapted from ALEBAKI et al. (2015).
CODE ITEM
ES_1 Prior knowledge or familiarity with the place
ES_2 Positive recommendations by others
ES_3 Pior positive experience
ES_4 To rest of the group influenced to visit the winery
ES_6 Positive reviews in media
28
METHODOLOGY METHODOLOGY
Product Involment scale was measured by three items (Table 6) adapted from ALEBAKI et al.
(2015).
Table 6 - Product Involvement (PI). Author: Adapted from ALEBAKI et al. (2015).
CODE ITEM
PL_1 I have a strong interest in wine
PL_2 Wine is important to me in my lifestyle
PL_3 Drinking wine gives me pleasure
Visit Frequency scale was measured by 3 items (Table 7).
Table 7 - Visit Frequecy (VF).
CODE ITEM
VF_1 Frequency of Visit to Porto
VF_2 Frequency of Visit to Rioja
VF_3 Frequency of Visit to Bordeaux
29
METHODOLOGY METHODOLOGY
Return Intention scale was measured by 3 items (Table 8).
Table 8 - Return Intention (RI).
CODE ITEM
RI_1 Return Intention to Porto
RI_2 Return Intention to Rioja
RI_3 Return Intention to Bordeaux
2.1.3.| SAMPLE AND PROCEDURE
The sample used for the present research was a non-probabilistic convenience sample.
According to MALHOTRA (2006), the convenience sampling technique is a non-probabilistic
technique that seeks to obtain a sample of convenient elements. The selection of sampling
units is left to the researcher. As strengths, the author highlights: lower financial charges, less
time consuming and more convenient.
Regarding our sample, respondents were adults (≥ 18 years), existing consumers of enotourism
programs in Porto, Rioja and Bordeaux Wine Regions.
The study was conducted from January to June 2016. A pre-test was launched with the
purpose to identify and solve problems that might occur with scales and to understand if there
might be any difficulties of understanding and other possible constraints like the length or the
formulation of the questions.
An email was sent with the hyperlink to the questionnaire and a covering e-letter explaining
the purpose of the study and providing assurance of the confidentiality of responses in each
questionnaire. A total of 40 emails were sent, yielding usable 29 questionnaires.
Some analysis to pre-test were made to verify the internal consistency of the measures. The
results were acceptable and also some language adaptations were incorporated.
30
METHODOLOGY METHODOLOGY
Subsequently, final questionnaire was released (see Appendix 1). The questionnaire was
actively promoted in collaboration with some local wine tourism partners from Porto, Rioja and
Bordeaux, mainly winners from GWC awards from previous years. The questionnaire was self-
administered by the respondents that spent online an average of 12 minutes to complete it.
The data was collected during March and June 2016.
In order to encourage respondents to participate an ebook about “Greatest Wine Estates in
Douro Region” was produced and distributed freely to the inquirees after filling out the survey
(figure 6 and Appendix 1). Several digital materials (banners, social media images, etc) were also
produced and distributed to all wine tourism partners so that they could promote the survey
among their costumers. Some advertising (promoted posts) was also made in Facebook to a
segmented audience related to wine and enotourism (Figure 7).
Figure 6 - eBook produced delivered at the end of the survey
Note: The e-book can be downloaded at: http://bit.ly/EnoTurismo
31
METHODOLOGY METHODOLOGY
Figure 7 - Posts on Facebook promoting the survey
The purposes of this chapter are (1) to analyse missing data and normality of the variables (2) to
present descriptive statistics analysis, (3) to characterize the respondents’ profile, (4) to ascertain
exploratory factor analysis (5) to proceed with multivariate data analysis (regression and cluster
analysis) (6) and to present detailed analysis for each wine region of the study.
Missing data, descriptive statistics analysis, normality of data, exploratory factor analysis,
regressions were obtained and analysed through SPSS 20.0 software for Windows.
Exploratory factor analysis with Principal Component Analysis was performed with the purpose to
assess firstly the dimensionality of the measures, as indicated by PING (2004) and GERBING AND
ANDERSON (1988). Then, multivariate data analysis(regression and cluster analysis) were
conducted.
RESULTS ANALYSIS
33
RESULTS ANALYSIS
3.1| MISSING DATA
Although the responses were mandatory on the questionnaire, some respondents did not
completed it. Therefore, before conducting the exploratory factor analysis, missing data needs
to be analysed. It must be determined if missing data is systematic (represent bias) or can be
ignored. Little's missing completely at random (MCAR test) (LITTLE AND RUBIN, 2002), which
is a chi-square test for missing completely at random was used for the analysis.
Little's MCAR test was run on the full 307 questionnaire responses, resulting in χ2=770,260,
df=738, p=0,199. This statistically nonsignificant result indicated that unanswered
questionnaire questions did not follow any systematic patterns, and consequently, incomplete
records could be deleted without biasing the data (TABACHNICK AND FIDELL, 2007).
Furthermore, a manual check was undertaken to remove potentially bug responses.
To sum up, in total, there were 307 respondents, of which 256 were complete and therefore
used in the study.
34
RESULTS ANALYSIS
3.2 | NORMALITY OF DATA
Testing whether the assumptions for multivariate normality are met is impractical as it involves
examining an infinite number of linear combinations. One solution is to examine the
distribution of each observed variable (KLINE, 2005).
The parametric tests are robust to lower absolute values of skewness to 3 and absolute values
of kurtosis inferior to 7-10 (KLINE, 1998). Therefore, the analysis of skewness and kurtosis
(Table 9) indicate that data tend to a normal distribution.
Table 9 - Skewness and Kurtosis.
SKEWNESS KURTOSIS
Educational Experience 0,259 -0,135
Core Wine -0,593 0,369
Escape and Socialization -0,589 0,616
Awareness and Recognition -0,370 0,375
Product Involvement -1,210 2,304
Return Intention -0,092 -0,162
Visit Frequency 0,689 0,382
35
RESULTS ANALYSIS
3.3 | DESCRIPTIVE STATISTICS ANALYSIS
Table 10 provides the mean and standard deviation scores of the constructs adopted in this
study. Respondents were asked to rate each item on a 5 point scale ranging. Overall, the mean
scores for the seven scales shows positive mean values which ranged from 2,36 to 4,15.
Table 10 - Descriptive Statistics for each variable.
MEAN STD. DEVIATION
Educational Experience 2,83 0,81
Core Wine 3,67 0,68
Escape and Socialization 3,82 0,70
Awareness and Recognition 3,33 0,70
Product Involvement 4,15 0,76
Return Intention 3,56 0,75
Frequency of Visit 2,36 0,71
36
RESULTS ANALYSIS
3.4 | DESCRIPTIVE STATISTICS OF EACH DIMENSION
According to Table 11, among Educational Experience, visit to wineries and vineyards (mean
3,30), visit to cellars (3,16) and visit to wine bars (3,14) are the activities with more engagement
among respondents.
Table 11 - Descriptive Analysis – Educational Experience
Educational Experience n = 256
MEAN STD. DEVIATION
EE - Visit to Wineries and
Vineyards 3,30 1,039
EE - Visit to Cellars 3,16 1,013
EE - Visit to Wine Bars 3,14 1,013
EE - Partipation in Wine
Tastings 3,11 1,104
EE - Visit to Wine Festivals 2,73 1,132
EE - Stay in Wine Hotels &
Spas 2,54 1,184
EE - Participation in Wine
Courses/Workshops 2,37 1,147
EE - Wine Tours (by bus, by
cruise, etc) 2,28 1,227
37
RESULTS ANALYSIS
Regarding Core Wine and as per Table 12, to taste winery’s products (mean 3,92), to increase
knowledge about wine and viticulture (3,88) and to learn how to appreciate wine (3,84) are the
activities that mostly motivated the respondents.
Table 12 - Descriptive Analysis – Core Wine
Core Wine = 256
MEAN STD. DEVIATION
CW - To taste the winery's products 3,92 0,815
CW - To increase my knowledge about
wine and viticulture 3,88 0,863
CW - To learn how to appreciate wine 3,84 0,907
CW - To taste rare/fine wines 3,75 0,982
CW - To have a tour through the vineyards 3,74 0,833
CW - To meet the winemaker 3,65 1,006
CW - To learn about the winemaking
process 3,42 0,983
CW - To purchase wines 3,24 1,004
38
RESULTS ANALYSIS
According to Table 13, among Escape & Socialization, enjoy the rural landscape and scenery
(mean 4,12), to relax (4,07) and to be with friends/family (3,95) are the activities with more
engagement among respondents.
Table 13 - Descriptive Analysis – Escape & Socialization
Escape & Socialization n = 256
MEAN STD. DEVIATION
ES - To enjoy the rural landscape and
scenery 4,12 0,737
ES - To relax 4,07 0,811
ES - To be with friends/family 3,95 0,913
ES - To participate in a new and different
activity 3,66 0,965
ES - To escape routine 3,56 0,976
ES - To socialize 3,54 1,095
39
RESULTS ANALYSIS
Regarding Awareness and Reputation and as per Table 14, positive recommendations by others
(mean 3,68), prior positive experience (3,60) and positive reviews in media (3,40) are the factors
that mostly motivated the respondents.
Table 14 - Descriptive Analysis – Awareness & Reputation
Awareness & Reputation n = 256
MEAN STD. DEVIATION
AR - Positive recommendations by others 3,68 0,817
AR - Prior positive experience 3,60 0,985
AR - Positive reviews in media 3,40 0,936
AR - Prior knowledge or familiarity with the place 3,05 0,960
AR - The rest of the group influenced my intention to
visit the winery 2,93 1,036
40
RESULTS ANALYSIS
According to Table 15, among Product Wine Involvement, drinking wine as a pleasure (mean
4,35), strong interest in wine (4,19) and wine as a lifestyle (3,91) are all highly valued by
respondents.
Table 15 - Descriptive Analysis – Product Involvement
Descriptive Statistics n = 256
Regarding Visit Frequency in Porto as per Table 16, 39,1 % visited Porto wine region lot of
times. 20,7% several times and only 7,4 never visited.
Table 16 - Descriptive Analysis – Visit Frequency (Porto)
VF - Oporto (Portugal)_frequency of visit
MEAN STD. DEVIATION
PI - Drinking wine gives me pleasure 4,35 0,703
PI - I have a strong interest in wine 4,19 0,849
PI - Wine is important to me in my lifestyle 3,91 0,994
FREQUENCY PERCENT
A lot of time (6 or more times) 100 39,1
Several times (4-5 times) 53 20,7
Some times (3 times) 38 14,8
A few times (1 or 2 times) 46 18,0
Never 19 7,4
41
RESULTS ANALYSIS
According to Table 17, regarding Visit Frequency to Rioja 27,3% of respondents state they
come a few times and 59,8% state they never went there.
Table 17 - Descriptive Analysis – Visit Frequency (Rioja)
VF - Rioja (Spain)_frequency of visit
Regarding Visit Frequency in Bordeaux as per Table 18, 60,5% never visited it and 19,9%
visited a few times.
Table 18 - Descriptive Analysis – Visit Frequency (Bordeaux)
VF - Bordeaux (France)_frequency of visit
FREQUENCY PERCENT
A lot of time (6 or more times) 6 2,3
Several times (4-5 times) 12 4,7
Some times (3 times) 15 5,9
A few times (1 or 2 times) 70 27,3
Never 153 59,8
FREQUENCY PERCENT
A lot of time (6 or more times) 19 7,4
Several times (4-5 times) 16 6,3
Some times (3 times) 15 5,9
A few times (1 or 2 times) 51 19,9
Never 155 60,5
42
RESULTS ANALYSIS
According to Table 19, regarding Return Intention to Porto, 60,2% of respondents state they
would return for sure and 27,3% state that it might be very likely.
Table 19 - Descriptive Analysis – Visit Return Intention (Porto)
Regarding Return Intention to Rioja as per Table 20, 43,4% state that it is somewhat probable
to come back and 20,7% state that is might be somewhat improbable.
Table 20 - Descriptive Analysis – Visit Return Intention (Rioja)
FREQUENCY PERCENT
Not probable 1 0,4
Somewhat improbable 9 3,5
Somewhat probable 22 8,6
Very likely 70 27,3
For sure 154 60,2
FREQUENCY PERCENT
Not probable 18 7,0
Somewhat improbable 53 20,7
Somewhat probable 111 43,4
Very likely 50 19,5
For sure 24 9,4
43
RESULTS ANALYSIS
According to Table 21, regarding Return Intention to Bordeaux, 39,1% of respondents state
that returning is somewhat probable and 19,5% state that it might be very likely.
Table 21 - Descriptive Analysis – Visit Return Intention (Bordeaux)
Regarding unique visitors by each wine region, 114 respondents (out of 256) have indicated
they had only visited Porto, only 1 had only visited Rioja and 15 have only visited Bordeaux.
Due to this fact, multivariate data analysis will be applied to the three regions as a whole.
FREQUENCY PERCENT
Not probable 17 6,6
Somewhat improbable 49 19,1
Somewhat probable 100 39,1
Very likely 50 19,5
For sure 40 15,6
44
RESULTS ANALYSIS
3.5 | RESPONDENTS’ SOCIAL-DEMOGRAPHICS
As aforementioned, in total there were 256 valid respondents. According to Figure 8, males
comprised about 59% of valid respondents, while female are 41 %.
Figure 8 - Gender
Male; 152; 59%
Female, 104, 41%
Male Female
45
RESULTS ANALYSIS
The profile of the respondents discloses that 41% were aged between 35 to 44 and 75,7% of
the respondents have between 25 and 65 and older years old. Only, 24,3% have less than 35
years (Figure 9)
Figure 9 - Age
14
48
105
52
27
1005
19
41
20
1104
Up to 24 years old 25-34 years old 35-44 years old 45-54 years old 55-64 years old 65 and older
Frequency Percent
46
RESULTS ANALYSIS
Regarding educational level, 47,3% of respondents have a degree, 29,7% a master and 6,6%
hold a PhD (figure 10).
Figure 10 - Educational Level
7
35
121
76
17
2,7
13,7
47,3
29,7
6,6
0
20
40
60
80
100
120
140
160
180
Below High School High School Degree Master PhD
Frequency Percent
47
RESULTS ANALYSIS
In terms of income, 48% of respondents have a similiar Monthly Income (gross) in relation to
average in their country. 38,3% have a high Monthly Income (gross) in relation to average and
5,9% very high. Only 5,9% report having a lower monthly income and 2,0% very low compared
with the average in their country (Figure 11).
Figure 11 - Monthly Income (gross) in relation to average in their country
15
98
123
15
506
38
48
0602
Very High (comparedwith average)
High (compared withaverage)
Similar (compared withaverage)
Low (compared withaverage)
Very Low
Frequency Percent
48
RESULTS ANALYSIS
Regarding country of origin, 62,1% come from Portugal, 16,4% come from France and 5,5%
come from Brazil and Spain each.
Figure 12 – Country of Origin
4
4
42
14
159
1
3
14
8
1
1
1
1
3
United Kingdom
United States of Ameria
France
Spain
Portugal
Italy
Germany
Brazil
Benelux
Sweden
Denmark
Finland
Russia
Other
49
RESULTS ANALYSIS
3.6| INTERNAL CONSISTENCY AND RELIABILITY
Cronbach's alpha coefficient of equivalence, which is usually simply called by Cronbach Alpha
coefficient or α coefficient, is widely used in scale reliability study (GERBING AND
ANDERSON, 1988). It indicates the proportion of the variance of the scale that is assigned to
the true value of the underlying latent variable of the items (DEVELLIS, 1991). Cronbach’s alpha
coefficient is the basic statistic for determining the reliability of a measure based on internal
consistency (CHURCHILL AND GILBERT, 1979).
As can be depicted on Table 22, except for Visit Frequency, Cronbach’s alpha ranges from
0,604 to 0,889. DEVELLIS (1991) states that, Cronbach’s alpha coefficient values below 0,60
are unacceptable, between 0,65 and 0,70 are minimally acceptable, between 0,70 and 0,80 are
good, and between 0,80 and 0,90 are very good. In this case, Cronbach’s alpha good, except
for Visit Frequency that is unacceptable. For this reason, multivariate analysis will not include
this construct.
Table 22 - Reliability
DIMENSION CRONBACH'S ALPHA N OF ITEMS
Core Wine 0,889 7
Educational Experience 0,875 8
Escape & Socialization 0,852 6
Awareness & Reputation 0,791 5
Product Involvement 0,872 3
Visit Frequency 0,090 3
Return Intention 0,604 3
50
RESULTS ANALYSIS
3.7 | WINE TOURISM CONSUMERS: SOCIO-DEMOGRAPHIC PROFILE
In order to better understand the profile of the visitants of Porto, Rioja and Bordeaux wine
regions and to ascertain H1 (There are similarities between Porto, Rioja and Bordeaux wine
tourism consumers in terms of their socio-demographic and psychographic profile (gender, age,
income, education level, frequency of visit and return intention), a crosstabs descriptive
analysis was made between visit frequency and return intention (psychographic) with
sociodemographic variables (gender, age, income, education level).
3.7.1 | PORTO WINE TOURISM PROFILE
As can be depicted on Figure 13 and Figure 14, 55,9 % of the total of the respondents have
already visited Porto and are males. From this percentage 37,9% are frequent visitors.
53,1% of these segment indicated that it is very likely/for sure they will return.
36,7% of the total of the respondents have already visited Porto and are females. From this
percentage 21,9% are frequent visitors.
34,4% of these segment indicated that it is very likely/for sure they will return.
51
RESULTS ANALYSIS
Figure 13 - Visit Frequency by Gender – Porto
Table 23 –Pearson Chi-Square – Frequency and Gender
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 3,341a 4 0,502
Likelihood Ratio 3,329 4 0,504
Linear-by-Linear Association 2,778 1 0,096
N of Valid Cases 256
a. 0 cells (0,0%) have expected count less than
5. The minimum expected count is 7,72.
4%
10%
8%
13%
25%
4%
8%7%
8%
14%
Never A few times (1 or 2 times)
Some times (3 times) Several times (4-5 times)
A lot of time (6 or more times)
Gender Male % of Total Gender Female % of Total
52
RESULTS ANALYSIS
Figure 14 - Visit Return Intention by Gender – Porto
Table 24 - Pearson Chi-Square – Visit Return and Gender
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 2,678a 4 0,613
Likelihood Ratio 3,005 4 0,557
Linear-by-Linear
Association 1,202 1 0,273
N of Valid Cases 256
a. 3 cells (30,0%) have expected count less than
5. The minimum expected count is 0,41.
0%2%
4%
16%
37%
0%2%
4%
11%
23%
Not probable Somewhat improbable
Somewhat probable
Very likely For sure
Gender Male % of Total Gender Female % of Total
53
RESULTS ANALYSIS
On Figure 15 and Figure 16, we can see that 39,5% of the Porto wine tourists’ that visit
several/a lot of times have between 35-44 years, followed by 45-54 years with 11,7%.
36,3% that said that it is very likely to return have between 35-44 years, followed by 45-54
years that represent 18,8% that are very likely to return.
Figure 15 - Visit Frequency by Age - Porto
Table 25 - Pearson Chi-Square – Frequency and Age
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 35,158a 20 0,019
Likelihood Ratio 32,522 20 0,038
Linear-by-Linear
Association 0,047 1 0,828
N of Valid Cases 256
a. 14 cells (46,7%) have expected count less than 5. The minimum expected
count is 0,74.
1%
3%
1%0% 0%
2%
3%3%
3%
8%
2%
5%
6%
11%
18%
2%3% 3%
4%
7%
1%2%
1%2%
4%
0%
2%
1%0%
1%
Never A few times (1 or 2 times)
Some times (3 times)
Several times (4-5 times)
A lot of time (6 or more times)
Age Up to 24 years old % of Total Age 25-34 years old % of Total
Age 35-44 years old % of Total Age 45-54 years old % of Total
Age 55-64 years old % of Total Age 65 and older % of Total
54
RESULTS ANALYSIS
Figure 16 - Visit Return Intention by Age - Porto
Table 26 - Pearson Chi-Square – Visit Return and Age
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 24,052a 20 0,240
Likelihood Ratio 22,009 20 0,340
Linear-by-Linear
Association 0,212 1 0,645
N of Valid Cases 256
a. 19 cells (63,3%) have expected count less than 5. The minimum expected count is
0,04.
0%1% 0%
2% 2%
0%1%
2%
4%
11%
0% 0%
4%
10%
27%
0% 0% 1%
7%
12%
0% 0% 0%
3%
7%
0% 0% 1%2% 1%
Not probable Somewhat improbable Somewhat probable Very likely For sure
Age Up to 24 years old % of Total Age 25-34 years old % of TotalAge 35-44 years old % of Total Age 45-54 years old % of TotalAge 55-64 years old % of Total Age 65 and older % of Total
55
RESULTS ANALYSIS
As can be observed on Figure 17, 30,9% of the Porto wine tourism consumers visit the wine
region several/a lot of times have a degree and 11,3% hold a master.
41,8% that state that are very likely/for sure will return have a degree and 25,8% a master.
Figure 17 - Visit Frequency by Education Level - Porto
Table 27 - Pearson Chi-Square – Frequency and Education
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 17,464a 16 0,356
Likelihood Ratio 19,413 16 0,248
Linear-by-Linear
Association 0,021 1 0,884
N of Valid Cases 256
a. 10 cells (40,0%) have expected count less than
5. The minimum expected count is ,52.
0% 1% 1%0%
1%1%
4%
1%
4%4%
2%
7% 7%
9%
21%
4%5% 5%
7%
10%
0%
2%
1% 1%
3%
Never A few times (1 or 2 times)
Some times (3 times) Several times (4-5 times)
A lot of time (6 or more times)
Education Level Below High School % of Total Education Level High School % of TotalEducation Level Degree % of Total Education Level Master % of TotalEducation Level PhD % of Total
56
RESULTS ANALYSIS
Figure 18 - Visit Return Intention by Education Level - Porto
Table 28 - Pearson Chi-Square – Visit Return and Education
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 41,768a 16 0,000
Likelihood Ratio 14,078 16 0,593
Linear-by-Linear
Association 1,407 1 0,236
N of Valid Cases 256
a. 16 cells (64,0%) have expected count less than
5. The minimum expected count is ,03
0% 0% 0%1% 1%
0%1% 1%
4%
8%
0%1%
4%
13%
29%
0%1%
3%
8%
18%
0% 0% 0%
2%4%
Not probable Somewhat improbable Somewhat probable Very likely For sure
Education Level Below High School % of Total Education Level High School % of TotalEducation Level Degree % of Total Education Level Master % of TotalEducation Level PhD % of Total
57
RESULTS ANALYSIS
As can be depicted on Figure 19 and 20, 28,9% of Porto wine region tourists that visit several/a
lot of times have an income similar to the average, followed by 25% that have a higher income
compared to the average.
40,2% that are very likely/for sure will return have an income similar to the average and 35,2
higher than average.
Figure 19 - Visit Frequency by Income - Porto
Table 29 - Pearson Chi-Square – Frequency and Income
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 30,488a 16 ,016
Likelihood Ratio 33,232 16 ,007
Linear-by-Linear
Association 3,054 1 ,081
N of Valid Cases 256
a. 13 cells (52,0%) have expected count less than 5. The minimum expected count is
0,37.
0%
2%
0%1%
3%
4%4%
6%
8%
17%
3%
11%
6%
11%
18%
0%
2%2%
1% 1%0% 0%
1%
0% 0%
Never A few times (1 or 2 times)
Some times (3 times) Several times (4-5 times)
A lot of time (6 or more times)
Very High (compared with average) % of Total High (compared with average) % of Total
Similar (compared with average) % of Total Low (compared with average) % of Total
Very Low % of Total
Monthly Income (gross) in relation to average in your country:
58
RESULTS ANALYSIS
Figure 20 - Visit Return Intention by Income – Porto
Table 30 - Pearson Chi-Square – Visit Return and Income
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 19,422a 16 0,247
Likelihood Ratio 18,526 16 0,294
Linear-by-Linear
Association 9,559 1 0,002
N of Valid Cases 256
a. 17 cells (68,0%) have expected count less than
5. The minimum expected count is 0,02.
0% 0% 0%1%
4%
0%1%
2%
9%
27%
0%
2%
5%
14%
27%
0% 0% 0%
3%2%
0% 0% 0% 1% 0%
Not probable Somewhat improbable Somewhat probable Very likely For sure
Very High (compared with average) % of Total High (compared with average) % of Total
Similar (compared with average) % of Total Low (compared with average) % of Total
Very Low % of Total
Monthly Income (gross) in relation to average in your country:
59
RESULTS ANALYSIS
3.7.2 | RIOJA WINE TOURISM PROFILE
As can be depicted on Figure 21 and Figure 22, 59,8% never visited Rioja. 24,2% that visited
are men and 16% female. 43,4% of males and 28,9% of females that visited said that is probable
to return.
Figure 21 - Visit Frequency by Gender – Rioja
Table 31 - Pearson Chi-Square – Frequency and Gender
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 9,360a 4 0,053
Likelihood Ratio 9,361 4 0,053
Linear-by-Linear Association 2,541 1 0,111
N of Valid Cases 256
a. 3 cells (30,0%) have expected count less than 5. The minimum expected
count is 2,44.
35%
19%
3%2% 1%
25%
8%
3% 3%2%
Never A few times (1 or 2 times)
Some times (3 times)
Several times (4-5 times)
A lot of time (6 or more times)
Gender Male % of Total Gender Female % of Total
60
RESULTS ANALYSIS
Figure 22 - Visit Return Intention by Gender - Rioja
Table 32 - Pearson Chi-Square – Return Intention and Gender
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 2,271a 4 0,686
Likelihood Ratio 2,266 4 0,687
Linear-by-Linear Association 0,436 1 0,509
N of Valid Cases 256
a. 0 cells (,0%) have expected count less than 5. The minimum expected count is 7,31.
4%
12%
28%
11%
5%
3%
9%
16%
9%
5%
Not probable Somewhat improbable
Somewhat probable Very likely For sure
Gender Male % of Total Gender Female % of Total
61
RESULTS ANALYSIS
On Figure 23 and Figure 24, we can see that 17% of the visitants are between 35-44 years,
followed by 45-54 years. 31,6% of visitants that have between 35-44 years said is probable to
return.
Figure 23 - Visit Frequency by Age - Rioja
Table 33 - Pearson Chi-Square – Frequency and Age
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 21,645a 20 0,360
Likelihood Ratio 27,482 20 0,122
Linear-by-Linear Association 3,386 1 0,066
N of Valid Cases 256
a. 19 cells (63,3%) have expected count less than 5. The minimum expected
count is 0,23.
5%
0% 0% 0% 0%
13%
5%
0% 0% 0%
23%
11%
3% 2%
1%
11%
5%
2% 2%
0%
5% 5%
0% 0% 0%
2%
1%
0% 0% 0%
Never A few times (1 or 2 times)
Some times (3 times) Several times (4-5 times)
A lot of time (6 or more times)
Age Up to 24 years old % of Total Age 25-34 years old % of TotalAge 35-44 years old % of Total Age 45-54 years old % of TotalAge 55-64 years old % of Total Age 65 and older % of Total
62
RESULTS ANALYSIS
Figure 24 - Visit Return Intention by Age - Rioja
Table 34 -Return Intention and Age
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 27,588a 20 0,120
Likelihood Ratio 31,065 20 0,054
Linear-by-Linear
Association 0,460 1 0,497
N of Valid Cases 256
a. 15 cells (50,0%) have expected count less than 5. The minimum expected count is
0,70.
1% 2%1%
2%
0%
2%
5%
9%
1%2%2%
7%
19%
9%
3%
1%
4%
7% 6%
3%
0%
3%
5%
1% 1%0%
1%
2%
0% 0%
Not probable Somewhat improbable
Somewhat probable Very likely For sure
Age Up to 24 years old % of Total Age 25-34 years old % of TotalAge 35-44 years old % of Total Age 45-54 years old % of TotalAge 55-64 years old % of Total Age 65 and older % of Total
63
RESULTS ANALYSIS
As can be observed on Figure 25, 18,4% of the visitants have a degree and 12,1% a master.
34% of visitants that have a degree and 21,5% that have a master said is probable to return.
Figure 25 - Visit Frequency by Education Level - Rioja
Table 35 - Pearson Chi-Square – Frequency and Education
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 8,116a 16 0,945
Likelihood Ratio 8,010 16 0,949
Linear-by-Linear
Association 0,446 1 0,504
N of Valid Cases 256
a. 16 cells (64,0%) have expected count less than 5. The minimum expected
count is 0,16.
2%
0% 0% 0% 0%
8%
4%
1% 1% 0%
29%
14%
3%
1% 1%
18%
8%
1%2%
1%
4%
2%1% 0% 0%
Never A few times (1 or 2 times)
Some times (3 times) Several times (4-5 times)
A lot of time (6 or more times)
Education Level Below High School % of Total Education Level High School % of Total
Education Level Degree % of Total Education Level Master % of Total
Education Level PhD % of Total
64
RESULTS ANALYSIS
Figure 26 - Visit Return Intention by Education Level - Rioja
Table 36 - Pearson Chi-Square – Return Intention and Education
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 12,839a 16 ,684
Likelihood Ratio 14,986 16 ,526
Linear-by-Linear
Association ,577 1 ,448
N of Valid Cases 256
a. 11 cells (44,0%) have expected count less than 5. The minimum expected
count is 0,49.
% 1% 1% % %1%
3%
8%
1%2%
4%
10%
20%
11%
4%
2%
6%
12%
5%
4%
%1%
3% 2%
%
Not probable Somewhat improbable Somewhat probable Very likely For sure
Education Level Below High School % of Total Education Level High School % of Total
Education Level Degree % of Total Education Level Master % of Total
Education Level PhD % of Total
65
RESULTS ANALYSIS
As can be depicted on Figure 27 and 28, 17,4% of the visitants have an income similar to the
average and 17,2% higher than average.
34% of visitants that have an income similar to the average and 29,7% that have higher said it
is probable to return.
Figure 27 - Visit Frequency by Income - Rioja
Table 37 - Pearson Chi-Square – Frequency and Income
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 20,015a 16 0,220
Likelihood Ratio 23,217 16 0,108
Linear-by-Linear
Association 7,191 1 0,007
N of Valid Cases 256
a. 16 cells (64,0%) have expected count less than 5. The minimum expected count is
,12.
2%3%
0% 0% 0%
21%
10%
4%
2%1%
30%
13%
1%2%
1%
4%
2%0% 0% 0%
2%
0% 0% 0% 0%
Never A few times (1 or 2 times)
Some times (3 times) Several times (4-5 times)
A lot of time (6 or more times)
Very High (compared with average) % of Total High (compared with average) % of Total
Similar (compared with average) % of Total Low (compared with average) % of Total
Very Low % of Total
Monthly Income (gross) in relation to average in your country:
66
RESULTS ANALYSIS
Figure 28 - Visit Return Intention by Income – Rioja
Table 38 - Pearson Chi-Square – Visit Return and Income
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 27,498a 16 0,036
Likelihood Ratio 25,781 16 0,057
Linear-by-Linear Association 7,780 1 0,005
N of Valid Cases 256
a. 13 cells (52,0%) have expected count less than 5. The minimum expected count is
0,35.
1% 1% 1%
2%1%2%
7%
16%
10%
4%3%
11%
23%
7%
4%
0%
2%
3%
1%0%
1% 0% 1%0% 0%
Not probable Somewhat improbable Somewhat probable Very likely For sure
Very High (compared with average) % of Total High (compared with average) % of Total
Similar (compared with average) % of Total Low (compared with average) % of Total
Very Low % of Total
Monthly Income (gross) in relation to average in your country:
67
RESULTS ANALYSIS
3.7.3 | BORDEAUX WINE TOURISM PROFILE
As can be depicted on Figure 29 and Figure 30, 61% of the total visitants never visited
Bordeaux. From the percentage that visited (39%), 22% are male and 16,8 are female.
45,3% of males and 28,9% of females said that it is probable to return.
Figure 29 - Visit Frequency by Gender - Bordeaux
Table 39 - Pearson Chi-Square – Frequency and Gender
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 1,280a 4 0,865
Likelihood Ratio 1,280 4 0,865
Linear-by-Linear
Association 0,145 1 0,704
N of Valid Cases 256
a. 0 cells (,0%) have expected count less than 5. The minimum expected
count is 6,09.
37%
11%
04% 04% 04%
24%
09%
02% 02%04%
Never A few times (1 or 2 times)
Some times (3 times)
Several times (4-5 times)
A lot of time (6 or more times)
Gender Male % of Total Gender Female % of Total
68
RESULTS ANALYSIS
Figure 30 - Visit Return Intention by Gender – Bordeaux
Table 40 - Pearson Chi-Square – Visit Return and Gender
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 10,414a 4 0,034
Likelihood Ratio 10,788 4 0,029
Linear-by-Linear
Association 0,047 1 0,828
N of Valid Cases 256
a. 0 cells (,0%) have expected count less than 5. The minimum expected count is
6,91.
5%
9%
24%
13%
8%
1%
11%
15%
6%7%
Not probable Somewhat improbable
Somewhat probable Very likely For sure
Gender Male % of Total Gender Female % of Total
69
RESULTS ANALYSIS
On Figure 31 and Figure 32, regarding age 12,9% of the visitants have between 35-44 years,
followed by 10,5% that have between 45-54 years. 30,1% of these that reported that they
would probable return have between 35-44 years.
Figure 31 - Visit Frequency by Age - Bordeaux
Table 41 - Pearson Chi-Square – Frequency and Age
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 24,857a 20 0,207
Likelihood Ratio 26,101 20 0,163
Linear-by-Linear Association 0,319 1 0,572
N of Valid Cases 256
a. 17 cells (56,7%) have expected count less than 5. The minimum expected
count is 0,59.
3%
0% 1%0%
1%
12%
4%
1%0%
2%
28%
7%
2% 2% 2%
10%
5%
2% 2% 2%
5%4%
0%2%
0%
2%
1%0% 0% 0%
Never A few times (1 or 2 times)
Some times (3 times)
Several times (4-5 times)
A lot of time (6 or more times)
Age Up to 24 years old % of Total Age 25-34 years old % of TotalAge 35-44 years old % of Total Age 45-54 years old % of TotalAge 55-64 years old % of Total Age 65 and older % of Total
70
RESULTS ANALYSIS
Figure 32 - Visit Return Intention by Age - Bordeaux
Table 42 - Pearson Chi-Square – Visit Return and Age
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 18,939a 20 0,526
Likelihood Ratio 21,023 20 0,396
Linear-by-Linear
Association 0,236 1 0,627
N of Valid Cases 256
a. 13 cells (43,3%) have expected count less than 5. The minimum expected count is
0,66.
1%1%
%
2% 2%2%
4%
7%
3% 3%2%
9%
17%
7%6%
1%
3%
7%
6%
3%
%
2%
5%
2%1%
1% 1%
2%
%%
Not probable Somewhat improbable
Somewhat probable Very likely For sure
Age Up to 24 years old % of Total Age 25-34 years old % of Total
Age 35-44 years old % of Total Age 45-54 years old % of Total
Age 55-64 years old % of Total Age 65 and older % of Total
71
RESULTS ANALYSIS
As can be observed on Figure 33, in terms of education, 16,4% of visitors have a degree and
5,9% have a master. 44,1% of the ones that would come back have a degree and 22,7% have
a master.
Figure 33 - Visit Frequency by Education Level – Bordeaux
Table 43 - Pearson Chi-Square – Frequency and Education
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 23,835a 16 0,093
Likelihood Ratio 20,877 16 0,183
Linear-by-Linear Association 0,079 1 0,779
N of Valid Cases 256
a. 14 cells (56,0%) have expected count less than 5. The minimum expected count is
0,41.
1%0% 0%
1% 0%
8%
2% 2%1% 1%
31%
9%
3%2%
3%
17%
7%
1%2%
4%4%
1%0%
1%0%
Never A few times (1 or 2 times)
Some times (3 times) Several times (4-5 times)
A lot of time (6 or more times)
Education Level Below High School % of Total Education Level High School % of Total
Education Level Degree % of Total Education Level Master % of Total
Education Level PhD % of Total
72
RESULTS ANALYSIS
Figure 34 - Visit Return Intention by Education Level - Bordeaux
Table 44 - Pearson Chi-Square – Visit Return and Education
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 11,083a 16 0,804
Likelihood Ratio 11,363 16 0,787
Linear-by-Linear
Association 0,043 1 0,836
N of Valid Cases 256
a. 10 cells (40,0%) have expected count less than 5. The minimum expected count is
0,46.
% %1%
%
1%1% 2%
5%
2%3%3%
11%
18%
10%
5%
2%
5%
13%
5%5%
%1%
2%2%
1%
Not probable Somewhat improbable Somewhat probable Very likely For sure
Education Level Below High School % of Total Education Level High School % of Total
Education Level Degree % of Total Education Level Master % of Total
Education Level PhD % of Total
73
RESULTS ANALYSIS
As can be depicted on Figure 35 and 36, regarding income, 18,8% of visitors have income
similar to the average and 17,2% higher than average. 34% of the visitors that might return
have income similar to average and 30,1% higher.
Figure 35- Visit Frequency by Income - Bordeaux
Table 45 - Pearson Chi-Square – Frequency and Income
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 17,372a 16 0,362
Likelihood Ratio 24,114 16 0,087
Linear-by-Linear Association 1,163 1 0,281
N of Valid Cases 256
a. 13 cells (52,0%) have expected count less than 5. The minimum expected count is
0,29.
3%2%
1% 0% 0%
21%
9%
3% 3% 3%
29%
10%
2%3%
4%5%
0% 0% 0% 0%2%
0% 0% 0% 0%
Never A few times (1 or 2 times)
Some times (3 times) Several times (4-5 times)
A lot of time (6 or more times)
Very High (compared with average) % of Total High (compared with average) % of Total
Similar (compared with average) % of Total Low (compared with average) % of Total
Very Low % of Total
Monthly Income (gross) in relation to average in your country:
74
RESULTS ANALYSIS
Figure 36 - Visit Return Intention by Income - Bordeaux
Table 46 - Pearson Chi-Square – Return Intention and Income
Chi-Square Tests
VALUE df ASYMP. Sig. (2-SIDED)
Pearson Chi-Square 26,831a 16 0,043
Likelihood Ratio 27,715 16 0,034
Linear-by-Linear Association 9,362 1 0,002
N of Valid Cases 256
a. 13 cells (52,0%) have expected count less than 5. The minimum expected count is 0,33.
1%%
2% 2%2%
2%
7%
15%
9%
6%
3%
11%
18%
9%
7%
1%1%
4%
%%
1%% %
%%
Not probable Somewhat improbable Somewhat probable Very likely For sure
Very High (compared with average) % of Total High (compared with average) % of Total
Similar (compared with average) % of Total Low (compared with average) % of Total
Very Low % of Total
Monthly Income (gross) in relation to average in your country:
75
RESULTS ANALYSIS
To sum up, as we can see by the results of chi-square tests there are no significant differences
in terms of socio-demographic profile of wine tourism consumers from Porto, Rioja and
Bordeaux. So, H1 is confirmed, meaning that Porto, Rioja and Bordeaux wine tourism
consumers have a similar socio-demographic and psychographic background.
76
RESULTS ANALYSIS
3.8 | EXPLORATORY FACTOR ANALYSIS
In this first exploratory phase, Principal Component Analysis (PCA) was used to obtain
preliminary results on the dimensionality of the constructs and to ascertain H2 namely:
H2. Core wine products, product involvement and educational experience are primary
motivations to visit Porto, Rioja and Bordeaux wine regions.
Factor analysis can be used to evaluate whether the number of dimensions conceptualized
could be verified empirically (CHURCHILL AND GILBERT, 1979).
Thus, PCA was performed to assess the ability of the indicators to measure the constructs
theoretically presented. A principal component analysis with Varimax rotation was performed
with all items.
Thirty-seven items were examined through PCA using SPSS 20.0 for Windows. First of all, the
adequacy of data for factor analysis was assessed. The first concern was the sample size.
COMREY AND LEE (1992) defines sample sizes of 100 as poor, 200 as fair, 300 as good, 500
as very good, and 1000 as excellent. HAIR et al. (2005) recommended a sample superior to 200
and a minimum of five respondents for each estimated parameter, and considers more
appropriated a ratio of ten respondents per parameter. Thus, our data is adequate for factor
analysis as it includes 256 cases.
Then, Kaiser–Meyer–Oklin Measure (KMO) of Sampling Adequacy was assessed. The KMO is
calculated for individual and multiple variables and represents the ratio of the squared
correlation between variables to the squared partial correlation between variables (FIELD,
2000). The KMO value varies between 0 and 1. A value of 0 indicates that the sum of partial
correlations is large relative to the sum of correlations, In turn, a value close to 1 indicates that
the patterns of the correlations are compact, and so factor analysis will yield reliable factors.
KAISER (1974) recommendation is that values greater than 0,5 should be accepted.
HUTCHESON AND SOFRONIOU (1999) suggested that KMO values between 0,5 and 0,7 are
normal, values between 0,7 and 0,8 are good, values between 0,8 and 0,9 are great, and values
above 0,9 are superb. The result of our factor analysis revealed a KMO value of 0,893, which
is very good.
77
RESULTS ANALYSIS
Finally, Bartlett’s Test of Sphericity is supposed to reach a significance value to support the
factorability of the correlation matrix obtained from the items. Bartlett’s Test of Sphericity
revealed an approximated Chi-Square value of 4880,583 with a significance value of 0,0005,
which means that the factorability of our correlation matrix is suitable.
The KMO’s and Bartlett’s Test results are depicted on Table 47.
Table 47 - The KMO and Bartlett’s Test
KMO AND BARTLETT'S TEST
KAISER-MEYER-OLKIN MEASURE OF
SAMPLING ADEQUACY. 0,869
BARTLETT'S
TEST OF
SPHERICITY
Approx. Chi-Square 4880,583
df 630
Sig. 0,000
The PCA revealed the presence of seven components with eigenvalues greater than one
instead of the expected eight components, which explained 63,5% of the total variance. Details
regarding the total variance explained are provided in Table 48.
When variables with lower loadings of 0,40 exist, or cross-loadings are substantial, these
variables should be removed from analysis because they are either insufficiently representative
of the factor to which they are related, or are measuring together more than one factor, which
is not pretended to be (HAIR, et al.,1995; CHURCHILL AND GILBERT, 1979; FIELD, 2000).
Besides, PALLANT (2001) claims that if an item loading is above 0,4 (strong loading) it should
not be deleted. In our case, all items were maintained.
All the items were aggregated around the factor that were supposed to measure, given the
correlations between the observed variables and factors (loadings), except for one item (core
wine-to taste winery products). This item was then removed. The number of factors
correspond to what was presented in the study, except for the constructs Frequency of Visit
and Return Intention. This situation maybe due to the fact that indicators of both constructs
are related visitor’s intentions. This evidence was incorporated on model.
78
RESULTS ANALYSIS
Table 48 - Total Variance Explained
COMPONENT INITIAL
EIGENVALUES
EXTRACTION
SUMS OF
SQUARED
LOADINGS
ROTATION
SUMS OF
SQUARED
LOADINGS
Total
% of
Variance Cumulative
% Total
% of
Variance Cumulative
% Total
% of
Variance Cumulative
%
1 9,059 25,165 25,165 9,059 25,165 25,165 4,765 13,236 13,236
2 5,205 14,458 39,624 5,205 14,458 39,624 4,225 11,737 24,973
3 2,237 6,215 45,838 2,237 6,215 45,838 3,459 9,607 34,580
4 1,931 5,365 51,203 1,931 5,365 51,203 3,300 9,166 43,747
5 1,680 4,668 55,871 1,680 4,668 55,871 3,024 8,401 52,147
6 1,442 4,006 59,877 1,442 4,006 59,877 2,070 5,750 57,897
7 1,287 3,574 63,451 1,287 3,574 63,451 1,999 5,554 63,451
Extraction Method: Principal Component Analysis.
79
RESULTS ANALYSIS
Table 49 - Rotated Component Matrixa
COMPONENT
1 2 3 4 5 6 7
EE - Partipation in Wine Tastings 0,780 0,128 -0,015 0,000 0,302 -0,003 0,133
EE - Visit to Wineries and Vineyards 0,774 0,074 0,034 0,020 0,178 0,008 0,149
EE - Participation in Wine Courses/Workshops 0,761 0,167 -0,080 0,127 0,114 0,025 0,072
EE - Visit to Cellars 0,720 0,239 0,049 -0,015 0,168 -0,050 0,257
EE - Visit to Wine Festivals 0,698 0,162 0,037 0,066 0,115 0,020 0,141
EE - Visit to Wine Bars 0,597 0,229 0,048 0,004 0,278 0,076 0,007
EE - Stay in Wine Hotels & Spas 0,579 0,037 0,160 0,114 0,071 0,492 -0,053
EE - Wine Tours (by bus, by cruise, etc) 0,564 0,233 0,044 0,007 -0,189 0,262 0,105
CW - To learn about the winemaking process 0,162 0,767 0,050 -0,006 0,060 0,007 0,171
CW - To learn how to appreciate wine 0,090 0,746 0,112 0,193 0,104 0,141 0,100
CW - To increase my knowledge about wine and
viticulture 0,210 0,715 -0,015 0,002 0,334 0,077 0,152
CW - To taste rare/fine wines 0,207 0,707 0,036 0,154 0,292 0,052 -0,062
CW - To meet the winemaker 0,348 0,677 0,074 0,066 0,168 -0,131 0,029
CW - To have a tour through the vineyards 0,074 0,600 0,449 0,131 -0,135 0,034 0,147
CW - To purchase wines 0,203 0,581 0,040 0,284 0,282 -0,034 -0,111
ES - To relax 0,032 -0,036 0,820 0,133 0,066 0,041 -0,067
ES - To enjoy the rural landscape and scenery 0,035 0,046 0,798 -0,001 0,005 0,040 -0,068
ES - To escape routine 0,075 -0,016 0,780 0,169 -0,028 0,135 -0,053
ES - To participate in a new and different activity -0,119 0,210 0,623 0,428 -0,209 0,088 0,079
ES - To be with friends/family 0,006 0,152 0,579 0,337 -0,061 -0,043 0,003
ES - To socialize 0,048 0,237 0,571 0,484 -0,102 0,014 -0,022
AR - Positive recommendations by others 0,094 0,000 0,100 0,790 0,076 -0,026 -0,088
AR - The rest of the group influenced my
intention to visit the winery -0,085 0,120 0,222 0,763 -0,093 0,068 0,115
AR - Positive reviews in media 0,093 0,056 0,181 0,697 0,026 0,085 -0,039
AR - Prior positive experience -0,051 0,051 0,217 0,667 0,085 0,101 0,077
AR - Prior knowledge or familiarity with the place 0,178 0,208 0,010 0,571 -0,049 0,198 -0,004
PI - Drinking wine gives me pleasure 0,209 0,218 -0,039 0,008 0,752 0,090 0,099
PI - Wine is important to me in my lifestyle 0,299 0,250 -0,100 -0,026 0,747 0,105 0,133
80
RESULTS ANALYSIS
COMPONENT
1 2 3 4 5 6 7
PI - I have a strong interest in wine 0,270 0,369 -0,106 0,003 0,741 0,070 0,114
CW - To taste the winery's products 0,356 0,419 -0,016 0,035 0,419 0,165 -0,104
VF - Oporto (Portugal)_frequency of visit 0,139 0,037 0,050 0,168 0,020 0,797 0,046
VR-Oporto (Portugal)_return intention 0,083 0,077 0,100 0,108 0,264 0,737 0,091
VF - Rioja (Spain)_frequency of visit 0,228 0,061 -0,189 0,057 -0,114 0,163 0,712
VR-Rioja (Spain)_return intention 0,266 0,203 0,043 0,054 0,289 0,162 0,684
VR-Bordeaux (France)_return intention 0,220 0,090 0,059 -0,024 0,496 -0,258 0,600
VF - Bordeaux (France)_frequency os visit 0,240 0,046 -0,098 -0,118 0,209 -0,509 0,556
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 7 iterations.
81
RESULTS ANALYSIS
3.9 | MULTIVARIATE DATA ANALYSIS
In order to understand the predictive power of the motivations to explain the return intention
of the visitants (Figure 37) and to ascertain H3 (There is a positive relation between motivations
and visit return intention on existing customers) a linear multiple regression was runned
CW
EE
ES
AW
PI
RI
MOTIVATIONS DEPENDENT VARIABLE
Figure 37 – Causal Relations
82
RESULTS ANALYSIS
The regression model includes the motivations (core wine, educational experience, escape and
socialization, awareness and reputation and product involvement) as predictors of return
intention (outcome). This analysis indicates that Educational Experience and Product
Involvement were significant (p>0,01), while Escape and Socialization, Core Wine and
Awareness and Reputation lacked statistical significance (see table 52). The model has an R2 of
0,32. So, it explains 60,2% of variance in return of visit (table 50).
Table 50 - Regression – Model Summary
MODEL R R SQUARE ADJUSTED R SQUARE
1 0,602a 0,362 0,349
a. Predictors: (Constant), Core Wine, Escape and Socialization, Educational Experience, Awareness and Recognition, Product Involvement
Table 51 - ANOVA
MODEL SUM OF
SQUARES df
MEAN
SQUARE F Sig,
1 Regression 51,317 5 10,263 28,362 0,00
Residual 90,467 250 ,362
Total 141,784 255
a. Dependent Variable: VR b. Predictors: (Constant), Core Wine, Escape and Socialization, Educational Experience, Awareness and Recognition, Product Involvement
83
RESULTS ANALYSIS
Table 52 – Regression Coefficients
COEFFICIENTSa
MODEL
UNSTANDARDIZED COEFFICIENTS
STANDARDIZED COEFFICIENTS t Sig.
B Std. Error Beta
1
(Constant) 0,837 0,312 2,679 0,008
Educational Experience
0,238 0,058 0,259 4,135 0,000
Escape and Socialization
0,038 0,066 0,036 0,582 0,561
Awareness and Recognition
0,042 0,064 0,040 0,660 0,510
Product Involvement
0,368 0,065 0,377 5,669 0,000
Core Wine 0,062 0,076 0,056 0,814 0,417
a. Dependent Variable: VR
To sum up, H3 is confirmed. There is a positive relation between motivations and visit return
intention on existing customers. Educational Experience and Product Involvement are the
motivations that contribute to understand visitors return intention.
84
RESULTS ANALYSIS
3.9.1 | CLUSTER ANALYSIS
Following the findings of CHARTERS & ALI-KNIGHT (2000) and ALEBAKI AND IAKOVIDOU
(2010) that pointed out that wine tourism consumers cannot be considered as an
homogeneous group and to ascertain H4 (There are different segments of wine tourism
consumers), Two-step cluster analysis was conducted based motivations of wine tourism
consumers.
Results led to three clusters, as the optimum solution based on Schwarz criterion, as can be
seen on figure 38.
Figure 38 - Model Summary & Cluster Quality
From the total of 256 cases, 70 were assigned to the first cluster (27,4%), 93 to the second
(36,3%) and 93 (36,3%) to the third. These three clusters were named as: (i) The “Wine
Curious”, (ii), The “Wine Interested” and (iii) The “Wine Lovers”. Following is a description of
each cluster.
On Table 53, 54, 55 can be seen the characterization of each cluster. Detailed information can
be found on Appendix 5,6 and 7.
85
RESULTS ANALYSIS
Table 53 - Cluster 1 – The “Wine Curious” Characterization
SOCIO-DEMOGRAPHIC CHARACTERIZATION
70 people
53% female
37% 35-44 years
47% degree
49% income similar to average
54% probably return to visit the wine region
EDUCATIONAL EXPERIENCE
80% visit to wineries is moderately and slightly important
74% participation in wine tastings is moderately and slightly important
56% Participation in Wine Courses/Workshops is not important at all
36% Visit to wine bars is moderately important
44% Stay in Wine Hotels & Spas is not important at all
36% Visit to Wine Festivals is not important at all
80% Visit to Cellars is slightly or moderately important
86% Wine Tours (by bus, by cruise, etc) is slightly or not important at all
CORE WINE
82% Taste winery's products is moderately and very important
72% Learn about the winemaking process is slightly and moderately important
80% Learn how to appreciate wine is moderately and very important
72% Taste rare/fine wines is slightly and moderately important
74% Have a tour through the vineyards is moderately and very important
74% Meet the winemaker is slightly and moderately important
84% Purchase wines is slightly and moderately important
ESCAPE & SOCIALIZATION
79% Escape to routine is moderately and very important
82% Enjoy the rural landscape and scenery is very and extremely important
80% To Relax is very and extremely important
74% To be with friends/family is very and extremely important
80% To participate in a new and different activity is moderately and very important
72% To Socialize is moderately and very important
86
RESULTS ANALYSIS
AWARENESS & REPUTATION
70% Prior knowledge or familiarity with the place is slightly and moderately important
96% Positive recommendations by others are moderately and very important
77% Prior positive experience is moderately and very important
72% The rest of the group influenced my intention to visit the winery is moderately and very important
43% Positive Reviews in Media is moderately important
PRODUCT INVOLVEMENT
37% have strong interest in wine
37% Wine is part of lifestyle
67% Drink wine gives pleasure
87
RESULTS ANALYSIS
Table 54 - Cluster 2 – The “Wine Interested” Characterization
SOCIO-DEMOGRAPHIC CHARACTERIZATION
93 people
66% Male
73% 35-64 years
78% degree or master
89 % income similar or higher to average
83% probably/most likely return to visit the wine region
EDUCATIONAL EXPERIENCE
76% visit to wineries is moderately and very important
80% participation in wine tastings is moderately and very important
35% Participation in Wine Courses/Workshops is moderately
47% Visit to wine bars is moderately important
61% Stay in Wine Hotels & Spas is sligtly and moderately important
45% Visit to Wine Festivals is moderately important
83% Visit to Cellars is moderately and very important
66% Wine Tours (by bus, by cruise, etc)is slightly and not important at all
CORE WINE
86% Taste winery's products is very and extremely important
84% Learn about the winemaking process is very and extremely important
78% Learn how to appreciate wine is moderately and very important
74% Taste rare/fine wines is moderately and very important
88% Have a tour through the vineyards is moderately and very important
75% Meet the winemaker is moderately and very important
83% Purchase wines is moderately and very important
ESCAPE & SOCIALIZATION
79% Escape to routine is moderately and very important
82% Enjoy the rural landscape and scenery is very and extremely important
80% To Relax is very and extremely important
74% To be with friends/family is very and extremely important
80% To participate in a new and different activity is moderately and very important
72% To Socialize is moderately and very important
88
RESULTS ANALYSIS
AWARENESS & REPUTATION
66% Prior knowledge or familiarity with the place is slightly and moderately important
83% Positive recommendations by others are moderately and very important
67% Prior positive experience is moderately and very important
68% The rest of the group influenced my intention to visit the winery is slightly and moderated
68% Positive Reviews in Media is moderately important
PRODUCT INVOLVEMENT
59% have very strong interest in wine
47% Wine is part of lifestyle
58% Strongly Agree that drink wine gives pleasure
89
RESULTS ANALYSIS
Table 55 - Cluster 3 – The “Wine Lovers” Characterization
SOCIO-DEMOGRAPHIC CHARACTERIZATION
93 people
63% Male
73% 35-54 years
75% degree or master
90 % income similar or higher to average
81% probably/most likely return to visit the wine region
EDUCATIONAL EXPERIENCE
68% visit to wineries is moderately and very important
82% participation in wine tastings is very and extremely important
38% Participation in Wine Courses/Workshops is moderately important
31% Visit to wine bars is moderately important
61% Stay in Wine Hotels & Spas is slightly and moderately important
62% Visit to Wine Festivals is moderately and very important
69% Visit to Cellars is moderately and very important
53% Wine Tours (by bus, by cruise, etc) is slightly and moderately important
CORE WINE
90% Taste winery's products is very and extremely important
71% Learn about the winemaking process is very and extremely important
94% Learn how to appreciate wine is moderately and very important
89% Taste rare/fine wines is very and extremely important
92% Have a tour through the vineyards is very and extremely important
87% Meet the winemaker is very and extremely important
83% Purchase wines is moderately and very important
ESCAPE & SOCIALIZATION
85% Escape to routine is very and extremely important
96% Enjoy the rural landscape and scenery is very and extremely important
96% To relax is very and extremely important
94% To be with friends/family is very and extremely important
92% To participate in a new and different activity is very and extremely important
89% To socialize is very and extremely important
90
RESULTS ANALYSIS
AWARENESS & REPUTATION
82% Prior knowledge or familiarity with the place is moderately and very important
84% Positive recommendations by others are very and extremely important
81% Prior positive experience is very and extremely important
81 % The rest of the group influenced my intention to visit the winery is moderately and very important
46% Positive Reviews in Media is very important
PRODUCT INVOLVEMENT
54% have very strong interest in wine
42% Wine is part of lifestyle
53% Strongly agree that drink wine gives pleasure
To sum up, H4 is confirmed. There are different segments of wine tourism consumers.
More specifically, three segments were identified:
Segment 1: “wine curious” tourist has interest in wine, but escape and socialization motivations
are more important motivations than wine related activities (e.g. educational experiences).
Segment 2: The “wine interested” tourist likes wines and is eager to learn about wine.
Education experiences and core wine activities are very important for them.
Segment 3: The “wine lover” has a strong interest in wines and can discuss the finer points of
wine with the wine-maker. Visits the winery for buying, tasting and learning about wine.
91
RESULTS ANALYSIS
3.10| HYPOTHESES VALIDATION
The following Table 56 is a sum up of the hypotheses validation.
Table 56 - Hypotheses Validation
HYPOTHESES RESULT
H1. There are similarities between Porto, Rioja and Bordeaux wine
tourism consumers in terms of their socio-demographic and
pshychographic profile (gender, age, income, education level,
frequency of visit and return intention).
Confirmed
H2. Core wine products, product involvement and educational
experience are primary motivations to visit Porto, Rioja and
Bordeaux wine regions.
Not
Confirmed
H3. There is a positive relation between motivations and visit
return intention on existing customers. Confirmed
H4. There are different segments of wine tourism consumers. Confirmed
The research results provided interesting useful information about wine tourism consumers, both
for academia and for management. It has shown that Porto, Rioja and Bordeaux consumers have
similar sociodemographic profile. Their main motivations to visit these wine regions are educational
experiences, the existence of core wine activities and the desire for escape and socialization. When
we have analysed the motivations that mostly influence visitors to return to the wine region,
educational experiences and product involvement are the ones that significantly contribute to
consumer’s loyalty. These findings pose a great emphasis on the need to understand deeper wine
tourism consumer motivations. At the end, there are three distinct segments of these consumers:
the “wine curious”, the “wine interest” and “the wine lovers”. The following chapter discusses the
specific and detailed conclusions of each hypothesis, its theoretical and methodological
contributions as well as managerial and marketing implications.
DISCUSSION & CONCLUSIONS
93
DISCUSSION & CONCLUSIONS
One of the objectives of this study was to verify if wine tourism consumers’ socio-demographic
profile is similar in Porto, Rioja and Bordeaux wine regions, and H1 was assessed:
H1. There are similarities between Porto, Rioja and Bordeaux wine tourism consumers in
terms of their socio-demographic and psychographic profile (gender, age, income, education
level, frequency of visit and return intention).
The present study turned out that the profiles of the wine tourists from Porto, Rioja and
Bordeaux wine regions are similar. The chi-squared tests conducted reveal that there are no
significant differences between socio-demographic variables in this regions.
Generally, the profile of the visitants mostly male (nevertheless it is modeless well-balanced),
aged between 35-44 years and followed by the group of 45-54. In terms of income, they have
similar-high income when compared with the average of their countries of origin. Regarding
education, most part hold a degree or even a master. As a conclusion, in spite of the different
characteristics of each wine regions in terms of history, culture and traditions, due to its
proximity the wine tourism consumers’ profile have shown similarities in terms of socio-
demographic characteristics. They are mostly males, are active adults with high purchase
power and with academic background. We have also assessed to two psychographic variables
(frequency of visit and return intention) and most part of them are frequent visitors of Porto
and less frequent to Rioja and Bordeaux (maybe due to the sample characteristics). Most part
of them reveal an intention to return the visit.
The second and third objectives of this study was to verify what are the main motivations to
visit these wine regions and from these motivations which ones better explain visitor’s return
intention, and H2 and H3 were assessed:
H2. Core wine products, product involvement and educational experience are primary
motivations to visit Porto, Rioja and Bordeaux wine regions.
94
DISCUSSION & CONCLUSIONS
H3. There is a positive relation between motivations and visit return intention on existing
customers.
The current study aimed to examine the distinctiveness of wine tourism motivations as well as
to possible predictors of wine tourist's behaviour (return intention).
Based on previous conceptual work of GETZ AND BROWN (2006) and ALEBAKI ET AL. (2015),
this research proposes an integrative theoretical framework attempting to encompass the
multidimensionality of what visitors seek when engaging in wine tourism.
The originality of this study consists in utilizing the combined results of both Principal
Component and Regression analyses. In particular:
- Highlight the components that ranked number one, two and three in terms of importance by
visitors (main motivating factors, in descending order).
- Present the secondary motivations with lower scores.
- Explain which variables are statistically significant in predicting visitor's return intention.
This research may have important marketing and managerial implications, helping wine tourism
stakeholders to better understand what motivates visitors to opt for wine tourism
programmes.
For instance, educational experiences, core wine activities and escape and socialization
attributes and benefits must be enhanced on marketing campaigns.
It is recommended that educational experiences, such as learning/tasting wine related
activities are put in evidence in marketing campaigns. Digital marketing campaigns with
emphasis on social media can be used as tools to communicate that wine tourism provides
several education opportunities, including meeting the wine makers, discovery unique wines,
learn about wine histories and traditions.
95
DISCUSSION & CONCLUSIONS
Similarly, core wine activities and learning occasions are assumed to have greater appeal for
highly involved and knowledgeable consumers and this fact provides another differentiation
factor when developing targeted marketing programs.
For escape and socialization reflects the need of this consumers of activities that promote
relaxation and an atmosphere that foster socialization with their friends and family. It is
essential that promotional materials highlight winery visitation as a relaxing activity taking
place in a enjoyable and comfortable environment.
At the same time, each region's unique landscape may constitute the basic element for the
creation and development of a wine tourism destination brand (BRUWER AND ALANT, 2009;
ALEBAKI ET AL., 2015).
Other important factor is that educational experience together with product involvement are
the motivations that better help to explain the visit return. This contribute also to develop
loyalty programs focusing on deeper educational experiences and with a strong relation with
wine. So, as a conclusion we can see that what motivates consumers to return to the wine
region is the existence of wine related educational experiences. It can be for example, the
opportunity to taste a unique wine specially made for these consumers.
The fourth objective of this study was to verify if there are different segments of wine tourists
based on their motivations, and H4 was assessed:
H4. There are different segments of wine tourism consumers.
The findings showed three types of visitors who engage with wine Tourism in Porto, Rioja and
Bordeaux: the “wine curious”, that are tourist has interest in wine, but escape and socialization
motivations are more important motivations than wine related activities (e.g. educational
experiences); the “wine interested”, that are tourist likes wines and is eager to learn about wine.
Education experiences and core wine activities are very important for them; and the “wine
lovers”, that are tourists with a strong interest wines and can discuss the finer points of wine
with the wine-maker. They visit the winery for buying, tasting and learning about wine.
96
DISCUSSION & CONCLUSIONS
This classification has implications for the wine tourism stakeholders, as understanding the
specificities of each segment is vital in terms of product development. Thus, they can be
valuable to wine tourism operators since they can develop specific targets for their wine
tourism program offers. For example, for “the wine curious”, although they have an interest
about wine, their main motivation is to relax and be with family and friends. This confirms also
that not all wine tourists are truly wine tourists, because their main motivation is not to visit
wineries and learn about wine but engaging in leisure and recreational activities. For wineries,
these segments might have less commercial importance, even though they have potential to
become “wine interested”, since they also show a high return intention.
In turn, for “the wine interested” (that have potential to become lovers) and for the “wine
lovers”, the educational experiences and core wine activities, like immersive programs to learn
more about wine, to meet wine maker, to taste rare/fine wines, to visit the vineyards, to
discover wine traditions and culture appears to be important determinants of visitation. In this
case, winery visit may provide a competitive advantage both for the region and local wines. It
is crucial that these type of visitors have the opportunity to explore and discover by
participating in wine experiences.
To sum up, the proposed framework provides relevant insights for marketers to better
understand the profile of wine tourists of Porto, Rioja and Bordeaux, the relation between
motivations to engage in wine tourism programs and how to enhance loyalty by visit return
among existing customers. Finally, considering the existence of three main segments may
enable marketing managers to develop targeted strategies and deliver value-added
experiences to each segment and at the end to increase wine tourism business.
This research was conducted by generating a non-random, heterogeneous sample and hence the
results may not be generalized beyond the sample frame.
The results apply most directly to the sample. The concepts and behavioural items used in the study
can be traced, at least partially, to culture specific factors. Although this limits the generalizability
of the results, it simultaneously increases their practical relevance.
Additionally, even though the hypothesized relationships were previous researches, longitudinal
and/or experimental studies were interesting to be implemented in order to have richer insights
among the relationships between the variables of this study.
Moreover, the data used in this study was collected from one source (self-reported) using one
instrument. Measurement of perceptions and attitudes can meaningfully be explored and future
studies can reduce the possibility of common method variance by collecting data from different
sources.
Despite these limitations, the study provides additional and generalizable insights to the
understanding of wine tourism consumers behaviour.
For future research, applying this model to other wine regions is also recommended for more
advanced knowledge in the area.
LIMITATIONS AND FUTURE RESEARCH
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APPENDIX
APPENDIX 01 | QUESTIONNAIRE
Q1 How often have you engaged on the following Wine Tourism activities?
Never (1) Almost
Never (2) Occasionally
(3) Regularly (4)
Very Often (5)
Visit to Wineries
and Vineyards (1)
Partipation in Wine
Tastings (2)
Participation in
Wine
Courses/Workshops
(3)
Visit to Wine Bars
(4)
Stay in Wine
Hotels & Spas (5)
Visit to Wine
Festivals (6)
Visit to Cellars (7)
Wine Tours (by
bus, by cruise, etc)
(8)
Q2 How important are the following factors in your decision to participate in Wine Tourism
activities?
Not at all important
(1)
Slightly important
(2)
Moderately important (3)
Very important
(4)
Extremely important
(5)
To taste the
winery's products
(1)
To escape routine
(2)
To enjoy the rural
landscape and
scenery (3)
To relax (4)
To increase my
knowledge about
wine and
viticulture (5)
To learn about the
winemaking
process (6)
To learn how to
appreciate wine
(7)
To taste rare/fine
wines (8)
To be with
friends/family (9)
To participate in a
new and different
activity (10)
To have a tour
through the
vineyards (11)
To purchase wines
(12)
To socialize (13)
To meet the
winemaker (14)
To dine at the
local restaurants
(15)
To stay in local
hotels/guesthouses
(16)
Q3 Please rate the importance of each of the following factors in your decision to participate
in wine tourism activities:
Not at all
important (1) Slightly
important (2) Moderately
important (3) Very
important (4) Extremely
important (5)
Prior knowledge
or familiarity
with the place (1)
Positive
recommendations
by others (2)
Easy
accessibility of
the wine region
(3)
Prior positive
experience (4)
The rest of the
group influenced
my intention to
visit the winery
(5)
The existence of
many wineries in
the region (6)
Positive reviews
in media (7)
Q4 How often have you visited the following Wine Regions?
Never (1) A few times
(1 or 2 times) (2)
Some times (3 times) (3)
Several times (4-5 times) (4)
A lot of time (6 or more times) (5)
Oporto
(Portugal) (1)
Rioja (Spain)
(2)
Bordeaux
(France) (3)
Q5 Which places have you visited on the wine regions you have been?
Q15 With whom do you usually travel for Wine Tourism?
Family (1)
Friends (2)
Colleagues (business) (3)
Alone (4)
Other (5) ____________________
Q23 Please rate your agreement level with the following statements regarding Wine.
Strongly
Disagree (1) Disagree (2)
Neither Disagree nor
Agree (3) Agree (4)
Strongly Agree (5)
I have a
strong interest
in wine (1)
Wine is
important to
me in my
lifestyle (2)
Drinking wine
gives me
pleasure (3)
Q10 How likely are you to return to visit to the following Wine Regions?
Not probable
(1)
Somewhat improbable
(2)
Somewhat probable (3)
Very likely (4) For sure (5)
Oporto
(Portugal) (1)
Rioja (Spain)
(2)
Bordeaux
(France) (3)
Q11 Gender
Male (1)
Female (2)
Q12 Age
Up to 24 years old (1)
25-34 years old (2)
35-44 years old (3)
45-54 years old (4)
55-64 years old (5)
65 and older (6)
Q13 Education Level
Below High School (1)
High School (2)
Degree (3)
Master (4)
PhD (5)
Q16 Country of Origin
United Kingdom (10)
United States of Ameria (11)
France (12)
Spain (13)
Portugal (14)
Italy (15)
Germany (16)
Brazil (17)
Argentina (18)
Benelux (Netherlands, Luxemburg, Belgium) (19)
Norway (20)
Sweden (21)
Denmark (22)
Finland (23)
Russia (24)
China (25)
Japan (26)
Other (27)
Q17 Monthly Income (gross) in relation to average in your country:
Very High (compared with average) (1)
High (compared with average) (2)
Similar (compared with average) (3)
Low (compared with average) (4)
Very Low (5)
APPENDIX 02 | SOCIODEMOGRAPHIC ANALYSIS
GENDER
TWOSTEP CLUSTER NUMBER TOTAL
1 2 3
GENDER
MALE COUNT 33 61 58 152
% OF TOTAL 12,9% 23,8% 22,7% 59,4%
FEMALE COUNT 37 32 35 104
% OF TOTAL 14,5% 12,5% 13,7% 40,6%
TOTAL COUNT 70 93 93 256
% OF TOTAL 27,3% 36,3% 36,3% 100,0%
AGE
TWOSTEP CLUSTER NUMBER TOTAL
1 2 3
AGE
UP TO 24 YEARS OLD
COUNT 6 5 3 14
% OF TOTAL 2,3% 2,0% 1,2% 5,5%
25-34 YEARS OLD
COUNT 18 13 17 48
% OF TOTAL 7,0% 5,1% 6,6% 18,8%
35-44 YEARS OLD
COUNT 25 34 46 105
% OF TOTAL 9,8% 13,3% 18,0% 41,0%
45-54 YEARS OLD
COUNT 11 21 20 52
% OF TOTAL 4,3% 8,2% 7,8% 20,3%
55-64 YEARS OLD
COUNT 7 13 7 27
% OF TOTAL 2,7% 5,1% 2,7% 10,5%
65 AND OLDER
COUNT 3 7 0 10
% OF TOTAL 1,2% 2,7% 0,0% 3,9%
TOTAL COUNT 70 93 93 256
% OF TOTAL 27,3% 36,3% 36,3% 100,0%
EDUCATION LEVEL
TWOSTEP CLUSTER NUMBER TOTAL
1 2 3
EDUCATION LEVEL
BELOW HIGH
SCHOOL
COUNT 2 2 3 7
% OF TOTAL 0,8% 0,8% 1,2% 2,7%
HIGH SCHOOL
COUNT 7 13 15 35
% OF TOTAL 2,7% 5,1% 5,9% 13,7%
DEGREE COUNT 33 41 47 121
% OF TOTAL 12,9% 16,0% 18,4% 47,3%
MASTER
COUNT 22 31 23 76
% OF TOTAL 8,6% 12,1% 9,0% 29,7%
PHD
COUNT 6 6 5 17
% OF TOTAL 2,3% 2,3% 2,0% 6,6%
TOTAL COUNT 70 93 93 256
% OF TOTAL 27,3% 36,3% 36,3% 100,0%
MONTHLY INCOME
TWOSTEP CLUSTER NUMBER TOTAL
1 2 3
MONTHLY INCOME (GROSS) IN RELATION TO
AVERAGE IN YOUR COUNTRY:
VERY HIGH (COMPARED
WITH AVERAGE)
COUNT 3 8 4 15
% OF TOTAL 1,2% 3,1% 1,6% 5,9%
HIGH (COMPARED
WITH AVERAGE)
COUNT 20 40 38 98
% OF TOTAL 7,8% 15,6% 14,8% 38,3%
SIMILAR (COMPARED
WITH AVERAGE)
COUNT 34 43 46 123
% OF TOTAL 13,3% 16,8% 18,0% 48,0%
LOW (COMPARED
WITH AVERAGE)
COUNT 9 1 5 15
% OF TOTAL 3,5% ,4% 2,0% 5,9%
VERY LOW
COUNT 4 1 0 5
% OF TOTAL 1,6% ,4% 0,0% 2,0%
TOTAL COUNT 70 93 93 256
% OF TOTAL 27,3% 36,3% 36,3% 100,0%
APPENDIX 03 | MOTIVATIONS ANALYSIS – EDUCATIONAL EXPERIENCE
VISIT TO WINERIES AND VINEYARDS
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 8 1 5 14
Slightly important 21 7 3 31
Moderately important 35 40 39 114
Very important 4 31 24 59
Extremely important 2 14 22 38
TOTAL 70 93 93 256
PARTIPATION IN WINE TASTINGS
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 14 1 7 22
Slightly important 25 13 10 48
Moderately important 27 37 31 95
Very important 3 37 22 62
Extremely important 1 5 23 29
TOTAL 70 93 93 256
PARTICIPATION IN WINE COURSES/WORKSHOPS
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 39 14 17 70
Slightly important 25 31 19 75
Moderately important 5 33 35 73
Very important 1 12 10 23
Extremely important 0 3 12 15
TOTAL 70 93 93 256
VISIT TO WINE BARS
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 15 0 2 17
Slightly important 20 15 5 40
Moderately important 25 44 43 112
Very important 10 25 28 63
Extremely important 0 9 15 24
TOTAL 70 93 93 256
STAY IN WINE HOTELS & SPAS
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 31 23 11 65
Slightly important 16 26 12 54
Moderately important 20 31 36 87
Very important 2 11 21 34
Extremely important 1 2 13 16
TOTAL 70 93 93 256
VISIT TO WINE FESTIVALS
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 25 9 10 44
Slightly important 23 21 15 59
Moderately important 19 42 32 93
Very important 3 14 26 43
Extremely important 0 7 10 17
TOTAL 70 93 93 256
VISIT TO CELLARS
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 11 0 3 14
Slightly important 28 9 9 46
Moderately important 28 42 38 108
Very important 1 35 26 62
Extremely important 2 7 17 26
TOTAL 70 93 93 256
WINE TOURS (BY BUS, BY CRUISE, ETC)
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 38 25 20 83
Slightly important 22 36 22 80
Moderately important 7 18 27 52
Very important 2 9 9 20
Extremely important 1 5 15 21
TOTAL 70 93 93 256
TO TASTE WINERY'S PRODUCTS
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 1 0 0 1
Slightly important 11 2 0 13
Moderately important 31 11 9 51
Very important 26 52 54 132
Extremely important 1 28 30 59
TOTAL 70 93 93 256
TO LEARN ABOUT THE WINEMAKING PROCESS
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 10 1 0 11
Slightly important 18 3 4 25
Moderately important 32 37 30 99
Very important 10 41 36 87
Extremely important 0 11 23 34
TOTAL 70 93 93 256
TO LEARN HOW TO APPRECIATE WINE
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 4 1 0 5
Slightly important 9 4 0 13
Moderately important 32 21 6 59
Very important 24 52 43 119
Extremely important 1 15 44 60
TOTAL 70 93 93 256
TO TASTE RARE/FINE WINES
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 5 0 0 5
Slightly important 17 5 0 22
Moderately important 33 24 10 67
Very important 14 45 41 100
Extremely important 1 19 42 62
TOTAL 70 93 93 256
TO HAVE A TOUR THROUGH THE VINEYARDS
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 2 0 0 2
Slightly important 10 4 2 16
Moderately important 31 34 5 70
Very important 21 48 57 126
Extremely important 6 7 29 42
TOTAL 70 93 93 256
TO MEET THE WINEMAKER
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 8 0 0 8
Slightly important 19 3 0 22
Moderately important 33 30 12 75
Very important 9 40 48 97
Extremely important 1 20 33 54
TOTAL 70 93 93 256
TO PURCHASE WINES
TWOSTEP CLUSTER NUMBER TOTAL
1 2 3
Not at all important 8 3 1 12
Slightly important 31 8 4 43
Moderately important 28 41 29 98
Very important 3 36 38 77
Extremely important 0 5 21 26
TOTAL 70 93 93 256
TO ESCAPE ROUTINE
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 3 8 0 11
Slightly important 4 14 0 18
Moderately important 25 44 14 83
Very important 30 26 49 105
Extremely important 8 1 30 39
TOTAL 70 93 93 256
TO ENJOY THE RURAL LANDSCAPE AND SCENERY
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 1 0 0 1
Slightly important 3 1 0 4
Moderately important 9 25 4 38
Very important 36 56 42 134
Extremely important 21 11 47 79
TOTAL 70 93 93 256
TO RELAX
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 0 1 0 1
Slightly important 2 8 0 10
Moderately important 12 23 4 39
Very important 38 52 35 125
Extremely important 18 9 54 81
TOTAL 70 93 93 256
TO BE WITH FRIENDS/FAMILY
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 2 2 0 4
Slightly important 2 7 1 10
Moderately important 14 40 5 59
Very important 38 34 33 105
Extremely important 14 10 54 78
TOTAL 70 93 93 256
TO PARTICIPATE IN A NEW AND DIFFERENT ACTIVITY
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 3 5 0 8
Slightly important 4 18 0 22
Moderately important 16 40 7 63
Very important 40 28 51 119
Extremely important 7 2 35 44
TOTAL 70 93 93 256
TO SOCIALIZE
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 6 7 1 14
Slightly important 9 20 0 29
Moderately important 24 36 9 69
Very important 26 27 41 94
Extremely important 5 3 42 50
TOTAL 70 93 93 256
REPUTATION & AWARENESS
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 5 11 0 16
Slightly important 23 23 5 51
Moderately important 26 38 40 104
Very important 16 21 36 73
Extremely important 0 0 12 12
TOTAL 70 93 93 256
POSITIVE RECOMMENDATIONS BY OTHERS
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 1 5 0 6
Slightly important 1 9 1 11
Moderately important 23 34 14 71
Very important 44 43 53 140
Extremely important 1 2 25 28
TOTAL 70 93 93 256
PRIOR POSITIVE EXPERIENCE
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 2 9 0 11
Slightly important 7 11 2 20
Moderately important 26 36 8 70
Very important 28 35 52 115
Extremely important 7 2 31 40
TOTAL 70 93 93 256
THE REST OF THE GROUP INFLUENCED MY INTENTION TO VISIT HE WINERY
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 8 20 1 29
Slightly important 11 31 8 50
Moderately important 35 32 31 98
Very important 15 10 44 69
Extremely important 1 0 9 10
TOTAL 70 93 93 256
POSITIVE REVIEWS IN MEDIA
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Not at all important 2 9 0 11
Slightly important 10 13 2 25
Moderately important 30 42 22 94
Very important 25 29 49 103
Extremely important 3 0 20 23
TOTAL 70 93 93 256
VF
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Will no return 25 9 10 1
Probably Return 38 49 43 2
Most Likely return 7 27 32
For sure 0 8 8
TOTAL 70 93 93 256
APPENDIX 04 | PRODUCT INVOLVEMENT
I HAVE A STRONG INTEREST IN WINE
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Strongly Disagree 3 0 0 3
Disagree 9 0 0 9
Neither Disagree nor Agree 26 0 1 27
Agree 26 38 50 114
Strongly Agree 6 55 42 103
TOTAL 70 93 93 256
I HAVE A STRONG INTEREST IN WINE
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Strongly Disagree 7 0 0 7
Disagree 14 1 2 17
Neither Disagree nor Agree 19 9 18 46
Agree 26 44 39 109
Strongly Agree 4 39 34 77
TOTAL 70 93 93 256
DRINKING WINE GIVES ME PLEASURE
TWOSTEP CLUSTER NUMBER
TOTAL
1 2 3
Strongly Disagree 2 0 0 2
Disagree 4 0 0 4
Neither Disagree nor Agree 7 0 3 10
Agree 46 39 42 127
Strongly Agree 11 54 48 113
TOTAL 70 93 93 256
APPENDIX 05 | PORTO WINE TOURISM PROFILE
VISIT FREQUENCY BY GENDER – PORTO
NEVER
A FEW TIMES (1
OR 2 TIMES)
SOME TIMES (3 TIMES)
SEVERAL TIMES (4-5
TIMES)
A LOT OF TIME (6 OR
MORE TIMES)
TOTAL
GENDER
MALE COUNT 9 26 20 32 65 152
% OF TOTAL 3,5% 10,2% 7,8% 12,5% 25,4% 59,4%
FEMALE COUNT 10 20 18 21 35 104
% OF TOTAL 3,9% 7,8% 7,0% 8,2% 13,7% 40,6%
TOTAL COUNT 19 46 38 53 100 256
% OF TOTAL 7,4% 18,0% 14,8% 20,7% 39,1% 100,0%
VISIT RETURN INTENTION BY GENDER – PORTO
VR-OPORTO (PORTUGAL)_RETURN INTENTION TOTAL
NOT PROBABLE
SOMEWHAT IMPROBABLE
SOMEWHAT PROBABLE
VERY LIKELY
FOR SURE
GENDER
MALE
COUNT 1 4 11 41 95 152
% OF TOTAL 0,4% 1,6% 4,3% 16,0% 37,1% 59,4%
FEMALE
COUNT 0 5 11 29 59 104
% OF TOTAL 0,0% 2,0% 4,3% 11,3% 23,0% 40,6%
TOTAL
COUNT 1 9 22 70 154 256
% OF TOTAL ,4% 3,5% 8,6% 27,3% 60,2% 100,0%
VISIT FREQUENCY BY AGE – PORTO
VF - OPORTO (PORTUGAL)_FREQUENCY OF VISIT TOTAL
NEVER
A FEW TIMES
(1 OR 2 TIMES)
SOME TIMES
(3TIMES)
SEVERAL TIMES
(4-5 TIMES)
A LOT OF TIME
(6 OR MORE TIMES)
AGE
UP TO 24
YEARS OLD
COUNT 2 8 2 1 1 14
% OF TOTAL
0,8% 3,1% 0,8% 0,4% 0,4% 5,5%
25-34 YEARS OLD
COUNT 4 8 7 8 21 48
% OF TOTAL
1,6% 3,1% 2,7% 3,1% 8,2% 18,8%
35-44 YEARS OLD
COUNT 4 12 16 27 46 105
% OF TOTAL
1,6% 4,7% 6,3% 10,5% 18,0% 41,0%
45-54 YEARS OLD
COUNT 6 8 8 11 19 52
% OF TOTAL
2,3% 3,1% 3,1% 4,3% 7,4% 20,3%
55-64 YEARS OLD
COUNT 3 5 3 5 11 27
% OF TOTAL
1,2% 2,0% 1,2% 2,0% 4,3% 10,5%
65 AND OLDER
COUNT 0 5 2 1 2 10
% OF TOTAL
0,0% 2,0% 0,8% 0,4% 0,8% 3,9%
TOTAL
COUNT 19 46 38 53 100 256
% OF TOTAL
7,4% 18,0% 14,8% 20,7% 39,1% 100,0%
VISIT RETURN INTENTION BY AGE – PORTO
VF - OPORTO (PORTUGAL)_RETURN INTENTION TOTAL
NOT PROBABLE
SOMEWHAT IMPROBABLE
SOMEWHAT PROBABLE
VERY LIKELY
FOR SURE
AGE
UP TO 24
YEARS OLD
COUNT 0 2 1 6 5 14
% OF TOTAL
0,0% 0,8% 0,4% 2,3% 2,0% 5,5%
25-34 YEARS OLD
COUNT 0 3 5 11 29 48
% OF TOTAL
0,0% 1,2% 2,0% 4,3% 11,3% 18,8%
35-44 YEARS OLD
COUNT 0 1 11 25 68 105
% OF TOTAL
0,0% ,4% 4,3% 9,8% 26,6% 41,0%
45-54 YEARS OLD
COUNT 1 1 2 17 31 52
% OF TOTAL
0,4% 0,4% 0,8% 6,6% 12,1% 20,3%
55-64 YEARS OLD
COUNT 0 1 1 7 18 27
% OF TOTAL
0,0% 0,4% 0,4% 2,7% 7,0% 10,5%
65 AND
OLDER
COUNT 0 1 2 4 3 10
% OF TOTAL
0,0% 0,4% 0,8% 1,6% 1,2% 3,9%
TOTAL
COUNT 1 9 22 70 154 256
% OF TOTAL
,4% 3,5% 8,6% 27,3% 60,2% 100,0%
VISIT FREQUENCY BY EDUCATION LEVEL – PORTO
VF - OPORTO (PORTUGAL)_FREQUENCY OF VISIT
NEVER
A FEW TIMES (1 OR 2 TIMES)
SOME TIMES
(3 TIMES)
SEVERAL TIMES
(4-5 TIMES)
A LOT OF TIME
(6 OR MORE TIMES)
EDUCATION LEVEL
BELOW HIGH SCHOOL
COUNT 1 2 2 0 2
% OF TOTAL 0,4% 0,8% 0,8% 0,0% ,8%
HIGH SCHOOL
COUNT 3 9 3 9 11
% OF TOTAL 1,2% 3,5% 1,2% 3,5% 4,3%
DEGREE COUNT 5 18 19 24 55
% OF TOTAL 2,0% 7,0% 7,4% 9,4% 21,5%
MASTER COUNT 10 12 12 17 25
% OF TOTAL 3,9% 4,7% 4,7% 6,6% 9,8%
PHD COUNT 0 5 2 3 7
% OF TOTAL 0,0% 2,0% ,8% 1,2% 2,7%
TOTAL COUNT 19 46 38 53 100
% OF TOTAL 7,4% 18,0% 14,8% 20,7% 39,1%
VISIT RETURN INTENTION BY EDUCATION LEVEL – PORTO
VR-OPORTO (PORTUGAL)_RETURN INTENTION TOTAL NOT
PROBABLE SOMEWHAT IMPROBABLE
SOMEWHAT PROBABLE
VERY LIKELY
FOR SURE
EDUCATION LEVEL
BELOW HIGH
SCHOOL
COUNT 1 0 0 3 3 7
% OF TOTAL
0,4% 0,0% 0,0% 1,2% 1,2% 2,7%
HIGH SCHOOL
COUNT 0 3 3 9 20 35
% OF TOTAL
0,0% 1,2% 1,2% 3,5% 7,8% 13,7%
DEGREE
COUNT 0 3 11 32 75 121
% OF TOTAL
0,0% 1,2% 4,3% 12,5% 29,3% 47,3%
MASTER
COUNT 0 3 7 20 46 76
% OF TOTAL
0,0% 1,2% 2,7% 7,8% 18,0% 29,7%
PHD
COUNT 0 0 1 6 10 17
% OF TOTAL
0,0% 0,0% ,4% 2,3% 3,9% 6,6%
TOTAL
COUNT 1 9 22 70 154 256
% OF TOTAL
0,4% 3,5% 8,6% 27,3% 60,2% 100,0%
VISIT FREQUENCY BY INCOME – PORTO
VF - OPORTO (PORTUGAL)_FREQUENCY OF VISIT TOTAL
NEVER A FEW TIMES
(1 OR 2 TIMES)
SOME TIMES
(3TIMES)
SEVERAL TIMES
(4-5 TIMES)
A LOT OF TIME
(6 OR MORE TIMES)
MONTHLY INCOME (GROSS)
IN RELATION
TO AVERAGE IN YOUR
COUNTRY:
VERY HIGH (COMPARED
WITH AVERAGE)
COUNT 1 5 0 2 7 15
% OF TOTAL
0,4% 2,0% 0,0% ,8% 2,7% 5,9%
HIGH (COMPARED
WITH AVERAGE)
COUNT 10 9 15 21 43 98
% OF TOTAL
3,9% 3,5% 5,9% 8,2% 16,8% 38,3%
SIMILAR (COMPARED
WITH AVERAGE)
COUNT 7 27 15 27 47 123
% OF TOTAL
2,7% 10,5% 5,9% 10,5% 18,4% 48,0%
LOW (COMPARED
WITH AVERAGE)
COUNT 0 4 5 3 3 15
% OF TOTAL
0,0% 1,6% 2,0% 1,2% 1,2% 5,9%
VERY LOW
COUNT 1 1 3 0 0 5
% OF TOTAL
0,4% 0,4% 1,2% 0,0% 0,0% 2,0%
TOTAL
COUNT 19 46 38 53 100 256
% OF TOTAL
7,4% 18,0% 14,8% 20,7% 39,1% 100,0%
VISIT RETURN INTENTION BY INCOME – PORTO
VR-OPORTO (PORTUGAL)_RETURN INTENTION
TOTAL NOT
PROBABLE SOMEWHAT IMPROBABLE
SOMEWHAT PROBABLE
VERY LIKELY
FOR SURE
MONTHLY INCOME (GROSS)
IN RELATION
TO AVERAGE IN YOUR
COUNTRY:
VERY HIGH (COMPARED
WITH AVERAGE)
COUNT 0 0 1 3 11 15
% OF TOTAL
0,0% 0,0% 0,4% 1,2% 4,3% 5,9%
HIGH (COMPARED
WITH AVERAGE)
COUNT 0 3 5 22 68 98
% OF TOTAL
0,0% 1,2% 2,0% 8,6% 26,6% 38,3%
SIMILAR (COMPARED
WITH AVERAGE)
COUNT 1 5 14 35 68 123
% OF TOTAL
0,4% 2,0% 5,5% 13,7% 26,6% 48,0%
LOW (COMPARED
WITH AVERAGE)
COUNT 0 0 1 8 6 15
% OF TOTAL
0,0% 0,0% 0,4% 3,1% 2,3% 5,9%
VERY LOW
COUNT 0 1 1 2 1 5
% OF TOTAL
0,0% 0,4% 0,4% 0,8% 0,4% 2,0%
TOTAL
COUNT 1 9 22 70 154 256
% OF TOTAL
0,4% 3,5% 8,6% 27,3% 60,2% 100,0%
APPENDIX 06 | RIOJA WINE TOURISM PROFILE
VISIT FREQUENCY BY GENDER – RIOJA
NEVER
A FEW TIMES (1
OR 2 TIMES)
SOME TIMES (3 TIMES)
SEVERAL TIMES (4-5
TIMES)
A LOT OF TIME (6
OR MORE TIMES)
TOTAL
GENDER
MALE COUNT 90 49 7 4 2 152
% OF TOTAL 35,2% 19,1% 2,7% 1,6% ,8% 59,4%
FEMALE COUNT 63 21 8 8 4 104
% OF TOTAL 24,6% 8,2% 3,1% 3,1% 1,6% 40,6%
TOTAL COUNT 153 70 15 12 6 256
% OF TOTAL 59,8% 27,3% 5,9% 4,7% 2,3% 100,0%
VISIT RETURN INTENTION BY GENDER – RIOJA
VR-RIOJA (SPAIN)_RETURN INTENTION TOTAL
NOT PROBABLE
SOMEWHAT IMPROBABLE
SOMEWHAT PROBABLE
VERY LIKELY
FOR SURE
GENDER
MALE
COUNT 11 30 71 28 12 152
% OF TOTAL 4,3% 11,7% 27,7% 10,9% 4,7% 59,4%
FEMALE
COUNT 7 23 40 22 12 104
% OF TOTAL 2,7% 9,0% 15,6% 8,6% 4,7% 40,6%
TOTAL
COUNT 18 53 111 50 24 256
% OF TOTAL 7,0% 20,7% 43,4% 19,5% 9,4% 100,0%
VISIT FREQUENCY BY AGE – RIOJA
VF - RIOJA (SPAIN)_FREQUENCY OF VISIT TOTAL
NEVER
A FEW TIMES
(1 OR 2 TIMES)
SOME TIMES
(3TIMES)
SEVERAL TIMES
(4-5 TIMES)
A LOT OF TIME
(6 OR MORE TIMES)
AGE
UP TO 24
YEARS OLD
COUNT 13 0 1 0 0 14
% OF TOTAL
5,1% 0,0% 0,4% 0,0% 0,0% 5,5%
25-34 YEARS OLD
COUNT 33 12 1 1 1 48
% OF TOTAL
12,9% 4,7% 0,4% 0,4% 0,4% 18,8%
35-44 YEARS OLD
COUNT 60 29 7 6 3 105
% OF TOTAL
23,4% 11,3% 2,7% 2,3% 1,2% 41,0%
45-54 YEARS OLD
COUNT 29 13 5 4 1 52
% OF TOTAL
11,3% 5,1% 2,0% 1,6% ,4% 20,3%
55-64 YEARS OLD
COUNT 12 13 1 0 1 27
% OF TOTAL
4,7% 5,1% 0,4% 0,0% 0,4% 10,5%
65 AND OLDER
COUNT 6 3 0 1 0 10
% OF TOTAL
2,3% 1,2% 0,0% 0,4% 0,0% 3,9%
TOTAL
COUNT 153 70 15 12 6 256
% OF TOTAL
59,8% 27,3% 5,9% 4,7% 2,3% 100,0%
VISIT RETURN INTENTION BY AGE – RIOJA
VF - RIOJA (SPAIN)_RETURN INTENTION TOTAL
NOT PROBABLE
SOMEWHAT IMPROBABLE
SOMEWHAT PROBABLE
VERY LIKELY
FOR SURE
AGE
UP TO 24
YEARS OLD
COUNT 3 4 2 4 1 14
% OF TOTAL
1,2% 1,6% 0,8% 1,6% 0,4% 5,5%
25-34 YEARS OLD
COUNT 4 12 24 3 5 48
% OF TOTAL
1,6% 4,7% 9,4% 1,2% 2,0% 18,8%
35-44 YEARS OLD
COUNT 6 18 49 24 8 105
% OF TOTAL
2,3% 7,0% 19,1% 9,4% 3,1% 41,0%
45-54 YEARS OLD
COUNT 3 9 17 16 7 52
% OF TOTAL
1,2% 3,5% 6,6% 6,3% 2,7% 20,3%
55-64 YEARS OLD
COUNT 1 7 13 3 3 27
% OF TOTAL
0,4% 2,7% 5,1% 1,2% 1,2% 10,5%
65 AND
OLDER
COUNT 1 3 6 0 0 10
% OF TOTAL
0,4% 1,2% 2,3% 0,0% 0,0% 3,9%
TOTAL
COUNT 18 53 111 50 24 256
% OF TOTAL
7,0% 20,7% 43,4% 19,5% 9,4% 100,0%
VISIT FREQUENCY BY EDUCATION LEVEL – RIOJA
VF - RIORJA (SPAIN)_FREQUENCY OF VISIT
NEVER
A FEW TIMES (1 OR 2 TIMES)
SOME TIMES
(3 TIMES)
SEVERAL TIMES
(4-5 TIMES)
A LOT OF TIME
(6 OR MORE TIMES)
TOTAL
EDUCATION LEVEL
BELOW HIGH SCHOOL
COUNT 5 1 0 1 0 7
% OF TOTAL 2,0% 0,4% 0,0% 0,4% 0,0% 2,7%
HIGH SCHOOL
COUNT 20 9 3 2 1 35
% OF TOTAL 7,8% 3,5% 1,2% ,8% ,4% 13,7%
DEGREE COUNT 74 35 7 3 2 121
% OF TOTAL 28,9% 13,7% 2,7% 1,2% ,8% 47,3%
MASTER COUNT 45 21 3 5 2 76
% OF TOTAL 17,6% 8,2% 1,2% 2,0% ,8% 29,7%
PHD COUNT 9 4 2 1 1 17
% OF TOTAL 3,5% 1,6% ,8% ,4% ,4% 6,6%
TOTAL COUNT 153 70 15 12 6 256
% OF TOTAL 59,8% 27,3% 5,9% 4,7% 2,3% 100,0%
VISIT RETURN INTENTION BY EDUCATION LEVEL – RIOJA
VR- RIOJA (SPAIN)_RETURN INTENTION TOTAL NOT
PROBABLE SOMEWHAT IMPROBABLE
SOMEWHAT PROBABLE
VERY LIKELY
FOR SURE
EDUCATION LEVEL
BELOW HIGH
SCHOOL
COUNT 1 2 2 1 1 7
% OF TOTAL
0,4% 0,8% 0,8% 0,4% 0,4% 2,7%
HIGH SCHOOL
COUNT 2 7 20 2 4 35
% OF TOTAL
,8% 2,7% 7,8% ,8% 1,6% 13,7%
DEGREE
COUNT 9 25 51 27 9 121
% OF TOTAL
3,5% 9,8% 19,9% 10,5% 3,5% 47,3%
MASTER
COUNT 5 16 31 14 10 76
% OF TOTAL
2,0% 6,3% 12,1% 5,5% 3,9% 29,7%
PHD
COUNT 1 3 7 6 0 17
% OF TOTAL
0,4% 1,2% 2,7% 2,3% 0,0% 6,6%
TOTAL
COUNT 18 53 111 50 24 256
% OF TOTAL
7,0% 20,7% 43,4% 19,5% 9,4% 100,0%
VISIT FREQUENCY BY INCOME – RIOJA
VF - RIOJA (SPAIN)_FREQUENCY OF VISIT TOTAL
NEVER A FEW TIMES
(1 OR 2 TIMES)
SOME TIMES
(3TIMES)
SEVERAL TIMES
(4-5 TIMES)
A LOT OF TIME
(6 OR MORE TIMES)
MONTHLY INCOME (GROSS)
IN RELATION
TO AVERAGE IN YOUR
COUNTRY:
VERY HIGH (COMPARED
WITH AVERAGE)
COUNT 5 8 1 1 0 15
% OF TOTAL
2,0% 3,1% ,4% ,4% 0,0% 5,9%
HIGH (COMPARED
WITH AVERAGE)
COUNT 54 25 11 5 3 98
% OF TOTAL
21,1% 9,8% 4,3% 2,0% 1,2% 38,3%
SIMILAR (COMPARED
WITH AVERAGE)
COUNT 78 33 3 6 3 123
% OF TOTAL
30,5% 12,9% 1,2% 2,3% 1,2% 48,0%
LOW (COMPARED
WITH AVERAGE)
COUNT 11 4 0 0 0 15
% OF TOTAL
4,3% 1,6% 0,0% 0,0% 0,0% 5,9%
VERY LOW
COUNT 5 0 0 0 0 5
% OF TOTAL
2,0% 0,0% 0,0% 0,0% 0,0% 2,0%
TOTAL
COUNT 153 70 15 12 6 256
% OF TOTAL
59,8% 27,3% 5,9% 4,7% 2,3% 100,0%
VISIT RETURN INTENTION BY INCOME – RIOJA
VR- RIOJA (SPAIN)_RETURN INTENTION
TOTAL NOT
PROBABLE SOMEWHAT IMPROBABLE
SOMEWHAT PROBABLE
VERY LIKELY
FOR SURE
MONTHLY INCOME (GROSS)
IN RELATION
TO AVERAGE IN YOUR
COUNTRY:
VERY HIGH (COMPARED
WITH AVERAGE)
COUNT 3 2 2 5 3 15
% OF TOTAL
1,2% ,8% ,8% 2,0% 1,2% 5,9%
HIGH (COMPARED
WITH AVERAGE)
COUNT 4 18 41 25 10 98
% OF TOTAL
1,6% 7,0% 16,0% 9,8% 3,9% 38,3%
SIMILAR (COMPARED
WITH AVERAGE)
COUNT 8 28 58 18 11 123
% OF TOTAL
3,1% 10,9% 22,7% 7,0% 4,3% 48,0%
LOW (COMPARED
WITH AVERAGE)
COUNT 1 4 8 2 0 15
% OF TOTAL
0,4% 1,6% 3,1% ,8% 0,0% 5,9%
VERY LOW
COUNT 2 1 2 0 0 5
% OF TOTAL
0,8% 0,4% 0,8% 0,0% 0,0% 2,0%
TOTAL
COUNT 18 53 111 50 24 256
% OF TOTAL
7,0% 20,7% 43,4% 19,5% 9,4% 100,0%
APPENDIX 07 | BORDEAUX WINE TOURISM PROFILE
VISIT FREQUENCY BY GENDER – BORDEAUX
NEVER
A FEW TIMES (1
OR 2 TIMES)
SOME TIMES (3 TIMES)
SEVERAL TIMES (4-5
TIMES)
A LOT OF TIME (6
OR MORE TIMES)
TOTAL
GENDER
MALE COUNT 94 28 10 10 10 152
% OF TOTAL 36,7% 10,9% 3,9% 3,9% 3,9% 59,4%
FEMALE COUNT 61 23 5 6 9 104
% OF TOTAL 23,8% 9,0% 2,0% 2,3% 3,5% 40,6%
TOTAL COUNT 155 51 15 16 19 256
% OF TOTAL 60,5% 19,9% 5,9% 6,3% 7,4% 100,0%
VISIT RETURN INTENTION BY GENDER – BORDEAUX
VR-BORDEAUX (FRANCE)_RETURN INTENTION TOTAL
NOT PROBABLE
SOMEWHAT IMPROBABLE
SOMEWHAT PROBABLE
VERY LIKELY
FOR SURE
GENDER
MALE
COUNT 14 22 61 34 21 152
% OF TOTAL 5,5% 8,6% 23,8% 13,3% 8,2% 59,4%
FEMALE
COUNT 3 27 39 16 19 104
% OF TOTAL 1,2% 10,5% 15,2% 6,3% 7,4% 40,6%
TOTAL
COUNT 17 49 100 50 40 256
% OF TOTAL 6,6% 19,1% 39,1% 19,5% 15,6% 100,0%
VISIT FREQUENCY BY AGE – BORDEAUX
VF - BORDEAUX (FRANCE)_FREQUENCY OF VISIT TOTAL
NEVER
A FEW TIMES
(1 OR 2 TIMES)
SOME TIMES
(3TIMES)
SEVERAL TIMES
(4-5 TIMES)
A LOT OF TIME
(6 OR MORE TIMES)
AGE
UP TO 24
YEARS OLD
COUNT 8 1 2 0 3 14
% OF TOTAL
3,1% 0,4% ,8% 0,0% 1,2% 5,5%
25-34 YEARS OLD
COUNT 31 9 3 1 4 48
% OF TOTAL
12,1% 3,5% 1,2% ,4% 1,6% 18,8%
35-44 YEARS OLD
COUNT 72 17 5 5 6 105
% OF TOTAL
28,1% 6,6% 2,0% 2,0% 2,3% 41,0%
45-54 YEARS OLD
COUNT 25 13 4 5 5 52
% OF TOTAL
9,8% 5,1% 1,6% 2,0% 2,0% 20,3%
55-64 YEARS OLD
COUNT 13 9 1 4 0 27
% OF TOTAL
5,1% 3,5% ,4% 1,6% 0,0% 10,5%
65 AND OLDER
COUNT 6 2 0 1 1 10
% OF TOTAL
2,3% ,8% 0,0% 0,4% 0,4% 3,9%
TOTAL
COUNT 155 51 15 16 19 256
% OF TOTAL
60,5% 19,9% 5,9% 6,3% 7,4% 100,0%
VISIT RETURN INTENTION BY AGE – BORDEAUX
VF - BORDEAUX (FRANCE)_RETURN INTENTION TOTAL
NOT PROBABLE
SOMEWHAT IMPROBABLE
SOMEWHAT PROBABLE
VERY LIKELY
FOR SURE
AGE
UP TO 24
YEARS OLD
COUNT 2 3 1 4 4 14
% OF TOTAL
0,8% 1,2% 0,4% 1,6% 1,6% 5,5%
25-34 YEARS OLD
COUNT 4 10 18 8 8 48
% OF TOTAL
1,6% 3,9% 7,0% 3,1% 3,1% 18,8%
35-44 YEARS OLD
COUNT 6 22 43 18 16 105
% OF TOTAL
2,3% 8,6% 16,8% 7,0% 6,3% 41,0%
45-54 YEARS OLD
COUNT 2 8 19 15 8 52
% OF TOTAL
0,8% 3,1% 7,4% 5,9% 3,1% 20,3%
55-64 YEARS OLD
COUNT 1 4 14 5 3 27
% OF TOTAL
0,4% 1,6% 5,5% 2,0% 1,2% 10,5%
65 AND
OLDER
COUNT 2 2 5 0 1 10
% OF TOTAL
0,8% 0,8% 2,0% 0,0% 0,4% 3,9%
TOTAL
COUNT 17 49 100 50 40 256
% OF TOTAL
6,6% 19,1% 39,1% 19,5% 15,6% 100,0%
VISIT FREQUENCY BY EDUCATION LEVEL – BORDEAUX
VF - BORDEAUX (FRANCE)_FREQUENCY OF VISIT
NEVER
A FEW TIMES (1 OR 2 TIMES)
SOME TIMES
(3 TIMES)
SEVERAL TIMES
(4-5 TIMES)
A LOT OF TIME
(6 OR MORE TIMES)
TOTAL
EDUCATION LEVEL
BELOW HIGH SCHOOL
COUNT 3 1 0 2 1 7
% OF TOTAL 1,2% 0,4% 0,0% 0,8% 0,4% 2,7%
HIGH SCHOOL
COUNT 20 5 5 3 2 35
% OF TOTAL 7,8% 2,0% 2,0% 1,2% 0,8% 13,7%
DEGREE COUNT 79 24 7 4 7 121
% OF TOTAL 30,9% 9,4% 2,7% 1,6% 2,7% 47,3%
MASTER COUNT 43 18 2 4 9 76
% OF TOTAL 16,8% 7,0% ,8% 1,6% 3,5% 29,7%
PHD COUNT 10 3 1 3 0 17
% OF TOTAL 3,9% 1,2% 0,4% 1,2% 0,0% 6,6%
TOTAL COUNT 155 51 15 16 19 256
% OF TOTAL 60,5% 19,9% 5,9% 6,3% 7,4% 100,0%
VISIT RETURN INTENTION BY EDUCATION LEVEL – BORDEAUX
VR- BORDEAUX (FRANCE)_RETURN INTENTION TOTAL NOT
PROBABLE SOMEWHAT IMPROBABLE
SOMEWHAT PROBABLE
VERY LIKELY
FOR SURE
EDUCATION LEVEL
BELOW HIGH
SCHOOL
COUNT 1 1 2 0 3 7
% OF TOTAL
0,4% 0,4% 0,8% 0,0% 1,2% 2,7%
HIGH SCHOOL
COUNT 3 4 14 6 8 35
% OF TOTAL
1,2% 1,6% 5,5% 2,3% 3,1% 13,7%
DEGREE
COUNT 8 27 46 26 14 121
% OF TOTAL
3,1% 10,5% 18,0% 10,2% 5,5% 47,3%
MASTER
COUNT 4 14 32 14 12 76
% OF TOTAL
1,6% 5,5% 12,5% 5,5% 4,7% 29,7%
PHD
COUNT 1 3 6 4 3 17
% OF TOTAL
0,4% 1,2% 2,3% 1,6% 1,2% 6,6%
TOTAL
COUNT 17 49 100 50 40 256
% OF TOTAL
6,6% 19,1% 39,1% 19,5% 15,6% 100,0%
VISIT FREQUENCY BY INCOME – BORDEAUX
VF - BORDEAUX (FRANCE)_FREQUENCY OF VISIT TOTAL
NEVER A FEW TIMES
(1 OR 2 TIMES)
SOME TIMES
(3TIMES)
SEVERAL TIMES
(4-5 TIMES)
A LOT OF TIME
(6 OR MORE TIMES)
MONTHLY INCOME (GROSS)
IN RELATION
TO AVERAGE IN YOUR
COUNTRY:
VERY HIGH (COMPARED
WITH AVERAGE)
COUNT 8 4 2 1 0 15
% OF TOTAL
3,1% 1,6% 0,8% 0,4% 0,0% 5,9%
HIGH (COMPARED
WITH AVERAGE)
COUNT 54 22 8 7 7 98
% OF TOTAL
21,1% 8,6% 3,1% 2,7% 2,7% 38,3%
SIMILAR (COMPARED
WITH AVERAGE)
COUNT 75 25 4 8 11 123
% OF TOTAL
29,3% 9,8% 1,6% 3,1% 4,3% 48,0%
LOW (COMPARED
WITH AVERAGE)
COUNT 14 0 1 0 0 15
% OF TOTAL
5,5% 0,0% 0,4% 0,0% 0,0% 5,9%
VERY LOW
COUNT 4 0 0 0 1 5
% OF TOTAL
1,6% 0,0% 0,0% 0,0% 0,4% 2,0%
TOTAL
COUNT 155 51 15 16 19 256
% OF TOTAL
60,5% 19,9% 5,9% 6,3% 7,4% 100,0%
VISIT RETURN INTENTION BY INCOME – BORDEAUX
VR- BORDEAUX (FRANCE)_RETURN INTENTION
TOTAL NOT
PROBABLE SOMEWHAT IMPROBABLE
SOMEWHAT PROBABLE
VERY LIKELY
FOR SURE
MONTHLY INCOME (GROSS)
IN RELATION
TO AVERAGE IN YOUR
COUNTRY:
VERY HIGH (COMPARED
WITH AVERAGE)
COUNT 2 0 4 4 5 15
% OF TOTAL
0,8% 0,0% 1,6% 1,6% 2,0% 5,9%
HIGH (COMPARED
WITH AVERAGE)
COUNT 4 17 39 22 16 98
% OF TOTAL
1,6% 6,6% 15,2% 8,6% 6,3% 38,3%
SIMILAR (COMPARED
WITH AVERAGE)
COUNT 7 28 47 23 18 123
% OF TOTAL
2,7% 10,9% 18,4% 9,0% 7,0% 48,0%
LOW (COMPARED
WITH AVERAGE)
COUNT 2 3 9 1 0 15
% OF TOTAL
0,8% 1,2% 3,5% 0,4% 0,0% 5,9%
VERY LOW
COUNT 2 1 1 0 1 5
% OF TOTAL
0,8% 0,4% 0,4% 0,0% 0,4% 2,0%
TOTAL
COUNT 17 49 100 50 40 256
% OF TOTAL
6,6% 19,1% 39,1% 19,5% 15,6% 100,0%