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Taming AIRBNB Locally: Analysing Regulations in Amsterdam, Berlin and London

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European cities have responded differently to the growing number of short-term rentals (such as Airbnb) and proposed a variety of regulations, although little is known about their efficiency. This paper contributes to filling the gap by analyzing both policy documents and spatial distributions of Airbnb listings between 2015 and 2020 using Amsterdam, Berlin, and London as case studies. We also compare the results with those of nine other European capitals. Our results show that cities follow highly individualized approaches. According to the strictness of each regulation, we see different intensities in the growth (and drop) of Airbnb listings, the share of multi-hosts, and the share of apartments withdrawn from the regular housing market. There is also a spatial dispersion of listings from the center to the periphery. Our numbers insinuate that dynamically changing regulations force hosts to adapt continuously-which tames an uncontrolled proliferation, but more research is necessary.
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Tijdschrift voor Economische en Sociale Geograe – 2022, DOI:10.1111/tesg.12537, Vol. 0, No. 0, pp. 1–22.
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap.
TAMING AIRBNB LOCALLY: ANALYSING
REGULATIONS IN AMSTERDAM, BERLIN AND
LONDON
MARCUS HÜBSCHER & TILL KALLERT
Institute for Urban Development and Construction Management,Leipzig University, Leipzig, Germany.
E- mail: huebscher@wifa.uni-leipzig.de (Corresponding author)
Received: November 2021; accepted August 2022
ABSTRACT
European cities have responded differently to the growing number of short- term rentals (such as
Airbnb) and proposed a variety of regulations, although little is known about their efficiency. This
paper contributes to filling the gap by analyzing both policy documents and spatial distributions
of Airbnb listings between 2015 and 2020 using Amsterdam, Berlin, and London as case studies.
We also compare the results with those of nine other European capitals. Our results show that
cities follow highly individualized approaches. According to the strictness of each regulation,
we see different intensities in the growth (and drop) of Airbnb listings, the share of multi-
hosts, and the share of apartments withdrawn from the regular housing market. There is also
a spatial dispersion of listings from the center to the periphery. Our numbers insinuate that
dynamically changing regulations force hosts to adapt continuously– which tames an uncontrolled
proliferation, but more research is necessary.
Key words: Short- term rentals; Airbnb; Regulation; Amsterdam; Berlin; London
INTRODUCTION
Short- term rentals (STRs), such as those ar-
ranged through Airbnb, have revolutionized
the way we travel. Since its foundation, Airbnb
was accompanied by the apparently roman-
tic narrative of ‘authentic accommodations’
(Nieuwland & van Melik2018, p. 812) and shar-
ing your home with others. Today, little is left
of this sustainable concept in STRs that might
have prevailed one decade ago (Oskam2019).
Airbnb, the largest of these platforms, disrupts
not only the tourism industry (Geissinger et al.
2020), but also everyday life in neighbour-
hoods (Vives- Miró & Rullan2017).
The massive proliferation of STRs world-
wide contributes to phenomena such as gen-
trification (Wachsmuth & Weisler 2018) and
the commodification of housing (Gutiérrez
& Domènech2020). This proliferation is also
interpreted as one consequence of the ‘regu-
latory failure’ in the neoliberal city (Brenner
et al.2010, p. 218). Hence, it comes as no sur-
prise that a growing number of cities intend to
regulate STRs, despite the observed liberaliza-
tion of housing markets fuelled by many states
(Cocola- Gant2016, p. 7). However, the impacts
of these regulations often do not meet the ex-
pectations (Guttentag 2015, pp. 1202– 1203;
Espinosa2016, pp. 607– 609). In addition, reg-
ulations on STRs do not receive the same scien-
tific interest compared to other aspects related
to STRs (Guttentag2019, p. 819), although in
recent years, an increasing number of contri-
butions is observed (see for example Von Briel
& Dolnicar 2020; Chen et al.2021).
COVID- 19 might have attenuated some of
the immediate impacts of Airbnb in cities, as
the pandemic has ‘disrupted the disruptor’
(Dolnicar & Zare 2020, p. 1) due to travel
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MARCUS HÜBSCHER & TILL KALLERT2
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap.
restrictions and lockdown protocols. There
is the hope that perceiving this current crisis
as an opportunity might shift housing units
back to the regular housing market, but it is
too early to confirm and there is no empirical
evidence (Armas- Díaz et al.2021a, p. 13).
Hence, further research on regulating STRs
is necessary. In this paper, we pursue two ob-
jectives. First, we explore the regulatory ap-
proaches of 12 European cities (see Table1).
We chose these cities to broaden the systemati-
zation on regulation proposed by Nieuwland
and Van Melik (2018), who compared five
European cities with six American cities based
on data until 2017. Our study updates these
findings and develops the comparison further
within the European context. Apart from these
five European cases, we added seven cities to
achieve a broad range of different urban set-
tings (with regard to nation- state, population
numbers, socio- economic parameters, etc., see
Table1). Additionally, we selected cities with
different regulatory approaches, which was
ensured by conducting a preliminary analysis.
Half of these cities form part of a network that
requested the European Commission to set up a
‘new legislative framework’ (Eurocities2020, p.
2) that makes STR platforms ‘liable for fulfilling
their obligations’ (ibid.). We interpret this call
as a certain willingness of these cities to regulate.
Both for the preliminary and final analyses, we
collected press releases and policy documents
(see Section3, methodological framework).
Second, we investigate the impacts of
these regulations by analysing the geogra-
phies of Airbnb listings (as the largest STR
platform) from 2015 to 2020 in Amsterdam,
Berlin and London. We retrieved data from
Inside Airbnb,1 a web- scraping platform, and
analysed the spatial and structural develop-
ment of Airbnb listings. Amsterdam, Berlin
and London represent three out of the top
seven European cities with the highest num-
bers of Airbnb listings in 2020, and half of all
listings within this group (Statista2021a). The
selection of these cities was based on the hy-
pothesis that they all apply very different cop-
ing strategies (Nieuwland & Van Melik2018, p.
816). In addition, data availability for each of
the three cities is appropriate.
Inspired by comparative urban research,
we seek to identify similarities and differences
(Nijman2007) in how the different cities regu-
late STRs. Our comparison of these cities refers
to ‘most different systems’ (Pickvance2001, p.
14; with regard to how they regulate STRs). By
applying such a ‘variation- finding approach’
(Aguilera et al. 2019, p. 1694), we take up
the existing diversity in coping strategies in
(European) cities and the small amount of
‘comparative research to explain this diversity’
(Aguilera et al.2019, p. 1689). Hence, compar-
ing regulations in 12 cities will (i) contribute
to a further systemizing of existing regulatory
approaches to STRs— a field, that is regarded
as unsystematic (Vinogradov et al.2020, p. 2).
On that basis, exploring the spatiotemporal
characteristics of Airbnb listings in three se-
lected case studies helps (ii) to understand the
impacts of these regulations.
This paper is structured as follows. Section2
provides an overview of the existing research
about regulating STRs. Section 3 proposes
the methods to achieve the research objec-
tives. Section 4 presents the results and puts
them into context. The last section draws a
conclusion.
PLATFORM CAPITALISM: TAMING OR
LETTING?
Why regulate? – Since the global financial cri-
sis of 2008 (Srnicek2017), platform capitalism
has penetrated different areas of the economic
system. Platform capitalism refers to ‘interme-
diaries (companies) acting as matchmakers
in multisided platforms’ (Papadimitropou-
los2021, p. 249). The fact that the regulatory
frameworks in many cities were not prepared
for these new phenomena helped platforms
to have such success in the first place (Mc-
Namara 2015). As for STRs, it was through
American jurisprudence that these regulations
started to be analysed (Gottlieb 2013). Since
then, the number of studies on regulations has
increased considerably, as Guttentag’s litera-
ture review reveals(2019).
Differentiating between the motivations to
regulate is a first step to approach the issue.
Nieuwland and Van Melik point out that
‘most cities feel the urge […] to balance the
interests of visitors and local residents/busi-
nesses’(2018, p. 814). This implies an aim to
TAMING AIRBNB LOCALLY 3
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap.
Table 1. Context of case cities. Own elaboration.
Amsterdam Berlin London Athens Barcelona Copenhagen
City Population
(2020)a872,922 3,669,491 8,866,541
(2018)
664,046 (2014) 1,636,762 626,508 (2019)
Total number of
housing unitsb441,467 1,968,315 3,592,000 427,825 (2011) 682,1280 297,469 (2012)
Percentage of home-
ownership in %c31 15 49 68 (2013) 72 29
Percentage of
privately rented
housing in %c
29 78 29 35 26 52
Average rent per
square meter in €
(2020)d
18.7 7.3 20.1 8.86 19.6 19
Average monthly net
salary (after tax)
in €e
3092 2855 3539 801 1578 3266
Rate of unemploy-
ment in %f4 6 5 21 (2011) 9 6 (2012)
Number of tourists
(bednights) in
mio. 2019g
18 34 85 5.3 (2011) 20 9.0 (2018)
Number of Airbnb
listings (2020)h18,546 20,255 77,324 9430 19,681 8756
participation in the
EU protest letteriYes Yes Yes Yes Yes No
Dublin Lisbon Madrid Paris Rome Vienna
City Population
(2020)a544,107 (2018) 506,654 (2019) 3,223,334
(2018)
2,240,621 2,808,293 1,944,910 (2021)
Total number of
housing unitsb239,605 (2011) 323,915 1,480,099 1,312,426 1,137,391
(2011)
918,255
Percentage of home-
ownership in %c63 75 73 33 73 23
(Continues)
MARCUS HÜBSCHER & TILL KALLERT4
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
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Dublin Lisbon Madrid Paris Rome Vienna
Percentage of
privately rented
housing in %c
24 23 20 43.9 24 17
Average rent per
square meter in €
(2020)d
13.2 10.8 18.1 27.8 13.4 9.8
Average monthly net
salary (after tax)
in €e
2942 1007 1633 2912 1478 2355
Rate of unemploy-
ment in %f16 (2011) 12 (2011) 11 13 (2017) 11 (2018) 12 (2014)
Number of tourists
(bednights) in
mio. 2019g
15 14 21 52 29 19
Number of Airbnb
listings (2020)h7923 11,636 20,411 60,031 28,246 12,084
Participation in the
EU protest letteriNo No No Yes No Yes
aEurostat(2021a); UN Data(2021).
bEurostat(2021b).
cKnight Frank(2018); European Commission(2021); København Kommune(2021).
dDeloitte Czech Republic(2019).
eNumbeo(2021).
fEurostat(2021c).
gStatista(2021b).
hStatista(2021a); InsideAirbnb(2021); these are total numbers, which means that inactive listings are not excluded Nul20(2021); Athens Social Atlas (2015); Stadt
Wien(2021a).
iEurocities(2020).
Table 1. (Continued)
TAMING AIRBNB LOCALLY 5
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
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mitigate the various impacts on neighbour-
hoods, considering that, for example, Airbnb
is associated with rising rents (Sheppard &
Udell2016) and community conflicts (Gurran
& Phibbs 2017, p. 85). Apart from that, the
hotel industry demands to regulate platforms
such as Airbnb to enable a level playing field
(Mody et al.2017, p. 2378).
Adding complexity to the problem
Regulating STRs is an objective that is not
only complex, but also conflictive, and
the existing measures often do not work as
expected (Guttentag 2015, pp. 1202– 1203;
Espinosa2016, pp. 607– 609). Hence, ‘there
is no evidence upon which to draft policies’
(Quattrone et al.2016, p. 1385). This is due
to a set of aspects that complexifies the aim
of regulating STRs. Scanning through the
literature, we identified at least four areas in
which to cluster these difficulties, namely (i)
legal, (ii) economic, (iii) technical and (iv)
political aspects.
First, from a legal perspective, complexity
is added due to the different levels of juris-
diction that are involved in the legislative pro-
cedure. Although impacts of STRs are seen
locally, there might be a regional, national or
even supra- national jurisdiction with different
objectives (Joppe 2019, p. 257). Apart from
that, there is a strong discussion about the fine
line between regulation and the reduction in
personal rights (e.g. the right of ownership),
which makes the regulations vulnerable in law-
suits (Jefferson- Jones2015, p. 564).
Second, considering the economic point
of view, STRs are doubtlessly a driver of urban
development, and contribute to the local econ-
omy (Quattrone et al.2016, p. 1392), such as
those stakeholders providing ‘rent, food and
beverages, transportation’ (Gold 2019, p.
1587). Consequently, policymakers try not to
cut- off the positive effects, such as tax revenues
(Lee2016, pp. 244– 245).
This leads to the political dimension. As dif-
ferent stakeholders profit from STRs, there is
a growing number of lobby groups ‘mobilised
and coordinated to advocate for favourable
regulation’ (Yates2021, p. 18), exemplified
by Airbnb’s Home Sharing Clubs (ibid.).
These lobby groups successfully influence
the legislative procedure on the local and na-
tional levels, as has been shown in the case
of the United States (Guttentag 2015, pp.
1201– 1202).
Lastly, technical issues remain that make
efficient regulation of sharing platforms dif-
ficult. This is because decisions about regula-
tions ‘must be taken in the state of imperfect
information’ (Pawlicz 2019, p. 398), because
platforms such as Airbnb do not provide de-
tailed data. The existing doubts about the
efficiency of regulations go back to the uncer-
tainty over who is actually going to be affected
(private vs professionalized hosts; Armas- Díaz
et al.2021a, p. 6).
How to regulate? – There is a large
variety of approaches to regulate STRs.
Nieuwland and Van Melik classify these
regulatory frameworks by specifying their
strictness. They differentiate between ‘full
prohibition, the laissez- faire approach,
and the limitation’ (2018, p. 814). Others
even see four categories: liberal, moderate,
moderate- collaborative and protective
(Von Briel & Dolnicar 2020, p. 3). On
the contrary, Jefferson- Jones (2015, p.
564) focuses on labelling the measures
and attaching categories to them. The
author categorizes quantitative restrictions
(caps), proximity restrictions, operational
restrictions, licensing requirements and full
prohibition. Table2 summarizes some of the
most observed instruments to regulate STRs,
dividing them into quantitative, spatial and
qualitative measures.
Based on the above- mentioned multi-
ple approaches, our first aim is to explore,
how the 12 cities selected regulate STRs.
Although some authors confirm the success
of these regulations (Adamiak 2019, p. 5;
Guttentag 2019, p. 19), others observe the
opposite and question their effectiveness
(Von Briel & Dolnicar2020, p. 5). Hence, the
second aim of this paper is to evaluate the im-
pact of these regulations. Here, we put the
focus on Airbnb as the largest STR platform.
We do so by means of spatial and temporal
comparisons considering the effects on the
supply side of the Airbnb market. We will
focus on Amsterdam, Berlin and London
MARCUS HÜBSCHER & TILL KALLERT6
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Table 2. Selection of typical instruments, and their objectives and limitations. Own elaboration.
Instruments Objectives Limitations Sources
Complete ban Eliminate Airbnb- listings from a
city or a certain neighbourhood
Loss of positive effects of STR,
taxes etc.
Nieuwland and Van Melik (2018)
p. 816; Jefferson- Jones(2015, p.
564)
Quantitative regulations
Limit the number of days or max.
Guest numbers or max. Number
of rentings
Protect the availability of housing
units for long- term rentals
Monitoring necessary, but costly Guttentag(2015, p 0.9); Oskam and
Boswijk(2016, p. 30); Frenken
and Schor (2019, p. 131)
Limit the amount of entire
dwellings, but permit individual
bedroom
Protect the availability of housing
units for long- term rentals
Monitoring necessary, but costly Martínez Nadal(2019, p. 43);
Oskam and Boswijk(2016, p. 30);
Frenken and Schor (2019, p. 131)
Taxation Participate from the benefits;
reduce the number of listings;
level playing field in hospitality
industry
No precise instrument to manage
to impact of STR
Guttentag(2015, p. 10); Kagermeier
et al.(2015, p. 15)
Spatial restrictions
Limit the number of STRs per
multi- family house; permission of
owner associations
Find balance, integrate local
owners
Monitoring necessary, but costly Martínez Nadal(2019, p. 44);
Frenken and Schor (2019, p. 131)
Relative proportion between regu-
lar flats and Airbnb listings in a
neighbourhood
Contributes to the legal differ-
entiation between private and
commercial offers
Monitoring necessary, but costly Jefferson- Jones(2015, p. 565);
Frenken and Schor (2019, p. 131)
Spatial distance between two
Airbnb listings
Might prevent additional entrants
into the Airbnb market
Monitoring necessary, but costly Jefferson- Jones(2015, p. 565)
Qualitative restrictions
Qualify the listings, e.g. hygiene
and security standards
Customer protection, level playing
field in hospitality industry
Monitoring necessary, but costly Jefferson- Jones(2015, p. 565);
Kagermeier et al.(2015, p. 15)
Licensings/registration numbers Increase the cost for the pro-
cess; monitoring for city
administrations
Time and effort for administration Martínez Nadal(2019, p. 1);
Jefferson- Jones(2015, p. 564)
TAMING AIRBNB LOCALLY 7
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as case studies because they have all expe-
rienced the negative impacts of STRs (Von
Briel & Dolnicar2020, p. 1). However, they
still represent different regulatory regimes,
which means they address STRs differently
from a law- giving perspective (Nieuwland &
Van Melik2018, p. 817).
Neglecting other factors that influence the
proliferation of Airbnb listings, we suppose
that in cities where regulations have been
tightened, we will either see a decreasing
number of listings or at least a slower increase
compared to other cities. We also expect spa-
tial bans to increase the number of listings
in surrounding districts, even if other regu-
lations affect the whole city (Valentin2021,
p. 158). In addition, quantitative restrictions
(such as limiting the amount of offers per
host, see Table2) are expected to increase
the diversification of the host structure (more
hosts with less listings).
METHODOLOGICAL FRAMEWORK
Qualitative analysis – First, we conduct-
ed a document analysis to review existing
regulations of STRs systematically, and we
interpreted the material with a qualitative-
interpretative approach (Mayring 2016).
Due to their comparatively high validity, leg-
islative documents and press releases at the
federal, state and local levels were used (see
Table3). The search was carried out via the
Google search engine and the homepages of
the respective institutions. Frequently occur-
ring search terms were ‘Amsterdam/Berlin/
London,’ ‘short- term rental/Airbnb’ and
‘law/regulation/restrictions.’ We searched in
English and German. Documents that were
not in these languages were translated via the
DeepL translation website. Although there
may be discrepancies in content due to trans-
lation, we argue that the advantages of assess-
ing a wide range of European cities outweigh
the disadvantages.
We also examined the digital reporting from
national to local newspapers via the Google
News service, including documents from 2009
to 2021. This helped to understand the local
situation and possible development tendencies
within each city.
To compare the regulatory measures, we
propose the following set of indicators, which
is based on the systematization and references
presented in Table2: type of regulation (ban/
restriction), taxation, level of regulation (state/
province/municipality), maximum fine, regis-
tration/permit requirements and bearer of
legal responsibility (platform/host/guest). In
addition, we differentiated regulations for pri-
vate rooms, primary residences and secondary
residences.
Quantitative analysis – Second, we aimed
to evaluate the impacts of these regulations
on the geography of STRs in Amsterdam,
Berlin and London, focusing on Airbnb
listings. We did so by using open access data
from municipal databases, publications of
the tourism and real estate industry, and the
platform Inside Airbnb. The analyses were
supported by a QGIS geoinformation system
(QGIS2021).
In March 2021, we retrieved city- specific
datasets (Amsterdam, Berlin and London) for
the period 2015– 2020 for the month of August
in each year. With regard to the latest dataset
from August 2020, one has to question the va-
lidity due to the impacts of COVID- 19. Hence,
we will show how the Airbnb market changed
until 2020, and which trends existed prior to
COVID- 19, but we will refer to the year 2019
where adequate.
We examined whether municipal changes
occurred in the structure of Airbnb listings
(such as price, hosts, type of apartment, av-
erage length of stay, etc.), but also whether
possible developments could be attributed to
the regulatory interventions. We define ‘pro-
fessional hosts’ as those stakeholders ‘who use
one or more apartments or homes only for
rent’ (Adamiak2019, p. 3).2 Following Smigiel
et al.(2020), we then excluded inactive listings,
that is, those that did not receive a rating in
the previous year or were not offered for the
following year.
Since we could not extract full information
on the professionalization of platform users
from the raw data, we followed the calculations
of Wachsmuth and Weisler(2018). According
to their approach, a residential space that is
rented via STR platforms for a maximum of
MARCUS HÜBSCHER & TILL KALLERT8
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Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap.
Table 3. Regulations in selected case study cities. Own elaboration.
Amsterdam Berlin London Barcelona Vienna Madrid
Since 2020 2018 2017 2020 2019 2019
Type of regulation
(ban/restriction)
Partial ban +
restriction
Restriction Restriction Partial ban +
Restriction
Restriction Restriction
Taxation Yes Yes Yes Yes Yes Yes
Level of regulation
(city/country/state)
City City City City City City
Liability (Airbnb/
host/guest)
Host Host Host Host, Airbnb Host Host
Maximum fine in Euro 20,750 500,000 20,000 600,000 21,000 *
Registration Yes Yes No Yes No Yes
Measures in detail:
Listing of private
rooms
Yes Yes Yes Yes, but 1 year
suspended
Yes, if owner of
the apartment
Yes
Permission for private
rooms
Yes no, if <50%
of the
apartment
No Yes no, if primary
residence yes,
if secondary
residence
No
Daily limit for listing
private rooms
No No No, if owner is in the
apartment
No No 90 days
Apartment (main
residence) listing
Yes Yes Yes Yes Yes, if not in
residential
zone, no rental
apartment, no
community
building, no
objection of
other owner in
house
yes
Permission for main
residence
Yes Yes Only from 90 days of
renting
Yes, incl. Inspection,
approval,
cataloguing
No From 90 days
with licence
Daily limit for listing of
main residence
30 days No 90 days No No 90 days, after-
wards licence
(Continues)
TAMING AIRBNB LOCALLY 9
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Amsterdam Berlin London Barcelona Vienna Madrid
Apartment listing (sec-
ondary residence)
Yes Yes Yes Yes Yes, if not in
residential
zone, no rental
apartment, no
community
building, no
objection of
other owner in
house
Yes
Approval of secondary
residence
Yes Yes Only from 90 days
rental
Yes No From 90 days
with licence
Daily limit for second
home
30 days 90 days 90 days No No 90 days, after-
wards licence
Sources Rekenkamer
Metropool
Amsterdam
(2019); City
of Amsterdam
(2022)
Stadt Berlin
(2018); Land
Berlin(2013)
The Houses of
Parliament
(2015); Ferreri /
Sanyal(2018)
O’Sullivan(2021) Stadt Wien
(2021b)
Rodriguez-
Pina(2019)
Rome Copenhagen Athens Lisbon Paris Dublin
Since 2020 2018 2017 2016 2018 2019
Type of regulation
(ban/restriction)
Restriction Restriction Restriction Partial ban +
restriction
Restriction Restriction
Taxation Yes Yes Yes Yes Yes Yes
Level of regulation
(city/country/state)
Country, city Country, city Country City Country, city Country, city
Liability (Airbnb/
host/guest)
Host Host Host Host Airbnb, host Host
Maximum fine in Euro * * 30,000 40,000 12,500 Primary
residence;
50,000 second-
ary residence
10,000
Registration No No Yes Yes Yes Yes
Table 3. (Continued)
(Continues)
MARCUS HÜBSCHER & TILL KALLERT10
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Rome Copenhagen Athens Lisbon Paris Dublin
Measures in detail:
Listing of private
rooms
Yes Yes Yes Yes Yes Yes
Permission for private
rooms
No No No Ye s No No, if owner in
apartment
Daily limit for listing
private rooms
No No No No No No
Apartment (main
residence) listing
Yes Yes Yes Yes Yes Yes
Permission for main
residence
No No No Ye s No No, only from
90 days
Daily limit for listing
of main residence
No 70 days No No 120 days 90 days
Apartment listing (sec-
ondary residence)
Yes Yes Yes Yes Yes, if >1 year Yes
Approval of secondary
residence
No No No Ye s Yes Yes
Daily limit for second
home
No 70 days No No No No
Sources Airbnb
Helpcenter
(2021)
Airbnb(2021) Ernst &
Young(2020)
The Portugal
News(2018)
Paris(2020) Irish Statute
Book(2019)
*Missing information for the indicators.
Table 3. (Continued)
TAMING AIRBNB LOCALLY 11
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap.
60 days per year and is available on such plat-
forms for a maximum of 120 days per year, can
still be regarded as primary residence with a
regular residential use. While city administra-
tions propose a different maximum number of
days, we suppose that those cities with a stricter
regulation (e.g. 30- day rule in Amsterdam;
Rekenkamer Metropol Amsterdam2019) will
have more success in decreasing the share of
apartments that are exclusively rented out on
STR platforms such as Airbnb, compared to
less strict regulations (e.g. in London; Ferreri
and Sanyal2018).
Regarding the annual occupancy rate
of apartments withdrawn from the housing
market, we follow the assumptions made
by Smigiel et al. (2020, p. 157) and Seidl et
al. (2017). The authors assume that 50 per
cent of guests provide a rating and that
there is an average length of stay of 4 days.
They base their calculations on these two
parameters to estimate the occupancy rate.
Concludingly, such assumptions can only be
valid to a limited extent.
The significance of our study is also lim-
ited as regulations are not the only factor
influencing the Airbnb market. Tourist de-
mands and population development (hous-
ing as competing function) play a significant
role, too. Here, we argue that putting the
focus on regulations is still a relevant piece
in the puzzle to understand the regulations’
effectiveness.
THE REGULATORY APPROACH AS A
SUCCESS FACTOR IN DEALING WITH
AIRBNB
Regulatory approaches in Amsterdam, Ber-
lin, London and nine other cities – Analysing
regulatory approaches in our 12 cities reveals
that each municipality has developed its own
approach for dealing with STRs (Table3),
there is no one- size- fits- all solution (Gurran &
Phibbs2017, pp. 90– 91).
Even so, overarching patterns are certainly
noticeable. For example, to legally differen-
tiate commercial and private offerings, half
of the reviewed municipalities apply quantita-
tive restrictions on STRs. It is also instructive
that no city enforces a complete ban on STRs.
This suggests that despite significant negative
effects, the municipalities studied do not
want to forgo the undeniably high economic
benefits of STRs (Jefferson- Jones 2015, p.
560).
Another strategy is to impose spatial restric-
tions (Vienna, Dublin, Madrid). This can coun-
teract the STR pressure on central residential
neighbourhoods, as highlighted by Quattrone
et al.(2016, p. 1392), without depriving less af-
fected areas of benefits.
At the time of Airbnb’s founding in 2008,
Amsterdam (and Berlin) had legislation that
did not explicitly include the business prac-
tices of digital STR platforms. Von Briel and
Dolnicar (2020, p. 2) refer to this form as
‘gap’ regulation. Amsterdam, in particular,
has gone from being ‘Europe’s first shar-
ing city’ (shareNL2015) to one of the most
restrictive municipalities in Europe in just
a few years (Figure1). In 2014, there was a
temporary stop to approve new STRs and a
municipal task force to identify illegal list-
ings was established (Dredge et al. 2016, p.
24). In the following years, the regulations
have been tightened. From 2016 on, primary
and secondary residences were allowed to be
rented out for a maximum of 60 days per year,
which was reduced to 30 days in 2018 (Dredge
et al. 2016, p. 24; Rekenkamer Metropol
Amsterdam2019). Furthermore, the rental of
an entire apartment, but also a private room,
requires an official permit. Concerning the
rental of private rooms, only a limited num-
ber of offers will be allowed per district. In ad-
dition, the rental of entire residential units in
the particularly affected Old Town districts of
Burgwallen- Oude Zijde, Burgwallen- Nieuwe
Zijde and Grachtengordel- Zuid was banned in
July 2020. However, a court ordered to lift the
ban in March 2021 (City of Amsterdam2021).
As Table3 illustrates, Amsterdam’s jurisdic-
tion is strict, particularly compared to other
European metropolises. Although differences
in the content of the legislation are evident, the
ban- like measures in Amsterdam, Barcelona
and Madrid serve the same overarching pur-
pose, namely, to alleviate tourist pressure on
particular neighbourhoods (Nieuwland & Van
Melik2018, p. 5).
There are divergent opinions about how to in-
terpret Berlin’s so- called ‘Law on the Prohibition
MARCUS HÜBSCHER & TILL KALLERT12
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap.
of the Misappropriation of Residential Space’,
which was passed by the city’s Senate in 2014. Von
Briel and Dolnicar(2020, p. 3) and Apur(2018,
p. 11) speak of strict measures that have been
tightened over the years, while Busch(2019, p.
39) sees a certain liberalization due to 2018’s
novel. Cassell and Deutsch regard Berlin’s reg-
ulations as ‘weak but [they] were improved with
the latest amendment’(2020, p. 12).
Key element of 2014’s law is the necessity
to obtain a permit to do short- term renting.
There was a transition period saying that
until May 2016, existing listings were not
affected (Duso et al. 2020, p. 6). In April
2018, this law has been updated. Now, a reg-
istration is mandatory. Hosts are allowed to
rent out their (primary) residence under cer-
tain circumstances, for example, if they are
absent (Duso et al. 2020, p. 6). Apart from
that, it is also allowed to rent an apartment
as STR if the rented parts are less than half
of the total space, and in this case no permit
was required, but still a registration number
(Busch 2019, p. 39). Secondary residences
can be used as STR for less than 90 days per
year (Duso et al.2020, p. 7).
We regard the regulation’s evolution in
Berlin as a certain refinement, but also in-
terpret the new rules and fines in case of
violation (max. of 500.000 euros) as strict
(Busch 2019, p. 39; compared to other cit-
ies in Table3). This is also because the pub-
lic authorities founded a task force with 30
employees controlling local STRs (Senate
Department for Urban Development,
Building and Housing 2016). These mea-
sures are intended to reduce the influence of
purely commercial operators on the housing
market and hence protect affordable hous-
ing. Vienna and Dublin follow a similar goal.
As we retrieved data in 2015 and compared it
to 2019 and 2020, we expect to see the effect
of Berlin’s regulation in our data (such as a
slower growth of listings compared to other
cities). At the same time, the observed dissen-
sions within the academic discussion about
Berlin’s regulations make us expect rather
ambiguous empirical results, too.
Compared to Amsterdam and Berlin,
London has by far the most liberal jurisdiction.
London’s city administration started with a
comparatively strict and ‘protective’ (Von Briel
& Dolnicar 2020, p. 4) legislation shortly after
STR platforms such as Airbnb launched their
activity. After that, further deregulation and
cooperation with the platform were observed,
with the objective to promote the sharing
economy in the city (Ferreri & Sanyal2018, p.
3362).
Implementing the nationwide
Deregulation Act in 2015, the Greater
London Authority pushed for increased self-
regulation by the platform while liberaliz-
ing its use. Critics such as Interian(2016, p.
159) doubt the effectiveness, while others are
Figure 1. Evolution of restrictions (To assess this
evolution, we compared the restrictions discussed by
Nieuwland and Van Melik[2018] with the current status
quo [Table3]) in European cities in 2021 compared to
Nieuwland and Van Melik(2018).
TAMING AIRBNB LOCALLY 13
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap.
optimistic about the potentially high bene-
fits for both sides (Li & Biljecki2019, p. 80).
On that basis, Von Briel and Dolnicar define
London as ‘end- run city’ (2020, p. 3), and
regulations in London did not change funda-
mentally since then (Figure1).
The Deregulation Act includes a quantita-
tive restriction, and determines that below an
annual maximum rental period of 90 days, no
permission to change the use is needed (The
Houses of Parliament 2015, p. 37; London
Government 2021). The Airbnb platform au-
tomatically limits the offering of entire homes
in London to these 90 days, if the host does
not present a special permit (Airbnb 2022).
Private rooms can be rented out for an un-
limited period, provided that landlords are
present on the residential property (London
Government 2021). In addition, the Greater
London Authority cooperates closely with
Airbnb, as one of the STR platforms, using
an agreement (Woolf 2016). The company
itself agreed to control the abidance by the
laws (Government Digital Service2022), such
as the above- mentioned maximum rental pe-
riod. The intention here is to maintain qual-
ity of living for residents. Copenhagen, Rome,
Athens and to some extent Paris fall into the
same category. Based on the liberal approach
in London, we do not expect the number of
Airbnb listings to decrease. In addition, we can
even expect a further professionalization of
the market (shown, e.g., by an increasing share
of multi- hosts), which is regarded as an intrin-
sic process on the Airbnb market (Armas- Díaz
et al.2021b, p. 76).
Airbnb versus regulation: analysis of the
impact on municipalities – As a consequence
of the pandemic, the number of Airbnb
listings in the three case studies dropped 31
per cent both in Amsterdam and London,
and 23 per cent in Berlin between the Augusts
of 2019 and 2020. Before the pandemic, the
mitigating influence of regulation is most
prominent in Berlin. Here, the total number
of Airbnb listings grew only about 16 per cent
between 2015 and 2019, while the numbers
in Amsterdam (68%) and particularly in
London (91%) skyrocketed.
With regard to the supply structure, these
uneven trajectories between the three cities
continue. Amsterdam is the only city where the
share of multi- hosts (with more than one entry)
decreased continuously (Figure2). In Berlin,
the commercial influence decreased until 2017
but has increased since then, even though the
total number of listings decreased from 2015 to
2020. These results confirm the heterogeneous
interpretations of Berlin’s regulations. On the
one hand, this growing professionalism in the
host structure can be traced back to 2018’s up-
date of the regulation, where multi- hosting is
not banned per se. On the other hand, there is
a shift of 4000 STRs back to the regular hous-
ing market by the end of 2017 (Apur2018, p.
13), which is also displayed by the relatively
small growth of listings until 2019.
In London, our calculations show the most
dominant presence of multi- hosts. Their influ-
ence has grown notably: In 2020, hosts with
more than one offer held 49 per cent of all list-
ings, in 2015 it was only 41 per cent (Figure2).
Figure 2. Share of listings according to host structure (number of listings per host). Own elaboration based on data of
Inside Airbnb(2021).
MARCUS HÜBSCHER & TILL KALLERT14
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap.
Hence, in Berlin and London, these numbers
rather show the respective regulations’ weak-
nesses and support the argument that the
current regulations do not impede a further
professionalization of the host structure. This
is first because large operators know better how
to deal with rules and legislation (Smigiel2020,
p. 256; Anselmi2021, p. 4). Second, they also
learn how to circumvent certain regulations
(Chen et al.2021, p. 4).
The majority of Airbnb listings lie in central
districts, which is consistent with the findings
from other studies (Benitez- Aurioles 2018, p.
239; Hübscher et al.2020, p. 196). Table4 pro-
vides more insights into the development in
central and more peripheral districts in all three
cities for the years 2015– 2019. Here, we chose the
pre- COVID- 19 setting for better comparability.
Between 2019 and 2020, we only detect very small
structural changes (max. change of 1.5 p.p. [per-
centage points] in the share of listings per district
compared to the total Airbnb market).
Until 2019, all three cities show a relative
(rather than a total) decline of listings in those
urban districts that had the most listings in
2015 (mostly central districts), although we de-
tect different intensities (Table4). At the same
time, several other neighbourhoods recorded
substantial growth, particularly those in the
peripheries.
Among the central districts that in 2015
already had the highest shares of listings,
those located in London showed the strongest
growth (e.g. Tower Hamlets 127.5%). Contrary
to that, central districts in Amsterdam and
Berlin grew at a moderate (Amsterdam
Centrum West 19.9%) or even slow pace
(Berlin Friedrichshain- Kreuzberg 1.4%).
Figure3 exemplifies this shift in Amsterdam,
indicated by the changing distribution of hot
spots. The maps show a reduction of the den-
sity of Airbnb listings central districts, and a
clear growth in surrounding areas such as De
Pijp- Rivierenbuurt and Oud- Oost, which we in-
terpret as a ‘spillover’ effect due to the spatial
ban, as described in other cases (Valentin2021,
p. 154). However, these results must be inter-
preted carefully, as 2020’s data are affected due
to the global pandemic.
These results are more ambiguous than
we initially expected (Section 2). Comparing
Amsterdam to London, one might confirm
the effect of Amsterdam’s (temporary) spatial
ban. Contrary to that, the example of Berlin
Table 4. The development of Airbnb listings in selected central and more peripheral districts. Own elaboration based on
Inside Airbnb(2021).
Share on the total Airbnb- market
(%) Total number of Airbnb listings
2015 2019 Growth (p.p*) 2015 2019 Growth (%)
Amsterdam
Centrum West 17.4 12.4 −5.0 1281 1536 19.9
Centrum Oost 11.2 8.9 −2.3 830 1102 32.8
De Baarsjes— Oud- West 14.8 16.9 2.1 1092 2085 90.9
De Pijp— Rivierenbuurt 10.4 12.0 1.6 770 1489 93.4
Berlin
Mitte 21.4 22.2 0.8 2511 2929 16.6
Friedrichshain- Kreuzberg 26.4 23.0 −3.4 3100 3143 1.4
Neukölln 15.0 13.5 −1.5 1768 1848 4.5
Lichtenberg 1.7 3.2 1.5 199 439 120.6
Treptow 1.7 2.8 1.1 203 382 88.2
London
Tower Hamlets 12.4 9.6 −2.8 2069 4708 127.5
Hackney 11.5 6.5 −5.0 1908 3184 66.9
Islington 8.4 5.9 −2.5 1404 2899 106.5
Brent 0.9 3.1 2.2 149 1498 905.4
Barnet 0.3 1.7 1.4 55 849 1443.6
*Percentage points.
TAMING AIRBNB LOCALLY 15
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap.
indicates that also a combination of other
factors (such as saturation effects and other,
city- wide restrictions) influence the spatial dis-
tribution. Less surprising is the case of London,
which shows the highest overall growth rates
both in the centre and the peripheries and the
most liberal regulation among the three cities.
Apart from host structures and spatial pat-
terns, the number of housing units removed
from the housing market due to Airbnb is a
further aspect to evaluate current regulations.
According to Seidl et al.(2017), a housing unit
that is available on Airbnb at least 120 days and
occupied at least 60 days is regarded as ‘re-
moved’ from the regular housing market.
In all three cities, the percentage of hous-
ing units removed from the housing market
(compared to the total housing market) has
declined in recent years, even before the pan-
demic (see Figure4). In addition, the share
Figure 3. Hotspot maps in Amsterdam. Own elaboration based on Inside Airbnb(2021) and Open Street Map and
Geofabrik GmbH(2020).
Figure 4. Share of housing units that were available on Airbnb at least 120 days and occupied at least 60 days (Seidl
et al.2017), compared to the regular housing market (2015– 2020, August). Own elaboration based on data of Inside
Airbnb(2021).
MARCUS HÜBSCHER & TILL KALLERT16
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap.
of such units among all Airbnb listings has de-
creased, too (Figure5), which we interpret as
a certain decommercialization of the Airbnb
market. Still, there are significant differences.
Amsterdam, which had by far the highest shares
of housing units withdrawn from the housing
market due to Airbnb in 2015 (0.54%) saw the
most visible decline until 2020 (0.068%).3 At
the same time, the share of such units on the
total Airbnb market also decreased strongest in
Amsterdam, namely from 39 per cent in 2015
to only 5 per cent in 2020. We particularly ex-
pect the stricter quantitative regulations (such
as the 30- day rule in Amsterdam, compared
to the 90- day rule in Berlin, and no strict cap
in London, see Table3) to play a crucial role
for both drops in Figures4 and 5. These drops
were certainly reinforced by the increasing
strictness of the regulation in Amsterdam (60-
day rule from 2016 on; 30- day rule from 2018
on; Dredge et al. 2016, p. 24; Rekenkamer
Metropool Amsterdam2019).
In Berlin, the share of housing units with-
drawn from the regular housing market
decreased since 2015. It thus meets one of
the regulations’ original objectives, namely
to protect the local housing market (Land
Berlin 2013), although the impact is merely
slight.
In London, the picture is not as clear, be-
cause the share of housing units withdrawn
from the regular housing market increased be-
tween 2015 and 2019, and decreased in 2020,
which might be an effect of the pandemic.
CONCLUSION
Several of our 12 case cities represent what
is called the typical ‘European regulatory ap-
proach’, as most of them aim to reduce neg-
ative externalities (Prayag & Ozanne2018, p.
664). This study also confirms that munici-
palities put an individual focus on regulating
STRs (Dredge et al.2016, p. 35). Among the 12
cities, we detected a general trend to enforce
regulations during the last years (see Figure1),
although the pace and intensity differ, with
London being liberal and Amsterdam restric-
tive. The remaining cities group around these
two extremes.
Scholars often criticize the ‘minimal’ im-
pact of regulations on STRs (Von Briel &
Dolnicar2020, p. 5; Cocola- Gant et al.2021,
Figure 5. Share of housing units that were available on Airbnb at least 120 days and occupied at least 60 days (Seidl
et al. 2017), compared to the total Airbnb market (2015– 2020, August). Own elaboration based on data of Inside
Airbnb(2021).
TAMING AIRBNB LOCALLY 17
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap.
p. 1601). This might be true for some cities,
but at least in two of our three case studies,
we see that regulations do have an impact
and change the geographies of Airbnb. In
this sense, we can confirm some of our hy-
potheses. We expected a more pronounced
impact of regulations on the total number
of Airbnb listings in Berlin and Amsterdam,
compared to London, and this has been con-
firmed by the data.
In the case of London, our results add cer-
tainty to the prevailing question whether the
observed liberalization will actually curb the
city’s Airbnb market (Gurran 2018, p. 301).
The statistics show how London’s liberal regu-
lation (with no strict quantitative restrictions)
has virtually led to a doubling of Airbnb listings.
What is more difficult to explain, is the fact
that Berlin shows significantly lower growth
rates compared to Amsterdam until 2019,
with Amsterdam having the stricter regula-
tions. One possible explication is to trace
this back to Berlin’s relatively strict law from
2014, although this law was later modified and
liberalized (Busch 2019, p. 39). Still, Duso
et al. (2020, p. 41) confirm the decline of
Airbnb listings in Berlin, particularly after each
legal modification in 2016 and 2018, and we
added further evidence in this respect.
In Amsterdam, regulations proved to be
more effective regarding the structure of the
Airbnb market. On the one hand, regulations
impeded the ongoing professionalization of
the host structure that is observed in many
cities (Cocola- Gant et al.2021, p. 1061; Armas-
Díaz et al. 2021b, p. 76). Amsterdam was the
only case where this share of multi- hosts sig-
nificantly dropped in the given period. On
the other hand, the city’s regulations also led
to a notable decrease of the share of housing
units withdrawn from the regular housing
market (see Seidl et al.(2017) and definition
in Figure4). Here, we argue that gradually
tightening regulations plays a crucial role, as
Amsterdam passed from a 60- day cap in 2016,
to a 30- day cap in 2018, and temporarily even
had a spatial ban in 2020. Not only does this
make the business model of multi- hosts less
lucrative, it also forces hosts to continuously
adapt to new rules.
In a setting where particularly large-
scale actors are said to be resilient enough
to adapt to legal frameworks (Von Briel &
Dolnicar 2020, p. 5; Anselmi 2021, p. 4), a
dynamic regulatory setting might be the ad-
equate answer to successfully tame an uncon-
trolled proliferation of listings. The design of
our paper does not allow to draw a definite
conclusion here, which is why more research
should be done to explicitly investigate the
impact of changing regulations on STRs. Still,
our hypothesis is also confirmed by Chen
et al.(2021, p. 1), who observe how the im-
pact of regulations on the STR market in gen-
eral decreases in the long run.
In this sense, Amsterdam is a clear ex-
ception, since other academics diagnose
how most regulations do not restrict the
ongoing professionalization of host struc-
tures (Smigiel2020, p. 256). In London and
Berlin, we must confirm this observation.
Here, we see a notable increase of multi- hosts
until 2019. As for Berlin, regulations such as
a cap on renting out secondary residences
(90 days) and registrations alone were ap-
parently not enough to reduce the share of
multi- hosts.
Contrary to that, Berlin’s regulations in-
deed succeeded in reducing the share of
housing units withdrawn from the regular
housing market, at least marginally. Here,
we suppose that a further reduction of the
maximum number of days would help to de-
crease the pressure of Airbnb on the housing
market even more. We base this assumption
on our findings from Amsterdam, but also
other studies who found that caps have the
potential to limit the growth of listings (Chen
et al.2021, p. 12), and even make the Airbnb
market less unstable (Vinogradov et al.2020,
p. 8).
Lastly, the spatiality of these phenomena
is certainly the most intriguing and complex
question. We have observed a spatial de-
concentration of Airbnb listings in all three
cities. Such a spatial dispersion is certainly
the result of a saturation effect in city cen-
tres (Quattrone et al. 2016, p. 1385; Rabiei-
Dastjerdi & McArdle2020, p. 113), but strict
regulations in cities such as Amsterdam have
obviously reinforced this effect. In Berlin
(with no spatial ban on STRs in central dis-
tricts), we also suppose regulations that af-
fect particularly commercial listings (such as
MARCUS HÜBSCHER & TILL KALLERT18
© 2022 The Authors. Tijdschrift voor Economische en Sociale Geografie published by John Wiley & Sons Ltd on behalf of Royal
Dutch Geographical Society / Koninklijk Nederlands Aardrijkskundig Genootschap.
caps) to contribute to this deconcentration.
This is because in central districts we usually
expect the highest degree of professionaliza-
tion (Hübscher et al.2020). Comparing this
spatial development of listings to London’s
case reveals, how the absence of strict regu-
lations leads to high growth rates across the
whole city.
This study has provided further evidence
to believe in the effectiveness of certain regu-
latory instruments. However, given the chang-
ing and highly individual legal settings in each
city, the adopting character of STRs, and other
influencing factors such as visitor demands
or external shocks (COVID- 19), a continuous
monitoring (Smigiel 2020, p. 256) is funda-
mental to understand the evolving geographies
of STRs.
Acknowledgement
Open Access funding enabled and organized by
Projekt DEAL.
Endnotes
1 Inside Airbnb helps communities to comprehend
the impact of Airbnb (Inside Airbnb2021). This
non- commercial project is led by Murray Cox and
other activists. The data source has certain lim-
itations; however, it is a valuable approach to ex-
plore the geographies of Airbnb listings (see, e.g.,
the discussion in Gurran & Phipps[2017, p. 85]
and Smigiel et al.(2020), and the data assump-
tions presented by Inside Airbnb[2022]).
2 The scraped data provided by Inside Airbnb en-
tail a host ID for each listing, which helps to iden-
tify if one host offers several apartments.
3 This means that in 2015, 0.54% of all housing
units in Amsterdam were withdrawn from the
regular housing market due to Airbnb (0.068%
in 2020).
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