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DETUROPE – THE CENTRAL EUROPEAN JOURNAL OF REGIONAL DEVELOPMENT AND TOURISM
Vol. 13 Issue 2 2021 ISSN 1821-2506
Original scientific paper
34
IMPACTS AND POTENTIAL OF AUTONOMOUS VEHICLES
IN TOURISM
Márk MISKOLCZIa, László KÖKÉNYb, Katalin ÁSVÁNYIc,
Melinda JÁSZBERÉNYId, Tamás GYULAVÁRIe, Jhanghiz SYAHRIVARf
a Corvinus University of Budapest, Institute of Marketing, mark.miskolczi@uni-corvinus.hu
b Corvinus University of Budapest, Institute of Marketing, laszlo.kokeny2@uni-corvinus.hu
c Corvinus University of Budapest, Institute of Marketing, katalin.asvanyi@uni-corvinus.hu
d Corvinus University of Budapest, Institute of Marketing, jaszberenyi@uni-corvinus.hu
e Corvinus University of Budapest, Institute of Marketing, tamas.gyulavari@uni-corvinus.hu
f Corvinus University of Budapest, Institute of Marketing, jhanghiz@uni-corvinus.hu
Cite this article: Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J. (2021).
Impacts and potential of autonomous vehicles in tourism. Deturope, 13(2): 34-51.
Abstract
Autonomous vehicles (AVs) are developing rapidly, but the deeper understanding of tourists’ attitudes
towards AVs is still little explored in social sciences. Bearing this in mind, this study aims to identify the
expected changes in tourism arising from the technology, and the openness towards AV-based tourism
services. For this, an online data collection (n = 671) has been completed among Hungarian tourists. Prior
to the data collection, a literature review was conducted to identify and categorise the changes expected
from the spread of AVs. Based on the empirical results, tourists would be willing to give up control to the
AVs in a foreign environment, and so to pay more attention to the surroundings. The majority of
respondents would be also open to participating in AI-based city tours, especially those with the
“Extraversion” and “Openness to Experiences” personality types, based on the Big Five Theory. The
findings can serve as a basis for practitioners in preparing for the technology and for the further analysis of
attitudes towards tourism-based AV services (e.g., modeling of technology acceptance).
Keywords: autonomous vehicles (AVs), tourism service development, attitudes towards autonomous
vehicles, tourism consumer behavior
INTRODUCTION
Nowadays, one of the biggest issues of passenger transport is to find a balance between
economic sustainability, environmental regulations, and even travelers’ satisfaction (Tromaras
et al., 2018; Bagloee et al., 2016). Automation is one of the promising technologies of Industry
4.0 that can transform many industries, including tourism and passenger transport (Fagnant &
Kockelman, 2015). According to optimistic (pre-pandemic) estimates, 27 million AVs are
expected to be on the roads by 2030 in Europe, and 40% of passenger kilometers will be
performed by AVs (PWC, 2018). Despite this radical improvement, there are several
unanswered questions (legal – e.g., Glancy, 2015; moral and sectorial – e.g., Miskolczi et al.,
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
35
2021, De Sio, 2017; social – Bissell et al., 2020) around the technology. Most of the literature
on AVs consider primarily the technical feasibility (Run & Xiao, 2018; Zhao et al., 2018) as
well as the general advantages and disadvantages of spread (Nielsen & Haustein, 2018; Du &
Zheng, 2021).
In our study, we especially concentrate on the attitudes towards the use of AV for tourism
purposes. Our research aims to reveal how tourists with different consumer habits relate to AV-
based tourism services that we have identified in the literature. In our empirical research, the
correlation between the subjects’ personality type and attitude towards AVs has also been
analyzed. There are only a few papers (e.g., Tussyadiah & Zach & Wang, 2017; Cohen &
Hopkins, 2019) that analyze the impact of AVs on tourism which reinforces the relevance of
our research objective. Findings revealed a generally positive attitude towards AV-based
tourism services. According to respondents' assumptions, AVs would improve the tourism
experience, as their use would allow for a more convenient way of visiting the destination and
its attractions.
Our study is structured as follows: In Section 2, the basic definitions of AV technology and
the results of previous research related to our research topic are discussed. The process and
results of empirical research (Section 3) are interpreted along with three main topics (Section
4): tourism habits of subjects, attitudes towards AV-based tourism services, and the correlation
between personality types and openness to the AV technology. In Section 5, we answer our
research questions and make suggestions for the application of AVs in tourism.
THEORETICAL BACKGROUND
A significant part of transport is realized due to tourism motivations. Therefore, such disruptive
innovations like automation in passenger transport might also affect tourism (Jászberényi &
Munkácsy, 2018). Nowadays, the main objective of transport development initiatives is to
reduce the number of accidents caused by human error, which currently accounts for 90% of
road accidents (Menezes et al., 2017). Automation determines the replacement of processes by
machines that previously required human intervention (Fagnant & Kockelman, 2015; Nikitas
et al., 2017).
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
36
Automation is an incremental innovation in transport. To define the nature of this
phenomena, the SAE
1
(Society of Automotive) framework developed by the National
Highway Traffic Safety Administration (NHTSA
2
) should be interpreted, which is structured
as follows:
− Level 0: “No Automation”: Conventional way of using a vehicle without any
automation.
− Level 1: “Driver Assistance”: Only the human driver controls the vehicle, but there are
some supporting functions (e.g., cruise control).
− Level 2: “Partial Automation”: The human driver controls the vehicle, but advanced
driving assistance systems (ADAS) (e.g., lane-centering, IPAS
3
) are available.
− Level 3: “Conditional Automation”: The human driver is still responsible for
controlling the vehicle, but the continuous monitoring of the environment is no longer
required; artificial intelligence (AI) performs all driving operations. On the other hand, in
the case of special traffic situations, human drivers must take back control over the
machine. Currently, the most advanced vehicles achieve this level of automation (Honda
company's new development – Sensing Elite Traffic Jam Pilot
4
).
− Level 4: “High Automation”: The vehicle manages all driving functions and controls
itself under certain conditions (e.g., adequate 5G coverage of the operating zone).
− Level 5: “Full Automation”: The vehicle possesses and maintains all driving functions
completely (without zone restrictions).
GENERAL FORECASTS AND SOCIO-ECONOMIC IMPACTS OF AUTOMATION
The impacts of AVs from different aspects have been addressed by several researchers in recent
years. Researchers primarily examine how the spread of AVs changes the mobility patterns and
space utilization in urban environment (Bagloee et al., 2016; Madigan et al., 2017; Tokody &
Mezey, 2017), the role of car use in the future of passenger transport (Zmud et al., 2013; Arbib
& Seba, 2017; Lagadic, Verloes, & Louvet, 2019) and the travel experience (Prisecaru, 2016;
Clements & Kockelman, 2017; Marletto, 2019; Syahrivar et al., 2021).
1
https://www.sae.org/news/press-room/2018/12/sae-international-releases-updated-visual-chart-for-its-%E2%80
%9Clevels-of-driving-automation%E2%80%9D-standard-for-self-driving-vehicles
2
https://www.nhtsa.gov/
3
Intelligent Parking Assist System.
4
https://hondanews.com/en-US/honda-corporate/releases/release-e86048ba0d6e80b260e72d443f0e4d47-honda-
launches-next-generation-honda-sensing-elite-safety-system-with-level-3-automated-driving-features-in-japan
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
37
Altering mobility patterns
As technology evolves, travellers' mobility habits could change significantly. Studies addressed
some remarkable benefits of automation like the increased usefulness of travel time (e.g.,
decreasing traveling time and widening of activities during mobility – Kyriakidis et al., 2015;
Platt, 2017) and the environmental and economic benefits of automation (e.g., less energy
consumption, lower travel costs – Bagloee, 2016). Research on urban and transport
development (Freudendal-Pedersen et al., 2019; Schipper, 2020) emphasizes that, with the
widespread use of AVs, urban traffic flows could improve, fewer parking spaces will be needed,
thus reducing the environmental impact of the sector.
Research also suggests that the emergence of AVs may also widen the range of people who
were previously unable to travel alone (e.g., without a driving licence, due to health problems,
etc.). Sivak and Schoettle (2015) surveyed 1,500 people in the UK, Australia, and the United
States. The most important findings are that 60% of the people involved in the research had a
positive attitude towards technology (high willingness to try AVs). Platt’s (2017) research in
Canada examined different aspects of AVs. Results proved that frequent travelers are more
receptive and families with young children are the most distrustful (they consider it too risky to
hand over the driving tasks to the machine). The analysis of the general impacts, such as socio-
economic externalities (e.g., altering of consumer preferences, labor market reorganization),
are currently the most important and unanswered issues around the technology.
Altering car usage and perception of the machine
Research on travel psychology and behavior suggest that driving a car represents the dominance
of the person in a certain micro-community (e.g., family, friends) and enhances confidence
(Urry, 2004). In contrast, at the level of full automation, these psychological benefits (e.g.,
driving experience, enjoying gear shifting, control the vehicle, etc.) might disappear. At SAE
level 4-5, there will be no need for a driver’s license, which could also weaken the prestige of
automobiles. Research highlights that constantly evolving automation makes car use simpler
and more comfortable, which can guide travelers to this means of transport, i.e., the importance
of other environment-conscious modes (e.g., public transport) might be decreased in the long
run (Currie, 2018). One of the most important issues regarding AVs is road safety and data
security. Although increased road safety is one of the major benefits of automation, research
has shown (Xu et al., 2018; Liljamo et al., 2018) that there is noteworthy mistrust in fully
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
38
automated vehicles, primarily due to uncertainty and the lack of in-depth knowledge about the
machine.
Altering travel experience
Another significant influencing factor can be the novelty of the driving experience. Pitcher
(2011) highlights that the usage of AVs seems to be easy to learn, easy to operate, and does not
require meaningful efforts. Other research stresses the negative impacts of self-driving cars on
driver experience. It has been revealed that individuals who seek complex and intense sensory
experiences, tend to drive at a higher average speed (Becker & Axhausen, 2017) and keep
shorter tracking distance (Payre et al., 2014). Obviously, this cannot be provided by the usage
of self-driving cars; the human driver becomes a passive observer at higher levels of automation
(SAE Level 4-5). Individuals who are stick to intense driving experiences would be less likely
to prefer a complete handover of driver’s responsibilities, as this would reduce the intense
sensory experience they require (Gardner & Abraham, 2007). It is also worth pointing out that
a self-driving car may enhance the sense of freedom by serving special mobility needs as a
“moving living room, or office” and new activities on board.
Table 1. General issues regarding autonomous vehicles (SAE Level 4-5)
Source: Authors’ own editing based on the literature review
Impacts of AVs on tourism services
Although previous research analysing the impacts of AVs in tourism is limited, several possible
consequences can be identified. During the transition period (on a lower level of automation –
SAE Level 2-3), mobility opportunities may change (e.g., easier approaching of a more distant
Altering mobility patterns
1) Widening of activities
during mobility
2) Extending segment,
individuality
3) Environmental
benefits
4) Economic and social
consequences
Altering car usage and AI-
human interaction
1) Easier to use a car,
extending functionality
2) Cybersecurity, legal
and ethical issues
Altering travel experience
1) Elimination of driving
experience –or
becoming a unique
service
2) Compensation of
drivers –extending on-
board services while
traveling
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
39
destination with a car equipped with ADAS), but more radical tourism-related alterations can
be predicted on the full level of automation. Based on this, we focus on exploring the potential
effects of SAE level 4-5 automation.
The possible changes in the field of tourism are interpreted along with three main topics:
tourism alterations that can be associated with the handover of driving tasks, the increasing
accessibility, and the new (possible) applications of vehicles for tourism purposes.
Handover of driving tasks during tourism-related travel
At the level of full automation, the lack of the need for a driver’s license poses barriers for
travellers who, due to their age or health constraints, would not be able to travel alone for
tourism (Anderson et al., 2014). This consumer group becomes more independent and flexible
in their mobility and could reduce their social isolation (IFMO, 2016; Koul & Eydgahi, 2018).
Based on forecasts, the spread of AVs could increase travel demand by about 11% in the next
decade (Sivak & Schoettle, 2015). Research also emphasize (Cohen & Hopkins, 2019) that
passengers can embark on new activities while traveling (e.g., relaxation, admiring the
environment) instead of driving. Decreasing travel time can also change travel mode
preferences, making AVs more attractive than other modes of transport, such as rail transport
or aviation. Door-to-door mobility can also reduce travel time compared to public transport,
which may lead to a reduction in the use of public transport (IFMO, 2016). The use of AVs also
offers an additional option for people who have a driving licence but are reluctant to drive to a
foreign destination. When sitting in an AV, it is not necessary to be aware of the driving rules
of the destination (e.g., left- and right-hand traffic), thus, the unknown environment will no
longer be a limiting factor (Cohen & Hopkins, 2019).
Increasing accessibility of destinations and attractions
As a result of the optimized traffic realized by AVs, travel speed increases and travel time
decreases, allowing tourists to travel longer distances in the same time interval (Bagloee et al.,
2016). Due to the constant travel speed, route and travel time planning is more reliable and
predictable (Kim et al., 2015). Tourists will also be able to reach more distant and previously
little-visited attractions, giving AVs the opportunity to reach new destinations and attractions
(Cohen & Hopkins, 2019). In the light of the expected changes, AVs can replace the role of
conventional shuttle buses and taxi services, thus, completely repositioning the importance of
the means of passenger transport (Bainbridge, 2018).
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
40
New (possible) applications of AVs for tourism purposes
With the spread of automation, new AV-based services might also emerge in tourism. There
may be a need for using conventional vehicles (human-driven) if this is no longer possible in
the destination visited. On the other hand, testing self-driving cars on SAE Level 4-5 in places
where technology is not yet widespread can also appear as travel motivation (Ásványi et al.,
2020). With the application of AVs, a new way of sightseeing (AutoTour) could be created
(Bainbridge, 2018). This would work on a similar principle to hop on – hop off bus tours in
cities but could also replace walking tours. AutoTour services might be more flexible since the
route can be easily configured in real-time, along with tourists' preferences. At the same time,
the service raises sustainability issues. Tourism habits, the behavior of tourists might be
radically changed due to the emergence of AVs. Tourists – who were previously responsible
for driving and monitoring the environment – can drink alcohol since they are released from
the obligations. Evening tours and parties might become more attractive in urban spaces and
decrease the responsible attitude of visitors (Bainbridge, 2018). In the early stages of diffusion,
there may also be an increasing demand for test (experience) “driving” of AVs. Since the
interior design of AVs can be modified, vehicles can offer new (tourism-related) services that
might affect MICE
5
tourism, hospitality, and hotel industry. Passengers in specially designed
AVs can sleep while travelling, so passengers may not need to book accommodation as they
might not have to stop for a rest during a long-distance trip (Cohen & Hopkins, 2019).
Table 2 Impacts of AVs on tourism
Source: Authors’ own editing based on the literature review.
5
The umbrella term for business tourism: Meetings, Incentives, Conferences & Exhibitions.
Handover of driving tasks
1) Extension of
consumer group
2) Enhancing activities
that can be carried out
while traveling
3) Increasing travel
comfort, relieving
stress arising from
special travel
conditions (e.g., right-
or left-handed traffic)
Increasing accessibility
1) Optimized traffic
flow –better route and
time management
2) Better accessibility
of distant destinations
and attractions by road
transport (AVs)
3) Redefined passenger
transport –decreasing
role of conventional
means of transport
Possible applications of
vehicles for tourism
purposes
1) Driving a car/try an
AV as a tourism
attraction
2) AutoTour service
with MI tour guide
3) Radically changing
tourism behavior
4) Advanced interior
design of AVs –
moving hotel room,
meeting room
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
41
Research gaps identified by the literature review
Based on the literature review, the following key findings and research gaps have been
identified that determine the empirical phase of our research. The literature on the diffusion of
AVs is extensive, based on which we have synthesized the general impacts into three main
categories: Altering mobility patterns (1), Altering car usage and perception of the machine (2),
and Altering travel experience (3). Nevertheless, sector-specific analyses are limited, especially
the literature on tourism impacts. Based on the journal articles identified, a new framework of
expected tourism impacts has been developed (see Table 2). No empirical research on the
impact of self-driving cars on tourism has been found, nor did any other research consider
factors other than traditional sociodemographic variables. This confirmed the relevance of our
study and the application of the Big Five Personality Trait to extend the segmentation of tourists
who are open to using AVs.
In the light of these, the empirical research investigates attitudes towards possible tourism-
related AV applications identified in the literature: namely, the willingness to hand over the
driving tasks in foreign environment to better observe the surrounding, the openness to use AVs
for sightseeing, the intention to use AI-based tour guiding (AutoTour service), AVs for
experience driving, and the openness to do new activities while travelling (instead of driving –
relaxation, conduct meetings, etc.).
DATA AND METHODS
Data collection has been carried out online, between October-December 2020, and resulted in
671 responses. The number of subjects involved in the survey exceeds the expected size of
exploratory marketing research (Malhotra, 2009) and so the outcomes can be approved and
utilized for further analysis.
Based on the literature review, we have formulated three research questions (RQs):
− RQ1: How do tourists relate to the use of AVs at the level of full automation?
− RQ2: Which of the AV-based tourism services identified in the literature are attractive
among tourists?
− RQ3: What personality types are open to AV-based tourism services?
Respondents from Hungary who regularly takes part in trips for tourism purposes were
included in the analysis. Respondents had to associate with the pre-COVID19 period during the
completion of the survey.
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
42
With our questions, the tourism and mobility habits, the personality type of the subjects
based on the Big Five Personality Traits (Table 3) framework have been identified. The Big
Five is one of the most important personality models in psychology, according to which
subjects can be classified into five factor groups (Cobb-Clark & Schurer, 2012).
Extraversion (1) involves the free expression of impulses, and subjects in this category
are characterized by assertiveness and dominance in social behaviour (Cobb-Clark &
Schurer, 2012). The Conscientiousness (2) group includes those who are organized, self-
disciplined and duty conscious. Agreeableness (3) is usually referred to as the ability to
maintain relationships. Subjects of this category have high empathy and trust.
People in the Neuroticism (4) category are prone to unrealistic thinking, and less able to
control their impulses (Komarraju et al., 2011). Based on this, they might experience a lot
of stress, are anxious and more vulnerable. Subjects of the last category, the Openness to
Experience (5) are characterised by creativity, out of box thinking, and openness to new
ideas (De Raad, 2000).
Table 3. Main characteristics of Big Five Personalities based on Gosling et al. (2003) and
Komarraju et al. (2011)
Category
Main characteristics
Extraversion
sociable, energized by social interactions, outgoing
Conscientiousness
organized, self-disciplined, duty conscious
Agreeableness
high empathy, altruist, high trust
Neuroticism
experience a lot of stress, anxious, vulnerable
Openness to Experience
curious, creative, out of the box behaviour
Source: Authors’ own editing.
A Likert scale ranging from 1 to 7 has been applied to explore attitudes towards AV-
based tourism services. During the analysis, mean values above 4 were considered positive
(i.e., represents openness to tourism-based services). In addition to the basic descriptive
statistics (e.g., mean, standard deviation, mode, median), the Kruskal-Wallis test has been
employed to identify significant differences among variables. The strength of the test was
assessed based on Eta-squared test suggested by Tomczak and Tomczak (2014).
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
43
RESULTS
Sociodemographic characteristics of the sample
By gender, the sample is relatively balanced: of the 671 people surveyed, 56.3% are women
and 43.3% are men. The sample consists of subjects of all age groups. The largest proportion
(27%) is in the 18-29 age group, followed by the over-60 age group (25%). The 30-39 age group
has a slightly lower proportion (21%), while the 40-49 age group is represented by 15% and the
50-59 age group by 12%. Most of the respondents live in the capital (40.2%) of Hungary, 29.4%
in other cities, 17.4% in county seats, and 12.7% in villages.
Tourism-related consumer and mobility habits
Subjects’ tourism-related consumer habits have been analyzed in terms of travel frequency (1),
way of organizing travel (individual travel or package tour) (2), travel motivations (most
preferred tourism product) (3) and means of transport used to travel to (4) and from the
destination (5).
1 Based on the results, 6.5% of the total sample make several trips a month or more per year.
27.6–27.6% of respondents travel for tourism purposes every six months or every year. In
addition, a further 24.8% travel every few months.
2 Majority of respondents (80.2% of the total sample) organize their trips individually;
package tours are not common among subjects.
3 In terms of motivation, the most popular tourism activities are recreation (26%), urban and
cultural tourism (17%), wellness (15%) and VFR
6
(visiting friends and relatives) (13%). The
share of other tourism products (e.g., MICE, active tourism, festival tourism, niche elements)
is below 10%.
4 Majority of tourists use their cars (68.2%), but airplanes (44.2%), trains (32.8%), and buses
(27.7%) are also common ways to reach the destinations. A negligible proportion of tourists
rent a car (6.2%) or use carpooling services (1.7%).
5 At the destination, the vast majority of subjects travel by car (64.9%), use public transport
(50.9%) or approach attractions on foot (53.8%). Relatively few people rent a car (17.4%)
or decide to use shared mobility services (e.g., carsharing) (2.3%), or micro-mobility
vehicles (2.9%).
6
Visiting Friends and Relatives.
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
44
Attitudes towards tourism alterations based on AV use
Based on the attitudes towards AV-based tourism services, the following findings have been
revealed:
Respondents were asked how much they would prefer to use self-driving cars to pay
attention to the environment rather than driving. Based on the responses, there is a high
openness towards AVs in this context (Mean: 4.45; Median: 5). Tourists also stated that they
would be willing to give up control to the machine in a foreign environment (Mean: 4.52,
Median: 6). However, there is also a sense of caution among tourists, as they are less open to
leisure activities (e.g., sleeping, reading, etc.) while traveling in an AV (Mean: 3.55, Median:
3).
When asked whether tourists would use AVs for sightseeing, there was also a high
proportion of positive responses (Mean: 4.51, Median: 5). The willingness to visit more distant
destinations and to use AVs in a foreign environment also scores above 4.
Tourists would be open to a tourist service in which the machine (AI) would be the tour
guide (AutoTour) (Mean: 4.64, Median: 5). The openness towards experience driving with AVs
responses are particularly positive (Mean: 4.77, Median: 5).
The intention to use extended AV-based services (e.g., mobile meeting room – Mean: 4.21,
Median: 5; interior for sleeping – Mean: 4.05, Median: 4) is slightly lower but above 4. Standard
deviation values are below 2 in every cases. The most frequent element in every case is 5, which
also indicates a high degree of openness.
Table 4 Correlation between travel frequency and possible application of AVs for tourism
purposes
Item
Monthly
or often
A few times
a year
Twice
a year
Annually
Less
frequently
H statistics
Eta2
Openness to do
sightseeing conducted by
an AI-based tour guide
(AutoTour).
4.73
(1.84)
4.83
(1.81)
4.49
(1.82)
4.57
(1.86)
3.55
(1.90)
22.787***
0.03
Openness to use Avs that
are suitable to conduct
meetings.
4.21
(1.85)
3.69
(1.91)
3.42
(1.86)
3.44
(1.94)
3.06
(1.85)
16.429**
0.02
Openness to use AVs
which have an interior
design for sleeping.
4.14
(1.96)
3.84
(1.98)
3.67
(1.88)
3.57
(2.12)
3.25
(2.03)
9.466*
0.01
Openness towards tourism
services that include
“driving” experience (test
driving) with AVs.
5.04
(1.75)
4.98
(1.82)
4.79
(1.68)
4.74
(1.82)
3.91
(1.91)
19.531**
0.03
Note: ***: p < 0.001; **: p < 0.01; *: p < 0.05
Source: Authors’ own editing based on empirical research.
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
45
Based on Kruskall-Wallis-test, significant correlations between travel frequency and the
attitude towards AV-based tourism services have been revealed (Table 4). Among those who
travel more frequently for tourism purposes, the openness to use AVs is significantly higher.
The effect size based on Eta2 is low (below 0.06) in all cases.
Big-Five personality traits and tourism preferences
Respondents were classified into the personality types based on their self-assessment. The self-
assessment was based on answering standard questions
7
suggested by the Big Five Personality
Test. Based on the results, respondents of “Extraversion” category typically stay more than 3
nights in the destination visited. No significant differences by gender compared to the total
sample have been detected. By age, the 18–29 age group is found in higher proportion in this
category (40%). A significantly higher proportion of subjects belong to this category who are
interested in urban and cultural tourism.
The segment of “Agreeableness” has a higher share of longer trips (7-8 days), during which
the demand for VFR tourism and active tourism products dominates. No significant difference
by gender is observed compared to the overall sample. The proportion of age group 30–39 is
slightly higher here (42%) than in the total sample.
The group of “Conscientiousness” is also made up of subjects who prefer shorter trips of 1–
3 nights. By gender, men are in a higher proportion in this category. By age, no significant
difference has been found. Among respondents of the category “Neuroticism”, trips of 3–4 days
are the most common. In addition to VFR tourism, MICE tourism is also a popular travel
motivation among them. No significant differences have been revealed by age and gender.
The highest proportion of subjects belonging to the “Openness to Experiences” prefer long
trips (7–8 days). Female respondents make up a larger proportion of this group (66.6%). Among
them, urban tourism, active tourism and visiting festivals are the most popular reasons for
travelling.
Correlations between personality traits and attitude towards AV use for tourism purposes
have been found (Table 5). Based on the test statistics, the attitudes of subjects within the
category of “Extraversion” (A) are significantly more positive towards each alternative of
tourism related AV usage. Results revealed that there is also a significant correlation between
“Neuroticism” (D) personality and lower attractivity of tourism related AV services. Among
respondents of “Extraversion” (A) and “Agreeableness” (B) categories, the idea of experience
7
https://bigfive-test.com/
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
46
driving is the most attractive, whereas the same service is the least attractive among subjects
who belong to the “Neuroticism” (D) category. It can be concluded that respondents of the
“Conscientiousness” (C) category seems to be less open to using AVs for tourism purposes.
Among tourists of “Openness to Experiences” category (E), the evaluation of each tourism-
based alternative is significantly positive. In this category, the most attractive services are
also the idea of test driving as well as sightseeing with AVs.
Table 5. Correlations between the attitude towards AV use for tourism purposes and
personality traits based on Big Five theory
Item
A
B
C
D
E
Openness to use AVs to pay
more attention to the
surroundings.
0.090*
0.258***
Openness to carry out
additional activities (reading,
entertainment, etc.) during
traveling by AVs.
0.094*
0.090*
-0.095*
-0.107*
0.241***
Openness to use AVs in special
traffic situations (e.g., right- or
left-hand traffic).
0.191***
Intention to use AVs while
sightseeing.
0.273***
Willingness to visit more
distant destinations when using
AVs.
-0.098*
0.208***
Openness to AV use in
unfamiliar environments.
0.083*
0.213***
Openness to do sightseeing
conducted by an AI-based tour
guide (AutoTour).
0.198***
0.243***
Openness to use AVs that are
suitable to conduct meetings.
0.137***
-0.089*
0.232***
Openness to use AVs which
have an interior design for
sleeping.
0.133***
0.188***
Openness towards tourism
services that include “driving”
experience (test driving) with
AVs.
0.228***
-0.120**
-0.118**
0.279***
Notes: ***: p<0.001; **: p<0.01; *: p<0.05. Abbreviation to the table: A – Extraversion, B – Agreeableness,
C – Conscientiousness, D – Neuroticism, E – Openness to Experiences
Source: Authors’ own editing based on empirical research.
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
47
DISCUSSION AND CONCLUSION
This research aimed to explore the potential impacts of SAE Level 4–5 autonomous vehicles in
the field of tourism. As a result of the literature review, we have created three categories
(handover of driving tasks, increasing accessibility of destinations, new (possible) applications
of AVs for tourism purposes) that synthesize the potential tourism alterations resulting from the
use of AVs. Empirical research has revealed the attitudes of 671 respondents towards AVs for
tourism purposes.
Based on the results and in relation to the research questions (RQs), the following
conclusions have been drawn:
RQ1: How do tourists relate to the use of AVs at the level of full automation?
Based on respondents' attitudes towards services, there is a generally positive (all mean
values above 4) attitude towards the analysed applications of AVs in tourism.
RQ2: Which of the AV-based tourism services identified in the literature are attractive
among tourists?
Based on the evaluations, the openness to use AVs for sightseeing and AI-based guided tours
(AutoTour service) is particularly noteworthy. Tourists would also be open to use AVs while
staying at the destination (e.g., for sightseeing). Subjects see an opportunity to use AVs to better
observe the environment and to immerse themselves in the tourist experience instead of driving.
RQ3: What personality types are open to AV-based tourism services?
Higher openness can be detected among the 18-29 age group, who are taking longer trips
(3–7 nights), and in the “Extraversion” and “Openness to Experiences” segment. This segment
of tourists especially prefers urban and cultural tourism. It should be noted that the results show
lower openness among subjects with other personality types (e.g., “Neuroticism”).
The main added value of our research is that we have explored the potential impacts of AVs
on tourism, on which very few empirical studies and international publications have been done
before. In addition to the demographic data, we also specified the attitudes of the respondents
based on different personality types, which is also a unique approach in the social studies of
AVs and can be useful for a better market segmentation in the tourism sector. Although our
empirical research is not based on a representative sample, it proposes relevant inputs for further
research on tourism development, as a significant proportion of respondents regularly
participate in tourism trips and mainly organize their trips individually, thus we have explored
the view of an important consumer segment.
Miskolczi, M., Kökény, L., Ásványi, K., Jászberényi, M., Gyulavári, T., Syahrivar, J.
48
The attitude analysis concerning AVs provides a basis for further empirical research in
social sciences (e.g., modeling the technology acceptance of AVs in tourism, more detailed
elaboration of AV-based tourism service elements) and help to prepare for the technology
revolution for practitioners in tourism.
Acknowledgement
Project no. NKFIH-869-10/2019 has been implemented with support provided by the National Research,
Development, and Innovation Fund of Hungary, financed under the Tématerületi Kiválósági Programme
Funding Scheme.
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