WINE TOURISM CONSUMERS: WHO ARE THEY AND WHAT …...Wine tourism can be defined as visitation to...

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 34 -Return Intention and Age .................................................................................................... 62


Table 36 - Pearson Chi-Square – Return Intention and Education ............................................... 64


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 42 - Pearson Chi-Square – Visit Return and Age ................................................................... 70


Table 44 - Pearson Chi-Square – Visit Return and Education ........................................................ 72


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

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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.

13

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.

14

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.

15

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


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


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


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


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


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


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

http://bit.ly/EnoTurismo

31


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





Never 153 59,8

FREQUENCY PERCENT





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



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



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




Linear-by-Linear

Association 1,202 1 0,273




0%2%

4%

16%

37%

0%2%

4%

11%

23%

Not probable Somewhat improbable

Somewhat probable

Very likely For sure


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




Linear-by-Linear



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%


Some times (3 times)

Several times (4-5 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




Linear-by-Linear



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




Linear-by-Linear




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%




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




Linear-by-Linear




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%


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


Pearson Chi-Square 30,488a 16 ,016

Likelihood Ratio 33,232 16 ,007

Linear-by-Linear

Association 3,054 1 ,081



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%




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




Linear-by-Linear





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%




Very Low % of Total


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







count is 2,44.

35%

19%

3%2% 1%

25%

8%

3% 3%2%






60

RESULTS ANALYSIS

Figure 22 - Visit Return Intention by Gender - Rioja

Table 32 - Pearson Chi-Square – Return Intention and Gender

Chi-Square Tests






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%


Somewhat probable Very likely For sure


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


Chi-Square Tests







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%





62

RESULTS ANALYSIS

Figure 24 - Visit Return Intention by Age - Rioja

Table 34 -Return Intention and Age

Chi-Square Tests




Linear-by-Linear




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%




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


Chi-Square Tests




Linear-by-Linear




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%




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


Pearson Chi-Square 12,839a 16 ,684

Likelihood Ratio 14,986 16 ,526

Linear-by-Linear

Association ,577 1 ,448



count is 0,49.

% 1% 1% % %1%

3%

8%

1%2%

4%

10%

20%

11%

4%

2%

6%

12%

5%

4%

%1%

3% 2%

%





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


Chi-Square Tests




Linear-by-Linear




,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%






Very Low % of Total


66

RESULTS ANALYSIS

Figure 28 - Visit Return Intention by Income – Rioja

Table 38 - Pearson Chi-Square – Visit Return and Income

Chi-Square Tests







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%




Very Low % of Total


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




Linear-by-Linear



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%






68

RESULTS ANALYSIS

Figure 30 - Visit Return Intention by Gender – Bordeaux

Table 40 - Pearson Chi-Square – Visit Return and Gender

Chi-Square Tests




Linear-by-Linear



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%




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


Chi-Square Tests







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%






70

RESULTS ANALYSIS

Figure 32 - Visit Return Intention by Age - Bordeaux

Table 42 - Pearson Chi-Square – Visit Return and Age

Chi-Square Tests




Linear-by-Linear




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%

%%



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


Chi-Square Tests







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%







72

RESULTS ANALYSIS

Figure 34 - Visit Return Intention by Education Level - Bordeaux

Table 44 - Pearson Chi-Square – Visit Return and Education

Chi-Square Tests




Linear-by-Linear




0,46.

% %1%

%

1%1% 2%

5%

2%3%3%

11%

18%

10%

5%

2%

5%

13%

5%5%

%1%

2%2%

1%





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


Chi-Square Tests







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%






Very Low % of Total


74

RESULTS ANALYSIS

Figure 36 - Visit Return Intention by Income - Bordeaux

Table 46 - Pearson Chi-Square – Return Intention and Income

Chi-Square Tests






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%% %

%%




Very Low % of Total


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:



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


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


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


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


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


79% Escape to routine is moderately and very important


80% To Relax 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


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


58% Strongly Agree that drink wine gives pleasure

89

RESULTS ANALYSIS

Table 55 - Cluster 3 – The “Wine Lovers” 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


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


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


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


85% Escape to routine is very and extremely important


96% To relax 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


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


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


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:



94


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


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


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


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%


% OF TOTAL 27,3% 36,3% 36,3% 100,0%

EDUCATION LEVEL


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%


% OF TOTAL 27,3% 36,3% 36,3% 100,0%

MONTHLY INCOME


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%


% 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


TOTAL

1 2 3






TOTAL 70 93 93 256

PARTICIPATION IN WINE COURSES/WORKSHOPS


TOTAL

1 2 3






TOTAL 70 93 93 256

VISIT TO WINE BARS


TOTAL

1 2 3






TOTAL 70 93 93 256

STAY IN WINE HOTELS & SPAS


TOTAL

1 2 3






TOTAL 70 93 93 256

VISIT TO WINE FESTIVALS


TOTAL

1 2 3






TOTAL 70 93 93 256

VISIT TO CELLARS


TOTAL

1 2 3






TOTAL 70 93 93 256

WINE TOURS (BY BUS, BY CRUISE, ETC)


TOTAL

1 2 3






TOTAL 70 93 93 256

TO TASTE WINERY'S PRODUCTS


TOTAL

1 2 3






TOTAL 70 93 93 256

TO LEARN ABOUT THE WINEMAKING PROCESS


TOTAL

1 2 3






TOTAL 70 93 93 256

TO LEARN HOW TO APPRECIATE WINE


TOTAL

1 2 3






TOTAL 70 93 93 256

TO TASTE RARE/FINE WINES


TOTAL

1 2 3






TOTAL 70 93 93 256

TO HAVE A TOUR THROUGH THE VINEYARDS


TOTAL

1 2 3






TOTAL 70 93 93 256

TO MEET THE WINEMAKER


TOTAL

1 2 3






TOTAL 70 93 93 256

TO PURCHASE WINES


1 2 3






TOTAL 70 93 93 256

TO ESCAPE ROUTINE


TOTAL

1 2 3






TOTAL 70 93 93 256

TO ENJOY THE RURAL LANDSCAPE AND SCENERY


TOTAL

1 2 3






TOTAL 70 93 93 256

TO RELAX


TOTAL

1 2 3






TOTAL 70 93 93 256

TO BE WITH FRIENDS/FAMILY


TOTAL

1 2 3






TOTAL 70 93 93 256

TO PARTICIPATE IN A NEW AND DIFFERENT ACTIVITY


TOTAL

1 2 3






TOTAL 70 93 93 256

TO SOCIALIZE


TOTAL

1 2 3






TOTAL 70 93 93 256

REPUTATION & AWARENESS


TOTAL

1 2 3






TOTAL 70 93 93 256

POSITIVE RECOMMENDATIONS BY OTHERS


TOTAL

1 2 3






TOTAL 70 93 93 256

PRIOR POSITIVE EXPERIENCE


TOTAL

1 2 3






TOTAL 70 93 93 256

THE REST OF THE GROUP INFLUENCED MY INTENTION TO VISIT HE WINERY


TOTAL

1 2 3






TOTAL 70 93 93 256

POSITIVE REVIEWS IN MEDIA


TOTAL

1 2 3






TOTAL 70 93 93 256

VF


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


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


TOTAL

1 2 3


Disagree 14 1 2 17


Agree 26 44 39 109


TOTAL 70 93 93 256

DRINKING WINE GIVES ME PLEASURE


TOTAL

1 2 3


Disagree 4 0 0 4


Agree 46 39 42 127


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


SOMEWHAT PROBABLE

VERY LIKELY

FOR SURE


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)


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


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


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)


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


SOMEWHAT PROBABLE

VERY LIKELY

FOR SURE


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)


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


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


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)


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


SOMEWHAT PROBABLE

VERY LIKELY

FOR SURE


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%

WINE TOURISM CONSUMERS: WHO ARE THEY AND WHAT …...Wine tourism can be defined as visitation to...

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Transcript of WINE TOURISM CONSUMERS: WHO ARE THEY AND WHAT …...Wine tourism can be defined as visitation to...