政策研究論文

An Analysis of Overtourism Policies in Cities by Combining
Quantitative and Qualitative Criteria
Overtourism has emerged as a global concern because of its worldwide negative impacts on society, culture,
nature, and the environment. Local authorities have been implementing policies to solve the negative
consequences to some extent. However, links between overtourism and the policy have rarely been
investigated. This study categorised the policies into types and levels based on qualitative information andranked overtourism as ordinal with quantitative information. By investigating the data for selected cities, thecorrelation between policy strictness and overtourism degree was analysed. The findings indicate that the
combination of quantitative and qualitative indicators might be a useful tool to compare overtourism
degrees on a relative basis. Some typical types of reactions of destinations to the overtourism problem,
which might be a determinant of destination tourism development, were found.
Keywords

ヌエン ヴァン チューン

overtourism, qualitative analysis, quantitative analysis, overtourism policy

福田大輔

Nguyen Van Truong

博士（観光科学）
前 一般財団法人運輸総合研究所研究員
現 Lecturer, University of Transport and Communication,

FUKUDA, Daisuke
博士（工学）
東京大学大学院工学系研究科教授

Hanoi, Vietnam

environment” 15). Overtourism mitigation is a critical

1──Introduction

task contributing to SDGs.

Overtourism has emerged as a global concern. The

Butler (1980)16) introduced the concept of a tourist

overtourism phenomena have been recognised acrossarea cycle evolution; in the concept, he described that

States1),

the development of a tourist area often experiences

The negative

several stages (Figure—1). At the stage when theimpacts of overtourism have been observed in all

tourist volume approaches the local carrying capacity

aspect s of desti nations, for example, societ alb ec au se of t he m a ssi f ic at ion of tou r i sm, t hedisturbance to residents caused by too much noise,development of tourism at the destination tends tocontinents, for example, in the United
Europe 2– 4),

Oceania5),

andAsia 6,7).

behaviours8,9);

the overly

stagnate. At this stage, the destination, for example,

crowded condition endangers culture, nature, and thecommunities, nature, and culture, tends to be moreenvironment4,10,11);even in some cities, under thesensitive to the increase in tourist volume andovertourism pressure, the local demography andi n appr opr i ate b eh av iou r s. I f t he d e s t i n at ion

identity have been lost, for example, in Venice12) andsuccessfully implements the policy, tourism may

Dubrovnik13).

successfully redevelop; otherwise, it may be down-

littering, and inappropriate

The attendees at the G20 tourism ministersʼ
meeting14) in Kutchan, Hokkaido, expressed concerns

warded or decline because of the increase in negative
impacts.

about the global organisation to address overtourism.

Some international organisations have developed

The main theme of the meeting was “Shifting towards

and recommended a system of criteria for sustainable

more sust ai nable tour ism and m a x i m isi ng it s

tourism destinations, such as GSTC or GSTC-D17–19)

contribution to the Sustainable Development Goals

and ETIS20). Some countries, e.g., Japan, have adopted(SDGs).” The Chairman (Kazuyoshi Akaba) of thethose sustainable tourism criteria with some local

meeting said, “We must study measures to address

customisations for their promoting sustainable tourism

friction between tourists and locals and to protect theindustr y 21). Notwithstanding, those systems are006

運輸政策研究 Vol.24 2022

政策研究論文VolumeDevelopment

The boomof mass
tourism

Critical period ofmass tourism

Successful
redevelopment
Minor
modification

Stagnation
Consolidation
Resident:- Being proud- Excited- Comfortable- Being annoyed- Against tourists

Tourists:- Crowds areinteresting in somecases→Motivated to come
Blue: Tourist volume
Black: Negative impact

Downward or
decline(e.g. Northern
Ireland, riots, 1969)

Feeling- Inconvenient- Dissatisfied→Reduce revisit
Successful redevelopment
Minor modification
Downward or declineTime(adapted and adjusted based on Butler, 1980, The Concept of a Tourist Area Cycle of Evolution: Implications for Management of Resources)■Figure —1

Overtourism and destination development

important in promoting sustainable tourism byor under discussion in 14 European cities, three Asian

primarily proposing indicators that recommend

cities, and one US city. The study presented thetourism destinations to apply for the sustainable

overtourism situation and management in 19 cities,

development pur pose in general; they do notwhich relied on the 11 strategies and 68 measures

recommend models or evaluation methods to assess

proposed by UNWTO (2018)25). Weber et al. (2017)26)

the tourism industry at destinations. Overtourism is afocused on the impacts of tourism on economic,

special situation; thereby, both tourists and residents

political, environmental, social, and cultural aspects offeel there are too many tourists or too much adverse

11 destinations under the pressure of tourism.

impacts22). Because overtourism is much related to the

The commonalities of the aforementioned studies

ʻfeellingʼ of tourists and residents, the quantitative

are as follows: They emphasised the necessity tocriteria are not enough. This study offers an analyticalmanage social-economic drivers of tourism and ensure

approach to combine both quantitative (density,

benefits to destinations (e.g., local communities,

intensity of tourists, occupancy rate, day-night trips

environment, economy) and tourists to ensure theratio) and qualitative criteria (opinion of local experts)

sustainable development of tourism in the cities. Also

to evaluate overtouirsm at 28 cities worldwide.

necessary is cooperation across sectors and measures

To d at e, s e ve r a l s t ud ie s h ave i nve s t ig at e dconsidering the wider city-policy structure. Althoughovertourism policy implementations. The study ofthe overtourism in each city was well described, the(2018)23)

focused on six international

evaluation or comparison of overtourism situations,and four domestic areas. The study investigated thepolicy implementations, and the extent to which thetourism situations by using an email-based survey, apolicies were implemented according to the degree ofsite survey, and an informal survey through theovertourism had not been documented well.

MLIT in Japan

internet. The information on the negative phenomena

The objectives of this study were as follows: first,

p e r c e i ve d b y lo c a l d e s t i n a t io n m a n a g e m e n t

the overtourism degree (or level) in some cities wasorganisations (DMOs) to be caused by tourism andinvestigated and evaluated on a relative basis based on

local strategies were aggregated. Another study, by

the composite indicator, which was formed by relying

UNWTO (2019)24), reviewed the policies implemented

on both quantitative and qualitative criteria. Second,

政策研究論文Vol.24 2022 運輸政策研究

007

overtourism policies in those cities were investigatedand qualitatively ranked as ordinal to compare that

(1) Quantitative
statistical datacollection

result with the degree of overtourism. The remainder(2) (Qualitative)
opinion of local
experts ondegree of tourist
excessive(3) Informationof policy
provided by
local experts(4) Informationof policy
collected by theauthorsof the paper is organised as follows: In section 2, themethodologies, which include the data collection
method and analysis method, are presented. The

Quantitative
composite indicator of
tourist excessive level

results of the analysis are introduced. The discussions
Tourist excessive
degreeand conclusions are in the final section.

Tourist excessive
level – Policy
strictness correlation
analysis (Figure 8)

2──Study design and methods
2.1 Study design

The survey was designed as non-random. Fifty cities

Policy strictness(judged by theauthors)■Figure —2

Data collection and survey designthat reported overtourism were identified based on
newspapers, academic fora, UNWTO reports, andovertourism level. The interviewees were asked about

academic papers. The survey had two parts: (i) The

their general perceptions of the level of excess tourists

first part was an email-based survey conducted toduring the tourism seasons in some typical tourist

obt a i n t wo t y p es of i n for m at ion: qu a l it at ive

areas, such as tourist spots, local transport systems,

information on overtourism (opinion of local experts

restaurants, and shops and recreational areas (referredon the degree of excessive tourist, see box 2 in Figure

to as tourism locations). The second part, to collect the— 2), a n d i n f o r m a t i o n o f p o l i c y w h i c h a r e

information of policy implementation or under

implementing or under preparation (box 3 in Figure—discussion, was designed as an opened-end question.

2). (ii) The second part was data collection to obtain

The interviewees were encouraged to fill in the

two types of information: The quantitative statisticalopened-end question in the designated form with asdata (box 1 in Figure—2) and information of policy

much detail as possible of overtourism policies

implementing or under preparation (see box 4 in

(Table—1). In some cases, the interviewees provided

Figure—2). Because the policy information was not

the URLs to access the policy information. In thesealways fully provided by the interviewees, the policy

cases, as aforementioned, the policy information

information collection was required to obtain thecollection was conducted through the official websites

necessary information for judgment fully.

of local tourism authorities.

The interviewees were chosen to obtain reliable

Both policy information provided by local experts

information on the degree of excessive tourist andand collected by the authors gathered together forpolicies implemented in the cities. The interviewees

strictness judgment. The policy strictness waswere either local tourism officers, who directly worked

categorised into three levels by a judgment of thein tourism authorities (e.g., local tourism DMOs, local

authors based on how strong the policy impact

tourism bureaus, local tourism departments) or local

tourists. In particular, low strictness level was defined

tourism researchers who have published tourism

including policies that focus on educating tourists toresearch. The contact details of the local experts werechange their behaviours (e.g., education, propaganda);

identified through the websites of local tourism

medium strictness level was defined including policies

authorities and local research institutions.

such as tourist taxation, dispersion; and high strictness

The questionnaire for the e-mail-based survey

level included policies that strongly force tourists toincluded two parts. The first part, to collect thechange their behaviours, such as restriction of tourist

information about the degree of excessive tourist, wasarrivals, fine inappropriate behaviours of tourists.

designed as a five-point Likert scale, which supposes

The results of the e-mail-based survey contained

as a great discriminant27). In this study, the level of an

respondents of 28 cities worldwide (Figure—3): 12 inexcess of tourists was used as an indicator ofEurope, one in Thailand, one in China, seven in008

運輸政策研究 Vol.24 2022

政策研究論文Reykjavik,
IcelandSwedenIceland
NorwayUnitedKingdom
PolandLondon, UK
UkraineGhent, Belgium
Prague, Czechia
Lucerne,
VeniceDubrovnik, Croatia
Porto, Switzerland
Portugal
TurkeyBarcelona, Rome
Lisbon,Spain
Portugal
Iraq
Algeria
Mali

Libya Egypt

Niger

Europe: 12 cities
Jan-May
Asia: 162019
• Thailand 1; China 1• Viet Nam: 7 cities• Japan: 7 cities/areas (until June 2019)
Kazakhstan

Saudi
ArabiaChad Sudan

Nigeria

South
Korea

China

Iran Afghanistan
Pakistan
India

ChiangMai Thai
land

Japan
Japan 7 cities

Macao SAR
VN 7
citiesEthiopia

Source: authors composed data

■Figure — 3

The survey areas■Table —1 Surveys and collected items
Survey types
Criteria used in the study- Excess of tourists in general
at typical tourist spots in thearea (local transport systems,
restaurants, shopping malls
and recreational areas),(i) E-mail based survey- Policies have been
implemented or are underdiscussion (interviewees freely
provided any information as far
as their knowledge).
- Tourist density (tourists/Km2.
day),- Tourist intensity (tourists/
resident.year),- Seasonal distribution (ratio of
tourist volume in peak: offpeak season),(ii) Statistical data and- Day-night tourist volume
information collection
distribution (ratio of day andovernight tourist volume)- Average occupancy rate ofaccommodation in one year,- Policy information collection:
To elaborate on the information
provided by the interviewees.

accommodation, and the perception of local expertson the excess of tourists in tourist spots, local
transport, restaurants, shopping areas, and otherrecreational areas in tourism seasons. Generally, thevalues of the criteria indicate the different situations in
those cities. This leads to the significance of utilising
the composite indicator for comparison. Specifically,
tourist density (Figure—4, upper panel) indicates theaverage number of tourists per Km2 per day. Tourist
intensity (Figure—4, lower panel) presents the average
number of tourists that one local resident passively“welcomes” in one year.
The tourist density criterion showed that Venice,Lisbon, London, Macao, Barcelona, Sam Son are muchhigher than the others. Tourist intensity showed that
Venice, Dubrovnik, Cat Ba, and Biei-cho are very highVietnam, and seven in Japan. The second part of the

tourist-intensity cities. Moreover, the density andsurvey, data collection (box 1 and 4 in Figure—2),

intensity criteria provided information that may befocused only on these 28 cities. The statistical datainterpreted as the different impacts of the situation ofcollection included tourist volume to the cities

an excess of tourists on residents. For example, Macao,monthly, quarterly, or seasonally; the number of day

on the one hand, was relatively small in terms of

trips and night trips; peak season length in months;

geometrical area; thus, tourist density was high; on theoccupancy of accommodation; and population total

other hand, the population was relatively high, leading

and administrative area of the cities (the sources of theto the low tourist intensity. These figures for Macao

data collection is presented in Appendix). Five main

were in contrast to those of Venice, Dubrovnik, Cat

criteria were then determined (Table—1).

Ba, and Biei-cho, where geographical areas wererelatively larger, and the population was lower.

2.2 Results of the data collection and email-based survey

The ratio between tourist arrivals monthly in peak

In this subsection, we present tourist density, tourist

seasons and those in off-peak seasons is considered asintensity, seasonal distribution of tourists, day-nightthe seasonal distribution of tourists. In other words,

distribution of tourists, the occupancy rate ofthis criterion indicates the uneven distribution of

政策研究論文Vol.24 2022 運輸政策研究009

Miyakojima

Nagocity

Yonabaru city

Tomigusuku…

Miyakojima

Nagocity

Yonabaru city

Tomigusuku…

201
Nara

7
Biei-choMong Cai

Ha Long

Ba Ria Vung…

Da LatDa Nang

Cat BaSam Son

Ghent

LucerneBarcelonar

Warsaw

Macao

Dubrovnik

PragueRekjavik

Rome

LondonPorto

LisbonChiang Mai

Venice island
733

Tourist intensity
450

56
Nara

Biei-choMong Cai

Ha Long

Da LatBa Ria Vung…

Da Nang

Ghent

Cat BaWarsaw

21 43 13 56 22

47
Sam Son4

Lucerne13 16 38
Barcelonar

162

87
Macao

Rome

Dubrovnik

Porto

Prague5

Rekjavik

8

London14

Lisbon42

11 55 29 14

Chiang Mai

214

Venice island

800
700
600
500
400
300
200
100
0

Kyoto

No.tourists/
Resident.year

Kyoto

No.tourists/
Km2.day

Tourist density

1600
1378
1400
1200
1000
784
800
719
657
625
600
494
400
227
207
180
175
119
200
89 63 2137 101
12 64
14
29 20
3
0

(blank columns indicate the missing information)■Figure — 4

Tourist density and intensity

4.22

Nagocity

Yonabaru…

Tomigusuk…

Nagocity

Yonabaru…

Tomigusuk…

MiyakojimaNaraBiei-choMong Cai

Ha Long

Ba Ria…

Da LatDa Nang

Cat BaSam Son

Ghent

5.19

MiyakojimaNaraBiei-choMong Cai

Ha Long

Da Nang

Cat BaSam SonBa Ria…

0.45

0.00

Da Lat0.44
Warsaw

8.80

3.35

Barcelonar

Macao

0.620.94
Dubrovnik

PragueRekjavikLondonRome

0.000.00
Porto

LisbonVenice island

Kyoto

2.38

0.25 0.87

0.00

5.70

4.41

4.36
2.44

Took daytrip in Nara
9.59

Chiang Mai

2.00

1.71

and…

8.00
4.00

2.87 2.64

Day-night distribution

Spentovernight
in Kyoto

6.00

LucerneWarsaw

Barcelonar

Macao

1.19

Dubrovnik

Prague1.25

RekjavikLondon

Rome

Porto

LisbonChiang Mai

Venice island

1.24

2.10
2.04
1.35

Ghent

10.00

1.27

1.18

2.36

1.93

Lucerne12.00
Day:Overnight-trip
Ratio

5.23

Kyoto

Peak: off-peakseason vol

Seasonal distribution
6.00
5.00
4.00
3.00
2.00
1.00
0.00

(blank columns indicate the missing information)■Figure — 5

Tourist seasonal and day-night distribution

tourist arrivals between seasons (Figure—5, upper

tourist volume in the peak season was from 4 to 5

panel) in one year and the day time–night time

times higher than that in the off-peak season. In the(excursions-accommodation tourists) trips that werelower panel (Figure—4), the day–overnight trip ratio

supposed to be affected by overtourism.

demonstrates that Mong Cai, Lucerne, Biei-cho,

In Figure—5, the upper panel shows that Venice

Warsaw, and Venice island were highly unbalanced

and Dubrovnik were affected by the seasonality. The

between day and overnight trips. The day trips in

010

運輸政策研究 Vol.24 2022

政策研究論文

100
89
90
82 78
76 71
80 76 73 80
70
70
60
50
40
30
20
10
0

87 89

had a substantial excess of tourists in the tourism

81

69
54

55

62 60
44

50

Kyoto
Venice…
Chiang Mai
LisbonPorto
Rome
LondonRekjavik
PragueDubrovnik
Macao
Warsaw
Barcelonar
LucerneGhent
Sam SonCat BaDa Nang
Da LatBa Ria…
Ha Long
Mong Cai
Biei-choNara
Miyakojima
Nagocity
Yonabaru…
Tomigusuk…

Occupancy Rate(%rooms)（%）(blank columns indicate the missing information)■Figure — 6

Accommodation occupancy rateseason. Six cities—Rome, London, Prague, Lucerne,
Cat Ba, and Mong Cai—had a high excess of tourists.
The other cities had no or a moderate excess.
2.3 Policy strictness - Excessive tourist degree analysis
method
2.3.1 Excessive tourist degree

st udy, wa s a ssessed ba sed on t he composite

5
4quantit ative i ndicator, wh ich is based on t he3

quantitative criteria collected from data collection,2
1
0such as tourist density, tourist intensity, seasonality,
Kyoto
Venice island
Chiang Mai
LisbonPorto
Rome
LondonRekjavik
PragueDubrovnik
Macao
Warsaw
Barcelonar
LucerneGhent
Sam SonCat BaDa Nang
Da LatBa Ria Vung…
Ha Long
Mong Cai
Biei-choNara
Miyakojima
Nagocity
Yonabaru city
Tomigusuku…

Expert opinion
on excessive degree of tourists

Degree of excessive tourist of a destination, in this■Figure —7

 eneral perception of local experts on theGdegree of excessive tourist at local transport,
restaurants, shops and other recreational
areas in tourism season

day-night tourist distribution, occupancy rate aspresented in previous sections. Along with composite
quantitative indicator, opinions of local experts on the
degree of excessive tourist were also utilised.
Because the information on tourist volume wascollected, the overtourism level of the cities was
represented in terms of excessive degree. The

those cities were from more than 4 to 9 times higher

comparative analysis of policy and the degree ofthan the overnight trips. Further, based on theexcessive tourists was executed based on a relative

observations of tourist volume in Nara city and Kyoto,basis. The composite indicator was constructed bywe hypothesised that many tourists overnighted inrelying on the guidelines of the OECD, Union andKyoto, then took day trips to visit Nara, and thenCommission (2008)28).

returned to Kyoto. This indicates that Nara may be
more affected by day-trip visitors than Kyoto is.
Facility utilisation is also considered as a criterion of
overtourism. In most of the cities, for example, Kyoto,
Lisbon, and Barcelona, the average hotel occupancy
rates were from more than 70% to more than 80% (seeFigure—6).
Figure—7.General perception of local experts on the
degree of excessive tourist at local transpor t,
restaurants, shops and other recreational areas inwhere,: criterion k of city i,

tourism season
The results of the email-based survey of localk: criterion used in this study, for instance,experts on the level of the excess of tourists weretourist density, tourist intensity, seasonal

based on a five-point Likert scale (Figure—7). Four of

distribution, day-night distribution, and28 experts, each of them from one city, namely

accommodation occupancy rate,

Lisbon, Warsaw, Ghent, and Nara shared that the: mean of criterion k,

tou r i sm spot s, lo c a l t r a n spor t s ystem s, lo c a l: standard deviation of k,restaurants, shops, and other recreational areas in their: a composite indicator of city i,cities did not have an excess of tourists in general.

: degree of excessive of city i, andFive of them, in Venice, Dubrovnik, Macao, Barcelona,: quantile ofwith probability.

and Biei-cho, shared that those locations in their cities
政策研究論文Vol.24 2022 運輸政策研究

011

First, the criterion k was standardised (equation 1). The
composite indicatorof the city i was then estimated as

the mean of all five standardised criteria (equation 2).
Finally, the degree of excessive tourists was ranked on

3──Analysis results and discussions
3.1 Local experts’ opinions and the excessive degree of
tourists based on composite indicators

a five-point Likert scale corresponding to 20% quantile

The comparison of excessive degree based on(equation 3). The results of the composite indicator

composite indicators and expertsʼ opinion is presented), ranking (() are shown in Table—2).

in Table—2. In this study, we defined that if the

The degree of excess was based on the ranking withdifference between excessive degree based on thethe composite indicator. However, a composite indicator

composite indicator and expertsʼ opinion was ±1, theof some cities, such as Yonabaru, Tomigusuku,

ranking was considered consistent. This definition seems

Miyakojima, Nagocity, Biei-cho, was not available due

arbitrary; however, when using a five-point Likert scale,to the unavailability of the statistical data. The expertsʼ

the response tends to be dependent on personal

opinions were used for the cities that missed thepsychology or feelings. The ±1 difference could becomposite indicator. Because most (17/28) of the cities

acceptable. We found that, in most of the cities (17/28),

demonstrated that the excessive tourist degree

the opinions of local experts on the degree of excess at

obtained by local experts and by composite indicator

local tourism locations in general were consistent withwas consistent, we assumed that the excessive tourist

the ranking based on the composite indicator (Table—2).

degree at the cities that unavailability of the composite

In some cities, for example, Chiang Mai, Lucerne, Ba

indicator also was consistent with the opinion of local

Ria-Vung Tau, and Prague, the local experts supposed

experts.

that the excess degree of tourism locations was muchhigher than those of the entire city. Through the

2.3.2 Policy strictness and its correlation with excessive
tourist degree

Information on the policy implementations at cities,
which provided by the interviewees and collected by
the authors, was gathered. Based on self-judgment, thestrictness of tourism policies was categorised into
three levels relying on the strictness: 1. Low strictness
for policies focusing on raising the awareness oftour ists and residents, such as education andpropaganda; 2. Medium strictness for policies such as
taxation and tourist dispersion; 3. High strictness forpolicies that monitoring the tourist volume, such as
restriction tourist arrivals and fine bad behaviours(Table—2). Because tourism is promoted due to its
primary economic benefit, we hypothesize that thepolicy implementation of the cities may be dependent
on their social-economic condition. The 28 cities wereclassified into two categories, namely low income andhigh income. The qualitative correlation between
policy and the excessive degree was then analysed
and illustrated in Figure—8.

■Table —2

Excess degree based on composite indicatorsand experts’ opinion
Degree ofComposite excessive
PolicyExpertsʼ
with CI
No.
Citiesindicator
opinion strictness(DECI,(CI, Y‾į )L_quan )Consistency
−2.64
1
2
1
1 Da Lat
−2.45
1
2
1
2 Ha Long
−1.15
2
2
3
3 Kyoto−1.53
2
1
1
4 Nara−1.63
2
1
1
5 Ghent−1.66
2
3
1
6 Da Nang
−0.91
3
3
1
7 Porto−1.11
3
4
2
8 Rome−0.50
3
32
9 Reykjavík
10 Sam Son
0.80
3
2
1
11 Cat Ba
0.76
3
4
1
12 London
1.09
4
4
1
13 Barcelona
1.03
4
5
2
14 Venice
6.99
5
5
3
15 Dubrovnik
1.91
5
5
3
16 Macao
2.80
55
2
17 Mong Cai
1.33
5
4
1
Expert opinion 〉〉EDCI: (difference = 2+)
−2.34
1
3
1
18 Chiang Mai
−2.03
1
4
1
19 Lucerne
−3.08
1
3
1
20 BR Vung Tau
−1.89
2
4
2
21 Prague
Expert opinion〈〈 EDCI: (difference = 2+)
22 Lisbon
0.88
4
1
1
23 Warsaw
1.04
4
1
1
Cities that were missing statistical data−−
2
2
24 Yonabaru−−
2
1
25 Tomigusuku−−
3
1
26 Miyakojima−−
31
27 Nagocity−−
53
28 Biei-cho

Note: DECI, Degree of excessive tourists with a composite indicator

012

運輸政策研究 Vol.24 2022

政策研究論文Policystrictness

3

High(Limit arrivals,fine,…)

Note:
Blue: High income
Gray: low income(*): cities of Okinawa

Dubrovnik
VeniceKyoto
Biei-cho
Barcelona
Reykjavik

2

RomeMedium(Tax,
Dispersion …)

Yonabaru(*)
Da Nang
Miyakojima(*)
Ghent
Tomigusuku(*) Nago(*)
Ha Long Nara
Cat BaBR-Vung Tau
Sam Son
Da Lat1

Low(Education,
propaganda)

1

2

A little

LondonWarsaw
LisbonPorto

LucerneChiang Mai

Not excessive■Figure — 8

Ma CaoPrague3Moderate

4

Quite excessive

Mong Cai

5

Very excessive
Excessive degree

Excessive degree of tourists vs. policy strictness

comparison of the opinions of the local experts andidentify how concentrated tourists were at destination

the composite indicator, we found that in such cities,

tourism locations and understand more about thethere was a substantial imbalance in the concentration

viewpoints of local tourism experts.

of tourists between the tourism locations and theremaining areas of the cities. In other cities, such as
Lisbon and Warsaw, the ranking based on the

3.2 Correlation between overtourism policies and theexcessive degree

quantitative composite indicator indicated that the

The analysis of the correlation between policy

cities had an excess of tourists, suggesting that thestrictness and excessive degree is presented in Figure—degree of excessive tourist in the overall city area was

8. Qualitatively, the figure was divided into three areas

high. However, the local experts supposed that thecorresponding to three types of policy implementation.

tourism locations were not excessive. These opinions

The top-left area contains cities that applied stricterof local experts, to some extent, affected overtourism

policies to a lower excess degree of tourists. This area

policy implementation (Figure—8). Thereby the leveldescribes the citiesʼ early overtourism prevention. The

of tourism policy strictness was assessed as low.

bottom-right area contains the cities at a higher excess

The composite indicator, obtained from quantitative

degree that did not apply less strict policies. This area

criteria, expressed the average crowdedness of thei nd ic ate s t he c it ie sʼ mo s t r e ce nt r e ac t ion towhole city. Notably, overtourism is largely caused byovertourism. The middle area contains cities now

the spatial distribution of tourists, which was

implementing policies to ameliorate the negative

unavailable. In this study, the expertsʼ opinions as toconsequences of overtourism. Several important points

what extent they feel is an excessive number ofmust be discussed.

tourists in tourism spots, local transport systems,

T he first point is how the local authoritiesʼ

restaurants, and other recreational areas to express the

viewpoint affects policy implementation. For example,

spatial distribution of tourists were used to compare

in Lisbon, Porto, and Warsaw, the report was anwith the ordinal degree of excessive obtained withexcess of tourists. However, local experts also reportquantitative data. This comparison was to qualitatively

no overtourism. A tourism officer in Lisbon city

政策研究論文Vol.24 2022 運輸政策研究013

commented, “In Portugal, there are considerably

riding, taking picture prohibition at some specifictourists to Lisbon... we consider that we still do notareas8). Along with strict policies, the local residents

have overtourism problems” (The name, position,

are encouraged to support the tourism industry with

office address of the local experts was omitted as thetheir voluntary activities, for instance, cleaning areas

confidential requirement of the survey). In those cities,

in front of their houses, support tourists.

only educational measures or no specific policies had

The second case, Dubrovnik, Croatia, had the best

been implemented. Local authoritiesʼ viewpoint playedpolicy practices for controlling tourist volume toa vital role in issuing and implementing overtourism

mitigate the negative consequences. The mayor of thepolicies.

city said, “We will lose money in the next two years - a

The second point is the different policy trends inmillion euros maybe by cutting the number of tourists

low- and high-income cities. High-income cities- but in the future, we will gain much more. We

tended to apply stricter policies because they have adeserve to be a top-quality destination29).” The tourist

higher degree of excess tourists. Low-income cities

arrivals from cruise ships were limited to 〜4,000 at

applied solely to educational measures. We found thatany time. This measure was supposed to significantly

economic benefit may be a primary determinant for

reduce the tourist volume of 6,000–10,000 in the peakpolicy consideration. A local tourism officer in a cityseason. There were two reasons for the success ofof a developing country opined, “More crowded

Dubrovnik. First, the city prioritised controlling

tourists provide more economic benefit and job forovertourism over maximising economic benefits.

local. We see it is much positive than the negative

Second, the city took advantage of the special

impacts... ”.

condition of traffic access for policy implementation.

3.3 Best policy practices

This subsection aims to identify the best policy

4──Conclusions and recommendations

practices that may be generalisable to other cities. The

This study analysed 28 cities with a combination of

method is based on policy responses. However,quantitative and qualitative criteria. The qualitative

because the overtourism policies were mostly in thecorrelation between policy strictness and the degree of

early stages of implementation or under discussion,excessive tourists was also presented. We found thefew evaluation reports were available. This study

following: Firstly, an integration of composite indicator

identified the best policy practices from the viewpoint

and viewpoint of local experts on degree of excessiveof reacting to overtourism. We relied on reviewing the

tourist was useful to compare overtourism situations

information obtained from local experts (tourism

and policies. As aforementioned in section 3.1, either amanagers and/or researchers) and limited information

composite indicator or opinion of local expert on

from local government websites, and analysing thedegree of excessive tourist was appropriate to present

correlation between policy strictness and the excessive

overtourism situation for areas where the temporal-

tourist degree.

spatial distribution of tourists is quite even. In the

The first case was Kyoto city. The best policy

cases the distribution of tourists is too unbalanced, forpractices for the early prevention of overtourism

example, tourists concentrate on specific periods or(Figure—8) applied strong policies to a relatively low

locations, the integration of composite indicator andexcess of tourists. Although the composite indicator

the opinion of local experts provide insights for theand local exper t suggested that the degree ofovertourism situation at destinations.

excessive tourist in Kyoto was little in the whole city,

Secondly, the viewpoints of local tourism authorities

the local government has been implementing someplayed a vital role in overtourism policy implementation.

strict policies in integration with tourism dispersion to

In practice, the policy proposed by local tourism

ease the overtourism situation at some of the specificauthorities is dependent on the extent to the critical

tourism spots, such as world heritage sites. Some ofdegree of overtourism the decision-makers perceive.

the strict policies are fine for littering, bicycle drink

The critical degree of overtourism perceived by local

014

運輸政策研究 Vol.24 2022

政策研究論文tourism decision-makers is formed by their perception

inconsistent and statistical information is missing.

of excessive tourist degree, the frequency they observe

Further, most of the policies were in the early stages

inappropriate behaviours, as well as adverse impactsof implementation or under discussion; thus, few

of overtourism on local communities. In section 3.2,

policy evaluation reports were available to support

we demonstrated that the level of policy strictness was

identifying the best policy practices. In addition tohighly correlated with the degree of excessive tourist

local experts, i.e., local tourism officers and tourism

in high-income cities, which was believed that the

researchers, residents and tourists are the other twolevel of policy strictness was a reﬂection of the local

key stakeholders involved in overtourism. The impacts

expertsʼ perception.

of overtourism on residents and tourists should be

Thirdly, most of the high-income cities have been

topics for further research.

i mple me nt i ng p ol ic ie s to s olve t he neg at i ve
consequences of overtourism. The level of policy

Acknowledgement: The authors of this study

strictness was found to be associated with the degree

acknowledge the financial support from Japan Societyof excessive tourist. Reasons were still remained to be

for the Promotion of Science, JSPS KAKENHI Grant

elucidated; however, we assumed that the policies

Number JP19K20577.

were proposed as problem-solving centric rather thanproblem-preventing centric. In other words, policies
were proposed after the problems emerged. The
policies proposed a step before problems appear were
found rarely. The case of Kyoto, which has introduced
policies that are relatively stronger than necessary
compared with the degree of overtourism to prevent
further impacts from overtourism, was considered as agood case for overtourism prevention. This early
implementation policy should be encouraged andapplied to other cities.
Finally, the best policy practices for preventing
overtourism and controlling tourist arrivals wereidentified. Although the evaluation of the policy
i mplement ations at t he cities t hat exper ience
overtourism has not available yet, the best policy
practices were identified based on the action plans of
the local governments. This is one of the objective
limitations of the study. Nevertheless, as the mayor29)
of Dubrovnik city said, it is worth trading the shortterm benefit for more sustainable development in the
future. The appropriate policies should be considered
to tackle overtourism problems.
The analysis in this study was based on quantitative

Appendix. Sources of statistical data

No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28

CitiesDa LatHa Long
Kyoto
Nara
Ghent
Da Nang
Porto
Rome
Reykjavík
Sam SonCat BaLondonBarcelona
VeniceDubrovnik
Macao
Mong Cai
Chiang Mai
LucerneBR Vung Tau
PragueLisbonWarsaw
Yonabaru
Tomigusuku
Miyakojima
Nagocity
Biei-cho

Sources of statistical data
30–33）
34–39）
40–45）
46）
47–50）
51–55）
56–58）
59–63）
64–68,68–71）
72–76）
77–80）
81,82）
83–85）
60,86–89）
90–95）
96,96）
97,98）
99）
100–102）103–106）107）
108–110）
111）
NA
NA
NA
NA
112–115）

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（原稿受付2020年8月7日，受理2021年3月8日）

量的基準と質的基準を組み合わせた都市のオーバーツーリズム政策の分析
オーバーツーリズムは，社会，文化，自然，環境面で悪影響を及ぼしており，世界的な懸念事項となりつつある．そうした負の側面を解決するために，地元自治体等による対策が各地で講じられているものの，オーバーツーリズムと政策との関連性についてはほとんど調査されてない．本研究では，定性的情報に基づいて政策をそのタイプと関与度合いに応じて分類し，さらに定量的な統計情報等も加味した上で，オーバーツーリズムの観点から都市のランク付けを行った．その際，世界中から都市を選定しそのデータを分析することで，政策の厳格さとオーバーツーリズムの度合いの相関関係を分析した．これより，量的指標と定性的指標を組み合わせて用いることで，オーバーツーリズムの度合いを都市間で相対比較するための有用なツールとなりうる可能性があることが示唆された．さらに，オーバーツーリズム問題に対する典型的な対応策にはいくつかのタイプがあり得ることや，それが観光地の開発の方向性の要因となる可能性が示唆された．
キーワード：ツーリズム，質的分析，量的分析，ツーリズム政策018

運輸政策研究 Vol.24 2022

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