Tourism Management 36 (2013) 364e376
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Tourism Management
journal homepage: www.elsevier.com/locate/tourman
Second-home owners’ intention to purchase nature-based tourism activity
products e A Norwegian case study
Torvald Tangeland a, *, Birger Vennesland b, Erlend Nybakk b
a
b
National Institute for Consumer Research (SIFO), P.O. Box 4682, NO-0405 Oslo, Norway
Norwegian Forest and Landscape Institute, P.O. Box 115, NO-1431 Ås, Norway
h i g h l i g h t s
< The second-home market is important for nature-based tourism businesses.
< Their intention to purchase such products are influenced by leisure motives and demographic variables.
< Recreation experience preferences and reasons for having a second-home in an area influence their purchase intentions.
< Age and education level have a negative effect on the intention to purchase.
< Income has a positive effect on the intention to purchase.
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 5 May 2011
Accepted 8 October 2012
Tourism is acknowledged to be an important business sector in rural areas. This paper argues that
second-home owners constitute an important market segment for businesses that offer nature-based
tourism activities. Previous research has shown that a number of factors influence tourist behaviour.
This study examined how motivation and demographic variables affect second-home owners’ intention
to purchase three different types of activity products: learning, adventure, and hunting products. We found
substantial variations in the purchase intentions for these products among second-home owners. These
intentions were influenced by push and pull motivations, age, income and educational level. Secondhome owners with a high intention of purchasing nature-based tourism activity products tend to be
young, high-income, and socially oriented risk takers. Businesses offering nature-based tourism activity
products should use a combination of demographic and psychographic variables when they segment the
second-home market.
Ó 2012 Elsevier Ltd. All rights reserved.
Keywords:
Nature-based tourism activity products
Motivation
Behaviour models
Recreation experience preference (REP)
Purchase intention
Consumer behaviour
Market segmentation
1. Introduction
Tourism in rural areas has received attention in recent years and
has been acknowledged as an important business sector (Frochot,
2005). During the last two centuries, the agricultural sector in
Europe has been radically restructured. Rural areas that once
served primarily as locations for food and fibre production have
become sites for recreation and consumption (Burton & Wilson,
2006). The tourism trade is seen as a potential source of income
for rural municipalities in several countries, where traditional
business activities, such as agriculture and forestry, are seen as less
profitable (Briedenhann & Wickens, 2004; Nybakk, Crespell,
* Corresponding author. Tel.: þ47 98655822; fax: þ47 22043504.
E-mail addresses: torvald.tangeland@sifo.no (T. Tangeland), veb@
skogoglandskap.no (B. Vennesland), nye@skogoglandskap.no (E. Nybakk).
0261-5177/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.tourman.2012.10.006
Hansen, & Lunnan, 2009; Nybakk & Hansen, 2008; Place, 1991;
Tervo, 2008). This phenomenon also extends to emerging markets
(Sikora & Nybakk, 2012).
In Europe, the US and Canada, the scale of nature-based tourism,
a specific type of rural tourism, has increased sharply, partially due
to the rapid growth of second-home ownership in rural areas after
World War II (Jacobsen & Kristian, 1990; Kaltenborn, Andersen,
Nellemann, Bjerke, & Thrane, 2008). This increase has created
new economic opportunities for local communities. In recent years,
several Norwegian rural municipalities have built a large number of
second-homes, and companies have been established to sell
products and services to the owners of these homes. In 2008, there
were 388,220 second-homes in Norway, and approximately 1.2
million Norwegians (one in four) had access to one or more secondhomes (Statistikknett, 2010). These individuals therefore represent
an important segment of the Norwegian domestic market for
nature-based tourism products. However, second-home tourists
T. Tangeland et al. / Tourism Management 36 (2013) 364e376
differ from other tourists because they do not require accommodations and often independently organise transportation and
meals. When visiting their second-homes, they may choose to
perform outdoor activities in either non-commercial or commercial
contexts.
There is ongoing debate among researchers regarding the definition of nature-based tourism, and it has proven difficult to
establish an indisputable definition upon which the research
community can agree (Fennell, 2000; Mehmetoglu, 2007;
Rønningen, 2010). To further complicate the situation, the term
“nature-based tourism” is often used as a synonym for ecological,
sustainable, green, alternative, responsible or mountain tourism
(Higgings, 1996; Lee, 2009; Luzar, Diagne, Gan, & Henning, 1998;
Roberts & Hall, 2004; Weiler & Hall, 1992). These types of tourism,
which directly depend on the use of natural resources in relatively
pristine natural areas (Valentine, 1992), are collectively referred to
in this study as nature-based tourism.
Several nature-based tourism activity products revolve around
outdoor activities or include elements of outdoor activities.
Tourism and outdoor recreational activities performed in natural
areas often share the same resources and facilities and compete for
the same money and time, which makes the transitions between
them fluid (Carr, 2002; McKercher, 1996; Moore, Cushman, &
Simmons, 1995; Pomfret, 2006; Tangeland & Aas, 2011). In this
study, we argue that outdoor activities can be performed in four
different contexts defined by two dimensions: distance from home
and level of commercialisation (Fig. 1).
The World Tourism Organisation (WTO) defines tourists as
people “travelling to and staying in places outside their usual
environment for not more than one consecutive year for leisure,
business and other purposes” (1995: p. 1). Based on the WTO
definition, outdoor activities performed outside the context of one’s
daily life can be defined as tourism activities. There are two types of
nature-based tourism activities, non-commercial and commercial.
This study defines commercial nature-based tourism activity products as activities that take place primarily in nature, are dependent
on or enhanced by the natural environment and require a tourist to
pay a third party to participate (Tangeland & Aas, 2011). In contrast,
non-commercial nature-based tourism activities are defined as
activities that take place primarily in nature, are dependent on or
enhanced by the natural environment and are performed for free.
The challenge facing rural areas with a high number of secondhomes is their need to increase the number of homeowners who
purchase commercial activity products when they visit their
second-homes.
Commercial
Nature based
activity product
Nature-based tourism
activity products
365
Previous tourism research has shown that tourists’ behavioural
intentions and their actual behaviour are influenced by a range of
factors, such as age (Collins & Tisdell, 2002a), gender (Collins &
Tisdell, 2002b; Frew & Shaw, 1999; Meng & Uysal, 2008), family
life cycle (Fodness, 1992), household composition (Tangeland & Aas,
2011), nationality (Kim & Prideaux, 2005; Pizam & Sussmann,
1995), cultural background (Ng, Lee, & Soutar, 2007), personality
(Frew & Shaw, 1999), and values (Sirakaya & Woodside, 2005).
Although motivation has been a central research topic in tourism
since the 1970s and has been shown to be critical to understanding
and explaining tourist behaviour (Gnoth, 1997), and although
nature-based tourism has been a growth area for some time
(Fredman & Tyrväinen, 2010; Lee, 2009), few published studies
have examined tourists’ motivation to purchase nature-based
tourism products (Tangeland, 2011).
This study proposed the following research question: How do
the leisure motivations and demographic characteristics of secondhome owners influence their intention to purchase nature-based
tourism activity products? Previous studies have indicated that three
types of nature-based tourism activity products are relevant to the
rural mountain areas in Norway: learning products, adventure
products, and hunting products (Dervo, Aas, Kaltenborn, & Andersen,
2003; Nybakk, Vennesland, Hansen, & Lunnan, 2008; Tangeland &
Aas, 2011). In this study, we investigated second-home owners’
intention to purchase products in these three categories. The
findings obtained from this study will provide suppliers of naturebased tourism activity products with insight into tourist preferences and will establish a foundation for product development
based on the needs and desires of tourists in select market
segments. The findings will also provide planners in rural areas
with foundational knowledge that they can use to develop business
strategies that attract more second-home builders and to construct
targeted portfolios for local providers of nature-based tourism
products.
2. Theoretical framework
2.1. Behavioural models
Various academic disciplines have developed theories and
models to explain human behaviour. Social psychology has developed several theories and models that may explain behaviour
(Leone, Perugini, & Ercolani, 1999). The two most frequently used
models are the theory of reasoned action (Ajzen & Fishbein, 1980;
Fishbein & Ajzen, 1975) and its extended version, the theory of
planned behaviour (Ajzen, 1991) (Fig. 2). According to the latter
model, a person’s behaviour is influenced by his or her intention to
behave in a particular way. Intention is determined by three factors:
1) the person’s attitudes towards the behaviour; 2) the subjective
norms that he or she believes his or her significant other holds
Attitudes
Nature activity
near home
Non-commercial
tourism activity
Subjective
Norms
Intention
Behaviour
Free
Home/
Daily living
Away from
daily living
Fig. 1. Defining outdoor activities according to the context in which they are
performed.
Perceived
behavioural
control
Fig. 2. Ajzen’s theory of planned behaviour (Ajzen, 1991).
366
T. Tangeland et al. / Tourism Management 36 (2013) 364e376
concerning the behaviour; and 3) perceived behavioural control
(the perception of whether the behaviour can be performed). Both
the theory of reasoned action and the theory of planned behaviour
are considered to be simple and easily operationalised. These
theories have been applied with great success in a range of areas,
such as choice (Fishbein & Ajzen, 1981), leisure choice (Ajzen &
Driver, 1992), health (Reddy, York, & Brannon, 2010), education
(Poulter & McKenna, 2010), and career decision-making (Giles &
Rea, 1999).
However, Bagozzi and colleagues have criticised both theories
for not considering motivation as a condition for intention and
action (Bagozzi, 1992; Bagozzi & Kimmel, 1995; Bagozzi & Warshw,
1992; Perugini & Bagozzi, 2004). Furthermore, these authors have
criticised both of these theoretical models for claiming that attitudes affect direct intentions, noting that a positive attitude
towards a particular behaviour does not necessarily cause a person
to intend to behave accordingly. For example, a person may have
a positive attitude towards hiking on a glacier without having any
intention of purchasing an activity product that includes glacier
hiking. Bagozzi (1992) argued that the intention to perform an
action (e.g., to participate in a glacier expedition) does not develop
unless the person is motivated and has the desire to perform
a certain behaviour. Consequently, Bagozzi (1992) introduced
a third model, the theory of self-regulation (Fig. 3), which includes
a motivation variable. In this model, intention and behaviour are
dependent on desire as a motivation variable.
Leone et al. (1999) compared these three models (the theory of
reasoned action, the theory of planned behaviour and the theory of
self-regulation) and concluded that the self-regulation model had
the highest predictive power for intentions. Bagozzi and Kimmel
(1995) and Leone et al. (1999) indicated that the effects of attitudes and subjective norms on intentions cease to apply when the
motivation variable, desire, is included in the model. This finding
can be explained by the theory that attitudes are the result of
evaluations based on the cognitive and affective components of
specific objects (e.g., an action or product) (Eagly & Chaiken, 1993).
If the evaluation leads to a positive attitude, the evaluation motivates the person to perform the act (Perugini & Bagozzi, 2004).
Leone et al. (1999) suggested that further research should examine
the relationship between motivation and intention. Therefore, in
this study, we investigated how leisure motivations among secondhome owners influence their intention to purchase different types
of nature-based tourism activity products.
2.2. Motivation
Purchase motivation arises when a person is aware of a product
or service, and believes that purchasing and consuming that
product or service will produce a positive effect by satisfying an
unmet need (Goossens, 2000). Generally, motivation is defined as
the underlying psychological force that drives a person to act to
Attitudes
Desire
Intention
Behaviour
Subjective
Norms
Fig. 3. Bagozzi’s theory of self-regulation (Leone et al., 1999: p. 163).
achieve a goal (Iso-Ahola, 1982). According to motivation theory,
individuals constantly strive to achieve stability. Motivation is
believed to arise when there is a discrepancy between the
consumer’s ideal state and his or her actual state. This discrepancy
can create an uncomfortable level of tension (Fodness, 1994). When
this tension becomes sufficiently strong, it triggers actions intended
to reduce it.
Previous studies of tourist motivation have shown that motivation is the product of many motives, which makes it a complex
issue (Prebensen, 2006). A tourist may hope to satisfy several needs
by purchasing a product. Another factor that complicates the task of
predicting behaviour is that people may purchase different products to satisfy the same need. A third challenge is that people with
different needs may be motivated to purchase the same product
(Crompton & McKay, 1997). Nevertheless, it is agreed that motivation is a critical variable for explaining tourist behaviour, and
motivation has been used to explain decision-making and planning
processes (Bansal & Eiselt, 2004; Kim & Prideaux, 2005), destination choice (Beh & Bruyere, 2007; Goossens, 2000), destination
loyalty (Yoon & Uysal, 2005), and choices regarding activities and
products (Meric & Hunt, 1998; Qu & Ping, 1999; Tangeland, 2011).
Furthermore, motivation has been used with great success as the
core segmentation criterion in a number of studies (e.g. in Frochot,
2005; de Guzman, Leones, Tapia, Wong, & de Castro, 2006; Kibicho,
2005; Lee, Lee, & Wicks, 2004; Oh, Uysal, & Weaver, 1995; Park &
Yoon, 2009; Tangeland, 2011).
A review of the literature on tourism motivation indicates that
the pushepull model has served as the dominant paradigm for
formulating and testing motivation (Bansal & Eiselt, 2004). The
pushepull model provides a simple and intuitive approach to
exploring the underlying motivations of tourist behaviour
(Crompton, 1979; Dann, 1977). According to this model, push
factors are specific forces in a tourist’s life that lead him or her to
decide to travel outside his or her daily environment, and pull
factors are those forces that subsequently lead him or her to select
a destination (Klenosky, 2002). The push-motivation factors are
related to tourist needs and wants, such as the desire to take risks,
relax, be physically active, enjoy nature, learn something new, or
engage in social interaction (Devesa, Laguna, & Palacios, 2010). The
pull-motivation factors are linked to external, situational, or
cognitive factors, such as the attributes of the chosen destination
(Devesa et al., 2010; Klenosky, 2002). Examples of such attributes
for a rural mountain area include hiking opportunities, landscape
and scenery, and opportunities to hunt, angle, and ski. These
attributes motivate people to travel to a particular location or, in
this case, to purchase and travel to a second-home in a rural
municipality.
Crompton (1979) and Dann (1981) argued that push and pull
factors influence each other. Researchers have tended to use pushmotivation factors to explain the decision to travel and pullmotivation factors to explain location choice (Kim, Lee, &
Klenosky, 2003). However, several studies have shown that these
factors are not independent of each other (Kim et al., 2003; Oh
et al., 1995). Furthermore, research has shown that both factors
influence the initial travel decision and location choice (Klenosky,
2002; Yoon & Uysal, 2005). The sum of the push and pull motivations determines what a tourist does. It is therefore reasonable to
assume that people’s motivations for owning a second-home in
a certain location and their leisure motivations will influence the
activities that they intend to purchase when they visit their secondhomes.
During the last decade, motivation studies on nature-based
tourism have identified the following common push factors:
adventure and risk taking (Beh & Bruyere, 2007; Kim et al., 2003;
Luo & Deng, 2008; Skår, Odden, & Vistad, 2008), contemplation and
T. Tangeland et al. / Tourism Management 36 (2013) 364e376
escape from everyday routine (Beh & Bruyere, 2007; Kim et al.,
2003; Mehmetoglu, 2007; Skår et al., 2008), physical activity (Luo
& Deng, 2008; Mehmetoglu, 2007; Raadik, Cottrell, Fredman,
Ritter, & Newman, 2010; Skår et al., 2008), enjoyment of nature
(Luo & Deng, 2008; Raadik et al., 2010; Skår et al., 2008), selfdevelopment (Beh & Bruyere, 2007; Luo & Deng, 2008; Raadik
et al., 2010), and socialising (Eagles, 1992; Kim et al., 2003; Skår
et al., 2008; Tangeland, 2011). These motivational dimensions are
often measured using the recreation experience preference (REP)
scale, which was developed in leisure research to measure what
motivates people to perform activities in natural areas (Driver,
Tinsley, & Manfredo, 1991; Manfredo, Driver, & Tarrant, 1996). The
REP scale is widely used to measure people’s motivation to engage
in outdoor activities, and this scale has proven to be a reliable and
valid measurement tool (Hall, Seekamp, & Cole, 2010; Manfredo
et al., 1996; Raadik et al., 2010). The original REP scale consisted
of 19 motivational dimensions that were measured using 328 items
(Driver et al., 1991; Manfredo et al., 1996). Manfredo et al. (1996)
argued that a simplified version of the original REP scale could be
used if it was adapted to the context in which a study is implemented. In the past decade, several studies have employed
simplified REP scales to investigate push factors among tourists and
recreationists (e.g. Beh & Bruyere, 2007; Luo & Deng, 2008; Raadik
et al., 2010; Skår et al., 2008). The REP scale is part of a stream of
leisure-motivation research known as the experiential approach
(Manfredo et al., 1996). According to this approach, activities can
involve more than core activities such as angling and glacier hikes
and can be defined as psycho-physiological experiences that are
innately rewarding, take place during leisure time and are a result
of free will (Manfredo et al., 1996). This approach assumes that
behaviour is motivated and goal-oriented and that an individual’s
cognitive qualities, including his or her motives, needs, desires, and
benefits, are instrumental in directing behaviour (Ajzen & Driver,
1991). In a tourism context, this assumption means that tourists
believe that the benefits of an activity they perform (in terms of
their psycho-physiological experience) will be greater than the
costs (in terms of money and time). This belief is the basis for
exchanges between sellers and buyers (Mill & Morrison, 2009).
Pull-motivational factors are directly connected to a site’s
specific features. Thus, the factors identified in a study depend on
the study’s location. This dependence on location creates a challenge when researchers seek to generalise findings from one study
area to another. However, the common pull factors found in studies
conducted in rural areas are connected to landscapes and
surroundings (Eagles, 1992; Raadik et al., 2010; Saleh & Karwacki,
1996), opportunities to watch animals in their natural habitats
(Beh & Bruyere, 2007; Kim et al., 2003), wilderness and remoteness
(Eagles, 1992; Raadik et al., 2010; Saleh & Karwacki, 1996), and
opportunities for outdoor activities (Eagles, 1992; Saleh & Karwacki,
1996). Activities such as hiking, biking, hunting, angling and skiing
are examples of popular activities that Norwegians perform while
visiting their second-homes (Vaage, 2009). Clearly, there are
several pull factors that motivate people to travel to rural mountain
areas or, in this case, to purchase a second-home in a rural
municipality.
The a priori pushepull model has been shown to be a useful
means to understand tourist motivations in different contexts.
Therefore, the pushepull model was used in this study as the
conceptual framework for motivation. Furthermore, the literature
review indicates that some push and pull-motivational factors
significantly predict tourist behaviour in rural mountain areas.
Therefore, we examined how six push motivations (risk taking,
contemplation, physical fitness, enjoyment of nature, skill development, and social interaction) and three pull motivations (hiking
opportunities and surroundings, hunting and angling opportunities,
367
and proximity to ski resorts) affect the intention to purchase three
categories of nature-based tourism activity products (learning,
adventure, and hunting and angling) among tourists visiting their
second-homes. We believe that these motivational dimensions and
product categories are relevant to rural mountain areas. Clearly,
these motivational factors are location specific, and not all motivation factors affect the intention to purchase all three types of
products. However, this study suggests that these factors are generalisable to other countries and contexts.
3. Method
3.1. Questionnaire development and measurement
The questionnaire for this study was developed in the spring of
2007 using the principles of Dillman (2000) in cooperation with the
Ål municipality and tourism businesses in that area. The first draft
was read and commented upon by 12 representatives from various
forums (two from the municipality, six university students, two
local businesspeople and two second-home owners). Based on this
constructive feedback, we refined the questionnaire and sent the
new version to 15 second-home owners, 10 of whom responded.
We then implemented several minor changes based on the feedback of these second-home owners.
We measured the intention to purchase nature-based tourism
activity products by asking the respondents to rate how interested
they were in purchasing 13 such products on a scale from 1 to 7,
where only the endpoints were defined: 1 indicated “definitely not
purchasing the product” and 7 indicated “definitely purchasing the
product”. The three main types of nature-based tourism activity
products were learning products, adventure products, and hunting
products (Table 1). We defined learning products as tourism products that focus on the transfer of knowledge, either from businesses
to customers or among customers. Examples of important learning
themes include fauna, biodiversity, outdoor skills, history and
culture. The leisure and tourism literature defines adventure
differently depending on the context (Weber, 2001), but these
definitions share a degree of uncertainty connected to the outcome
of the activity. In this study, we define adventure products as
activities that take place in an outdoor area, are more exciting than
contemplative, and treat the outdoor environment as a setting for
the activity rather than as a place to enjoy scenery, plants or
animals. Furthermore, adventure products are activities that involve
the risk of injury or even death (Carnicelli-Filho, Schwartz, &
Tahara, 2010), such as kayaking, mountain biking, rafting, kiting
and downhill skiing. Hunting products are activities such as big- and
small-game hunting that are sold to tourists visiting the area.
Hunting is based on limited resources and private rights that can be
sold in a market. Across Europe, there is a long-standing tradition in
which landowners, both private and public, sell hunting privileges
on their land. However, the price of such activity products varies
greatly. Low-priced products usually include licences that provide
access to hunting areas, whereas high-priced products often
include accommodations and guides (Tangeland & Aas, 2011).
We measured push motivation using an abbreviated version of
the recreation experience preference (REP) scale (Driver et al., 1991;
Manfredo et al., 1996). The respondents used a scale of 1e7 (where
only the endpoints were defined: 1 corresponded to “strongly
disagree” and 7 corresponded to “strongly agree”) to rate how
strongly 25 items motivated them to engage in nature activities
(Table 2). These 25 items were related to six push-motivational
dimensions: risk taking, contemplation, physical fitness, enjoyment
of nature, skill development, and social interaction.
The respondents were then asked to use a scale of 1e7 (where
only the endpoints were defined: 1 meant “not important” and 7
368
T. Tangeland et al. / Tourism Management 36 (2013) 364e376
Table 1
Dependent variables: learning products, adventure products and hunting products.
Meanc (SD)
Item total
correlation
Alpha if item
deleted
Learning products (Depend1) (n ¼ 1003)
Activity products where I can learn about nature and animals
Activity products where I can learn about handling dangers
in the mountains
Activity products where I can experience unspoiled nature
Activity products where I can learn about outdoor skills
2.82 (1.59)
3.00 (1.82)
2.61 (1.69)
.86
.83
.86
.87
3.18 (1.96)
2.49 (1.64)
.78
.75
.88
.89
Adventure products (Depend2) (n ¼ 1008)
Activity products including kayak paddling or canoeing
Activity products including mountain biking
Activity products including white water rafting
Activity products including kiting
Downhill skiing
2.02
2.33
2.05
2.01
1.76
3.30
(1.32)
(1.69)
(1.56)
(1.55)
(1.45)
(2.25)
.66
.67
.78
.65
.38
.75
.75
.73
.76
.87a
Hunting products (Depend3) (n ¼ 1020)
Small-game hunting including guiding, coursing, food
and/or accommodation
Big game hunting including guiding, coursing food
and/or accommodation
1.92 (1.53)
2.05 (1.75)
.74
b
1.81 (1.50)
.74
b
a
b
c
Cronbach’s
alpha
.92
.81
Deleted
.88
Deleted because a lower alpha than alpha if deleted.
Two items only e alpha if deleted not relevant.
Scale: 1 ¼ “definitely not purchasing the product” and 7 ¼ “definitely purchasing the product”.
meant “very important”) to rate the degree to which nine characteristics of the area around the municipality influenced their
decision to purchase a second-home in that area (Table 3). These
nine characteristics were related to three pull-motivational
dimensions: hiking opportunities and surroundings, proximity to ski
resorts, and hunting and angling opportunities. The three pull
motivations were defined through discussions with the local
authorities and the office of tourism commerce in the region. We
also defined these pull motivations using the motivational
dimensions that had been identified as important in previous
research on destination choice in nature-based tourism.
In addition, we asked demographic questions about age,
income, and education, which we used as control variables in the
three models.
3.2. Data treatment
Intention and motivation were measured using seven-point
Likert scales, where only the endpoints were defined: these can be
observed in Tables 1e3. There is an ongoing debate about whether
such data should be treated as ordinal or continuous variables in
data analysis (Borgatta & Bohrnstedt, 1980; Jamieson, 2004;
Norman, 2010). In this paper, we treat these variables as continuous
even though the measurement variables are not mathematically
continuous (Stevens, 1951). Stevens (1951) argued that this
approach violates the assumption of continuity, which is a prerequisite for the use of parametric tests (e.g., mean, Pearson correlation,
ANOVA, and OLS regression). However, there are several reasons for
taking this approach (Hair, Anderson, Tatham, & Black, 2010). First,
when only the endpoints are defined, the values between them are
only meaningful in relation to the defined endpoints. For the
respondents, the measuring interval is experienced as continuous
from one to seven, even though the scale only includes seven points
and is not infinite, which it should be to be mathematically continuous (Adams, 2006). Furthermore, to use parametric tests, it is not
the measurement variable but the construct at the conceptual level
that must be continuous (Borgatta & Bohrnstedt, 1980), and we
assume that purchase intention is continuous.
Second, single Likert questions or items (like the ones we used)
may well be ordinal, but constructs that consist of sums across many
items can be converted into continuous variables when the number
of items increases (Norman, 2010; Vaske, 2008). In this study, the
constructs consist of between two and five items. Third, regarding
the robustness of parametric tests (the extent to which a test will
give the right answer even when assumptions are violated (Norman,
2010). Jamieson (2004) argues that when wrong statistical technique is used it increases the likelihood of coming to the wrong
conclusion. However, it has been argued that the robustness of
parametric tests is so high that there is a small chance of the latter
outcome even if some assumptions are violated (Borgatta &
Bohrnstedt, 1980; Norman, 2010; Vaske, 2008).
Fourth, according to Vaske (2008) and Norman (2010), there is
a long tradition within the quantitative social sciences of treating
data collected through surveys using five-, seven- or 11-point scales
as continuous variables and using parametric tests in analysing
them (e.g. in Berne, Garcia-Gonzalez, & Mugica, 2012). In this study,
we employ this established practice.
3.3. Sampling and data collection
To ensure the isolation of the study and minimal variation due to
unknown variables, we limited the data collection to one region.
After 1960, cars became common in Norwegian households,
allowing more people to build cabins in the mountains and on the
coast (Berg, Julsrud, & Kristiansen, 2003; Jacobsen & Kristian, 1990).
The Ål municipality was selected as a sample setting for this study
because it is a typical Norwegian mountain village and has developed in a manner that is similar to the trajectory of many other
Norwegian municipalities that are perceived as attractive locations
for second-homes in mountainous areas.
The questionnaires were sent via post to all of the private
second-home owners registered in the Ål municipality renovation
register, which includes all of the second-homes in the municipality
(2058). This procedure ensured that we contacted the individuals
who had the most knowledge about the use of these second-homes.
In the cover letter, the respondents were informed that they could
choose to complete the questionnaire on paper or online. A total of
1128 owners responded (54.8%). The majority of the respondents
returned the paper questionnaire (80%), and the remaining owners
chose to respond using the online version (20%).
T. Tangeland et al. / Tourism Management 36 (2013) 364e376
Table 2
Independent push-motivation variables.
Table 3
Independent pull-motivation variables.
Meanb (SD) Item total Alpha Cronbach’s
correlation if item alpha
deleted
Risk taking (Push 1) (n ¼ 1021)
Experience the thrill of speed
I get to experience the
excitement because the
task is challenging
The equipment allows for
experience of speed
Taking calculated risks
Experience adventure in a
nature area
2.66 (1.41)
3.02 (1.69) .80
3.04 (1.68) .78
Contemplation (Push 2)
(n ¼ 1027)
Getting away from the hustle
and bustle
Change from daily routine
Have time to think about life
I find peace and quiet
Getting away from
every daily life
6.27 (.89)
Physical fitness (Push 3)
(n ¼ 1039)
Exercise
Full body workout
Taking care of my own health
Become completely exhausted
Nature is perfect as a gym
6.00 (1.03)
Enjoyment of nature (Push 4)
(n ¼ 1033)
Experience peace and quiet
in nature
Experience fellowship with
nature
Experience the landscapes
and moods of nature
Enjoy flora and fauna
6.13 (.97)
Skill development (Push 5)
(n ¼ 1028)
I’m getting better at coping
with various
outdoor skills
I can develop different
outdoor skills
I feel they have control
over the body
4.46 (1.52)
Social interaction (Push 6)
(n ¼ 1037)
Being with family
Being with friend
Being with others who likes
to perform
same activities as me
5.55 (1.28)
a
b
.91
.89
.90
2.47 (1.62) .80
.89
2.36 (1.62) .69
2.40 (1.57) .83
.91
.88
.74
.89
6.33
5.96
6.39
6.26
.79
.74
.75
.80
.88
.89
.88
.87
(.98)
(1.26)
(.98)
(1.04)
(1.14)
(1.14)
(1.09)
(1.36)
(1.31)
6.43 (.98)
Meanb (SD)
Hiking opportunities and
surroundings (Pull 1)
(n ¼ 1010)
Hiking opportunities
Good access to cross
country ski trails
Access to the wild and
unspoiled nature
Second-home is located in
a child friendly area
Good conditions for cycling
5.20 (1.21)
Proximity to ski resorts
(Pull 2) (n ¼ 1018)
Local ski resorts
Other ski resorts in
the region
2.58 (1.73)
Hunting and angling
opportunities (Pull 3)
(n ¼ 1022)
Hunting opportunities
Angling opportunities
3.04 (1.74)
Item total
correlation
Alpha if
item
deleted
Cronbach’s
alpha
.72
6.23 (1.26)
6.03 (1.46)
.57
.53
.66
.66
5.02 (1.80)
.44
.69
4.39 (2.06)
.45
.69
4.30 (1.99)
.50
.67
.90
6.42 (.97)
6.10
6.06
6.13
5.75
6.00
369
.88
.62
.83
.74
.72
.69
.88
.83
.85
.85
.86
a
b
.85
.71
.81
6.01 (1.25) .76
.79
6.36 (.99)
.77
.79
5.72 (1.38) .61
.87
.85
4.43 (1.59) .87
.80
4.76 (1.60) .73
.93a
2.27 (1.99)
3.80 (2.12)
.71
.71
a
a
.60
.43
.43
a
a
Two items only e alpha if deleted not relevant.
Scale: 1 ¼ “not important” and 7 ¼ “very important”.
over 16 years of age has studied at a university (SSB, 2010). Half of
the second-home owners reported that two people were living in
their household, and one-third of the respondents lived in
a household consisting of three to five people.
3.5. Non-response bias test
.90
4.48 (1.56) .82
2.64 (1.88)
2.51 (1.85)
.83
The use of a questionnaire with a response rate that is not
extremely high generates concerns regarding non-response bias.
When the response rate is fairly high (as in this study), the response
rate may be a source of error (Needham & Vaske, 2008). We tested
for non-response bias by comparing the early and late responses
using a t-test, as recommended by Armstrong and Overton (1977).
The non-response bias test showed no significant differences for
the variables in question.
Deleted
3.6. Analyses
5.98 (1.35) .67
5.11 (1.60) .73
4.80 (1.74) .50
.78
.66
.59
.83a
Deleted
Deleted because a lower alpha than alpha if deleted.
Scale: 1 ¼ “strongly disagree” and 7 ¼ “strongly agree”.
3.4. Demographics
The ages of the second-home owners were relatively high: 57%
were between 46 and 64 years old, and 26% were 65 or older. Less
than 1% of the second-home owners were under the age of 26. The
average household income was 167,275 USD (898,000 NOK). The
educational level of the second-home owners in the sample was
also high: only one in four did not have a university degree and
almost half (46%) had studied for more than three years at
a university. Only one-fourth of the general Norwegian population
We performed all of the statistical analyses using SPSS 20 and
used Cronbach’s alpha analyses to test for reliability (i.e., “item total
correlation” and “alpha if item deleted”). Conventionally, a good
alpha score falls between .7 and .8 (Bryman & Cramer, 2001). We did
not accept scores lower then .6, which indicate weak consistency. In
addition, we deleted all items with an “alpha if item deleted” higher
than the overall Cronbach’s alpha. After the reliability analyses, we
constructed composite variables using the mean of the extracted
items for each factor (construct). We used OLS regression analyses to
test the impact of the nine motivation factors on purchase intention
in the three product categories (Hair et al., 2010). In nonexperimental social studies, the independent variables are virtually always intercorrelated. This intercorrelation creates a problem
for estimation when it becomes extreme (Lewis-Beck, 1980). LewisBeck (1980) argued that if the correlations between the independent
variables are less than .8, multicollinearity is not an issue. The
correlation matrix was controlled for values greater than .8, and
a variance inflation factor (VIF) test was conducted to check for
multicollinearity.
370
T. Tangeland et al. / Tourism Management 36 (2013) 364e376
4. Analysis and results
4.1. Reduction of items and construct reliability
We deleted three items related to the intention variables (which
are dependent in the three models) because they would have
increased the Cronbach’s alpha (Table 1). All three observed
intention variables had alpha scores ranging from .87 to .92, indicating good reliability. Two items related to the “push” constructs
were deleted because they would have increased the Cronbach’s
alpha (Table 2). All of the observed “push” constructs had alpha
scores ranging from .83 to .93, indicating good reliability. None of
the items related to the observed “pull” variables were deleted
because they had low “item total correlation” and high “alpha if
item deleted” (Table 3). However, two of the constructs had only
two items. Two of the constructs had acceptable alphas (.72 and
.83), which indicated acceptable reliability. The hunting and angling
opportunities construct had a low alpha (.60) but an acceptable
level. The Cronbach’s alpha test is strict when only two items are
present. The correlation coefficients show that overall, the three
dependent variables for purchase intention were significantly and
positively related to all of the variables, although adventure products and hunting products were not significantly related to
contemplation and enjoyment of nature (Table 4).
A descriptive analysis showed that of the three intention
variables, learning products had the highest mean (M ¼ 2.82 on
a seven-point scale; SD ¼ 1.59), followed by adventure products
(M ¼ 2.02; SD ¼ 1.32) and hunting products (M ¼ 1.92; SD ¼ 1.53)
(Table 1). All three product categories had relatively high standard
deviations, which indicate the presence of large variations among
the respondents in terms of their purchase intentions for products
in the three categories. We defined the respondents with
purchase intention scores above four (the mean value on the
seven-point scale) as potential buyers. One-fifth of the secondhome owners had the intention of purchasing learning products,
and one-tenth had the intention of purchasing adventure and/or
hunting products.
The contemplation factor was the most important pushmotivation factor (M ¼ 6.27 on a seven-point scale) and was the
most salient for the respondents. The contemplation factor had
a standard deviation of .89, which indicates that the individual
mean scores were closer to the sample mean than those of the
other factors (i.e., greater consensus existed within the sample;
Table 2). In terms of importance, this factor was followed by
enjoyment of nature (M ¼ 6.13; SD ¼ .97), physical fitness (M ¼ 6.00;
SD ¼ 1.03), and social interaction (M ¼ 5.55; SD ¼ 1.28). The two
least important push-motivation factors in the sample were skill
development and risk taking (M ¼ 4.46 and M ¼ 2.66, respectively).
However, these factors had the highest standard deviations
(SD ¼ 1.52 and SD ¼ 1.41, respectively) among the push-motivation
factors, which indicates that the respondents varied the most in
ranking the importance of these two factors.
Among the pull-motivation factors, hiking opportunities and
surroundings was the most important reason for having a secondhome in a rural mountain municipality (M ¼ 5.20 on a sevenpoint scale; SD ¼ 1.21), followed by hunting and angling opportunities (M ¼ 3.04; SD ¼ 1.74) and proximity to ski resorts (M ¼ 2.58;
SD ¼ 1.73) (Table 3). All three pull-motivation factors had relatively
high standard deviations, which indicated the existence of
substantial variations in the sample.
4.2. The effect of push and pull factors on the intention to purchase
nature-based tourism activity products
This paper studied the impact of risk taking, contemplation,
physical fitness, enjoyment of nature, skill development, social interaction, hiking opportunities and surroundings, hunting and angling
opportunities, and proximity to ski resorts on tourists’ intention to
purchase three types of nature-based tourism activity products
(learning, adventure and hunting products) during visits to their
second-homes. Age, income and educational level were used as the
control variables. The model was tested using an OLS regression
model, and the results are presented in Table 5.
Two of the six push-motivation factors had a significant effect
on the intention to purchase at least one of the three types of
nature-based tourism activity products. Risk taking had a positive
effect on the intention to purchase all three product types. Social
interaction had a positive effect on the intention to purchase
learning products. All three pull-motivation factors significantly
influenced the intention to purchase nature-based tourism activity
products. Hiking opportunities and surroundings had a positive effect
on the intention to purchase both learning and adventure products.
Proximity to ski resorts had a positive effect on the intention to
purchase both learning and adventure products. Hunting and angling
opportunities had a positive effect on the intention to purchase both
learning and hunting products. All three demographic control variables significantly influenced the intention to purchase naturebased tourism activity products. Age had a negative effect on the
intention to purchase adventure and hunting products. The intention
to purchase adventure and hunting products was positively affected
by income. Education had a negative effect on the intention to
purchase learning and hunting products.
As a whole, the model, which included six push-motivation
factors, three pull-motivation factors and three demographic variables, explained 11.9% of the variation in purchase intentions for
learning products, 21.9% of the variation in purchase intentions for
adventure products, and 12.6% of the variation in purchase intentions for hunting products (Table 5). The correlation matrix in
Table 4
Pearson correlation coefficients for the observed dependent and independent variables.
1
1. Depend1
2. Depend2
3. Depend3
4. Push 1
5. Push 2
6. Push 3
7. Push 4
8. Push 5
9. Push 6
10. Pull 1
11. Pull 2
12. Pull 3
2
1
.428**
1
3
4
.320**
.439**
1
.213**
.375**
.173**
1
5
6
7
8
9
10
11
12
.135**
.055
.044
.099**
1
.180**
.120**
.104**
.260**
.472**
1
.128**
.036
.022
.022
.524**
.407**
1
.192**
.145**
.098**
.424**
.355**
.466**
.419**
1
.227**
.072*
.078*
.197**
.419**
.364**
.285**
.343**
1
.278**
.188**
.105**
.250**
.321**
.356**
.278**
.300**
.324**
1
.151**
.255**
.149**
.274**
.058
.086**
.037
.124**
.148**
.260**
1
.178**
.098**
.285**
.159**
.142**
.141**
.190**
.247**
.142**
.265**
.218**
1
*Correlation is significant at the .05 level. **Correlation is significant at the .01 level.
T. Tangeland et al. / Tourism Management 36 (2013) 364e376
Table 5
Push and pull factors effect on intention two purchase nature-based tourism activity
products.a
Independent variables:
Push
Risk taking
Contemplation
Physical fitness
Enjoyment of nature
Skill development
Social interaction
Pull
Hiking opportunities
and surroundings
Proximity to ski resorts
Hunting and angling
opportunities
Control variable
Age
Income
Education
Dependent variables
Learning
products
Betab
Adventure
products
Betab
Hunting
products
Betab
.100***
.029
.036
.041
.012
.115***
.273***
.001
.023
.059
.001
.030
.086**
.028
.060
.013
.013
.013
.159***
.099***
.058*
.084**
.117***
.001
.047
.252***
.007
.008
.065*
.182***
.098***
.047
.065**
.151***
.078**
R2Adj: .119
Sig. F: .00
Df ¼ 12
N ¼ 965
R2Adj: .219
Sig. F: .00
Df ¼ 12
N ¼ 965
R2Adj: .126
Sig. F ¼ .00
Df ¼ 12
N ¼ 960
.001
P-value (*10%, **5%, ***1%).
a
All three models was tested in an OLS regression.
b
Standardised coefficients.
Table 4 showed no indication of multicollinearity problems, and all
of the correlations between the independent variables were below
.53. The variance inflation factor (VIF) values varied from 1.1 to 1.7
and indicated that there were no multicollinearity problems in the
three models.
5. Discussion
When tourists stay at their second-homes in rural areas, they
may choose to perform outdoor activities of a “free” and unorganised nature or within a well-organised “commercial” context. A
number of nature-based tourism activity products are based on
special-interest outdoor recreational activities such as hunting,
which often require participants to possess special skills to perform
the activity and require them to use necessary specialised equipment (Buckley, 2007). The necessary skills can take years to master
through practice in the field. However, in post-industrialised economies, these outdoor recreational activities are often treated as
short-term holiday experiences that can be purchased rather than as
skills that are gradually acquired over a lifetime (Kane & Zink, 2004).
It has been argued that a lack of experience and knowledge drives
some recreationists to give up some of their independence to enjoy
an unproblematic guided trip (Pomfret, 2011; Tangeland, 2011).
The study results revealed substantial variations in secondhome owners’ intention to purchase nature-based tourism
activity products during visits to their second-homes. The most
popular product category was learning products, which one-fourth
of the second-home owners intended to purchase. Adventure and
hunting products were tied for second place; one out of ten secondhome owners intended to purchase these products while staying at
their second-homes. The results also showed that among secondhome owners, the intention to purchase activity products was
influenced by push and pull factors and demographic variables.
371
The push factors extracted from the REP scale (Manfredo et al.,
1996) can be described to some extent as general motivation
factors for travelling to natural areas and performing activities. The
findings of this study support previous research on tourist and
recreationist motivations that concluded that contemplation, physical
fitness, enjoyment of nature, skill development, and social interaction
are central to explaining why people perform outdoor activities (e.g.
in Beh & Bruyere, 2007; Kim et al., 2003; Luo & Deng, 2008; Raadik
et al., 2010; Skår et al., 2008). Several studies have identified risk
taking as a central motivation for participating in outdoor activities
(e.g. in Beh & Bruyere, 2007; Kim et al., 2003; Luo & Deng, 2008; Skår
et al., 2008). The findings obtained from this study did not support
the notion that risk taking was a central motivation factor for secondhome owners given that risk taking had the lowest mean score
among the push-motivation factors for this segment as a whole.
Based on the literature review, we assumed that all six push
motives would impact purchase intentions. However, only risk
taking and social interaction affected the purchase intentions of the
surveyed second-home owners. Risk taking was the only push
motive that positively impacted purchase intentions for all three
types of nature-based tourism products studied in this paper.
Bentley and Page (2008) argued that it is important to distinguish
between actual risk and perceived risk. The risk of an outcome has
been assumed to be part of the motivation to participate in activities that can be seen as risky. However, previous research has
indicated that for many people, the actual risk does not significantly
influence participation in such activities (Weber, 2001). Cater
(2006) found that people engaging in adventure tourism activities are motivated by the experience of fear and excitement
(perceived risk) rather than by actual risk. Studies have also shown
that experiencing and controlling fear is the central motivation for
participating in adventure activities (Carnicelli-Filho et al., 2010).
Based on the five items that defined the risk motive, in this study,
our findings show that tourists who are motivated by risk are more
likely to spend money on activities in general. This observation
implies that attracting risk seekers increases the opportunity to
offer nature-based activity products in an area. The second push
factor that affected purchase intentions was social interaction,
which was positively related to learning products but not to the
other two product categories. Time spent with family and friends
can be associated with products that provide information concerning different animal species or wilderness survival for example.
Both adventure and hunting products, as defined in this study, are
products with a low social orientation. Although a minority of the
push factors that were extracted from the REP scale affected the
intention to purchase tourism activity products, the findings of this
study clearly show that aspects of the REP scale can be used to
predict the purchase of nature-based tourism activity products.
The four push factors, contemplation, physical fitness, enjoyment
of nature, or skill development, did not seem to affect the purchase
intentions of second-home owners. The high level of insignificance
of the push factors on purchase intentions can be explained by the
close relationship between non-commercial and commercial
nature-based tourism activities. The needs underlying the four
insignificant push factors can be satisfied by performing outdoor
activities regardless of the context in which those activities are
undertaken (Tangeland & Aas, 2011) or by remaining at one’s
second-home. Therefore, these needs do not create a desire to
purchase activity products. Nevertheless, we did not expect that
skill development would have no effect on the intention to purchase
learning products. This result shows that the second-home owners
who participated in this study believed that they could develop
skills by performing activities in both non-commercial and
commercial contexts. Another explanation is connected to the
needs underlying some of these motives (e.g., contemplation and
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T. Tangeland et al. / Tourism Management 36 (2013) 364e376
physical fitness). These needs can also be satisfied through the
consumption of other tourism products that are not nature based
(e.g., by visiting a cinema or fitness centre). Although these needs
do not influence purchase intentions, they are important to secondhome owners. To succeed, nature-based tourism businesses that
target the second-home market segment by emphasising risk and
social interaction should develop products that also satisfy the
needs underlying these insignificant push factors.
We found relatively large variations in importance for the three
pull factors. The differences can be partially explained by the
differing levels of generality of the constructs. The hiking opportunities and surroundings pull factor is a general motivation that many
people share. However, the other two pull factors, hunting and
angling opportunities and proximity to ski resorts, are more specialised, and their importance depends on more specific outdoor
recreational interests. Therefore, it was unsurprising that these two
pull factors were less important for the sample as a whole. The
substantial standard deviations for hunting and angling opportunities
and proximity to ski resorts indicate the large variation in the sample.
This study assumed that people’s motivations for having a secondhome at a specific location also affect their intention to engage in
various activities during their visits to those homes. As expected, all
three pull factors influenced second-home owners’ intention to
purchase nature-based tourism activity products, and all three pull
factors positively affected the intention to purchase learning products. The intention to purchase adventure products was positively
influenced by hiking opportunities and surroundings and proximity to
ski resorts. Only the hunting and angling opportunities pull factor had
an effect on the intention to purchase hunting products.
Our review of the tourism motivation literature indicated that
tourists’ intentions and behaviour are usually influenced by more
than one motive and that the sum of the push and pull factors
determines tourists’ actions (Funk & Bruun, 2007; Klenosky, 2002;
Prebensen, 2006). This study clearly showed that second-home
owners’ purchase intentions regarding nature-based tourism
activity products were simultaneously influenced by several
motivational dimensions and varied across product categories.
Furthermore, we showed that three of the motivational factors (risk
taking, hiking opportunity and surroundings, and proximity to ski
resorts) significantly affected purchase intentions in more than one
of the product categories. This finding indicates that tourists
believe that a particular need can be fulfilled through consumption
within different product categories.
The findings clearly show that people’s motivations for having
a second-home in a certain location (pull motives) and their preferences regarding their recreational experiences (push motives)
influence the activities that they intend to purchase when they visit
their second-homes. Our findings support the previous research on
the motivation and behaviour of tourists, which argued against the
existence of a one-to-one relationship between motives and
behaviour (Prebensen, 2006). We therefore argue that Bagozzi
(1992) oversimplified the concept of motivation by including only
one general motivational dimension, desire, in the theory of selfregulation. When attempting to predict the behaviour of tourists,
researchers must consider both push and pull factors.
It has been argued that socio-demographic variables have an
indirect effect on behaviour and therefore have lower predictive
power than variables that are more directly connected to behaviour, such as motivation (Frochot & Morrison, 2000; Lee et al., 2004;
Li, Huan, & Chi, 2009). Nevertheless, this study has shown that
purchase intentions for all three product categories were significantly affected by all three socio-demographic control variables
(i.e., age, income and educational level). The negative effect of age
on purchase intentions may indicate the presence of a generational
effect. Younger people are generally willing to pay for nature-based
activities that are often available for free. This finding has several
implications for the nature-based tourism industry. First, businesses should focus on young people when they develop and
market their products because more young people have a positive
intention to purchase nature-based tourism products. Second, if the
effect of age is connected to a generational effect, the demand for
nature-based tourism products will likely increase in the future.
Unsurprisingly, income had a positive effect on the intention to
purchase adventure and hunting products. Higher incomes tend to
increase spending power. Previous studies of tourists who purchase
nature-based tourism products have found a higher educational
level within this group than in the average population (Holden &
Sparrowhawk, 2002; Mehmetoglu, 2005; Meng & Uysal, 2008;
Meric & Hunt, 1998; Tangeland, 2011; Tangeland & Aas, 2011). We
expected that educational level would have a positive effect on the
intention to purchase nature-based tourism activity products,
especially learning products. We were therefore surprised to find
that education level negatively affected the intention to purchase
learning products. Education level also negatively affected the
intention to purchase hunting products. It is important to remember
that the general educational level in the study sample was high.
Although the average education level was lower among those who
exhibited higher purchase intentions than among those who
exhibited lower purchase intentions, the education level in the
sample was still higher than that of the general population.
6. Conclusions
This study aimed to investigate how the leisure motivations and
demographic characteristics of second-home owners influence
their intention to purchase nature-based tourism activity products.
The findings showed that second-home owners’ intention to
purchase nature-based tourism activity products were influenced
by push and pull factors as well as socio-demographic variables.
The results of this study have significant theoretical and practical
implications.
One of the theoretical implications relates to the behavioural
models developed within social psychology. We support Bagozzi
and colleagues (Bagozzi, 1992; Bagozzi & Kimmel, 1995; Bagozzi &
Warshw, 1992; Perugini & Bagozzi, 2004) in their criticism of both
the theory of reasoned action (Ajzen & Fishbein, 1980; Fishbein &
Ajzen, 1975) and the theory of planned behaviour (Ajzen, 1991)
due to these theories’ lack of a motivation variable as a condition for
intention and action. However, the findings obtained from this
study also show that purchase intentions are influenced by several
motives. Therefore, we argue that Bagozzi (1992) oversimplified the
concept of motivation by including only one general motivational
dimension, desire, in the theory of self-regulation. Furthermore,
purchase intentions are directly influenced by socio-demographic
variables. When using the theory of self-regulation to predict
tourist behaviour, researchers must use both push and pull-motivation factors as well as socio-demographic variables in the model.
Another theoretical implication is connected to the use of the
recreation experience preference (REP) scale. Traditionally, the REP
scale has been used to explain why people travel to natural areas
and perform outdoor activities (Raadik et al., 2010). The REP scale
has been shown to be a reliable and valid measurement tool
(Manfredo et al., 1996). The findings from this study show that the
REP scale can also be used to predict the purchase of nature-based
tourism activity products. This finding expands the applicability of
the REP scale to a new area.
The findings of this investigation also provide important
suggestions regarding the management and marketing of naturebased tourism attractions and destinations. The second-home
tourist market segment is clearly important for tourism
T. Tangeland et al. / Tourism Management 36 (2013) 364e376
businesses in rural areas that offer nature-based tourism activity
products. However, our findings showed substantial variations in
second-home owners’ intention to purchase nature-based tourism
activity products, which were influenced by both psychographic
and socio-demographic variables, showing that second-home
owners are a complex group of tourists with different needs and
desires that they wish to satisfy during visits to their secondhomes. Sub-segments within this group of tourists can be clearly
identified using leisure motivations and demographic variables as
the core segmentation criteria. Developing products tailored to the
needs and wants of the selected market segments is likely to
increase the turnover of the businesses in question because these
needs will increase purchase intentions and purchasing behaviours
in the targeted sub-segments within the second-home market.
Suppliers in areas with large numbers of second-homes should
regard the owners of these second-homes and their family
members and friends as potential customers.
These findings are also of interest to policymakers in rural areas.
Many rural municipalities aim to strengthen and expand secondhome villages. Particularly substantial investments have been
made in winter destinations and ski resorts. However, it is crucial to
gather as much information as possible about the owners of
second-homes to increase the chances of satisfying them and
attracting new owners. Most second-homes are intended to be
used for relaxation and vacationing. Therefore, we should focus on
the best ways to help the members of this consumer group to enjoy
themselves. In local economic development programmes,
numerous attempts have been made to transform free recreational
facilities into nature-based activity products to be sold in the
market (Lunnan, Nybakk, & Vennesland, 2006; Tangeland & Aas,
2011). If they understand what motivates a second-home owner
to relax in nature and which nature-based tourism products the
homeowner might be motivated to purchase, policymakers can
devise better strategies to strengthen and expand second-home
villages. However, for local rural economies to grow, visitors must
spend money while staying in their second-homes. Policymakers
must stimulate the formation of new business establishments in
the tourism industry to ensure the viability of rural areas.
Furthermore, tourists may take daily trips from their second-homes
to the surrounding areas, so products and services can be offered
within driving distance of second-home villages.
The results of this study should be viewed in light of the
following limitations. First, this study was cross-sectional and
cannot provide absolute conclusions regarding causality.
However, the study’s results, as supported by the relevant theory,
were consistent with our assumptions regarding causality.
Second, the study was conducted prior to the global recession,
and this event may have influenced the market for these products. Third, substantial regional differences exist with regard to
second-home owners’ preferred recreational experiences and
willingness to purchase nature-based tourism activity products. A
similar study should be conducted in multiple destinations to
determine whether the findings are consistent over time and
across regions.
Acknowledgements
This study was made possible by grants from the Norwegian
Research Council. We want to thank master’s student Kristian
Kvistad Holm and the Ål Municipality for their assistance with the
survey. We would also like to thank Dr. Øystein Aas (Norwegian
Institute for Nature Research and Norwegian University of Life
Sciences) and Dr. Jan Vidar Haukeland (Norwegian University of Life
Sciences) for reviewing an earlier version of the paper.
373
Appendix A
Appendix Table 1
Descriptive statistics for the dependent items.
N
Activity products where
I can learn about
nature and animals
Activity products where
I can learn about handling
dangers in the mountains
Activity products where I
can experience unspoiled
nature
Activity products where
I can learn about
outdoor skills
Activity products including
kayak paddling or
canoeing
Activity products including
mountain biking
Activity products including
white water rafting
Activity products including
kiting
Downhill skiing
Small-game hunting
including guiding,
coursing, food and/or
accommodation
Big game hunting including
guiding, coursing, food
and/or accommodation
Min Max Mean SD
Skewness Kurtosis
1031 1
7
3.00
1.808
.568
.727
1035 1
7
2.61
1.676
.883
.079
1020 1
7
3.18
1.955
.511
.921
1031 1
7
2.49
1.627 1.034
.316
1033 1
7
2.33
1.692 1.204
.479
1034 1
7
2.05
1.556 1.499
1.260
1037 1
7
2.01
1.552 1.574
1.529
1021 1
7
1.76
1.445 2.012
3.129
1037 1
1024 1
7
7
3.30
2.05
2.253 .420
1.745 1.643
1.328
1.513
1032 1
7
1.81
1.499 2.026
3.327
Appendix Table 2
Descriptive statistics for push items.
N
Experience peace and quiet
in nature
Experience fellowship with
nature
Experience the landscapes
and moods of nature
Enjoy flora and fauna
I’m getting better at coping
with various outdoor
skills
I can develop different
outdoor skills
I feel they have control
over the body
Experience the thrill of
speed
I get to experience the
excitement because
the task is challenging
The equipment allows for
experience of speed
Taking calculated risks
Experience adventure in a
nature area
Exercise
Full body workout
Taking care of my own
health
Become completely
exhausted
Nature is perfect as a gym
Getting away from the
hustle and bustle
Min Max Mean SD
Skewness Kurtosis
1042 1
7
6.43
.978 2.262
6.673
1039 1
7
6.00
1.254 1.305
1.412
1040 1
7
6.36
.991 2.085
5.790
1041 1
1035 1
7
7
5.72
4.48
1.377
1.563
.930
.213
.231
.460
1031 1
7
4.43
1.588
.179
.548
1032 1
7
4.76
1.602
.445
.418
1041 1
7
3.02
1.687
.515
.616
1037 1
7
3.04
1.681
.504
.602
1029 1
7
2.48
1.615
.958
.072
1034 1
1030 1
7
7
2.37
2.40
1.616
1.573
1.159
.997
.523
.113
1043 1
1043 1
1042 1
7
7
7
6.10
6.07
6.13
1.142 1.456
1.134 1.380
1.084 1.378
2.110
1.959
2.032
1041 1
7
5.75
1.355 1.160
1.156
1042 1
1039 1
7
7
6.00
6.42
1.307 1.500
.969 2.271
2.080
6.767
(continued on next page)
374
T. Tangeland et al. / Tourism Management 36 (2013) 364e376
Appendix Table 2 (continued )
Change from daily routine
Have time to think about life
I find peace and quiet
Getting away from every
daily life
Being with family
Being with friend
Being with others who
likes to perform same
activities as me
N
Min Max Mean SD
Skewness Kurtosis
1041
1039
1040
1037
1
1
1
1
7
7
7
7
6.33
5.95
6.38
6.26
.983
1.265
.982
1.038
1.905
1.346
2.162
1.776
4.721
1.750
6.163
4.041
1038 1
1042 1
1036 1
7
7
7
5.99
5.11
4.80
1.345 1.515
1.599 .620
1.739 .451
2.074
.306
.688
Appendix Table 3
Descriptive statistics for the pull items.
N
Hiking opportunities
Good access to cross
country ski trails
Local ski resorts
Other ski resorts in
the region
Hunting opportunities
Angling opportunities
Access to the wild and
unspoiled nature
Second-home is located
in a child friendly
area
Good conditions for
cycling
Min Max Mean SD
Skewness Kurtosis
1034 1
1030 1
7
7
6.22
6.03
1.270 2.185
1.452 1.815
5.199
3.003
1026 1
1020 1
7
7
2.64
2.51
1.884
1.852
.893
1.026
.357
.096
1024 1
1027 1
1025 1
7
7
7
2.28
3.82
5.03
1.996
2.122
1.801
1.435
.081
.803
.631
1.322
.241
1022 1
7
4.39
2.060
.355
1.103
1025 1
7
4.30
1.989
.329
1.038
Appendix B. Supplementary data
Supplementary data associated with this article can be found, in the
online version, at http://dx.doi.org/10.1016/j.tourman.2012.10.006.
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Dr. Torvald Tangeland is a research scientist at the
National Institute for Consumer Research. He was working
as a researcher at the Norwegian Institute for Nature
Research and conducting his PhD at the Norwegian
University of Life Sciences while working on this paper.
Dr. Birger Vennesland is a research scientist at the
Norwegian Forest and Landscape Institute.
Dr. Erlend Nybakk is a research scientist at the Norwegian
Forest and Landscape Institute.Their research interests
include nature-based tourism, the forest sector, innovation, consumer behaviour and marketing.