Original Scientific Article
Travellers’ Destination Attribute Preferences:
A Choice-Based Conjoint (CBC) Analysis
Meltem Altınay Özdemir
Muğla Sıtkı Koçman University, Turkey
meltemozdemir@mu.edu.tr
The study used a choice-based conjoint analysis to investigate Turkish travellers’
preferences for destination choice based on five attributes (destination type, distance,
length of stay, season, and value for money). Using purposive sampling, data were
obtained from Turkish travellers in Istanbul with an experimental questionnaire be-
tween April and May 2019. The questionnaire included sixteen destination profiles
produced using an orthogonal experimental design. Travellers had one go-to code
for all profile cards from highest to lowest preference. The data were analysed with
spss Conjoint. The findings revealed that destination type was the most important
attribute, followed by the length of stay, season, distance, and value for money. T-
test and anova results showed that travellers’ destination preferences also differed
by their socio-demographic characteristics. The study provides an alternative per-
spective for future research by examining destination choice using an experimental
approach. Furthermore, it offers practical implications for travel companies seeking
to understand Turkish travellers’ destination preferences.
Keywords: destination choice, destination preference, tourist behaviour, travel
motivation, experimental design
https://doi.org/10.26493/2335-4194.15.217-231
Introduction
Destinations, like other tourism businesses, can seg-
ment their visitors for more effective marketing (De-
nizci Guillet et al., 2015; Huertas Garcia et al., 2014).
Destinations can implement basic socio-demographic
segmentation by segmenting visitors based on several
attributes. Tourists seek products that satisfy their de-
mands (Wong & Yeh, 2009), therefore each destina-
tion’s desirability is determined by how well its mar-
keting elementsmeet those needs (Hanlan et al., 2006,
p. 214). Tourists are also concerned about making bad
choices that lead to a negative shopping experience.
Destination marketing that is effective allows for a
better grasp of the complexities involved in the des-
tination decision process. The act of recognizing and
selecting potential solutions to a problem is known
as decision-making (Al-Tarawneh, 2012). Many stud-
ies show that tourism suppliers need to understand
tourist behaviour and travel motivation in order to
meet demand and aid tourists in making decisions
(Blasco et al., 2014; Decrop & Kozak, 2014; Yiamjanya
&Wongleedee, 2014). Previous research has used con-
joint analysis to investigate travel preference segmen-
tation (Chiam et al., 2009; Nuraeni et al., 2015; Pai &
Ananthakumar, 2017).
This study investigates the segmentation of Turk-
ish travellers based on five attributes (destination type,
distance, length of stay, season, and value for money)
through a choice-based conjoint analysis. It segmented
Turkish travellers’ preferences for destination choice
using an experimental method of conjoint analysis.
The research can help travel companies figure out the
Academica Turistica, Year 15, No. 2, August 2022 | 217
Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
attributes and levels of destinations travellers prefer.
As a result, the study offers a novel way of segmenting
travellers. The experimental analysis can show travel
companies new ways to reach target travellers.
Decision-Making and Destination Choice
Decisions are complex and multidimensional, while
the travel decision-making process is intuitive and
spontaneous (Smallman & Moore, 2010). Destination
choice is affected by various factors (Buhalis, 2000;
Hanlan et al., 2006; Hsu et al., 2009; Li et al., 2017;
Oppewal et al., 2015; Pestana et al., 2020; Seyidov &
Adomaitienė, 2017). Many studies draw attention to
key aspects of the destination choice process and of-
fer theoretical models (Cao et al., 2020; Dey et al.,
2020;Hsu et al., 2009; Seddighi&Theocharous, 2002).
Some studies have identified the factors and motiva-
tions affecting destination choice (Dey et al., 2020;
Jang & Cai, 2002; Pawaskar et al., 2020; Qiu et al.,
2018; Sirakaya &Woodside, 2005;Wong& Yeh, 2009).
Experimentation using choice-based techniques has
been employed in several destination studies (Hsu et
al., 2009; Li et al., 2017; Oppewal et al., 2015). Sirakaya
and Woodside (2005) incorporated major conceptual
and empirical studies in their thorough qualitative
evaluation of the tourist decision-making literature.
They concluded that the Um and Crompton (1990)
destination choice set model is theoretically more
widespread and methodologically more robust than
others in tourist decision research (Hsu et al., 2009).
However, various destination choice models have also
been proposed in the literature. Hong et al. (2006)
stated that tourists compare and evaluate the attrac-
tiveness, accessibility, ease of travel, and varied infras-
tructure of the destination vis-à-vis alternatives, at the
specific time, situation, and context of travel. In addi-
tion, Yoo et al. (2018) proposed the multinomial logit
model (mnl) analysis to conclude that tourist psy-
chographic types can be varied by their demographic
pattern, travel type decisions, frequencies, duration of
travel, purpose of visit, and destination setting.
Identifying and selecting among possible solutions
to a problem is what decision-making entails (Al-
Tarawneh, 2012). Choosing also comprises convert-
ing a motive into a purchase process, in which the
final purchasing decision is made after a multi-stage
process (Hanlan et al., 2006, p. 10). As a result, re-
search shows that motivations should be explored be-
cause they have the power to influence tourists’ choices
(Nikjoo & Ketabi, 2015; Pestana et al., 2020; Prayag &
Ryan, 2011; Yiamjanya & Wongleedee, 2014).
Travel Motivation
It is crucial to figure out what influences people’s des-
tination choices in order to improvemarketing efforts.
Age, income, gender, personality, education, cost, dis-
tance, nationality, risk, and motivation are some of
these determinants (Hsu et al., 2009). Motivation,
which is an important research topic in the tourism
literature, is a dynamic concept that varies between in-
dividuals and destinations. Several motivational the-
ories have been proposed to understand travel moti-
vation, such as Maslow’s hierarchy of needs, Alderfer’s
existence theory, Herzberg’s motivator-hygiene the-
ory, and the push and pull theory (Vujičić et al., 2020).
Undoubtedly, the most extensively used is Crompton’s
(1979) push and pull theory (Chen & Chen, 2015; Hsu
et al., 2009; Nikjoo & Ketabi, 2015; Prayag & Ryan,
2011).
According to the push-pull theory, tourists are
pushed to travel by internal desires or emotional fac-
tors and pulled by external factors like destination
attributes (Yoon & Uysal, 2005; Cohen et al., 2014).
Crompton (1979) identified seven push motives (es-
cape from a perceived ordinary environment, explo-
ration and evaluation of self, relaxation, prestige, re-
gression, enhancement of kinship relationship, and
facilitation of social interaction) and two pull motives
(novelty and education). While there are a variety of
theories for explaining tourist motivations, the push-
pull theory is one of the most extensively addressed in
the tourism literature (Güzel et al., 2020; Liro, 2020;
Prabawa & Pertiwi, 2020).
There are various typologies of motivation fac-
tors for tourism. Hanqin and Lam (1999) identified
five push factors (knowledge, prestige, enhancement
of human relationships, relaxation, and novelty) and
five pull factors (expenditure, accessibility, service at-
titude and quality, sightseeing variety, and cultural
links). Jang andCai (2002) also suggested six push fac-
218 | Academica Turistica, Year 15, No. 2, August 2022
Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
tors (novelty experience; escape; knowledge-seeking;
fun, and excitement; relaxation; family/friend togeth-
erness) and six pull factors (natural and historic en-
vironment; cleanliness and safety; easy to access; eco-
nomic deal; outdoor activities; sunny and exotic at-
mosphere). Confirming previous studies, Pearce and
Lee (2005) argued for four push factors: novelty seek-
ing, escape/relaxation, relationship enhancement, and
self-development. Prayag and Ryan (2011) suggested
push factors such as escape, novelty, social interac-
tion, and prestige to describe the kind of experiences
tourists are looking for.
Psychological characteristics determine the push
factors, while destination attributes determine the
pull factors, according to Yiamjanya and Wongleedee
(2014). They identified the following push and pull
factors: experiencing a foreign country, eating tradi-
tional food, learning about a new culture, relaxing in
a foreign country, wanting to learn new things, be-
ing interested in local culture and traditional markets,
escaping from routine daily life and enjoying activi-
ties, adventure, and good weather. Hsu et al. (2009)
analysed tourist destination choice using the Analytic
Hierarchy Process (ahp) while incorporating Cromp-
ton’s push and pull factors as internal and external
forces, respectively. They identified four internal force
factors (psychological, physical, social interaction, and
seeking/exploration) and two external force factors
(tangible and intangible).
Based on a literature review, Danthanarayana et
al. (2020) concluded that tourists are influenced by
the following push factors: motivation for romance,
desire to escape, relaxation, expectations of differ-
ent cuisines, prestige, income, personal safety, and
excitement. They also identified the following pull
factors: attractions, location and attributes, facilities
and amenities, quality of accommodation, reasonable
travel cost, the romance of the destination, advertising
of the destination, shopping opportunities, climate,
and tourist sites/activities. The push factors are useful
for explaining travel intentions, whereas the pull fac-
tors help explain destination choice (Goossens, 2000;
Hsu et al., 2009). In other words, tourists are pushed
by travel needs and pulled by destination attributes
(Cohen et al., 2014).
Tourists tend to select destinations based on their
aims; therefore, destinations are attractive based on
how well they meet those aims. From the past (Awari-
tefe, 2004; Jang & Cai, 2002) to the present (Awaritefe,
2004), travel motivation and destination choice have
been researched extensively (Morris et al., 2021; Pa-
waskar et al., 2020; Pestana et al., 2020; Yoo et al., 2018).
As a result, understanding destination attributes is es-
sential for explaining travellers’ destination choice be-
haviour.
Destination Attributes
Before making a final decision, destination attributes
play a significant role in the information-gathering
phase (Oppewal et al., 2015). Because destination se-
lection is fluid, alternative approaches should be tested
regularly (Deng et al., 2021). Alternative methods,
such as the choice-based conjoint model (Hung et al.,
2019; Lupu et al., 2020; Nuraeni et al., 2015; Suh &
McAvoy, 2005) or ahp (Hsu et al., 2009) can be used
to determine destination choice and destination at-
tributes. Researchers can use these analyses to improve
the attributes of a destination systematically. Push fac-
tors are linked to the origins and desires of travellers.
The desire to escape, relax, experience adventure, and
improve one’s well-being are among them. Pull factors
are linked to the attractiveness of a destination, such
as diversity, uniqueness, accommodation, recreational
facilities, and cultural and historical resources (Dwyer
& Kim, 2003; Klenosky, 2002). Every destination has
a unique set of attributes (Prayag & Ryan, 2011). As a
result, travellers’ evaluations of destination attributes
and perceived utility values can be associatedwith des-
tination choice (Suresh et al., 2021).
Pull factors, according toHsu et al. (2009), are both
tangible and intangible external factors. Tangible fac-
tors include transportation facilities; friendliness of
people; quality and variety of food; accommodation
facilities; personal safety; price; culture and histori-
cal resources; good shopping; environmental safety,
and quality, whereas intangible factors include des-
tination image and benefit expectations. Nuraeni et
al. (2015) used four main attributes and 12 levels to
examine the decision-making process using conjoint
analysis. The attributes were: value for money (3 lev-
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Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
els), what the traveller looks for in the recreational
site (5 levels), comfort during the holiday (2 levels),
and distance from the place of origin (2 levels). Pai
and Ananthakumar (2017) also applied conjoint anal-
ysis with six attributes and 30 levels to examine tourist
preferences for travel packages. The attributes were
price (5 levels), length of stay (5 levels), hotel rating
(5 levels), season (5 levels), destination type (5 levels),
and mode of transport (5 levels).
Health, safety, travel time, and distance all influ-
ence destination choice (Bansal & Eiselt, 2004), as
does value for money, which refers to ‘what travellers
get for the money’ (Nuraeni et al., 2015, p. 315). Travel
expenditure, length of stay, income, exploring new
places, and/or things, getting away from the daily rou-
tine, stress, and troubles are also important factors for
destination choice (Denizci Guillet et al., 2011). Attrac-
tions, natural beauty, safety and security, festivals, and
events are crucial to attracting visitors to the destina-
tion (Dahiya & Batra, 2016).
The tourists’ destination choice process is a func-
tional or utilitarian decision-making process influ-
enced by a variety of factors such as psychological,
personal, socioeconomic, and travel characteristics
(Pandey & Joshi, 2021). Destination attributes and
tourist-specific features significantly affect destination
choice (Seyidov &Adomaitienė, 2017; Qiu et al., 2018).
The main factors are tourism activities (Awaritefe,
2004) and cost (Seddighi & Theocharous, 2002), al-
though travel time and travel distance (Cao et al.,
2020) also affect destination choice alongwith tourism
areas and destination amenities (Nicolau&Más, 2006;
Tseng et al., 2015). Climate and weather conditions
also significantly impact destination choice, although
mostly temporarily (Hamilton & Lau, 2006). There-
fore, the first research question regarding destination
attributes is as follows:
rq1 Which attributes have more importance in trav-
ellers’ preference for destination choice?
Some studies have shown that tourists’ sociode-
mographic characteristics significantly influence their
destination choice (Limtanakool et al., 2006). Charac-
teristics such as income, education level, cost, distance,
risk, and motivation are likely to influence destination
choices (Almeida-Santana & Moreno-Gil, 2018; Hsu
et al., 2009; Kozak, 2002). This leads to the following
research question:
rq2 Do travellers’ destination attribute preferences
differ according to sociodemographic character-
istics?
Methodology
Choice-Based Conjoint (CBC) Analysis
The study segmented Turkish travellers based on five
attributes: destination type, distance, length of stay,
season, the value for money, and sociodemographic
variables using cbc analysis. The selection of attri-
butes, design of profiles or choice sets, data collection,
analysis methods, and usefulness of the results are all
technical aspects of cbc analysis (Rao, 2014, p. 16),
which has the following five stages (Rao, 2009):
1. Determine destination attributes and levels;
2. Design profiles;
3. Collect data;
4. Analyse data;
5. Determine part-worth values and attributes.
A higher part-worth utility value indicates a greater
preference for that attribute level. Another key advan-
tage is that the method uses preference simulators to
answer ‘what if ’ questions. These simulators rely on
the findings of conjoint analysis data collected on both
hypothetical and real alternatives (Rao, 2014, p. 8). Rel-
ative importance is a measure to evaluate the impor-
tance of each attribute for choice preferences (Orme,
2010). Therefore, this study applied cbc analysis to
understand Turkish travellers’ preferences for destina-
tion choice.
cbc involves offering respondents multiple hypo-
thetical scenarios that include different combinations
of preference attributes (Lee, 2016, p. 71). It is a mul-
tivariate approach used to explain consumers’ prefer-
ences for products or services. Respondents evaluate
the value of each product or service by combining dif-
ferent levels of each attribute. cbc analysis uses the
following techniques (Rao, 2014, p. 19):
• A measurement technique: measuring purchaser
values:
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Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
• An analytical technique: predicting the likely re-
action of purchasers to new products;
• A segmentation technique: identifying groups of
purchasers with similar interests;
• A simulation technique: assessing new products
and services in a competitive market;
• An optimization technique: searching for prod-
uct profiles offering the highest profit.
Each attribute in this study describes a destination
characteristic, and the level represents a range of pos-
sible values for each attribute. As a result, levels in an
attribute set based on a conjoint set characterize the
destination combination. According to an ortho-
plan in conjoint analysis, the combination presents
a preference list of destination options, comprising at-
tributes and levels describing destinations. Travellers
sequence levels of attributes from highest to lowest
according to their preferences (Orme, 2002). For con-
joint attributes, the part-worth represents the level’s
utility. Based on the levels of destination attributes,
the part-worth utility values aid in determining which
destination is highly preferred.
Attributes and Levels of the Research
cbc analysis is a suitable approach for examining
travellers’ destination preferences. The first thing to
do is to describe the attributes and levels that indicate
what travellers consider in their destination choices.
The following five attributes (and fourteen levels) were
identified for this study: destination type (3), distance
(2), season (3), length of stay (4), and value for money
(2) based on previous studies, as shown in Table 1 (Nu-
raeni et al., 2015; Pai & Ananthakumar, 2017). The at-
tributes and levels for what travellers look for in des-
tination (destination type), season, and length of stay
were retrieved from Pai and Ananthakumar, while the
distance from the place of origin and value for money
were drawn from Nuraeni et al. (2015). Table 1 shows
the full list of attributes and levels.
Experimental Survey
Destination profileswere created and provided to trav-
ellers using the above attributes. Full factorial de-
sign profiles contain all combinations of attribute lev-
Table 1 Destination Choice Attributes and Levels
Sources Attributes Levels
Pai & Anan-
thakumar ()
Nuraeni et al.
()
What the traveller
looks for in a
destination
Nature, activity,
and adventure
Culture and heritage
Sea, sand, and sun
Nuraeni et al.
()
Distance from the
place of origin
Domestic trip
International trip
Pai & Anan-
thakumar ()
Season Spring or summer
Autumn or winter
Summer or autumn
Pai & Anan-
thakumar ()
Length of stay
(days)
–
–
–
≥
Nuraeni et al.
()
Value for money Expenses focus
on comfortable
accommodation,
delicious food, and
entertainment
Expenses focus
on comfortable
accommodation
and delicious food
els (Rao, 2014, p. 46). In this study, using all levels
would have resulted in 144 (3x2x3x4x2) profiles. How-
ever, because the respondents did not have enough
time to consider all profiles, the design was restricted
to 16 destination options using an orthogonal ex-
perimental design (orthoplan) in spss 22. This
method is commonly employed since it is difficult to
use all conceivable combinations in a single exper-
iment, and more advantageous findings can be ac-
quired by analysing possible combinations. Because
it more accurately mimics various real-life judgments
and is compatible with random utility theory, the dis-
crete choice method was applied to build preferences
(Louviere et al., 2000).
As a result, the cbc questionnaire contained a
combination of attributes and levels (16 destination
choice cards and 4 simulation cards) based on an or-
thogonal experimental design (Appendix). Travellers
assigned numbers to the profile cards, ranging from
1 (most preferred) to 16 (least preferred). There were
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Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
22 questions in the questionnaire, including 16 profile
cards, 5 demographic questions (gender, age, mari-
tal status, working status, monthly income), and 1 for
travel frequency.
Sample
The respondents were chosen through purposeful
sampling. Turkish travellers who travel at least once
a year met the eligibility criteria. Between April 15 and
May 30, 2019, data were collected face-to-face from
students and academics at a university in Istanbul,
Turkey. Only 105 of the 120 questionnaires distributed
were returned. However, 19 questionnaires were con-
sidered invalid due to repeated numbers, leaving 86
questionnaires to be examined.
Data Analysis
spss Conjoint was used to analyse the data. First, data
were input along with the 16 combination cards and
descriptive questions. Second, average utilities for the
destination cards were calculated and the part-worth
utility was determined. The data were drawn from a
normal distribution, according to the Kolmogorov-
Smirnov (K-S) test (p > 0.05), therefore, parametric
tests were applied. Third, T-tests and anova were
employed to see if travellers had similar preferences
for the relative importance of different destination at-
tributes.
Findings
A total of 86 questionnaires that could be used were
examined. The sample profile is shown in Table 2.
Gender distribution was nearly equal. Most respon-
dentswere younger than 25 years old. Almost everyone
was working, but they mostly had 1500 try and less
monthly income. More than half of the respondents
stated that they travel once a year.
The Pearson coefficient (0.816) showed that the re-
sults were highly significant (Rao, 2014). Similarly, a
high Kendall coefficient suggests that observed and
predicted preferences are highly correlated. Kendall’s
Tau value, which evaluates the model’s representa-
tion strength, was 0.600 (p = 0.000), showing that the
model was statistically significant. These values show
that the model fit is satisfactory (Table 3). The high
Table 2 Sample Profile
Item n 
Gender Female  .
Male  .
Age (years) –  .
–  .
–  .
–  .
–  .
–  .
 or more  .
Marital status Single  .
Married  .
Working status Working  .
Not working  .
Monthly Income
(try)
 or less  .
–  .
–  .
–  .
 or more  .
Travel Frequency Once a year  .
Twice a year  .
Three times a year  .
Four or more times a year  .
Notes n = 86.
Table 3 Model Fit
Item Value p
Pearson coefficient . .
Kendall’s Tau . .
predictive accuracy and internal validity of a conjoint
model are shown by its fit and efficiency (Tripathi &
Siddiqui, 2010, p. 9).
A cbc analysis offers values of the utility of the rel-
ative importance of attributes. Figure 1 shows themea-
sures of the relative importance of attributes based on
the range of each part-worth function. Regarding rq1,
the respondents produced the following rank order of
average attribute importance percentages: 29.93 for
destination type, 26.30 for the length of stay, 26.97
222 | Academica Turistica, Year 15, No. 2, August 2022
Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
Destination .
Season .
Length of stay .
Distance .
Value for money .
Figure 1 Relative Percentage Importance of Attributes
for the season, 16.73 for distance from the place of
origin, and 10.05 for value for money.
Part-worth utility-a measure of relative desirabil-
ity or worth-provides further insights into travellers’
preferences, with a higher utility showing that a fac-
tor is more desirable in a traveller’s choice (Orme,
2010). Part-worth means utilities of level for conjoint
attributes. When multiple attributes come together
to describe the total worth of the product, the util-
ity values for the separate parts of the product are
part-worth. Part-worth can be used to predict prefer-
ences for items in any choice set, while these estimates
can be used to predict the customer’s first choice and
last choice (Rao, 2014, p. 19). In this study, part-worth
is utilized to establish the intended destination at-
tributes and levels, as well as their relative importance.
The part-worth utilities for destination attributes are
shown in Table 4. First, the sea, sand, and sun level
contributed more to the total utility (0.5954) than the
other levels for the destination type attribute, indi-
cating that this level was preferred over the others in
destination choice. Cultural and heritage had a nega-
tive utility (–0.6764), indicating that it was less desired
than other levels of the same attribute.
Second, the domestic trip level had a higher utility
score (0.1642) than the international trip level, indi-
cating that it contributed more to the attribute’s total
utility. The utility for the international level was neg-
ative (–0.1642), indicating that international destina-
tions were the least preferred by travellers. Third, the
utility of the spring and summer level (0.2742) and au-
tumn and summer level (0.2364) contributed more to
the total utility than autumn or winter for the season
attribute. As a result, the autumn or winter utility was
negative (–0.5107). Fourth, the utility of staying for 12
days or more contributed more to total utility (0.1512)
than the other levels, followed by 9–11 days (0.1134).
As a result, stays of 9 or more days were more impor-
Table 4 Estimated Part-Worth Values for Destination
Choice
Attribute Level Part-worth value
What traveller
looks for in a
destination
Culture and heritage –
.
Nature, activity, and adventure .
Sea, sand, and sun .
Dist. from the
place of origin
Domestic trip .
International trip –
.
Season Summer or autumn .
Spring or summer .
Autumn or winter –
.
Length of stay
(days)
– –
.
– –
.
– .
≥ .
Value for
money
Expenses focus on comfortable
accommodation, delicious food,
and entertainment
–
.
Expenses focus on comfortable
accommodation and delicious
food
.
Constant .
Notes The highest score of each attribute is shown in bold.
tant than the other levels. The utility levels for 1–4 days
(–0.0029) and 5–8 days (–0.2616) were also negative,
indicating that travellers thought these lengths of stay
were less desirable than the others. Therefore, the util-
ity values of the longer stay levels were higher than the
shorter stay levels.
Finally, the utility of the ‘Expenses focus on com-
fortable accommodation and delicious food’ level con-
tributed more (0.0538) to the total utility of value for
themoney attribute than the other levels. Comfortable
accommodation and delicious food are prioritized
by travellers over comfortable accommodation, deli-
cious food, and entertainment. In otherwords, tourists
did not consider the expenditure on entertainment
Academica Turistica, Year 15, No. 2, August 2022 | 223
Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
Table 5 Differences in Attribute and Level Utility Score Averages by Socio-Demographic Variables
Attribute Attribute level Age Income Travel frequency
F p Diff. F p Diff. F p Diff.
What travellers
look for in a
destination
Culture and heritage . . – . .* .< . . –
Nature, activity, and adven. . . – . .* <. . . –
Sea, sand, and sun . . – . . – . . –
Dist. from the
origin place
Domestic trip . .** .<. . . – . .** <
International trip . .** .<. . . – . .** <
Season Summer or autumn . . – . . – . . –
Spring or summer . . – . . – . . –
Autumn or winter . . . . – . . –
Length of stay
(days)
– days . .** .< . . – . . –
– days . . – . . – . . –
– days . .** <. . .** <. . . –
≥ days . . – . . – . . –
Value for
money
Expenses focus on comfort-
able accommodation, deli-
cious food, and entertainment
. . – . . – . . –
Expenses focus on comfort-
able accommodation and
delicious food
. . – . . – . . –
Notes Age (years): 1 – 18–19, 2 – 20–21, 3 – 22–24, 4 – 25–35, 5 – 36–46, 6 – 47–57, 7 – 57 or more. Income (try): 1 – 1,500
and less, 2 – 1,501–2,500, 3 – 2,501–3,500, 4 – 3,501–4,500, 5 – 4,501 or more. Travel frequency: 1 – once a year, 2 – twice a year,
3 – three times a year, 4 – four or more times a year. n = 86; * p < 0.10; ** p < 0.05.
at the destination. Rather, they preferred comfortable
accommodation and delicious food to get value for
money.
The significance of differences in utility score aver-
age of attributes and levels by sociodemographic vari-
ables was determined using the anova test. The dif-
ferences between homogeneous groups were defined
using Post Hoc-lsd (Table 5). The attribute of dis-
tance from the place of origin differed by age. That
is, those aged 20–24 preferred domestic destinations
over those aged 47 and older (F = 2.844; p < 0.05).
Travellers aged 47–57 preferred to stay 1–4 days in a
destination (F = 2.305; p < 0.05), whereas those aged
20–24 preferred to stay 9–11 days (F = 2.501; p < 0.05).
Tourists with an income of 2,501–3,500 try pre-
ferred a cultural and heritage destination more than
those with an income of 2,500 try and less (F = 2.170;
p < 0.10). Those with an income of 1,501–2,500 try
preferred nature, activity, and adventure more than
tourists with an income of 2,501–3,500 try (F = 2.225;
p < 0.10). Finally, those with an income of 2,500 try
and less preferred to stay for 9–11 days more than
those with an income of 2,501–3,500 try (F = 3.118;
p < 0.05).
Travellers who travel three times a year preferred a
domestic destination, whereas those who travel once a
year preferred an international destination (F = 2.682;
p < 0.05). Thus, in response to rq2, destination choice
attributes differed by sociodemographic variables, ex-
cept for value for money. In particular, the levels of
culture and heritage versus nature, activity, and adven-
ture, domestic versus international trips, and 1–4 days
versus 9–11 days differed by sociodemographic vari-
ables.
224 | Academica Turistica, Year 15, No. 2, August 2022
Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
Ta
bl
e6
U
til
ity
Sc
or
e
Av
er
ag
e
an
d
t-
Te
st
Sc
or
es
of
A
tti
tu
de
sa
nd
Le
ve
ls
by
So
ci
o-
D
em
og
ra
ph
ic
Va
ri
ab
le
s
A
ttr
ib
ut
e
Le
ve
l
G
en
de
r
M
ar
ita
ls
ta
tu
s
W
or
ki
ng
st
at
us
Fe
m
al
e
(n
=

)
M
al
e
(n
=

)
t
p
Si
ng
le
(n
=

)
M
ar
ri
ed
(n
=

)
t
p
W
or
ki
ng
(n
=

)
N
ot
w
or
ki
ng
(n
=

)
t
p
m
sd
m
sd
m
sd
m
sd
m
sd
m
sd
W
ha
t
tr
av
el
le
rs
lo
ok
fo
r
in
a
de
st
i-
na
tio
n
C
ul
tu
re
an
d
he
rit
ag
e
–
.

.

–
.

.

.

.

*
–
.

.

.

.

–
.

.

*
–
.

.

–
.

.

.

.

N
at
ur
e,
ac
tiv
ity
,
an
d
ad
ve
nt
ur
e
–
.

.

.

.

–
.

.

.

.

–
.

.

.

.

**
–
.

.

.

.

–
.

.

Se
a,
sa
nd
,a
nd
su
n
.

.

.

.

–
.

.

.

.

.

.

–
.

.

.

.

.

.

.

.

D
ist
an
ce
fr
om
pl
ac
e
of
or
ig
in
D
om
es
tic
tr
ip
–
.

.

.

.

–
.

.

**
.

.

.

.

.

.

–
.

.

.

.

–
.

.

In
te
rn
at
io
na
l
tr
ip
.

.

–
.

.

.

.

**
–
.

.

–
.

.

–
.

.

.

.

–
.

.

.

.

Se
as
on
Su
m
m
er
or
au
tu
m
n
.

.

.

.

.

.

.

.

.

.

–
.

.

.

.

.

.

.

.

Sp
ri
ng
or
su
m
-
m
er
.

.

.

.

–
.

.

.

.

.

.

.

.

.

.

.

.

–
.

.

A
ut
um
n
or
w
in
te
r
–
.

.

–
.

.

.

.

–
.

.

–
.

.

.

.

–
.

.

–
.

.

.

.

Le
ng
th
of
st
ay
(d
ay
s)
–

–
.

.

.

.

–
.

.

–
.

.

.

.

–
.

.

*
.

.

–
.

.

.

.

**
–

–
.

.

–
.

.

.

.

–
.

.

.

.

–
.

.

–
.

.

–
.

.

.

.

–

–
.

.

.

.

–
.

.

.

.

–
.

.

.

.

*
–
.

.

.

.

–
.

.

**
≥

.

.

–
.

.

.

.

.

.

–
.

.

.

.

.

.

.

.

–
.

.

Va
lu
e
fo
r
m
on
ey
Ex
pe
ns
es
fo
cu
s
on
co
m
fo
rt
ab
le
ac
co
m
m
od
a-
tio
n,
de
lic
io
us
fo
od
,a
nd
en
te
r-
ta
in
m
en
t
–
.

.

–
.

.

.

.

–
.

.

.

.

–
.

.

.

.

–
.

.

.

.

Ex
pe
ns
es
fo
cu
s
on
co
m
fo
rt
ab
le
ac
co
m
m
od
at
io
n
an
d
de
lic
io
us
fo
od
.

.

.

.

–
.

.

.

.

–
.

.

.

.

–
.

.

.

.

–
.

.

N
ot
es
Th
e
hi
gh
es
ts
co
re
of
ea
ch
at
tr
ib
ut
e
is
sh
ow
n
in
bo
ld
.n
=
86
;*
p
<
0.
10
;*
*p
<
0.
05
.
Academica Turistica, Year 15, No. 2, August 2022 | 225
Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
T-tests revealed differences in attitude and level
utility score averages by gender, marital status, and
working status (Table 6). Regarding gender, female
travellers preferred cultural and heritage destinations
more than males (t = 1.67; p < 0.10). Male travellers
tend to prefer domestic destinations (t = 1.81; p < 0.05)
while females prefer international destinations (t =
1.81; p < 0.05). Regarding marital status, married trav-
ellers preferred cultural and heritage destinations (t
= –1.66; p < 0.10), whereas single travellers preferred
nature, activity, and adventure destinations (t = 2.88; p
<0.05).Married travellers preferred to stay for 1–4 days
(t = –1.62; p < 0.10), whereas single travellers preferred
9–11 days (t = 1.83; p < 0.10). Regardingworking status,
working travellers preferred to stay for 1–4 days (t =
2.42; p < 0.05), and non-working travellers preferred
to stay for 9–11 days (t = –2.76; p < 0.05).
As a result, in response to rq2, these findings show
that travellers’ destination preferences differ by at-
tributes and levels based on sociodemographic factors.
More specifically, destination type preferences vary by
gender and marital status; distance preferences vary
by gender, and length of stay varies by marital and
working status.
Discussion and Conclusion
Destination choice is a popular study issue. The study
focuses on destination attributes to understand trav-
ellers’ destination preferences. Travellers are prone to
prioritizing essential destination attributes while plan-
ning a trip. Destination choice behaviour is affected
by several internal and external factors, but mostly by
basic attributes such as destination type, distance, sea-
son, length of stay, and value for money. Although the
decision-making process in tourism has been exten-
sively studied, few studies have attempted to use con-
joint analysis to identify the priority of attributes and
levels of destination choice. As a result, using a cbc
analysis, this study attempted to fill this gap by reveal-
ing how travellers make destination choices. The pur-
pose of this study was to figure out which attributes
travellers prioritize the most when choosing where
to travel. Quantitative data were collected by a con-
joint method offering multiple hypothetical scenarios
and examined based on amultivariate approach. Con-
joint analysis was utilized to understand more about
tourists’ preferences for destination choice. Overall,
Turkish travellers mostly prefer domestic destinations
of sea, sand, and sun for 9–11 days in spring or sum-
mer, while focusing on comfortable accommodation
and delicious food. By investigating destination choice
from a different perspective, this study contributes to
the literature by examining the priority attributes of
destination choice. Using cbc analysis, this empiri-
cal study identified the importance of the attributes
and levels in travellers’ destination choices. As a re-
sult, by offering an experimental perspective, the work
aids future research. It also offers a variety of practi-
cal implications for how tourism destinations might
strengthen their product offerings.
Theoretical Contributions
Theoretically, this study can help clarify unexplored
aspects for further research into the attributes and lev-
els of destination choice. Destination choice research
will continue to increase in popularity in the future,
thus researchers should focus on using choice-based
tests to better understand tourists’ preferences. Card-
7 was shown to be the most popular destination pro-
file among travellers. The part-worth utility of its at-
tributes proves that Turkish travellers prefer domes-
tic sea, sand, and sun destinations in spring and sum-
mer for nine or more days while focusing on com-
fortable accommodation and delicious food. As seen
in the study by Pai and Ananthakumar (2017), spring
is the most favourite season for travelling. However,
length of stay varied, as longer stays were preferred
over medium or shorter holidays. Turkish travellers
have different preferences for length of stay than In-
dians, and they have different preferences for distance
from their origin than Indonesians. As a result, the
attributes and levels of destination choice differ de-
pending on the tourists’ nationality (e.g. Nuraeni et al.,
2015; Pai & Ananthakumar, 2017). This is an interest-
ing finding for future research.
Indirect methodology-based studies have utilized
conjoint analysis to investigate tourists’ preferences
for accommodation and tour packages (Chiam et al.,
2009; Denizci Guillet et al., 2011, 2015; Huertas Gar-
cia et al., 2014; Pai & Ananthakumar, 2017; Tripathi
226 | Academica Turistica, Year 15, No. 2, August 2022
Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
& Siddiqui, 2010), and to investigate the travel pref-
erences of youths (Nuraeni et al., 2015; Vukic et al.,
2015). However, comprehensive research on the fac-
tors that influence destination choice for people of
different backgrounds is still needed. This research
implemented an experimental approach to determine
which destination attributes and levels travellers pre-
fer most when choosing a destination, and then ex-
amined these attributes and levels in light of travellers’
sociodemographic characteristics.
This study highlights three main contributions of
the conjoint approach. First, it has not beenmuch used
previously to explore destination choice, although this
has shown that it is well suited to this research field.
Thus, this approach can be very useful for evaluating
and understanding destination preferences. Second,
the factors that travellers pay attention to in their desti-
nation choice were presented based on choice profiles.
Third, travellers’ preferences were segmented based
on sociodemographic characteristics.
Practical Implications
The results have significant managerial implications
for travel companies. According to the findings, fo-
cusing on destination attributes can accurately pre-
dict Turkish travellers’ preferences. The study, like the
study by Qiu et al. (2018), reveals that people with dif-
ferent aims prefer to choose different destinations. The
findings also show that Goossens’ (2000) push factors,
or destination attributes, have an impact on destina-
tion choice. Furthermore, the research uncovers useful
information about destination attribute preferences.
Travellers aged 20–24 prefer domestic destinations,
while those aged 47 and over prefer international des-
tinations, according to the findings. Those with low
incomes prefer nature, activity, and adventure desti-
nations more than those with high incomes. Another
interesting finding is that those who travel three times
a year travel more domestically than people who only
travel once a year. International destinations are pri-
oritized by Turkish travellers who travel at least once a
year. Younger travellers (20–24 years old) want to stay
for 9 days or more, whereas elder visitors (47–57 years
old) want to stay for 1–4 days. Females prefer interna-
tional cultural and heritage destinations, while males
prefer the opposite. Single travellers prefer to stay 9–
11 days in nature, activity, and adventure destinations,
whereas married travellers prefer to stay 1–4 days in
cultural and heritage destinations. Travellers who are
working prefer a shorter stay than those who are not.
Thus, these findings support arguments that sociode-
mographic characteristics affect destination choice.
Given these findings, travel companies could cre-
ate diverse tour packages based on sociodemographic
factors to increase product quality and sales, as desti-
nation choice decisions play a significant role in tour
planning andmarketing. Travel companies should, for
example, offer tour packages with lengthier domestic
stays for young Turkish travellers (20–24 years old)
and shorter international stays for older Turkish trav-
ellers (47–57 years old). They should suggest interna-
tional cultural and heritage destinations for females,
but domestic non-cultural and heritage destinations
formales. Short-stay tour packages to cultural andher-
itage destinations should be geared toward married
travellers, while longer-stay nature, activity, and ad-
venture destinations should be geared toward singles.
Finally, travel companies should provide both short-
stay and long-stay tours for working and non-working
travellers.
Limitations and Future Research
The study contains four major shortcomings. First, 86
questionnaires were analysed for research. The small
sample size is a limitation; Pai and Ananthakumar
(2017) analysed 150 questionnaires, while Lee (2016)
only received 117. Although the sample size is small in
conjoint analysis, it has a representative feature. Re-
searchers can use conjoint analysis for even the small-
est samples if they access enough respondents to ade-
quately represent the population (Orme, 2010, p. 62).
Second, because the importance of attributes differs by
country, the results are particular to Turkish travellers.
As a result, future research should investigate the rela-
tionship between sociodemographic factors and des-
tination choices in various countries. Following Deng
et al. (2021), tourists’ preferences can be researched
by age, profession, education, gender, and living en-
vironment to develop a clearer understanding of des-
tination choice. Third, this study was limited to de-
Academica Turistica, Year 15, No. 2, August 2022 | 227
Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
termining Turkish travellers’ destination preferences
based on five attributes. Multivariate techniques could
be used in future studies to investigate more attributes
and levels that potentially influence destination choice
decisions. Fourth, because understanding destination
choice is crucial, tourism scholars are attempting to
identify the key factors that influence these decisions
or preferences. As a result, future research could focus
on essential aspects of the issue.
Appendix 1 Destination Attributes Profiles/Cards
1. Domestic trip to a place that is nature-based, activity,
and adventure for 9–11 days in spring or summer. Ex-
penses focus on comfortable accommodation and deli-
cious food.
2. International trip to a place that is nature-based, activ-
ity and adventure for 9–11 days in autumn or winter. Ex-
penses focus on comfortable accommodation, delicious
food, and entertainment.
3. Domestic trip to a place that is cultural and heritage for
9–11 days in summer or autumn. Expenses focus on com-
fortable accommodation and delicious food.
4. Domestic trip to a place that is nature-based, activity,
and adventure for 5–8 days in summer or autumn. Ex-
penses focus on comfortable accommodation and deli-
cious food.
5. Domestic trip to a place that is cultural and heritage for
9–11 days in spring or summer. Expenses focus on com-
fortable accommodation, delicious food, and entertain-
ment.
6. International trip to a place that is cultural and heritage
for 5–8 days in summer or autumn. Expenses focus on
comfortable accommodation and delicious food.
7. Domestic trip to a place that is sea, sand, and sun for
more than 12 days in summer or autumn. Expenses fo-
cus on comfortable accommodation, delicious food, and
entertainment.
8. International trip to a place that is sea, sand, and sun for
1–4 days in spring or summer. Expenses focus on com-
fortable accommodation and delicious food.
9. Domestic trip to a place that is cultural and heritage for
1–4 days in autumn or winter. Expenses focus on com-
fortable accommodation and delicious food.
10. International trip to a place that is sea, sand, and sun for
9–11 days in summer or autumn. Expenses focus on com-
fortable accommodation and delicious food.
11. Domestic trip to a place that is cultural and heritage for
1–4 days in summer or autumn. Expenses focus on com-
fortable accommodation and delicious food.
12. Domestic trip to a place that is sea, sand, and sun for 5–8
days in autumn or winter. Expenses focus on comfort-
able accommodation, delicious food, and entertainment.
13. International trip to a place that is cultural and heritage
for more than 12 days in summer or autumn. Expenses
focus on comfortable accommodation, delicious food,
and entertainment.
14. International trip to a place that is nature-based, activity
and adventure for 1–4 days in summer or autumn. Ex-
penses focus on comfortable accommodation, delicious
food, and entertainment.
15. International trip to a place that is cultural and heritage
for more than 12 days in autumn or winter. Expenses fo-
cus on comfortable accommodation and delicious food.
16. International trip to a place that is cultural and heritage
for 5–8 days in spring or summer. Expenses focus on
comfortable accommodation, delicious food, and enter-
tainment.
Appendix 2 Simulation Cards
1. Domestic trip to a place that is sea, sand, and sun for 9–11
days in summer or autumn. Expenses focus on comfort-
able accommodation and delicious food.
2. Domestic trip to a place that is nature-based, activity and
adventure for 1–4 days in autumn or winter. Expenses fo-
cus on comfortable accommodation, delicious food, and
entertainment.
3. Domestic trip to a place that is nature-based, activity,
and adventure for 9–11 days in summer or autumn. Ex-
penses focus on comfortable accommodation and deli-
cious food.
4. Domestic trip to a place that is cultural and heritage for
9–11 days in summer or autumn. Expenses focus on com-
fortable accommodation, delicious food, and entertain-
ment.
References
Almeida-Santana, A., &Moreno-Gil, S. (2018). Understand-
ing tourism loyalty: Horizontal vs. destination loyalty.
Tourism Management, 65, 245–255.
Al-Tarawneh, H. A. (2012). The main factors beyond de-
cision making. Journal of Management Research, 4(1).
https://doi.org/10.5296/jmr.v4i1.1184
Awaritefe, O. (2004). Motivation and other considerations
in tourist destination choice: A case study of Nigeria.
Tourism Geographies, 6(3), 303–330.
Bansal, H., & Eiselt, H. A. (2004). Exploratory research of
tourist motivations and planning.TourismManagement,
25(3), 387–396.
228 | Academica Turistica, Year 15, No. 2, August 2022
Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
Blasco, D., Guia, J., & Prats, L. (2014). Tourism destina-
tion zoning in mountain regions: A consumer-based
approach. Tourism Geographies, 16(3), 512–528.
Buhalis, D. (2000).Marketing the competitive destination of
the future. Tourism Management, 21(1), 97–116.
Cao, J., Zhang, J., Wang, C., Hu, H., & Yu, P. (2020). How
far is the ideal destination? Distance desire, ways to ex-
plore the antinomy of distance effects in tourist destina-
tion choice. Journal of Travel Research, 59(4), 614–630.
Chen, L.-J., & Chen, W.-P. (2015). Push-pull factors in in-
ternational birders’ travel. Tourism Management, 48(C),
416–425.
Chiam, M., Soutar, G., & Yeo, A. (2009). Online and off-line
travel packages preferences: A conjoint analysis. Interna-
tional Journal of Tourism Research, 11(1), 31–40.
Cohen, S. A., Prayag, G., &Moital, M. (2014). Consumer be-
haviour in tourism: Concepts, influences and opportu-
nities. Current Issues in Tourism, 17(10), 872–909.
Crompton, J. L. (1979). Motivations for pleasure vacation.
Annals of Tourism Research, 6(4), 408–424.
Dahiya, K. S., & Batra, D. K. (2016). Tourist decisionmaking:
Exploring the destination choice criteria. Asian Journal
of Management Research, 7(2), 140–153.
Danthanarayana, C. P., Rajapakshe, R. M. P. D. K., & Mad-
husankha, W. A. I. (2020). Push and pull motives to se-
lect Sri Lanka as a honeymoon destination. Journal of
Tourism Economics and Applied Research, 4(2), 64–74.
Decrop, A., & Kozak,M. (2014). Consumer goals in vacation
decisionmaking. Journal of Travel & TourismMarketing,
31(1), 71–81.
Deng, B., Xu, J., & Wei, X. (2021). Tourism destination pref-
erence prediction based on edge computing. Mobile In-
formation Systems, 551208. https://doi.org/10.1155/2021
/5512008
DenizciGuillet, B., Guo, Y., &Law,R. (2015). Segmenting ho-
tel customers based on rate fences through conjoint and
cluster analysis. Journal of Travel & Tourism Marketing,
32(7), 835–851.
Denizci Guillet, B., Lee, A., Law, R., & Leung, R. (2011). Fac-
tors affecting outbound tourists’ destination choice: The
case of Hong Kong. Journal of Travel & TourismMarket-
ing, 28(5), 556–566.
Dey, B., Mathew, J., & Chee-Hua, C. (2020). Influence of
destination attractiveness factors and travel motivations
on rural homestay choice: The moderating role of need
for uniqueness. International Journal of Culture, Tourism
and Hospitality Research, 14(4), 639–666.
Dwyer L., & Kim, C. (2003) Destination competitiveness.
Current Issues in Tourism, 6(5), 369–414.
Goossens, C. (2000). Tourism information and pleasuremo-
tivation. Annals of Tourism Research, 27(2), 301–321.
Güzel, Ö., Sahin, I., & Ryan, C. (2020). Push-motivation-
based emotional arousal: A research study in a coastal
destination. Journal of DestinationMarketing&Manage-
ment, 16, 100428. https://doi.org/10.1016/j.jdmm.2020
.100428
Hamilton, J. M., & Lau, M. A. (2006). The role of climate in-
formation in tourist destination choice decisionmaking.
In S. Gössling&M.C.Hall (Eds.),Tourism and global en-
vironmental change: Ecological, social, economic and po-
litical interrelationships (pp. 229–264). Routledge.
Hanlan, J., Fuller, D., & Wilde, S. (2006). Destination deci-
sion making. Tourism and Hospitality Planning & Devel-
opment, 3(3), 209–221.
Hanqin, Z. Q., & Lam, T. (1999). An analysis of main-
land Chinese visitors’ motivations to visit Hong Kong.
Tourism Management, 20(5), 587–594.
Hong, S. K., Kim, J. H., Jang, H., & Lee, S. (2006). The roles
of categorization, affective image and constraints on
destination choice: An application of the nmnl model.
Tourism Management, 27(5), 750–761.
Hsu, T. K., Tsai, Y. F., & Wu, H. H. (2009). The preference
analysis for tourist choice of destination: A case study of
Taiwan. Tourism Management, 30(2), 288–297.
Huertas Garcia, R., Laguna García, M., & Consolación, C.
(2014). Conjoint analysis of tourist choice of hotel at-
tributes presented in travel agent brochures. Interna-
tional Journal of Tourism Research, 16(1), 65–75.
Hung, K., Guillet, B. D., & Zhang, H. Q. (2019). Understand-
ing luxury shopping destination preference using con-
joint analysis and traditional item-based measurement.
Journal of Travel Research, 58(3), 411–426.
Jang, S., & Cai, L. A. (2002). Travel motivations and destina-
tion choice: A study of British outbound market. Journal
of Travel & Tourism Marketing, 13(3), 111–133.
Klenosky, D. B. (2002). The ‘pull’ of tourism destinations:
A means-end investigation. Journal of Travel Research,
40(2), 385–395.
Kozak, M. (2002). Comparative analysis of tourist motiva-
tions by nationality and destinations. Tourism Manage-
ment, 23(3), 221–232.
Lee, S. H. (2016). How hotel managers decide to discount
room rates: A conjoint analysis. International Journal of
Hospitality Management, 52, 68–77.
Li, C., McCabe, S., & Chen, Y. (2017). Destination choice of
Chinese long-haul outbound tourists and market seg-
mentation. Journal of China Tourism Research, 13(3),
298–315.
Academica Turistica, Year 15, No. 2, August 2022 | 229
Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
Limtanakool, N., Dijst, M., & Schwanen, T. (2006). The in-
fluence of socioeconomic characteristics, land use and
travel time considerations on mode choice for medium-
and longer-distance trips. Journal of Transport Geogra-
phy, 14(5), 327–341.
Liro, J. (2020). Visitors’ motivations and behaviours at pil-
grimage centres: Push and pull perspectives. Journal of
Heritage Tourism, 16(1), 79–99.
Louviere, J. J., Hensher, D. A., Swait, J. D., & Adamowicz, W.
(2000). Stated choice methods: Analysis and application.
Cambridge University Press.
Lupu, C., Padhi, S. S., Pati, R. K., & Stoleriu, O. M. (2020).
Tourist choice of heritage sites in Romania: A conjoint
choice model of site attributes and variety seeking be-
havior. Journal of Heritage Tourism, 16(6), 646–668.
Morris, S., Dwyer, T., &Mulligan, J. (2021).Destinationman-
agement: The influence of local food. The Irish Journal of
Management, 39(2), 99–112.
Nicolau, J. L., & Mas, F. J. (2006). The influence of distance
and prices on the choice of tourist destinations: The
moderating role of motivations. Tourism Management,
27(5), 982–996.
Nikjoo, A. H., & Ketabi, M. (2015). The role of push and pull
factors in the way tourists choose their destination.Ana-
tolia, 26(4), 588–597.
Nuraeni, S., Arru, A. P., & Novani, S. (2015). Understanding
consumer decision-making in tourism sector: Conjoint
analysis. Procedia – Social and Behavioral Sciences, 169,
312–317.
Oppewal, H., Huybers, T., & Crouch, G. I. (2015). Tourist
destination and experience choice: A choice experimen-
tal analysis of decision sequence effects. Tourism Man-
agement, 48, 467–476.
Orme, B. K. (2002). Formulating attributes and levels in con-
joint analysis (Sawtooth Software ResearchPaper Series).
Sawtooth Software, Sequim, wa.
Orme, B. K. (2010). Getting started with conjoint analysis:
Strategies for product design and pricing research (2nd
ed.). Research Publishers.
Pai, S., & Ananthakumar, U. (2017). Understanding tourist
preferences for travel packages: A conjoint analysis ap-
proach. Asia Pacific Journal of Tourism Research, 22(12),
1238–1249.
Pandey, K., & Joshi, S. (2021). Trends in destination choice
in tourism research: A 25-year bibliometric review. fiib
Business Review, 10(4), 371–392.
Pawaskar, P., Mekoth, N., & Thomson, A. R. (2020). Travel
motivation and choice of destination attributes: Empiri-
cal evidences based on tourist perceptions. International
Journal of Advanced Science and Technology, 29(8), 634–
649.
Pearce, P. L., & Lee, U.-I. (2005). Developing the travel ca-
reer approach to tourist motivation. Journal of Travel Re-
search, 43(3), 226–237.
Pestana,M. H., Parreira, A., &Moutinho, L. (2020). Motiva-
tions, emotions and satisfaction: The keys to a tourism
destination choice. Journal of DestinationMarketing and
Management, 16, 100332. https://doi.org/10.1016/j.jdmm
.2018.12.006
Prabawa, I. W. S. W., & Pertiwi, P. R. (2020). The digi-
tal nomad tourist motivation in Bali: Exploratory re-
search based on push and pull theory. Athens Journal of
Tourism, 7(3), 161–174.
Prayag, G., & Ryan, C. (2011). The relationship between the
‘push’ and ‘pull’ factors of a tourist destination: The role
of nationality – An analytical qualitative research ap-
proach. Current Issues in Tourism, 14(2), 121–143.
Qiu, R. T. R., Masiero, L., & Li, G. (2018). The psychological
process of travel destination choice. Journal of Travel &
Tourism Marketing, 35(6), 691–705.
Rao, V. R. (2009). Developments in conjoint analysis. In B.
Weiringa (Ed.), Handbook of marketing decision models
(pp. 23–53). Springer.
Rao, V. R. (2014). Applied conjoint analysis. Springer.
Seddighi, H. R., & Theocharous, A. L. (2002). A model of
tourism destination choice: A theoretical and empirical
analysis. Tourism Management, 23(5), 475–487.
Seyidov, J., & Adomaitienė, R. (2017). Factors influencing lo-
cal tourists’ decision-making on choosing a destination:
A case of Azerbaijan. Ekonomika, 95(3), 112–127.
Sirakaya, E., &Woodside, A. G. (2005). Building and testing
theories of decision making by travellers. Tourism Man-
agement, 26(6), 815–832.
Smallman,C., &Moore, K. (2010). Process studies of tourists’
decision-making. Annals of Tourism Research, 37(2),
397–422.
Suh, Y. K., &McAvoy, L. (2005). Preferences and trip expen-
ditures: A conjoint analysis of visitors to Seoul, Korea.
Tourism Management, 26(3), 325–333.
Suresh, K., Wilson, C., Quayle, A., Khanal, U., & Managi,
S. (2021). Which national park attributes attract interna-
tional tourists? A Sri Lankan case study. Tourism Eco-
nomics. https://doi.org/10.1177/13548166211019865
Tripathi, S. N., & Siddiqui, M. H. (2010). An empirical study
of tourist preferences using conjoint analysis. Interna-
tional Journal of Business Science and Applied Manage-
ment, 5(2). https://doi.org/10.1201/b12231-6
Tseng, C., Wu, B., Morrison, A. M., Zhang, J., & Chen, Y.
230 | Academica Turistica, Year 15, No. 2, August 2022
Meltem Altınay Özdemir Travellers’ Destination Attribute Preferences
(2015). Travel blogs on China as a destination image for-
mation agent: A qualitative analysis using Leximancer.
Tourism Management, 46, 347–358.
Um, S., & Crompton, J. L. (1990). Attitude determinants
in tourism destination choice. Annuals of Tourism Re-
search, 17(3), 432–448.
Vujičić, M. D., Stamenković, I., Stankov, U., Kovačić, S.,
Vasiljević, D. A., & Locke, J. P. (2020). What will pre-
vail within citybreak travel, motivation or demotivation?
Case study of Novi Sad, Vojvodina, Serbia. Geographica
Pannonica, 24(1), 42–55.
Vukic, M., Kuzmanovic, M., & Kostic Stankovic, M. (2015).
Understanding the heterogeneity of Generation Y’s pref-
erences for travelling: A conjoint analysis approach. In-
ternational Journal of Tourism Research, 17(5), 482–491.
Wong, J. Y., & Yeh, C. (2009). Tourist hesitation in destina-
tion decision making. Annals of Tourism Research, 36(1),
6–23.
Yiamjanya, S., & Wongleedee, K. (2014). International tour-
ists’ travel motivation by push-pull factors and the deci-
sion making for selecting thailand as destination choice.
Social, Behavioral, Educational, Economic and Manage-
ment Engineering, 8(5), 1335–1340.
Yoo, C. K., Yoon, D., & Park, E. (2018). Tourist motivation:
An integral approach to destination choices.TourismRe-
view, 73(2), 169–185.
Yoon, Y., & Uysal, M. (2005). An examination of the effects
of motivation and satisfaction on destination loyalty: A
structural model. Tourism Management, 26(1), 45–56.
Academica Turistica, Year 15, No. 2, August 2022 | 231