Description
Understanding consumer behaviour in rural tourism is a necessary condition for the successful diversification of any rural socio-economic system. This paper aims to analyse the consumer behaviour of tourists and residents in an Italian marginal rural area in order to verify the opportunities for sustainable local development through rural tourism activities.
77
PAGRI 3/2013
Consumer Behaviour in Rural
Tourism. Conjoint analysis of Choice
Attributes in the Italian-Slovenian
cross-boundary area
JEL classification: Q01, Q26, Q56
Francesco Marangon*, Stefania Troiano*, Tiziano Tempesta**,
Daniel Vecchiato**
Abstract. Understanding consumer behaviour
in rural tourism is a necessary condition for the suc-
cessful diversification of any rural socio-economic
system. This paper aims to analyse the consumer
behaviour of tourists and residents in an Italian
marginal rural area in order to verify the opportuni-
ties for sustainable local development through rural
tourism activities.
First of all we give some conceptual considera-
tion to the notion of rural tourism and the relation-
ship with sustainable local development. Secondly,
we examine the suitability of conjoint analysis for
predicting consumer behaviour in relation to rural
tourism. Finally, we report on a survey which we
carried out in a rural area located in a region of
North-Eastern Italy: the Natisone Valley. The results
provided insights into how each type of characteristic
of rural sites competes for the selection of destina-
tion. In particular, the most important attribute in
selecting rural sites for tourism is the availability of
information.
These results could provide useful insight for
decision makers, in particular as regards local plan-
ning strategies. We discuss the results with emphasis
on the implications for marketing of rural tourism.
In fact, recommendations are made in view of the
findings, specifically focusing on internal marketing
strategies.
Keywords: consumer behaviour, rural tourism,
conjoint analysis.
1. Introduction
Rural tourism offers opportunities for improving the socio-economic development of rural
areas, in particular by emphasizing a bottom-up approach that involves local stakeholders and
uses endogenous resources (Cawley and Gillmore, 2008; Kastenholz et al., 2012). Understand-
ing consumer behaviour in rural tourism is necessary for the successful diversification of rural
economic systems.
There are several studies about demand for rural tourism (Park and Yoon, 2009; Roberts and
Hall, 2001). Nevertheless, studies on consumer behaviour are scarce. In general, they agree on
the complexity of tourism experience (Kastenholz et al., 2012; Park and Yoon, 2009; Sharpley
* Department of Economics and Statistics, University of Udine, (Italy).
** Department of Land, Environment, Agriculture and Forestry, University of Padova, (Italy).
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
78
and Jepson, 2011; Uriely, 2005). In detail, demand for rural tourism seems to be influenced not
only by demographic features but also by attitudes and motivational concepts.
How people make trade-offs among the various categories of rural destinations or assess
their respective utilities still appears difficult to understand. In order to manage rural tourism
destinations successfully, operators should provide consumers with alternatives more useful for
competing by offering them the type of services they expect. As stated by Albaladejo and Díaz
(2005), for strengthening rural tourism it is necessary to determine the tourist profile cor-
responding to different types of accommodation, existing or to be developed. In particular,
purpose-designed products of rural tourism, tailored to the needs of consumers, should be iden-
tified in order to facilitate the formulation, promotion, and delivery of rural tourism products
(Park and Yoon, 2009).
They would increase the probability of the specific rural destination being chosen. In fact,
consumers select the alternative that maximizes their utility which is based upon the evaluation
of services available and their corresponding quality.
In this study we have tried to give support to decisions by operators in rural tourism by
examining consumer behaviour. The study presents findings of a research investigation aimed
at understanding the factors that explain how consumers make choices between rural tourism
destinations and analysing the characteristics considered in choosing a rural area. In particular,
specific attention was paid to consumer behaviour in a cross-border rural area between the Friuli
Venezia Giulia Region in Italy and Slovenia.
A conjoint analysis was carried out in order to predict consumer behaviour by considering
the preferences of respondents for hypothetical alternative tourism destinations. We surveyed a
sample of tourists.
The results of the study establish how each type of characteristic of the rural site competes for
the selection of the destination.
The empirical results provide support for decision makers, in particular as regards local plan-
ning strategies. We discuss the results with an emphasis on the implications for marketing of
rural tourism.
2. Literature Reviews
2.1 The concept of rural tourism
There is not a unique, clear and basic definition for rural tourism (Cawley and Gillmor,
2008; Lane, 1994; Sharpley and Roberts, 2004; Sznajder et al., 2009). Although a full review of
the literature on rural tourism is beyond the scope of this paper, we carried out a wide-rangeing
examination of it that reveals the existence of numerous labels and definitions based on a variety
of characteristics. Nevertheless, we can take, as a definition of rural tourism, a tourist activity
developed in rural areas, where the main motivation of tourists is the contact with a rural way
of life and/or landscape and environmental resources (Gannon, 1994; Lane, 1994; Sznajder et
al., 2009).
In spite of the strong expansion of rural tourism in most Western countries, there is an
absence of systematic sources of data regarding its diffusion, but it must be pointed out that
there are several constraints on collecting accurate data: for example, neither the World Tourism
Organization (WTO) nor OECD are able to use appropriate measures to quantify the diffusion
of rural tourism.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
79
It is should also be noted that there are many disparities between national definitions and
descriptions of this type of tourism: for example, on one hand you can consider only farm and
nature tourism, on the other, you can include many economic activities located outside of
urban areas. It must also be kept in mind that many rural tourists are excursionists, rather than
tourists making overnights stays. Moreover rural tourism is characterized by great diversity and
fragmentation: in fact there are many and varied private enterprises and, in some cases, also
public initiatives.
It seems, nevertheless, to be important to study rural tourism as it generates several benefits
first of all for the host community, i.e. creation of new businesses especially in the service sec-
tor, improvement of local infrastructures and public services, etc.; secondly, in favour of local
countryside capital (Garrod et al., 2006), in particular landscape preservation and environmental
resource conservation, and last but not least it is of benefit to the tourist by improving his/her
physical and mental well-being or cultural exchange (San Martin and Herrero, 2012; Sharpley
and Jepson, 2011).
Due to these benefits there is a consensus about some key objectives in developing rural tour-
ism (Roberts and Hall, 2001). The first regards the economic field: development of rural tourism
could be considered as a way of helping to revitalize struggling rural areas. It could increase jobs,
thus stimulating socio-economic growth and arresting rural depopulation and degradation of the
local socio-economic system. It could also improve the standard of living of the local population
as it offers an opportunity for income generation and job creation. Rural tourism is therefore able
to help the provision of additional economic activity, but it could also replace traditional rural
economic activities now in decline, like agriculture.
The second key objective is the protection of landscape and environmental resources. In
fact, these resources are of strategic importance to rural tourism. To conserve these resources it
is consequently necessary to create appropriate legislation, and also a balanced approach to plan-
ning. Moreover the adoption of the best practice approach to running rural tourism enterprises
is fundamental in order to ensure that the environment will be protected.
The third strategic objective regards the legal framework. The provision of appropriate legis-
lation and rules is a necessary pre-condition for obtaining successful rural tourism development.
Moreover the support and involvement of a number of institutional decision makers seem to
be fundamental.
Another very important key objective regards the quality of life and is linked to the first key
objective we discussed. As previously stated, the presence of a flow of tourists into rural areas can
help the maintenance or the improvement of existing services, thereby contributing to raising the
quality of life of the local socio-economic system.
Last but not least, the conservation and protection of local culture and traditions are also key
objectives as they can play a significant role in ensuring satisfaction of the rural tourist.
Rural tourism includes several activities conducted in rural areas (Hall et al., 2003; INEA,
2001; Marangon, 2008; Yun, 2009). One of these is agritourism, which is a style of vacation
that is normally spent on a farm. Consequently it is possible to create a relationship between
rural tourism and agritourism (Phillip et al., 2010): Fig. 1 shows firstly that rural tourism com-
prises agritourism, secondly, it is a specific subset of tourism in rural areas as a broader concept,
that could be also mass tourism and alternative tourism (European Commission, 2010; WTO,
2010; WTTC, 2010).
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
80
Fig. 1 - The “hierarchical positioning” of rural tourism
Source: Sznajder et al., 2009
Local government investment in rural tourism and private stakeholders’ projects can attract
tourists and increase local socioeconomic development (Smith et al., 2010). An increasing
number of institutional and private efforts are trying to create or improve rural tourism attrac-
tions in order to strengthen development in rural areas, in particular as regards marginal rural
areas. In fact, many undeveloped and marginal countries have detected it as a chance for socio-
economic prosperity.
A necessary condition for the successful development of tourism activity is to understand
consumers’ behaviour. It seems necessary to understand this profile also as regard rural tourism.
3. Methods
3.1 Conjoint analysis
Several descriptive analyses have been conducted on rural tourism (Asciuto et al., 2013; Caw-
ley and Gillmor, 2008; Ohe, 2002); nevertheless a more generalized framework is required in
order to allow exploration of consumer behaviour in greater detail and the creation of useful rural
tourism services in order to compete more effectively.
Conjoint analysis is a statistical technique applied in market research to determine how people
value different features composing an individual product or service. This technique originated in
mathematical psychology and was developed by P.E. Green (Green and Srinivasan, 1978). Other
prominent conjoint analysis researchers include Richard Johnson, who developed the Adaptive
Conjoint Analysis technique in the 1980s, and Jordan Louviere.
Conjoint analysis allows the researcher to measure consumers’preferences for products or
services in a direct, controlled manner. This is possible by measuring consumers’ responses when
facing hypothetical products or services (Dellaert et al., 1998). Conjoint analysis is a multivariate
TOURISM IN RURAL AREAS
RURAL TOURISM
AGRITOURISM
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
81
technique. It has been applied to understand how respondents develop preferences for products
or services, including tourist services (Thyne et al., 2006). In fact, it helps in estimating and
predicting consumer’s preferences given a set of alternatives that are specified in terms of levels
of different attributes (Green and Srinivasan, 1978 and 1990; Hair et al., 1998). While tradi-
tional techniques used to assess consumer’s preferences tend to consider each attribute independ-
ently, conjoint analysis can help to understand how a consumer trades off one attribute against
another. Consumers do not consider each product attribute independently when formulating a
choice decision. They evaluate the total value of a good/service (tourist service) by combining
the separate amounts of utility for each attribute level. Conjoint analysis gives information on
how consumers are likely to make a buying decision. Therefore, it is possible to understand how
respondents develop their preferences.
Conjoint analysis determines what combination of a limited number of product attributes is
most important in respondent choice or consumer decision making (Levy, 1995).
Conjoint analysis asks the consumers to choose among a controlled set of potential prod-
ucts or services. By analyzing the respondent’s preferences among these products, the implicit
importance of a specific attribute of the product or service can be identified. Conjoint analysis
also points out the tradeoffs that respondents make during the decision-making process and the
price they are willing to pay for it (Toombs and Bailey, 1995). Conjoint analysis assumes that the
choice between the alternatives is driven by the respondent’s utility. In detail, the respondent’s
indirect utility is broken down into two components. While the first component is deterministic,
and is a function of the attributes of alternatives, the second one is an error term and regards the
characteristics of the respondents and a set of unknown parameters.
The utility of an attribute is a numerical expression of the value the respondents give to an
attribute level and represents the relative value of the attribute (low utility means less value, while
high utility indicates more value).
It is also possible to quantify the importance of an attribute. In fact, it can be calculated by
analyzing the difference between the lowest and the highest utilities inside the range of the levels
of attributes.
Conjoint analysis is very useful in identifying consumer segmentation as it groups respond-
ents with similar preferences.
The implicit valuations (utilities or part-worths) can be used to create market models that
estimate market share, revenue and even profitability of new products or services.
4. Materials
4.1 Analysis of rural tourists’ behaviour in a cross-border region
To investigate the opportunities for developing the rural socio-economic system through
rural tourism, we analysed consumer behaviour. The aim of our study was to collect preferences
about the factors that can increase rural tourism. In detail, to identify the preferences, we carried
out a survey in a rural area located a in a cross-border region located between the North-Eastern
part of Italy, the Friuli Venezia Giulia region, and Slovenia. In particular we chose a marginal
rural area, the Natisone Valley, in order to help the local decision making process in counteract-
ing depopulation and the decline of this area.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
82
In Table 1 the decline in local population and the low value of density of population in this
rural area are evident.
To understand consumer behavior and tourists’ preferences better, we used the conjoint
experiment. The conjoint experiment was designed and administered through a questionnaire
by using a convenience sample. We conducted 400 interviews in the area (200 pilgrims to a local
holy place and 200 tourists to a local Lombard town). The questionnaires were collected between
August 2009 and January 2010: the choice of this period is based on an expert opinion that it is
important to ensure that responses were based on a full range of experience at different levels of
tourism. This ensures that a wide range of opinions were captured, deriving from respondents
with different experience. The conjoint experiment was included in a larger questionnaire which
was also designed to measure further aspects of the social impacts of rural tourism. The conjoint
experiment was pre-tested to determine the most efficient format. The questionnaire also includ-
ed a general demographic section.
A set of tours in the rural cross-border area considered were shown to respondents. We chose
four types of rural destination of the Natisone Valley. The first one is Matajur, a mountain 1642
meter high in the Julian Alps on the border between Slovenia and Italy. The second is the cave of
San Giovanni d’Antro, which is an original cave church. The third concerned votive chapels that
are widely distributed over the territories of the Natisone Valleys. Typically, they date from the
15th and 16th Centuries and were mainly erected in isolated locations away from human settle-
ments, where they were more secure from depredation. Last but not least we chose the “Villaggio
degli orsi” (Bears’ Village) visitors centre located in Stupizza village, where one can learn about
the bear and the other carnivorous animals (lynx, wolf), which inhabit the wildest and most
evocative areas of the Friuli Venezia Giulia region and Slovenia.
The respondents were asked to select and rank the tours they were shown. All examples were
similar enough to each other so that consumers would see them as close substitutes, but dissimilar
enough clearly to determine the respondent’s preference.
4.2. The selection of attributes
As stated, this study aims to identify the choice attributes of general tourists, therefore we
selected the constituent attributes of previous tours using a questionnaire based on literature
Tab. 1 - Inhabitants, surface and density of population in the Natisone Valley
Municipality
1951
inhabitants
2012
inhabitants
% change
1951-2012
Surface
(km²)
Density
(in/km²)
Drenchia (Dreka - Drèncje) 1,392 134 -90.4 13.28 10.1
Grimacco (Garmak - Grimàc) 1,737 370 -78.7 14.5 25.5
Pulfero (Podbonesec - Pulfar) 3,735 1,031 -72.4 48.03 21.5
San Leonardo (Podutana o Svet Lienart -
San Lenàrt)
2,283 1,156 -49.4 27.00 42.8
San Pietro al Natisone (Špietar
- San Pieri dai Sclavons)
3,088 2,219 -28.1 23.98 92.5
Savogna (Sovodnje - Savògne) 2,077 477 -77.0 22.11 21.6
Stregna (Srednje - Stregne) 1,883 403 -78.6 19.7 20.5
“Valli del Natisone” (Natisone Valley) 16,195 5,790 -64.2 168.6 34.3
Source: calculations on ISTAT data (2010)
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
83
reviews (Green and Srinivasan, 1990). Generally, three to seven attributes are suggested (Green
and Srinivasan, 1990). We selected four attributes for our study: 1) meal; 2) information; 3)
transport; 4) price.
4.3. The selection of levels
The sets of tours were created from a combination of levels of the attributes. The levels are the
differentiated representation of an attribute. Meal, in this case, was presented with two levels: as
“yes”, i.e. presence of meal, or “no”., i.e. no meal,. Information was presented as “guided tour”,
i.e. the presence of an expert who describes the context, or “brochure”, i.e. the tourist is invited
to read some information without an opportunityof putting questions. Transport was presented
as “bus”, or “car”. Price was presented as “€ 5”, or “€ 30” (Tab. 2).
Tab. 2 - The attributes and levels included in the factorial design of the conjoint analysis
Tour Attributes Levels
MEAL yes; no
INFORMATION guided tour; brochure
TRANSPORT bus; car
PRICE € 5; € 30
Fig. 2 - The choice set
Options Tour 1 Tour 2
Neither tour 1
nor tour 2.
I will not go
on a tour
MEAL
INFORMATION
TRANSPORT
PRICE €
Only tour
Brochure
Car
5
Tour and meal
Guided tour
Bus
30
Please indicate your
preference (check only
one option)
? ? ?
4.4. Full factorial design
We were able to consider all the number of combinations of attributes and levels (profiles),
i.e. a full factorial design, to determine the consumer preferences. In full factorial design the
ideal profile can be designed where the correlation between parameters becomes 0. With the full
profile method, the number of cases would be 16 (2×2×2×2).
We constructed 8 choice sets. Each choice set consists of 2 alternatives (Fig. 2). We also
included the “status quo” option (or “do nothing” option), i.e. pay nothing and get nothing,
so the experiment could be used to compute the value (Willingness To Pay - WTP) of each
alternative. In fact, by designing the study in an appropriate manner it is possible to use statisti-
cal analysis to identify the value of each attribute of the tour in driving the customer’s decision.
Nevertheless in this paper we do not describe these results.
In order to evaluate the preference of respondents we decided to adopt a scoring method using
Likert’s scale. As this method tends to lead to the centralization of responses and consequently
to reduce the power of discrimination, the interviewers had to guide the respondents to produce
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
84
a wider range of responses. Specifically, a 10-point Likert’s scale was used for the measurement
of respondent’s preference of each profile, where 1 point refers to the lowest preference and 10
points the highest (Goossen & Langers, 2000; Yun & Im, 2006). This scaling does not have a
mean point, unlike the widely used 5-point or 7-point scales, but we chose 10-point Likert’s scale
as it is easier to convert it into percentages. In addition, more reliable data can be captured by
collecting more variable values compared with other scales.
The range of the utility values for each factor provides a measure of its importance. We know
that factors with greater utility ranges play a more significant role than those with smaller ranges.
Conjoint utilities are scaled to an arbitrary additive constant within each attribute and are
interval data. The arbitrary additive constant, origin of the scaling within each attribute, results
from dummy coding in the design matrix. However, if we add a constant to the part-worths for
all levels of an attribute or to all attribute levels in the study, it does not change our interpretation
of the results. When using a specific kind of dummy coding called effects coding, utilities are
scaled to sum to zero within each attribute.
5. Results and discussion
5.1. General statistics of respondents
General statistics about the respondents show that females predominated (51%) among
respondents and that the age group 30-59 years prevails (52.2%), while 26.0% were under 30
years of age (Tab. 3).
Data on education indicated that 73.5% respondents had at least a high school education.
Tab. 3 - Some basic socio-economic information
Characteristic % Characteristic %
Male 49.0 Young (< 30) 26.0
Female 51.0 Adult (30-59) 52.2
Primary 3.0 Senior (60 and +) 21.8
Secondary 21.8 Local (FVG) 73.5
High 49.5 Other (Italy) 26.5
Graduate 25.7 Young (< 30) 26.0
In order to illustrate certain characteristics of consumers we analyzed their behaviour by age
(Tab. 4). The percentages describe the number of respondents within their category.
We clarify that the scores greater than or equal to 8 (in a scale 1-10) are considered as
“excellent”.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
85
The respondents indicated Matajur mountain as their most preferred destination (70%
excellent scores). Also the cave of San Giovanni d’Antro obtained a good percentage of prefer-
ences (68%).
As regards education, we noticed that the higher the level of education, the less the votive
chapels were preferred (Tab. 5).
Tab. 4 - Consumer behaviour by age
Age (years)
Tours
Matajur mountain Votive Chapels
N° of excellent scores % N° of excellent scores %
60 61 70 51 59
Total 280 70 151 38
Church cave Bear village
N° of excellent scores % N° of excellent scores %
60 60 69 41 47
Total 272 68 225 56
Tab. 5 - Consumer behaviour by education
Education
Tours
Matajur mountain Votive Chapels
N° of excellent scores % N° of excellent scores %
Primary school 10 83 7 58
Secondary 56 64 36 41
High 143 72 75 38
Graduate 71 69 33 32
Total 280 70 151 38
Church cave Bear village
N° of excellent scores % N° of excellent scores %
Primary school 9 75 4 33
Secondary 59 68 48 55
High 135 68 109 55
Graduate 69 67 64 62
Total 272 68 225 56
Source: own calculation
Moreover the higher the education level, the greater was the preference in favour of Bear Vil-
lage. It is important to note that the great part of interviewees over 60 years old had attended only
primary school and most of the respondents under 30 were graduates.
Gender does not influence the preferences.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
86
5.2. Importance and utility
We used SPSS to analyse the data we collected. The utility analysis on the entire responses
indicated very high internal validity of the model. In fact it resulted in Pearson’s R index of 0.991
and Kendall’s tau index of 0.933. These indices provide measures of the correlation between the
observed and estimated preferences and represent a correlation between the preference of each
profile and deduced utility value. Since higher correlation can be interpreted as a higher explan-
atory power of deduced utility, it is useful for evaluating the internal validity of the model. The
average preference of the concerned profile was represented by the value of the constant, which
was uniformly distributed close to 7.3.
The importance of each attribute was between 21-27% (Figs. 3 and 4). These results show
that consumers who intend to visit rural sites consider all attributes important during the choice
process. However, the meal was shown to have less importance in the choice of rural site. This
is because, unlike ordinary tourist’s behavior, those who intend to visit rural sites aim to enjoy a
unique experience that cannot be similar to those available in urban settings.
Fig. 3 - Conjoint analysis results
Source: own calculation
21,14
27,86
26,65
24,34
SUBFILE SUMMARY
Average
Importance Utility
,2106
– ,2106
0
1
–
–
––
––
–
–
–
––––
,3230
– ,3230
0
1
– ,0969
,0969
0
1
– ,1267
– ,7605
5,00
30,00
7,2601
B = – ,2106
Pearson’s R = ,991
Kendall’s tau = ,933
Signi?cance = ,0000
Signi?cance = ,0000
informazione
Factor
CONSTANT
METAL
INFO
TRANSPORT
PRICE
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
87
The presence of a meal (“0”) has a positive utility value, while the absence received a nega-
tive utility value. We clarify that this does not mean that the absence was unattractive. In fact,
the absence may have been acceptable to all respondents. But, all being equal, the presence is
better.
The utilities are scaled to sum to zero within each attribute, so the absence must have a nega-
tive utility value. The guided tour (“0”) has a positive value. The auto (“1”) received positive
utility value too. It can be seen that with a higher price we have a negative utility value.
Fig. 4 - The importance of attributes
Importance summary
Meal
Info
Transport
Price
Factor
30
20
10
0
A
v
e
r
a
g
e
I
m
p
o
r
t
a
n
c
e
The respondents who intend to visit rural sites consider information and transport important
attributes.
6. Conclusions
The key contribution of this paper is an insight into consumer behavior in rural tourism.
In particular, the paper has provided insight into a research area underdeveloped,as regards
tourism i.e. tourist behavior in a rural marginal area (Marangon et al., 2008). Often, in this
type of zone, tourism could be a strategic activity in favour of local socio-economic develop-
ment. Nevertheless, the supply of tourism activities is not preceded by an analysis of consumer
behaviour/demand. It is important to identify tourist needs in order to create the best supply
of rural tourism. In order to improve this knowledge, the present study seems to provide useful
information through the analysis of attributes determining choice from the consumers’ perspec-
tive for the selection of rural tourism sites, as part of the rural development planning process.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
88
In detail, through conjoint analysis it was possible to detect those characteristics or preferences
of the tourist facilities offered that will be most influential in the choice of one type of rural
tourism experience as opposed to another.
The results of the analysis revealed a high level of importance for information facilities and
transport. It was also noticed that the presence of a meal and the cost were considered less
important.
As marketing strategies should identify what the potential tourist needs and then provide
it; according to the results shown in this paper, information facilities and programs should be
developed or increased.
In order to improve the provision of information, cross-border cooperation also seems to be
important, with an integrated and territorial approach for increasing participation and including
support for the creation of equitable, sustainable, and integrated rural tourism (Cawley and Gill-
mor, 2008; Saxena and Ilbery, 2008). It is necessary to enable cooperation and to form cohesive
cross-border, nature-based tourism business partnerships.
Having drawn these conclusions, it is also important to consider some of the limitations of
the research. Firstly, we were not able to use conjoint analysis for valuation purposes. To over-
come this limit we are still processing the data in order to compute the value of each alternative.
Secondly, relating to the notion of integration in favour of rural cross-border tourism, further
research is needed to obtain a deeper understanding of the mechanisms that help to improve
tourism activities. These will be our next steps.
References
Albaladejo P.I.P. and Díaz D.M.T. (2005), Rural tourism demand by type of accommodation, Tourism
Management, 26(3): 951-959.
Asciuto A., Di Franco C.P., Schimmenti E. (2013), An exploratory study of sustainable rural tourism in Sic-
ily, International Journal of Business and Globalisation 11(2): 149-158.
Cawley M., Gillmor D.A. (2008), Integrated rural tourism: concepts and practice, Annals of Tourism Research
35(2): 316-337.
Dellaert B.G.C., Prodigalidad M., Louviere J.J. (1998), Using conjoint analysis to study family travel prefer-
ence structures: a comparison of day trips and 1-week holidays, Tourism Analysis 2: 67-75.
European Commission (2010), Europe, the world’s No 1 tourist destination - a new political framework for tour-
ism in Europe. COM(2010)352. 30.06.2010: Bruxelles.
Gannon A. (1994), Rural tourism as a factor in rural community economic development for economies in
transition, Journal of Sustainable Tourism 2(1-2): 51-60.
Garrod B., Wornell R., Youell R. (2006), Re-conceptualising rural resources as countryside capital: the case
of rural tourism, Journal of Rural Studies 22: 117-128.
Green P.E., Srinivasan V. (1978), Conjoint Analysis in Counsumer Research: Issues and Outlook, The Jour-
nal of Consumer Research 5(2): 103-123.
Green P.E., Srinivasan V. (1990), Conjoint Analysis in Marketing: New Developments with Implications for
Research and Practice, The Journal of Marketing 54(4): 3-19.
Goossen M., Langers F. (2000), Assessing quality of rural areas in the Netherlands: finding the most impor-
tant indicators for recreation, Landscape and Urban Planning 46(4): 241-251.
Hall D., Roberts L., Mitchell M. (2003) New directions in rural tourism. Hants, Ashgate Publishing Limited.
Hair J.F., Anderson R.E., Tatham R.L., Black W.C. (1998), Multivariate data analysis. New Jersey, Prentice-
Hall International Inc.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
89
INEA (2001), Lo sviluppo rurale. Turismo rurale, agriturismo prodotti agroalimentari. Rome, Quaderno
informativo 4.
Jakovica A. (2003), Rural Tourism - A New Trend in Europe. Proceedings 1° European Congress on Rural
Tourism: Spain.
Kastenholz E., Carneiro M.J., Marques C.P., Lima, J. (2012), Understanding and managing the rural tourism
experience - the case of a historical village in Portugal, Tourism Management Perspectives 4: 207-214.
Lane B. (1994), What is rural tourism?, Journal of Sustainable Tourism 2(1-2): 7-21.
Levy D.S. (1995) Modern marketing research techniques and the property professional, Property Management
13: 33-40.
Marangon F. (2008), Imprese e territorio nella progettazione di un sistema regionale di strade del vino:
l’esperienza del Friuli Venezia Giulia. In Nuovi turismi. Strumenti e metodi di rilevazione, modelli interpre-
tativi, Romano F. (ed). Pisa, Edizioni ETS, 123-138.
Marangon F., Visintin F., Zaccomer G.P. (2008), Ruolo, caratteristiche e profili di consumo degli eno-
escursionisti. L’indagine Cantine Aperte in Friuli Venezia Giulia. In Economia e management del vino.
Misurazione, sviluppo e gestione di un patrimonio del Friuli Venezia Giulia, Marangon F., Moretti A., Zac-
comer G.P. (eds). Turin, Giappichelli, 229-259.
Ohe Y. (2002), Evaluating Household Leisure Behaviour of Rural Tourism in Japan. 10
th
EAAE Congress
Exploring Diversity in the European Agri -Food System, 28-31 August 2002: Zaragoza.
Park D., Yoon Y. (2009), Segmentation by motivation in rural tourism: a Korean case study, Tourism Man-
agement 30 (1): 99-108.
Phillip S., Hunter C., Blackstock K. (2010), A typology for defining agritourism, Tourism Management 31:
754-758.
Roberts L., Hall D. (2001), Rural Tourism and Recreation: Principles to Practice. Wallingford, CABI Pub-
lishing.
San Martin H., Herrero A. (2012), Influence of the user’s psychological factors on the online purchase inten-
tion in rural tourism: integrating innovativeness to the UTAUT framework, Tourism Management 33:
341-350.
Saxena G., Ilbery B. (2008), Integrated rural tourism: a border case study, Annals of Tourism Research, 35(1):
233-254.
Sharpley R., Jepson D. (2011), Rural tourism. A spiritual experience?, Annals of Tourism Research, 38(1):
52-71.
Sharpley R., Roberts L. (2004), Rural Tourism — 10 Years On, International Journal of tourism research 6:
119-124.
Smith S., Davis N., Pike J. (2010), Rural Tourism Development: a Case Study of the Shawnee Hills Wine
Trail in Southern Illinois, Journal of Extension 48(5): 1-11.
Sznajder M., Przezbórska L., Scrimgeour F. (2009) Agritourism. Oxfordshire, CAB International.
Thyne M., Lawson R., Todd S. (2006), The use of conjoint analysis to assess the impact of the cross-cultural
exchange between hosts and guests, Tourism Management 27(2): 201-213.
Toombs K., Bailey G. (1995), How to redesign your organization to match customer needs, Managing Service
Quality 5(3): 52-56.
UNEP (2009), Policy recommendations on sustainable tourism development.http://www.unep.fr/scp/tourism/
activities/taskforce/. date of access: 2
nd
March 2011.
Uriely N. (2005), The tourist experience: Conceptual developments, Annals of Tourism Research, 32 (1):
199-216.
Yun H.J. (2009) Conjoint Analysis of Choice Attributes and Market Segmentation of Rural Tourists in
Korea, Journal of Rural Development 32(2): 89-109.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
90
Yun H.J, Im S.B. (2006) A study on the multi-sensory preferences and image influences of outdoor leisure
spaces, Journal of the Korean Institute of Landscape Architecture 34(3): 23-31.
WTO (2010), Tourism and Biodiversity, UNWTO News, n. 3, Madrid, World Tourism Organization.
WTTC (2010), Tourism impact data and forecast.http://www.wttc.org/, date of access: 2
nd
March 2011.
doc_668504354.pdf
Understanding consumer behaviour in rural tourism is a necessary condition for the successful diversification of any rural socio-economic system. This paper aims to analyse the consumer behaviour of tourists and residents in an Italian marginal rural area in order to verify the opportunities for sustainable local development through rural tourism activities.
77
PAGRI 3/2013
Consumer Behaviour in Rural
Tourism. Conjoint analysis of Choice
Attributes in the Italian-Slovenian
cross-boundary area
JEL classification: Q01, Q26, Q56
Francesco Marangon*, Stefania Troiano*, Tiziano Tempesta**,
Daniel Vecchiato**
Abstract. Understanding consumer behaviour
in rural tourism is a necessary condition for the suc-
cessful diversification of any rural socio-economic
system. This paper aims to analyse the consumer
behaviour of tourists and residents in an Italian
marginal rural area in order to verify the opportuni-
ties for sustainable local development through rural
tourism activities.
First of all we give some conceptual considera-
tion to the notion of rural tourism and the relation-
ship with sustainable local development. Secondly,
we examine the suitability of conjoint analysis for
predicting consumer behaviour in relation to rural
tourism. Finally, we report on a survey which we
carried out in a rural area located in a region of
North-Eastern Italy: the Natisone Valley. The results
provided insights into how each type of characteristic
of rural sites competes for the selection of destina-
tion. In particular, the most important attribute in
selecting rural sites for tourism is the availability of
information.
These results could provide useful insight for
decision makers, in particular as regards local plan-
ning strategies. We discuss the results with emphasis
on the implications for marketing of rural tourism.
In fact, recommendations are made in view of the
findings, specifically focusing on internal marketing
strategies.
Keywords: consumer behaviour, rural tourism,
conjoint analysis.
1. Introduction
Rural tourism offers opportunities for improving the socio-economic development of rural
areas, in particular by emphasizing a bottom-up approach that involves local stakeholders and
uses endogenous resources (Cawley and Gillmore, 2008; Kastenholz et al., 2012). Understand-
ing consumer behaviour in rural tourism is necessary for the successful diversification of rural
economic systems.
There are several studies about demand for rural tourism (Park and Yoon, 2009; Roberts and
Hall, 2001). Nevertheless, studies on consumer behaviour are scarce. In general, they agree on
the complexity of tourism experience (Kastenholz et al., 2012; Park and Yoon, 2009; Sharpley
* Department of Economics and Statistics, University of Udine, (Italy).
** Department of Land, Environment, Agriculture and Forestry, University of Padova, (Italy).
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
78
and Jepson, 2011; Uriely, 2005). In detail, demand for rural tourism seems to be influenced not
only by demographic features but also by attitudes and motivational concepts.
How people make trade-offs among the various categories of rural destinations or assess
their respective utilities still appears difficult to understand. In order to manage rural tourism
destinations successfully, operators should provide consumers with alternatives more useful for
competing by offering them the type of services they expect. As stated by Albaladejo and Díaz
(2005), for strengthening rural tourism it is necessary to determine the tourist profile cor-
responding to different types of accommodation, existing or to be developed. In particular,
purpose-designed products of rural tourism, tailored to the needs of consumers, should be iden-
tified in order to facilitate the formulation, promotion, and delivery of rural tourism products
(Park and Yoon, 2009).
They would increase the probability of the specific rural destination being chosen. In fact,
consumers select the alternative that maximizes their utility which is based upon the evaluation
of services available and their corresponding quality.
In this study we have tried to give support to decisions by operators in rural tourism by
examining consumer behaviour. The study presents findings of a research investigation aimed
at understanding the factors that explain how consumers make choices between rural tourism
destinations and analysing the characteristics considered in choosing a rural area. In particular,
specific attention was paid to consumer behaviour in a cross-border rural area between the Friuli
Venezia Giulia Region in Italy and Slovenia.
A conjoint analysis was carried out in order to predict consumer behaviour by considering
the preferences of respondents for hypothetical alternative tourism destinations. We surveyed a
sample of tourists.
The results of the study establish how each type of characteristic of the rural site competes for
the selection of the destination.
The empirical results provide support for decision makers, in particular as regards local plan-
ning strategies. We discuss the results with an emphasis on the implications for marketing of
rural tourism.
2. Literature Reviews
2.1 The concept of rural tourism
There is not a unique, clear and basic definition for rural tourism (Cawley and Gillmor,
2008; Lane, 1994; Sharpley and Roberts, 2004; Sznajder et al., 2009). Although a full review of
the literature on rural tourism is beyond the scope of this paper, we carried out a wide-rangeing
examination of it that reveals the existence of numerous labels and definitions based on a variety
of characteristics. Nevertheless, we can take, as a definition of rural tourism, a tourist activity
developed in rural areas, where the main motivation of tourists is the contact with a rural way
of life and/or landscape and environmental resources (Gannon, 1994; Lane, 1994; Sznajder et
al., 2009).
In spite of the strong expansion of rural tourism in most Western countries, there is an
absence of systematic sources of data regarding its diffusion, but it must be pointed out that
there are several constraints on collecting accurate data: for example, neither the World Tourism
Organization (WTO) nor OECD are able to use appropriate measures to quantify the diffusion
of rural tourism.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
79
It is should also be noted that there are many disparities between national definitions and
descriptions of this type of tourism: for example, on one hand you can consider only farm and
nature tourism, on the other, you can include many economic activities located outside of
urban areas. It must also be kept in mind that many rural tourists are excursionists, rather than
tourists making overnights stays. Moreover rural tourism is characterized by great diversity and
fragmentation: in fact there are many and varied private enterprises and, in some cases, also
public initiatives.
It seems, nevertheless, to be important to study rural tourism as it generates several benefits
first of all for the host community, i.e. creation of new businesses especially in the service sec-
tor, improvement of local infrastructures and public services, etc.; secondly, in favour of local
countryside capital (Garrod et al., 2006), in particular landscape preservation and environmental
resource conservation, and last but not least it is of benefit to the tourist by improving his/her
physical and mental well-being or cultural exchange (San Martin and Herrero, 2012; Sharpley
and Jepson, 2011).
Due to these benefits there is a consensus about some key objectives in developing rural tour-
ism (Roberts and Hall, 2001). The first regards the economic field: development of rural tourism
could be considered as a way of helping to revitalize struggling rural areas. It could increase jobs,
thus stimulating socio-economic growth and arresting rural depopulation and degradation of the
local socio-economic system. It could also improve the standard of living of the local population
as it offers an opportunity for income generation and job creation. Rural tourism is therefore able
to help the provision of additional economic activity, but it could also replace traditional rural
economic activities now in decline, like agriculture.
The second key objective is the protection of landscape and environmental resources. In
fact, these resources are of strategic importance to rural tourism. To conserve these resources it
is consequently necessary to create appropriate legislation, and also a balanced approach to plan-
ning. Moreover the adoption of the best practice approach to running rural tourism enterprises
is fundamental in order to ensure that the environment will be protected.
The third strategic objective regards the legal framework. The provision of appropriate legis-
lation and rules is a necessary pre-condition for obtaining successful rural tourism development.
Moreover the support and involvement of a number of institutional decision makers seem to
be fundamental.
Another very important key objective regards the quality of life and is linked to the first key
objective we discussed. As previously stated, the presence of a flow of tourists into rural areas can
help the maintenance or the improvement of existing services, thereby contributing to raising the
quality of life of the local socio-economic system.
Last but not least, the conservation and protection of local culture and traditions are also key
objectives as they can play a significant role in ensuring satisfaction of the rural tourist.
Rural tourism includes several activities conducted in rural areas (Hall et al., 2003; INEA,
2001; Marangon, 2008; Yun, 2009). One of these is agritourism, which is a style of vacation
that is normally spent on a farm. Consequently it is possible to create a relationship between
rural tourism and agritourism (Phillip et al., 2010): Fig. 1 shows firstly that rural tourism com-
prises agritourism, secondly, it is a specific subset of tourism in rural areas as a broader concept,
that could be also mass tourism and alternative tourism (European Commission, 2010; WTO,
2010; WTTC, 2010).
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
80
Fig. 1 - The “hierarchical positioning” of rural tourism
Source: Sznajder et al., 2009
Local government investment in rural tourism and private stakeholders’ projects can attract
tourists and increase local socioeconomic development (Smith et al., 2010). An increasing
number of institutional and private efforts are trying to create or improve rural tourism attrac-
tions in order to strengthen development in rural areas, in particular as regards marginal rural
areas. In fact, many undeveloped and marginal countries have detected it as a chance for socio-
economic prosperity.
A necessary condition for the successful development of tourism activity is to understand
consumers’ behaviour. It seems necessary to understand this profile also as regard rural tourism.
3. Methods
3.1 Conjoint analysis
Several descriptive analyses have been conducted on rural tourism (Asciuto et al., 2013; Caw-
ley and Gillmor, 2008; Ohe, 2002); nevertheless a more generalized framework is required in
order to allow exploration of consumer behaviour in greater detail and the creation of useful rural
tourism services in order to compete more effectively.
Conjoint analysis is a statistical technique applied in market research to determine how people
value different features composing an individual product or service. This technique originated in
mathematical psychology and was developed by P.E. Green (Green and Srinivasan, 1978). Other
prominent conjoint analysis researchers include Richard Johnson, who developed the Adaptive
Conjoint Analysis technique in the 1980s, and Jordan Louviere.
Conjoint analysis allows the researcher to measure consumers’preferences for products or
services in a direct, controlled manner. This is possible by measuring consumers’ responses when
facing hypothetical products or services (Dellaert et al., 1998). Conjoint analysis is a multivariate
TOURISM IN RURAL AREAS
RURAL TOURISM
AGRITOURISM
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
81
technique. It has been applied to understand how respondents develop preferences for products
or services, including tourist services (Thyne et al., 2006). In fact, it helps in estimating and
predicting consumer’s preferences given a set of alternatives that are specified in terms of levels
of different attributes (Green and Srinivasan, 1978 and 1990; Hair et al., 1998). While tradi-
tional techniques used to assess consumer’s preferences tend to consider each attribute independ-
ently, conjoint analysis can help to understand how a consumer trades off one attribute against
another. Consumers do not consider each product attribute independently when formulating a
choice decision. They evaluate the total value of a good/service (tourist service) by combining
the separate amounts of utility for each attribute level. Conjoint analysis gives information on
how consumers are likely to make a buying decision. Therefore, it is possible to understand how
respondents develop their preferences.
Conjoint analysis determines what combination of a limited number of product attributes is
most important in respondent choice or consumer decision making (Levy, 1995).
Conjoint analysis asks the consumers to choose among a controlled set of potential prod-
ucts or services. By analyzing the respondent’s preferences among these products, the implicit
importance of a specific attribute of the product or service can be identified. Conjoint analysis
also points out the tradeoffs that respondents make during the decision-making process and the
price they are willing to pay for it (Toombs and Bailey, 1995). Conjoint analysis assumes that the
choice between the alternatives is driven by the respondent’s utility. In detail, the respondent’s
indirect utility is broken down into two components. While the first component is deterministic,
and is a function of the attributes of alternatives, the second one is an error term and regards the
characteristics of the respondents and a set of unknown parameters.
The utility of an attribute is a numerical expression of the value the respondents give to an
attribute level and represents the relative value of the attribute (low utility means less value, while
high utility indicates more value).
It is also possible to quantify the importance of an attribute. In fact, it can be calculated by
analyzing the difference between the lowest and the highest utilities inside the range of the levels
of attributes.
Conjoint analysis is very useful in identifying consumer segmentation as it groups respond-
ents with similar preferences.
The implicit valuations (utilities or part-worths) can be used to create market models that
estimate market share, revenue and even profitability of new products or services.
4. Materials
4.1 Analysis of rural tourists’ behaviour in a cross-border region
To investigate the opportunities for developing the rural socio-economic system through
rural tourism, we analysed consumer behaviour. The aim of our study was to collect preferences
about the factors that can increase rural tourism. In detail, to identify the preferences, we carried
out a survey in a rural area located a in a cross-border region located between the North-Eastern
part of Italy, the Friuli Venezia Giulia region, and Slovenia. In particular we chose a marginal
rural area, the Natisone Valley, in order to help the local decision making process in counteract-
ing depopulation and the decline of this area.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
82
In Table 1 the decline in local population and the low value of density of population in this
rural area are evident.
To understand consumer behavior and tourists’ preferences better, we used the conjoint
experiment. The conjoint experiment was designed and administered through a questionnaire
by using a convenience sample. We conducted 400 interviews in the area (200 pilgrims to a local
holy place and 200 tourists to a local Lombard town). The questionnaires were collected between
August 2009 and January 2010: the choice of this period is based on an expert opinion that it is
important to ensure that responses were based on a full range of experience at different levels of
tourism. This ensures that a wide range of opinions were captured, deriving from respondents
with different experience. The conjoint experiment was included in a larger questionnaire which
was also designed to measure further aspects of the social impacts of rural tourism. The conjoint
experiment was pre-tested to determine the most efficient format. The questionnaire also includ-
ed a general demographic section.
A set of tours in the rural cross-border area considered were shown to respondents. We chose
four types of rural destination of the Natisone Valley. The first one is Matajur, a mountain 1642
meter high in the Julian Alps on the border between Slovenia and Italy. The second is the cave of
San Giovanni d’Antro, which is an original cave church. The third concerned votive chapels that
are widely distributed over the territories of the Natisone Valleys. Typically, they date from the
15th and 16th Centuries and were mainly erected in isolated locations away from human settle-
ments, where they were more secure from depredation. Last but not least we chose the “Villaggio
degli orsi” (Bears’ Village) visitors centre located in Stupizza village, where one can learn about
the bear and the other carnivorous animals (lynx, wolf), which inhabit the wildest and most
evocative areas of the Friuli Venezia Giulia region and Slovenia.
The respondents were asked to select and rank the tours they were shown. All examples were
similar enough to each other so that consumers would see them as close substitutes, but dissimilar
enough clearly to determine the respondent’s preference.
4.2. The selection of attributes
As stated, this study aims to identify the choice attributes of general tourists, therefore we
selected the constituent attributes of previous tours using a questionnaire based on literature
Tab. 1 - Inhabitants, surface and density of population in the Natisone Valley
Municipality
1951
inhabitants
2012
inhabitants
% change
1951-2012
Surface
(km²)
Density
(in/km²)
Drenchia (Dreka - Drèncje) 1,392 134 -90.4 13.28 10.1
Grimacco (Garmak - Grimàc) 1,737 370 -78.7 14.5 25.5
Pulfero (Podbonesec - Pulfar) 3,735 1,031 -72.4 48.03 21.5
San Leonardo (Podutana o Svet Lienart -
San Lenàrt)
2,283 1,156 -49.4 27.00 42.8
San Pietro al Natisone (Špietar
- San Pieri dai Sclavons)
3,088 2,219 -28.1 23.98 92.5
Savogna (Sovodnje - Savògne) 2,077 477 -77.0 22.11 21.6
Stregna (Srednje - Stregne) 1,883 403 -78.6 19.7 20.5
“Valli del Natisone” (Natisone Valley) 16,195 5,790 -64.2 168.6 34.3
Source: calculations on ISTAT data (2010)
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
83
reviews (Green and Srinivasan, 1990). Generally, three to seven attributes are suggested (Green
and Srinivasan, 1990). We selected four attributes for our study: 1) meal; 2) information; 3)
transport; 4) price.
4.3. The selection of levels
The sets of tours were created from a combination of levels of the attributes. The levels are the
differentiated representation of an attribute. Meal, in this case, was presented with two levels: as
“yes”, i.e. presence of meal, or “no”., i.e. no meal,. Information was presented as “guided tour”,
i.e. the presence of an expert who describes the context, or “brochure”, i.e. the tourist is invited
to read some information without an opportunityof putting questions. Transport was presented
as “bus”, or “car”. Price was presented as “€ 5”, or “€ 30” (Tab. 2).
Tab. 2 - The attributes and levels included in the factorial design of the conjoint analysis
Tour Attributes Levels
MEAL yes; no
INFORMATION guided tour; brochure
TRANSPORT bus; car
PRICE € 5; € 30
Fig. 2 - The choice set
Options Tour 1 Tour 2
Neither tour 1
nor tour 2.
I will not go
on a tour
MEAL
INFORMATION
TRANSPORT
PRICE €
Only tour
Brochure
Car
5
Tour and meal
Guided tour
Bus
30
Please indicate your
preference (check only
one option)
? ? ?
4.4. Full factorial design
We were able to consider all the number of combinations of attributes and levels (profiles),
i.e. a full factorial design, to determine the consumer preferences. In full factorial design the
ideal profile can be designed where the correlation between parameters becomes 0. With the full
profile method, the number of cases would be 16 (2×2×2×2).
We constructed 8 choice sets. Each choice set consists of 2 alternatives (Fig. 2). We also
included the “status quo” option (or “do nothing” option), i.e. pay nothing and get nothing,
so the experiment could be used to compute the value (Willingness To Pay - WTP) of each
alternative. In fact, by designing the study in an appropriate manner it is possible to use statisti-
cal analysis to identify the value of each attribute of the tour in driving the customer’s decision.
Nevertheless in this paper we do not describe these results.
In order to evaluate the preference of respondents we decided to adopt a scoring method using
Likert’s scale. As this method tends to lead to the centralization of responses and consequently
to reduce the power of discrimination, the interviewers had to guide the respondents to produce
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
84
a wider range of responses. Specifically, a 10-point Likert’s scale was used for the measurement
of respondent’s preference of each profile, where 1 point refers to the lowest preference and 10
points the highest (Goossen & Langers, 2000; Yun & Im, 2006). This scaling does not have a
mean point, unlike the widely used 5-point or 7-point scales, but we chose 10-point Likert’s scale
as it is easier to convert it into percentages. In addition, more reliable data can be captured by
collecting more variable values compared with other scales.
The range of the utility values for each factor provides a measure of its importance. We know
that factors with greater utility ranges play a more significant role than those with smaller ranges.
Conjoint utilities are scaled to an arbitrary additive constant within each attribute and are
interval data. The arbitrary additive constant, origin of the scaling within each attribute, results
from dummy coding in the design matrix. However, if we add a constant to the part-worths for
all levels of an attribute or to all attribute levels in the study, it does not change our interpretation
of the results. When using a specific kind of dummy coding called effects coding, utilities are
scaled to sum to zero within each attribute.
5. Results and discussion
5.1. General statistics of respondents
General statistics about the respondents show that females predominated (51%) among
respondents and that the age group 30-59 years prevails (52.2%), while 26.0% were under 30
years of age (Tab. 3).
Data on education indicated that 73.5% respondents had at least a high school education.
Tab. 3 - Some basic socio-economic information
Characteristic % Characteristic %
Male 49.0 Young (< 30) 26.0
Female 51.0 Adult (30-59) 52.2
Primary 3.0 Senior (60 and +) 21.8
Secondary 21.8 Local (FVG) 73.5
High 49.5 Other (Italy) 26.5
Graduate 25.7 Young (< 30) 26.0
In order to illustrate certain characteristics of consumers we analyzed their behaviour by age
(Tab. 4). The percentages describe the number of respondents within their category.
We clarify that the scores greater than or equal to 8 (in a scale 1-10) are considered as
“excellent”.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
85
The respondents indicated Matajur mountain as their most preferred destination (70%
excellent scores). Also the cave of San Giovanni d’Antro obtained a good percentage of prefer-
ences (68%).
As regards education, we noticed that the higher the level of education, the less the votive
chapels were preferred (Tab. 5).
Tab. 4 - Consumer behaviour by age
Age (years)
Tours
Matajur mountain Votive Chapels
N° of excellent scores % N° of excellent scores %
60 61 70 51 59
Total 280 70 151 38
Church cave Bear village
N° of excellent scores % N° of excellent scores %
60 60 69 41 47
Total 272 68 225 56
Tab. 5 - Consumer behaviour by education
Education
Tours
Matajur mountain Votive Chapels
N° of excellent scores % N° of excellent scores %
Primary school 10 83 7 58
Secondary 56 64 36 41
High 143 72 75 38
Graduate 71 69 33 32
Total 280 70 151 38
Church cave Bear village
N° of excellent scores % N° of excellent scores %
Primary school 9 75 4 33
Secondary 59 68 48 55
High 135 68 109 55
Graduate 69 67 64 62
Total 272 68 225 56
Source: own calculation
Moreover the higher the education level, the greater was the preference in favour of Bear Vil-
lage. It is important to note that the great part of interviewees over 60 years old had attended only
primary school and most of the respondents under 30 were graduates.
Gender does not influence the preferences.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
86
5.2. Importance and utility
We used SPSS to analyse the data we collected. The utility analysis on the entire responses
indicated very high internal validity of the model. In fact it resulted in Pearson’s R index of 0.991
and Kendall’s tau index of 0.933. These indices provide measures of the correlation between the
observed and estimated preferences and represent a correlation between the preference of each
profile and deduced utility value. Since higher correlation can be interpreted as a higher explan-
atory power of deduced utility, it is useful for evaluating the internal validity of the model. The
average preference of the concerned profile was represented by the value of the constant, which
was uniformly distributed close to 7.3.
The importance of each attribute was between 21-27% (Figs. 3 and 4). These results show
that consumers who intend to visit rural sites consider all attributes important during the choice
process. However, the meal was shown to have less importance in the choice of rural site. This
is because, unlike ordinary tourist’s behavior, those who intend to visit rural sites aim to enjoy a
unique experience that cannot be similar to those available in urban settings.
Fig. 3 - Conjoint analysis results
Source: own calculation
21,14
27,86
26,65
24,34
SUBFILE SUMMARY
Average
Importance Utility
,2106
– ,2106
0
1
–
–
––
––
–
–
–
––––
,3230
– ,3230
0
1
– ,0969
,0969
0
1
– ,1267
– ,7605
5,00
30,00
7,2601
B = – ,2106
Pearson’s R = ,991
Kendall’s tau = ,933
Signi?cance = ,0000
Signi?cance = ,0000
informazione
Factor
CONSTANT
METAL
INFO
TRANSPORT
PRICE
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
87
The presence of a meal (“0”) has a positive utility value, while the absence received a nega-
tive utility value. We clarify that this does not mean that the absence was unattractive. In fact,
the absence may have been acceptable to all respondents. But, all being equal, the presence is
better.
The utilities are scaled to sum to zero within each attribute, so the absence must have a nega-
tive utility value. The guided tour (“0”) has a positive value. The auto (“1”) received positive
utility value too. It can be seen that with a higher price we have a negative utility value.
Fig. 4 - The importance of attributes
Importance summary
Meal
Info
Transport
Price
Factor
30
20
10
0
A
v
e
r
a
g
e
I
m
p
o
r
t
a
n
c
e
The respondents who intend to visit rural sites consider information and transport important
attributes.
6. Conclusions
The key contribution of this paper is an insight into consumer behavior in rural tourism.
In particular, the paper has provided insight into a research area underdeveloped,as regards
tourism i.e. tourist behavior in a rural marginal area (Marangon et al., 2008). Often, in this
type of zone, tourism could be a strategic activity in favour of local socio-economic develop-
ment. Nevertheless, the supply of tourism activities is not preceded by an analysis of consumer
behaviour/demand. It is important to identify tourist needs in order to create the best supply
of rural tourism. In order to improve this knowledge, the present study seems to provide useful
information through the analysis of attributes determining choice from the consumers’ perspec-
tive for the selection of rural tourism sites, as part of the rural development planning process.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
88
In detail, through conjoint analysis it was possible to detect those characteristics or preferences
of the tourist facilities offered that will be most influential in the choice of one type of rural
tourism experience as opposed to another.
The results of the analysis revealed a high level of importance for information facilities and
transport. It was also noticed that the presence of a meal and the cost were considered less
important.
As marketing strategies should identify what the potential tourist needs and then provide
it; according to the results shown in this paper, information facilities and programs should be
developed or increased.
In order to improve the provision of information, cross-border cooperation also seems to be
important, with an integrated and territorial approach for increasing participation and including
support for the creation of equitable, sustainable, and integrated rural tourism (Cawley and Gill-
mor, 2008; Saxena and Ilbery, 2008). It is necessary to enable cooperation and to form cohesive
cross-border, nature-based tourism business partnerships.
Having drawn these conclusions, it is also important to consider some of the limitations of
the research. Firstly, we were not able to use conjoint analysis for valuation purposes. To over-
come this limit we are still processing the data in order to compute the value of each alternative.
Secondly, relating to the notion of integration in favour of rural cross-border tourism, further
research is needed to obtain a deeper understanding of the mechanisms that help to improve
tourism activities. These will be our next steps.
References
Albaladejo P.I.P. and Díaz D.M.T. (2005), Rural tourism demand by type of accommodation, Tourism
Management, 26(3): 951-959.
Asciuto A., Di Franco C.P., Schimmenti E. (2013), An exploratory study of sustainable rural tourism in Sic-
ily, International Journal of Business and Globalisation 11(2): 149-158.
Cawley M., Gillmor D.A. (2008), Integrated rural tourism: concepts and practice, Annals of Tourism Research
35(2): 316-337.
Dellaert B.G.C., Prodigalidad M., Louviere J.J. (1998), Using conjoint analysis to study family travel prefer-
ence structures: a comparison of day trips and 1-week holidays, Tourism Analysis 2: 67-75.
European Commission (2010), Europe, the world’s No 1 tourist destination - a new political framework for tour-
ism in Europe. COM(2010)352. 30.06.2010: Bruxelles.
Gannon A. (1994), Rural tourism as a factor in rural community economic development for economies in
transition, Journal of Sustainable Tourism 2(1-2): 51-60.
Garrod B., Wornell R., Youell R. (2006), Re-conceptualising rural resources as countryside capital: the case
of rural tourism, Journal of Rural Studies 22: 117-128.
Green P.E., Srinivasan V. (1978), Conjoint Analysis in Counsumer Research: Issues and Outlook, The Jour-
nal of Consumer Research 5(2): 103-123.
Green P.E., Srinivasan V. (1990), Conjoint Analysis in Marketing: New Developments with Implications for
Research and Practice, The Journal of Marketing 54(4): 3-19.
Goossen M., Langers F. (2000), Assessing quality of rural areas in the Netherlands: finding the most impor-
tant indicators for recreation, Landscape and Urban Planning 46(4): 241-251.
Hall D., Roberts L., Mitchell M. (2003) New directions in rural tourism. Hants, Ashgate Publishing Limited.
Hair J.F., Anderson R.E., Tatham R.L., Black W.C. (1998), Multivariate data analysis. New Jersey, Prentice-
Hall International Inc.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
89
INEA (2001), Lo sviluppo rurale. Turismo rurale, agriturismo prodotti agroalimentari. Rome, Quaderno
informativo 4.
Jakovica A. (2003), Rural Tourism - A New Trend in Europe. Proceedings 1° European Congress on Rural
Tourism: Spain.
Kastenholz E., Carneiro M.J., Marques C.P., Lima, J. (2012), Understanding and managing the rural tourism
experience - the case of a historical village in Portugal, Tourism Management Perspectives 4: 207-214.
Lane B. (1994), What is rural tourism?, Journal of Sustainable Tourism 2(1-2): 7-21.
Levy D.S. (1995) Modern marketing research techniques and the property professional, Property Management
13: 33-40.
Marangon F. (2008), Imprese e territorio nella progettazione di un sistema regionale di strade del vino:
l’esperienza del Friuli Venezia Giulia. In Nuovi turismi. Strumenti e metodi di rilevazione, modelli interpre-
tativi, Romano F. (ed). Pisa, Edizioni ETS, 123-138.
Marangon F., Visintin F., Zaccomer G.P. (2008), Ruolo, caratteristiche e profili di consumo degli eno-
escursionisti. L’indagine Cantine Aperte in Friuli Venezia Giulia. In Economia e management del vino.
Misurazione, sviluppo e gestione di un patrimonio del Friuli Venezia Giulia, Marangon F., Moretti A., Zac-
comer G.P. (eds). Turin, Giappichelli, 229-259.
Ohe Y. (2002), Evaluating Household Leisure Behaviour of Rural Tourism in Japan. 10
th
EAAE Congress
Exploring Diversity in the European Agri -Food System, 28-31 August 2002: Zaragoza.
Park D., Yoon Y. (2009), Segmentation by motivation in rural tourism: a Korean case study, Tourism Man-
agement 30 (1): 99-108.
Phillip S., Hunter C., Blackstock K. (2010), A typology for defining agritourism, Tourism Management 31:
754-758.
Roberts L., Hall D. (2001), Rural Tourism and Recreation: Principles to Practice. Wallingford, CABI Pub-
lishing.
San Martin H., Herrero A. (2012), Influence of the user’s psychological factors on the online purchase inten-
tion in rural tourism: integrating innovativeness to the UTAUT framework, Tourism Management 33:
341-350.
Saxena G., Ilbery B. (2008), Integrated rural tourism: a border case study, Annals of Tourism Research, 35(1):
233-254.
Sharpley R., Jepson D. (2011), Rural tourism. A spiritual experience?, Annals of Tourism Research, 38(1):
52-71.
Sharpley R., Roberts L. (2004), Rural Tourism — 10 Years On, International Journal of tourism research 6:
119-124.
Smith S., Davis N., Pike J. (2010), Rural Tourism Development: a Case Study of the Shawnee Hills Wine
Trail in Southern Illinois, Journal of Extension 48(5): 1-11.
Sznajder M., Przezbórska L., Scrimgeour F. (2009) Agritourism. Oxfordshire, CAB International.
Thyne M., Lawson R., Todd S. (2006), The use of conjoint analysis to assess the impact of the cross-cultural
exchange between hosts and guests, Tourism Management 27(2): 201-213.
Toombs K., Bailey G. (1995), How to redesign your organization to match customer needs, Managing Service
Quality 5(3): 52-56.
UNEP (2009), Policy recommendations on sustainable tourism development.http://www.unep.fr/scp/tourism/
activities/taskforce/. date of access: 2
nd
March 2011.
Uriely N. (2005), The tourist experience: Conceptual developments, Annals of Tourism Research, 32 (1):
199-216.
Yun H.J. (2009) Conjoint Analysis of Choice Attributes and Market Segmentation of Rural Tourists in
Korea, Journal of Rural Development 32(2): 89-109.
Consumer behaviour in rural tourism. Conjoint analysis of choice attributes in the italian-slovenian
90
Yun H.J, Im S.B. (2006) A study on the multi-sensory preferences and image influences of outdoor leisure
spaces, Journal of the Korean Institute of Landscape Architecture 34(3): 23-31.
WTO (2010), Tourism and Biodiversity, UNWTO News, n. 3, Madrid, World Tourism Organization.
WTTC (2010), Tourism impact data and forecast.http://www.wttc.org/, date of access: 2
nd
March 2011.
doc_668504354.pdf