Study on the Assessment of the Regulatory Aspects Affecting the Collaborative Economy in the Accommodation Sector in the 28 Member States (580/PP/GRO/IMA/15/15111J)

European Commission - Directorate General Internal Market, Industry, Entrepreneurship and SMEs (DG GROW)

Task 4

Market Case study –

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This study was carried out for the European Commission by Spark Legal Network and Valdani Vicari & Associati.

Spark Legal Network

Valdani Vicari & Associati

Julia Rzepecka Marius Dragulin Lison Rabuel Ricardas Juskevicius Vilma Kuuliala Timothe Peroz Iva Plasilova Adriana Rodriguez Diaz

DISCLAIMER

By the European Commission, Directorate General Internal Market, Industry, Entrepreneurship and SMEs. The information and views set out in this study are those of the author(s) and do not necessarily reflect the official opinion of the Commission. The Commission does not guarantee the accuracy of the data included in this study. Neither the Commission nor any person acting on the Commission’s behalf may be held responsible for the use which may be made of the information contained therein.

ISBN 978-92-79-84011-1 doi: 10.2873/97716

© European Union, (2018). All rights reserved. Certain parts are licensed under conditions to the EU.

TABLE OF CONTENT

1 OVERVIEW OF THE ACCOMMODATION SECTOR ...... 5 1.1 Main players in the collaborative economy accommodation sector ...... 6 1.2 Overview of economic development of the collaborative economy accommodation market ...... 6 1.3 Overview of applicable local rules and regulatory developments ...... 8 1.4 Summary of indicators ...... 9 2 REAL ESTATE AND HOUSING AVAILABILITY ...... 11 2.1 Overview of average rental market prices ...... 11 2.2 Overview of number of available properties ...... 13 2.3 Overview of occupancy ...... 17 3 INCOME AND OTHER TOURISM INDICATORS ...... 19 3.1 Income indicators ...... 19 3.2 Tourism indicators ...... 20 4 IMPACT ON LOCAL COMMUNITIES...... 21 4.1 Development of ancillary services ...... 21 4.2 Housing supply changes ...... 21 4.3 Inhabitants’ perception of collaborative short-term rental platforms ...... 22 4.4 Impact on public services ...... 22 5 FUTURE DEVELOPMENTS ...... 23 6 ANNEX 1: LIST OF REFERENCES ...... 24

TABLES

Table 1: Average monthly rents for long-term rentals in 2016 ...... 12 Table 2: Average daily and monthly rates for AirBnB listings and rooms in 2016...12 Table 3 Summary overview of average rental market prices for long- and short-term rentals – Florence ...... 13 Table 4: Summary overview of number of available properties for short- or long-term rental in 2016 ...... 16 Table 5: Summary overview of occupancy rates in Florence in 2016 ...... 18 Table 6: Summary overview of income indicators – Florence ...... 19 Table 7: Summary overview of tourism indicators – Florence ...... 20

FIGURES

Figure 1: Map of Florence ...... 6 Figure 2: Total available listings on AirBnB, by type ...... 7 Figure 3: AirBnB visitation by neighbourhood (2016) ...... 7 Figure 4: AirBnB properties vs. ...... 8 Figure 5: Italian house price index trend - Annual average (base 2010=100) ...... 11 Figure 6: Long-term rent of one-bedroom apartments in Florence (in EUR) ...... 12 Figure 7: Average daily rates: AirBnB entire place and hotel room ...... 13 Figure 8: Hotels and similar establishments in Florence ...... 14 Figure 9: Establishments in and other short-stay accommodation ...... 15 Figure 10: Occupancy rate AirBnB all listings and hotel rooms ...... 17 Figure 11: Net occupancy rate of bedrooms in ...... 18 Figure 12: Revenue for Airbnb entire place ...... 19 Figure 13: 10 highest hotel stays in Florence by origin (2014) ...... 20

Task 4 – Annex 6 - Market Case study – Florence

DEFINITIONS:

The key terms used in the case study are defined below. It should be noted that these definitions may differ from the definitions used by the European Commission.

Primary residences: those residences (dwellings) where the person resides more than 180 days per year.

Secondary residences: those residences (dwellings) where the owner spends at least some days per year.

Short-term rental: the rental of an accommodation (room or entire property) on a short- term basis. “Short-term” can be defined by local laws as the maximum period per year during which an accommodation provider can rent out their property or part thereof under specific circumstances.

Long-term rental: the rental of an accommodation (room or entire property) on a long- term basis. “Long-term” can be defined as a period exceeding any short-term threshold imposed by local, regional or national laws (see definition of “short-term rental”).

Vacant property: A residence (dwelling) that is not occupied by their owners or any tenants.

Peer provider: For the purpose of this study, the term is used to designate all providers of short-term rentals on collaborative platforms. In certain cases, where data are available, the text makes a distinction between “peer” and “professional” provider. In this case, “peer provider” refers to individuals who do not conduct such activities on a professional basis, i.e. earning the majority of their income through to short-term rentals.

Conventional dwelling: The term is defined according to its definition on EUROSTAT, namely a room or a suite of rooms and its accessories in a permanent building or structurally separated part thereof which by the way it has been built, rebuilt or converted; it is designed for habitation by one private household all the year round and is not at the time of the census used wholly for non-residential purposes.

Vacant conventional dwelling: According to EUROSTAT, vacant conventional dwellings are conventional dwellings (see above) which have no usual residents at the time of the census but are available to become the principal usual residence of at least one person. Vacant dwellings could be either: seasonally vacant, holiday homes, seasonal workers' quarters, non-seasonally vacant, secondary residences, for rent, for sale, for demolition, or for other purposes.

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Task 4 – Annex 6 - Market Case study – Florence

1 Overview of the accommodation sector

This section gives an overview of the short-term accommodation sector in Florence. It describes the main players, and gives an insight of the economic development, and explains the main local rules shaping the short-term rental market.

Facts and figures – Florence

Florence is the capital city of the Italian region of Tuscany and it is the most populous city in the region, with 383,083 inhabitants.1 It represents 10% of the total Tuscan population of 3,74 million2. Florence is also very important economically to the region. In 2014, its GDP of EUR 35,587 million3 represented 32% of the total GDP of Tuscany (EUR 110,332 million4), and 2% of total GDP of (EUR 1,645,439 million5).

Florence is one of the most important tourist centres in Italy. In 2014, it was the 4th most visited city (after Rome, Milan and Venice), attracting 7% of all tourists visiting Italy6. At the end of 2015, there were 5 million tourist arrivals in Florence, an increase of 2.9% in comparison to 20147. Over 70% of tourist arrivals came from outside of Italy. Tourist spending accounted for EUR 2.5 billion, a growth of 5.2% in comparison to 2014.8 Florence's governance is divided broadly into executive and legislative branches. The executive branch is represented by the Mayor and the Mayor’s Council (Giunta) and the legislative branch is represented through the City Council.

 The Mayor is responsible for the organization of local government, issuing decisions (ordinanze).9 The Mayor is directly elected by citizens every 5 years.  The Mayor’s Council (Giunta) is made up of councillors selected by the Mayor. They are responsible for executing the general policies put forward by the legislative branch of the government, which is represented by the City Council.10  The City Council is elected every 5 years and it is composed by members of political party representatives.

Florence is divided into 5 districts: Centro Storico, Campo di Marte, Gavinana-Galluzzo, Isolotto-Legnaia, Rifredi (Figure 1). Each one of these districts has a certain level of independence and manages some local services such as public works (i.e. building maintenance) and the provision of local social and education services.11

The map on the following page shows the area of Florence and its districts (quartieri).

1 Data from 2013 available at: http://demo.istat.it/ 2 Data from Eurostat: Population on 1 January by age, sex and NUTS 2 region [demo_r_d2jan] 3 Data from Eurostat: Gross domestic product (GDP) at current market prices by NUTS 3 regions [nama_10r_3gdp] 4 Data from Eurostat: Gross domestic product (GDP) at current market prices by NUTS 2 regions [nama_10r_2gdp] 5 Data from Eurostat: Gross domestic product (GDP) at current market prices by NUTS 2 regions [nama_10r_2gdp] 6 Federalberghi (2015) Datatur: Trend e statistiche sull’economia del Turismo. Centro Study Federalberghi. 7 Ibid. 8 Ibid. 9 http://en.comune.fi.it/administration/municipality/city_mayor.htm 10 http://en.comune.fi.it/administration/municipality/board_and_council.htm 11 http://en.comune.fi.it/administration/municipality/districts.htm

Task 4 – Annex 6 - Market Case study – Florence

Figure 1: Map of Florence

1.1 Main players in the collaborative economy accommodation sector

In 2016, AirBnB offered around 8,300 listings (see section 1.2). One of the earliest collaborative short-term rental platforms – HomeAway, established in 2004 – offers 7,822 listings in Florence, close second to AirBnB.12

Other collaborative short-term rental platforms are substantially smaller. Among European players, Wimdu, a German-born peer-to-peer accommodation rental platform, offers 1,027 listings in Florence.13 9flats, a similar German platform, offers around 610 listings.14 HomeExchange, a US-based home swapping platform, reports 128 listings.15 The platform has been acquired in March 2017 by GuestToGuest, a French home swapping platform, which offers 650 listings. LoveHomeSwap, another US-based home swapping platform created in 2012, advertises about 168 properties in Florence.16Lastly, hotel booking websites, such as Booking.com and Tripadvisor, also offer peer-to-peer short-term rentals. For instance, Booking.com offers 2,137 listings, all of which are entire properties.17 Tripadvisor offers 2,693 holiday rentals,18 but its platforms like HouseTrip and FlipKey list up to 8,790 entire properties19.

It is important to note that peer providers can simultaneously use more than one collaborative short-term rental platform to advertise their listing. This leads to a likely double counting of listings on such websites. Due to lack of data available on the number of double listings, the information presented in this case study regarding the total number of listings on collaborative short-term rental platforms (see sub-section 2.2) should be taken as an approximation.

1.2 Overview of economic development of the collaborative economy accommodation market

12 Snapshot of https://www.homeaway.co.uk/results/refined/keywords:florence/page:1 as of 26/05/2017 13 Snapshot of http://www.wimdu.co.uk/florence as of 25/05/2017. 14 Snapshot of https://www.9flats.com/florence-florence-tuscany-italy as of 25/05/2017. 15 Snapshot of https://www.homeexchange.com/en/search/Florence as of 25/05/2017. 16 Snapshot of https://www.lovehomeswap.com/location/italy/tuscany/florence as of 25/05/2016. 17 Snapshot of https://www.booking.com/ as of 10/08/2017. 18 Snapshot of https://www.tripadvisor.co.uk/ as of 10/08/2017. 19 Snapshot of https://www.flipkey.com/ and https://www.housetrip.com/ as of 09/08/2017. 6

Task 4 – Annex 6 - Market Case study – Florence

In the last six years, AirBnB experienced an exponential growth in listed properties, climbing to over 9,000 in 2017.20 In terms of type of accommodation, by far the largest category are “entire places” (Figure 2). In 2016, AirBnB had 3,700 hosts, typically earning around EUR 6,300. Typical listing hosted 64 days in that year.21

Figure 2: Total available listings on AirBnB, by type

9.000 8.000 7.000 6.000 5.000 4.000 3.000 2.000 1.000 0

Entire Place Private Room Shared Room

Source: AirDNA data

The growth in available listings is increased in line with growing numbers of visitors (Figure 3). In 2016, AirBnB hosts hosted approximately 364,000 guests, who stayed 3.2 nights on average.22 This translated to a substantial guest spending. AirBnB estimates that local households earned around EUR 38 million, while Florence businesses benefited from approximately EUR 169 million.23

Figure 3: AirBnB visitation by neighbourhood (2016)

Source: AirBnB. Overview of the AirBnB Community in Italy. Available at: https://www.AirBnBcitizen.com/wp- content/uploads/2016/05/overview_of_the_AirBnB_community_in_italy.pdf

The economic benefit from AirBnB attracting guests is very likely to be more dispersed across Florence and less concentrated in the city’s centre in comparison to traditional

20 https://www.airdna.co/city/it/florence 21 AirBnB. Overview of the AirBnB Community in Italy. Available at: https://www.AirBnBcitizen.com/wp- content/uploads/2016/05/overview_of_the_AirBnB_community_in_italy.pdf 22 Ibid. 23 Ibid. 7

Task 4 – Annex 6 - Market Case study – Florence

tourist accommodation, if judged by looking at the location of AirBnB properties in comparison to hotels (Figure 4).

Figure 4: AirBnB properties vs. Hotels

Source: AirBnB. Overview of the AirBnB Community in Italy. Available at: https://www.AirBnBcitizen.com/wp- content/uploads/2016/05/overview_of_the_AirBnB_community_in_italy.pdf

1.3 Overview of applicable local rules and regulatory developments

This sub-section provides a brief overview of the regulatory framework applied to collaborative short-term rental platforms and to peer-to-peer rentals in Florence. More detailed information regarding this framework is available in Task 1 reports. Note that, while the Task 1 report assesses all relevant regulation passed up to January 2017, this case study expands the timeline to June 2017. Because of the different timelines, some small differences in the regulatory information presented may exist.

There is a specific regulatory framework in Tuscany, setting out the characteristics of short- term rental.

Regional Law of the 20th of December 2016 - No. 86, Article 70 (Touristic Rentals) - specifies that only furnished homes and apartments can be rented for touristic purposes, without providing any extra or complementary services.24 Therefore, only homes and apartments that do not provide extra and complementary services can be rented out under the Tuscany Touristic Rentals legal framework. It is forbidden for the providers in the collaborative economy to provide extra or complementary services (for example, food and cleaning) in the homes and/or apartments they rent out. The legal framework introduced by the Tuscany Region does not exclude the rental of rooms (rooms can also be rented). Collaborative economy providers renting rooms cannot offer any extra or complementary services. Accommodations rented for touristic purposes must also respect the same structural and hygienic standards set for residential buildings, they must be safe and secure.

There is a specific regulatory framework setting out the characteristics of the accommodation related to maximum number of apartments held by a service provider.25 A peer provider can rent out:  only two apartments in a year. If the peer rents out only two apartments, the number of times he/she rents them out is irrelevant;

24 VVA Europe and Spark research Qquestionnaire. Study on the Assessment of the Regulatory Aspects Affecting the Collaborative Economy in the Tourism Accommodation Sector in the 28 Member States (580/PP/GRO/IMA/15/15111J). 21 April, 2017. 25 Ibid. 8

Task 4 – Annex 6 - Market Case study – Florence

 more than two apartments in a year. If the peer rents more than two apartments, he can rent them no more than eighty times.  A professional provider can rent out an indefinite number of apartments.

There are additional information requirements that collaborative economy hosts have to comply with. The Regional Law of the 20th of December 2016 - No. 86, Article 70 (Touristic Rentals) – provides the possibility of enacting an information obligation for collaborative economy providers to communicate to the Municipality of Florence, where the apartments are located, and additional information.26 However, at the moment of this research (April 2017), the Tuscany Region has not yet enacted the implementing Regulation specifying what information needs to be communicated27 because the Italian Government has recently (23 February 2017) sued the Tuscany Region before the Italian Constitutional Court28 as it argues that the competence to legislate on the “renting activity” is at national level.

The Regional Law of the 20th December of 2016 - No. 86 - does not apply to home swapping.29 There is no explicit reference to home swapping in the law. Therefore, home swapping - which takes place without the exchange of money - remains unrestricted.

The Municipality of Florence has specific tax rules, applicable to the collaborative economy. In 2011, the City introduced a tax revenue per night per client (la tassa di soggiorno) for touristic facilities.30 From 2014, the revenue is applicable also to collaborative economy hosts and users. The City and AirBnB also signed an agreement in January 2016 according to which AirBnB, on city’s behalf should collect EUR 2.50 per night per client and for each apartment rented through the platform. It is not clear under Italian law, however, if the City has the power to impose the obligation to collect tax that is currently collected voluntarily by AirBnB. In-depth revision of the local tax system has been initiated and it involves stakeholders such as the State, the Region and AirBnB.31

1.4 Summary of indicators

Table 1 presents an overview of indicators collected throughout the case study. Further information is provided in the following sections.

Table 1: Summary of indicators No. Indicators Categories Value Average market rental One bedroom EUR 583 prices for long-term Two bedrooms N/A rentals (2016, Three bedrooms EUR 1,130 monthly)32 All categories N/A A1 Average market rental AirBnB single room EUR 2,006 prices for short-term AirBnB shared room EUR 1,003 rentals (2016, AirBnB entire home/apartment EUR 3,136 monthly)33 AirBnB all listing categories EUR 2,705

26Legge regionale 20 dicembre 2016, n. 86. Available at:http://raccoltanormativa.consiglio.regione.toscana.it/articolo?urndoc=urn:nir:regione.toscana:legge:2016-12- 20;86&dl_t=text/xml&dl_a=y&dl_id=&pr=idx,0;artic,0;articparziale,1&anc=cap4 27 http://www.regione.toscana.it/-/turismo-la-nuova-legge-regionale-testo-unico-sul-sistema-turistico-regionale- 28 http://www.regioni.it/news/2017/02/24/comunicato-stampa-del-consiglio-dei-ministri-n-14-del-23-02-2017-501281/ 29 VVA Europe and Spark research Qquestionnaire. Study on the Assessment of the Regulatory Aspects Affecting the Collaborative Economy in the Tourism Accommodation Sector in the 28 Member States (580/PP/GRO/IMA/15/15111J). 21 April, 2017. 30 The tax is paid for each overnight stay (i.e. per person per night) in the accommodation facilities and in the properties for tourist use within the territory of the City of Florence, up to a maximum of 7 consecutive overnight stays. Decreto Legislativo 14 marzo 2011 n.23 http://servizi.comune.fi.it/servizi/scheda- servizio/imposta-di-soggiorno 31 VVA Europe and Spark research Qquestionnaire. Study on the Assessment of the Regulatory Aspects Affecting the Collaborative Economy in the Tourism Accommodation Sector in the 28 Member States (580/PP/GRO/IMA/15/15111J). 21 April, 2017. 32 Average rental price for renting an entire property for long-term (more than 90 days) in the urban area considered. The value corresponds to the monthly average rent paid in the last reference year considered in this study. 33 Average rental price for renting a room or entire property on AirBnB or an average hotel on a short-term basis (less than 90 days) in the urban area considered. The value corresponds to the average daily rate on AirBnB or an average hotel multiplied by 30.4167 (in order to represent both months with 30/31 days). Note that the value does not consider potential discounts offered for renting a place for more than a day, even though such discounts are common on collaborative short-term rental platforms and in some hotels. The rooms considered in this indicator can accommodate up to two guests. 9

Task 4 – Annex 6 - Market Case study – Florence

No. Indicators Categories Value Hotel room EUR 2,736 A2 Rooms or residences Rooms 2,229 available for short-term Entire primary and secondary 21,603 rental34 residences or touristic houses35 A3 Number of available residences (housing stock)36 N/A Number of available properties for long-term rental (vacant A4 411,896 dwellings)37 Number of available properties offered through collaborative A5 23,884 short-term rental platforms For short-term rentals (AirBnB) 54% For hotel rooms (Tuscany) 45% Short-term occupancy A6 rate38 Number of nights peer providers rent out their property (AirBnB - N/A median) For short-term rentals (AirBnB) 3.2 Average length of A7 For hotels or conventional stay39 3 accommodation providers (Italy) AirBnB providers (AirBnB, median) 6,300/year Income gained through A8 short-term rental AirBnB providers (InsideAirBnB) N/A 40 Hotels or conventional activities N/A accommodation providers Percentage of total provider revenues accounted for by A9 N/A short-term rental activities (AirBnB)41 Number of tourists Total number of tourists on AirBnB 364,000 using collaborative (2016)42 B1 short-term rental Total number of nights spent in 1,16 million platforms AirBnB locations (2016)43 Share of collaborative Nights spent (2016)44 (indicative) 22.4% economy users out of tourists using B2 Number of tourists (2016)45 conventional 17.4% accommodation (indicative) services

34 The sum of all listings, divided by rooms and entire places, found on the EU-level and local collaborative short-term rental platforms considered in this case study. Note that the values do not take into account the possibility of double listings, i.e. the same room or property being listed on multiple collaborative short-term rental platforms. The value, however, excludes listings in hotels, but it may include rooms in or other type of touristic houses (e.g. B&Bs) that operate as businesses. 35 The information presented on collaborative short-term rental platforms does not allow us to distinguish between primary and secondary residences, or between residences (dwellings) and touristic houses. Where available, such distinctions for one or several collaborative short-term rental platforms are indicated in the text, while the indicator value corresponds to the sum of all entire listings available on the EU-level and local collaborative short-term rental platforms considered. 36 The total number of registered residences (dwellings) available in the urban area under study in the latest reference year considered. The number excludes all dwellings serving purposes other than residential ones. 37 The number of vacant residences (dwellings) out of the total number of registered residences (dwellings) in the urban area under study in the latest reference year considered. 38 The occupancy rate refers to the percentage of nights a given property is rented out, out of the total number of nights that property is available. Note that, depending on local laws, properties listed on collaborative short-term rental platforms may be subject to a maximum limit of calendar days of availability. This aspect is considered in the indicator: the ratio refers to the actual occupancy rate (i.e. considering the number of days the listing is available), rather than a theoretical occupancy rate, which assumes availability up to the maximum limit permitted, or up to the maximum number of calendar days per year. 39 The value refers to the average monthly length of rental for a property, either on collaborative short-term rental platforms using AirBnB as a proxy, or in conventional accommodation providers such as hotels. 40 The value refers to the yearly median or average income gained from the rental of an average listing on collaborative short-term rental platforms using AirBnB as a proxy, or for an average room rented via a conventional accommodation provider. Note that for collaborative short-term platforms, various sources are indicated, so as to provide a more impartial value for this indicator. 41 The value refers to the percentage of annual income of the peer provider accounted for by revenues deriving from their collaborative short-term rental platform activities. Due to data availability, the indicator uses AirBnB statistics as a proxy for all collaborative short-term rental platforms in the urban area under study. 42 The value refers to the yearly number of individuals that used collaborative short-term rental platforms for accommodation, taking AirBnB as a proxy for the industry. Note that this is not the same as the total number of nights spent in AirBnB listings, since tourists may rent out properties as a group, rather than as individuals. The value also ignores the number of nights stayed per guest, which is considered in the indicator “Total number of nights spent in AirBnB locations”. 43 The value refers to the total number of nights during which listings on the collaborative short-term rental platform AirBnB were rented during the latest year considered in this study. The value is computed using the following formula: [(total number of tourists using AirBnB listings as accommodation in the given year) x (average length of stay in an AirBnB listing)] / (average size of the group renting an AirBnB property). 44 The value refers to the ratio between the number of nights spent in AirBnB listings, taking AirBnB as a proxy for all collaborative short-term rental platforms activity, and the number of nights spent in conventional accommodation providers. 45 The value refers to the ratio between the number of tourists using AirBnB listings for their accommodation, taking AirBnB as a proxy for all collaborative short-term rental platforms activity, and the number of tourists using conventional accommodation providers. 10

Task 4 – Annex 6 - Market Case study – Florence

2 Real estate and housing availability

This section gives an overview of the real estate market and housing availability in Florence, notably rental prices, number of available properties, and occupancy rates.

Due to the lack of data on other collaborative short-term rental platforms, AirBnB is used as a proxy for the collaborative economy market when no other data are available.

2.1 Overview of average rental market prices

Since the early 2010s the residential property values in Italy fell by 15% (Figure 5).

Figure 5: Italian house price index trend - Annual average (base 2010=100)

105 100 95 90 85 80 75 2010 2011 2012 2013 2014 2015 2016

Source: data extracted on 25 May 2017 15:12 UTC (GMT) from I.Stat: https://www.istat.it/en/

The downward trend in residential property values in Italy broadly reflects the fall in long- term rental prices46 in Florence with the biggest changes outside the city centre (Figure 5).47

See Figure 6 on the next page, for an overview of the long-term rent of one bed-room apartments in Florence inside the city centre and outside of the city centre and Table 2 for the average monthly rents for long-term rentals in 2016.

46 In this study, long-term rentals are understood to be rooms or entire properties rented out over a period exceeding any short-term threshold imposed by local laws (see definition of “short-term rental”). See sub-section 1.3 for a description of such thresholds. Where there is no such threshold, it is assumed to be a period longer than 120 days per year. 47 : https://www.numbeo.com/cost-of-living/historical-data?itemId=27&itemId=26&itemId=29&itemId=28&city_id=5636&name_city_id=¤cy=EUR 11

Task 4 – Annex 6 - Market Case study – Florence

Figure 6: Long-term rent of one-bedroom apartments in Florence (in EUR)

900 800 700 600 500 400 300

Rent prices Rent prices inEUR 200 100 0 2012 2013 2014 2015 2016 2017

In the city centre Outside of the city centre

Source: https://www.numbeo.com/cost-of-living/. Table 2: Average monthly rents for long-term rentals in 2016 Categories Average (EUR) One bedroom 583 Two bedrooms N/A Three bedrooms 1,130

Source: Calculated using data from https://www.numbeo.com/cost-of-living/, computed as the average rent between one city centre and one outside city centre apartment. To illustrate the average market price for short-term rentals the AirBnB average nightly rate is used as a proxy (Table 3). The average cost for a night on AirBnB was EUR 89. On the platform, prices vary depending on the type of listing: an entire home/apartment costs EUR 103, a private room EUR 66 and a shared room EUR 33 on average.

This study uses the price of AirBnB entire place average as a comparable alternative to hotel room (double-bed standard room). This alternative is considered comparable because it offers the same level of privacy (e.g. own key, own entrance and private bathroom facilities). Hotel rooms, in this study, are not compared with AirBnB listed rooms because the level of privacy is lower on AirBnB.

Table 3: Average daily and monthly rates for AirBnB listings and hotel rooms in 201648 Categories Average daily Average monthly (EUR) (EUR) AirBnB all listing categories 89 2,705 AirBnB entire home/apartment 103 3,136 AirBnB single room 66 2,006 AirBnB shared room 33 1,003 Hotel room 90 2,736

Source: AirDNA data for AirBnB listings in 2016, calculated as an average of all monthly daily rates Figure 7 illustrates the evolution of the average daily rate for Airbnb entire property from August 2015 to April 2017. In comparison, the average hotel room rates for the same period is provided.

48 Average rental price for renting a room or entire property on AirBnB or an average hotel on a short-term basis (less than 90 days) in the urban area considered. The value corresponds to the average daily rate on AirBnB or an average hotel multiplied by 30.45 (in order to represent both months with 30/31 days). Note that the value does not consider potential discounts offered for renting a place for more than a day, even though such discounts are common on collaborative short-term rental platforms and in some hotels. The rooms considered in this indicator can accommodate up to two guests. 12

Task 4 – Annex 6 - Market Case study – Florence

Figure 7: Average daily rates: AirBnB entire place and hotel room49

€200 €180 €160 €140 €120 €100 €80 €60 €40 €20

€0

juil-16

avr-16 avr-17

oct-15 oct-16

déc-15 déc-16

nov-15 nov-16

mai-16

juin-16

févr-16 févr-17

janv-16 janv-17

sept-15 sept-16

août-15 août-16

mars-16 mars-17

Florence AirBnB Florence Hotel

Source: AirDNA

Table 4 combines the findings illustrated in this section and shows an overview of average rental market prices for long- and short-term rentals in Florence. Reported to monthly rates, the price for a room in a short-term rental (nightly basis) is 2.7 times higher than for a long-term rental (monthly basis).

Table 4 Summary overview of average rental market prices for long- and short- term rentals – Florence No. Indicators Categories Value (EUR) Average market rental One bedroom 583 prices for long-term Two bedrooms N/A rentals (2016, Three bedrooms 1,130 monthly)50 All categories N/A AirBnB single room 2,006 A1 AirBnB shared room 1,003 Average market rental AirBnB entire prices for short-term 3,136 home/apartment rentals (2016, AirBnB all listing monthly)51 2,705 categories Hotel room 2,736

2.2 Overview of number of available properties

Between 2012 and 2015 the overall number of hotels (and hotel-tourism residences) grew by 2% only (Figure 8).

49 The average daily rate charged per booked entire place listing. ADR includes cleaning fees but not other Airbnb service fees or taxes. 50 Average rental price for renting an entire property for long-term (more than 90 days) in the urban area considered. The value corresponds to the monthly average rent paid in the last reference year considered in this study. 51 Average rental price for renting a room or entire property on AirBnB or an average hotel on a short-term basis (less than 90 days) in the urban area considered. The value corresponds to the average daily rate on AirBnB or an average hotel multiplied by 30. Note that the value does not consider potential discounts offered for renting a place for more than a day, even though such discounts are common on collaborative short-term rental platforms and in some hotels. The rooms considered in this indicator can accommodate up to two guests. 13

Task 4 – Annex 6 - Market Case study – Florence

Figure 8: Hotels and similar establishments in Florence

700

600

500

400

300

200

100

0 2012 2013 2014 2015

5 star-5 star deluxe hotels 4 star hotels 3 star hotels 2 star hotels 1 star hotels hotel-tourism residences

Source: data extracted on 10 May 2017 16:33 UTC (GMT) from I.Stat: https://www.istat.it/en/52

However, there were asymmetric trends within the sector. The growth was concentrated in the mid-to high luxury sub-sector. The number of 5 star, 4-star and 3 star hotels increased by 16%, 9% and 4% respectively, together with a 9% growth in hotel-tourism residences. On the other hand, the number of 2 star and 1-star hotels declined by 7% and 10% respectively. The more fine-grained analysis of growth patterns suggests that the sector growth is healthier than the total trend. The mid to high market segments experienced strong increase. This indicates that the growth of the collaborative economy in the accommodation sector might not present significant challenge to the sub-sector. However, this might be the case in the low end of the market as tourists might be more inclined to use accommodation via peer-to-peer platforms rather than 1 star or 2-star hotels.

Between 2012 and 2015, the overall growth in bed-places in hotels was stagnant.53 However, there are differences between sub-sectors broadly in line with trends in the number of available hotels. While the lower end of the market experienced decline, 5-star, 4 star and hotel-tourism residences (HTR) increased their bed-places. Overall, in 2015 there were nearly 45,000 bed-places in Florence.54 In terms of proportions, the overwhelmingly large numbers of bed-places were in two sub-sectors: 4-star hotels occupied 46%, while 3-star hotels 34%.55 Furthermore, in 2015 there were 19,000 bed places in holiday dwellings for renting;56 11,000 bed places in farmhouses; and 2,200 bed places in hostels.

Growth was also observed in most sectors representing alternatives to more traditional hotels (Figure 9). Since 2012, the number of holiday dwellings for renting57 had grown by 15% topping 1,400 in 2015. The number of Youth hostels and Farmhouses also increased, by 8% and 6% respectively.

52 In order to facilitate retrieval of the statistics, specific topics should be provided, in this instance it is: Services / Tourism 53 Data extracted on 10 May 2017 16:33 UTC (GMT) from I.Stat: https://www.istat.it/en/ 54 Ibid. 55 Ibid. 56 Data extracted on 10 May 2017 16:33 UTC (GMT) from I.Stat: https://www.istat.it/en/ 57“Holiday dwellings” is a separate category used in Italian statistics. This class includes the provision of accommodation, typically on a daily or weekly basis, principally for short stays by visitors, in self-contained space consisting of complete furnished rooms or areas for living/dining and sleeping, with cooking facilities or fully equipped kitchens. This may take the form of apartments or flats in small free-standing multi-storey buildings or clusters of buildings, or single storey bungalows, chalets, cottages and cabins. Very minimal complementary services, if any, are provided. This class includes accommodation provided by: children and other holiday homes; visitor flats and bungalows; cottages and cabins without housekeeping services; youth hostels and mountain refuges. It is not clear however if this category includes accommodation provided on collaborative short-term rental platforms, but for the purpose of this study we assume it is not. 14

Task 4 – Annex 6 - Market Case study – Florence

Figure 9: Establishments in holiday and other short-stay accommodation

2500

13 2000 13 11 12 677 663 1500 636 644

1000

1407 1224 1241 1294 500

0 2012 2013 2014 2015

Holiday dwellings (rented) Farmhouses Youth hostels Mountain refuges

Source: data extracted on 10 May 2017 16:33 UTC (GMT) from I.Stat: https://www.istat.it/en/58

Further data with exact numbers of available dwelling and vacant dwellings, for instance on EUROSTAT, is not available for Florence.

There are around 23,884 available properties for short-term rental59 in Florence, including the listings from the following collaborative short-term rental platforms. Note that, as explained in sub-section 1.1, the counting does not make any provision for potential double listings, i.e. properties listed on more than one platform, and therefore double counted:  AirBnB: 8,379 available listings, among which: - 2,076 private rooms (24.8% of all the listings), - 6,251 entire home/apartment (74.6% of all the listings); and - 52 of shared room (0.6% of all the listings)60;  Wimdu: 1,027 available listings, among which 140 private rooms, 874 apartments, 12 villas and 1 farmhouse61;  9flats: 610 available listings, of which 597 entire places and 13 private rooms62;  HomeAway: 7,822 available listings, among which 5,993 apartments, 1,313 villas, 232 farmhouses, 179 chateaus, 105 cottages (there are no rooms in shared accommodation on the platform)63;  HomeExchange: 128 available listings64;  GuestToGuest: 650 available listings65;  LoveHomeSwap: 168 available listings66;  Booking.com: 2,137 available listings, among which 2,099 apartments, 30 holiday homes and 8 homestays (there are no rooms in shared accommodation on the platform)67;  Tripadvisor: 2,963 available listings, all of which rentals68.

58 In order to facilitate retrieval of the statistics, specific topics should be provided, in this instance it is: Services / Tourism 59 Excluding holiday dwellings for renting 60 AirDNA Florence. Available at: https://www.airdna.co/city/it/florence. Accessed on 20/06/17. 61 Snapshot of the Wimdu website for Florence. Available at: http://www.wimdu.com/florence. Accessed on the 20/04/17. 62 Snapshot of 9flats website. Available at: www.9flats.com. Accessed on: 20/06/17. 63 Snapshot of HomeAway website. available at: https://www.homeaway.com/results/keywords:florence. Accessed on 20/06/2017. 64 Snapshot of HomeExchange website. Available at: https://www.homeexchange.com/en/search/florence. Accessed on the 20/06/2017. 65 Information received from GuestToGuest during a phone interview on 24/04/2017. 66 Snapshot of https://www.lovehomeswap.com/preview?search=Florence%2C+Metropolitan+City+of+Florence%2C+Italy as of 24/05/2017. 67 Snaphsot of Booking. Available at: www.booking.com/florence. Accessed on 20/06/17. 68 Snapshot of https://www.tripadvisor.com/Hotels-g187895-Florence_Tuscany-Hotels.html as of 24/05/2017. 15

Task 4 – Annex 6 - Market Case study – Florence

This study does not make a distinction between primary and secondary residences, and between residences and holiday homes. This is because there is no indication on the collaborative short-term rental platforms of the type of residence the listing is. Even though platforms may indicate whether the listing is an apartment, house or other (e.g. castle, boat, bungalow, etc), it is not clear whether they are the owner’s primary or secondary residences. The same is true for rooms, which could be in a primary or secondary residence.

The number of available properties offered through collaborative short-term rental platforms is, therefore, 23,884. This is the sum of all rooms and properties offered through the collaborative short-term rental platforms considered in this study. The figure generally excludes accommodation provided via traditional means, such as hotels, hostels or bed and breakfasts. However, in certain circumstances, and bed and breakfasts managers list their properties on collaborative short-term platforms (e.g. AirBnB), and it is difficult to immediately distinguish between peers and professionals. While the figure for the number of available properties offered through collaborative short-term rental platforms tries to exclude professionals (e.g. by avoiding hotels/hostels from the counting on websites such as Booking.com, or by only considering “holiday rentals”, rather than “hotels” on TripAdvisor), it may nevertheless include some.

The sum of short-term rental properties in Florence should be taken as an approximation. First, it is difficult to list all collaborative short-term rental platforms due to the size of the accommodation offer. Second, attention must be paid to the duplication of listings, as hosts may advertise the same room or property across multiple platforms. Unfortunately, no adequate proxy as to the percentage of duplicate listings exists for Florence.

There is no available data for the number of available properties for long-term rental (vacant dwellings) on local, national or European publicly-available databases. Eurostat last recorded the number of vacant dwellings in Florence in 2011, when it amounted to 411,896 vacant dwellings69.

The table below provides an overview of the findings illustrated in this section. Table 5: Summary overview of number of available properties for short- or long- term rental in 2016 No. Indicators Number

A2 Number of rooms in primary residences70 2,229

A2 Number of entire primary and secondary residences71 21,603

Number of available properties for long-term rental A4 411,896 (vacant dwellings) Number of available properties offered through A5 23,884 collaborative short-term rental platforms

69 The number of accommodations: http://dati-censimentopopolazione.istat.it/Index.aspx?DataSetCode=dica_abit_pr 70 The number was calculated by summing up the number of rooms in shared apartments available on online platforms. 71 The number was calculated by summing up the number of entire properties (apartments, houses, etc) available on online platforms. 16

Task 4 – Annex 6 - Market Case study – Florence

2.3 Overview of occupancy

Data regarding the short-term occupancy rate for collaborative short-term rental platforms are only available for AirBnB, which will be used as a proxy for this sector.

In April 2017, the short-term occupancy rate for rooms/properties advertised online on AirBnB is estimated by AirDNA at 72.6%72. The occupancy rate fluctuated, following the tourism season, dipping in January and peaking in April (Figure 10). However, in comparison to 2016, occupancy rates in 2017 were higher by roughly 5% during the respective months. On average, the occupancy rate in 2016 was 54%. See Figure 10 below for the occupancy rates of AirBnB all listings and hotels in Florence.

Figure 10: Occupancy rate AirBnB all listings and hotel rooms

80,00% 70,00% 60,00% 50,00% 40,00% 30,00% 20,00% 10,00% 0,00%

Florence AirBnB Florence Hotel

Source: AirDNA data

Room occupancy of hotels in the region of Tuscany declined by 10% between 2012 and 2014 (Figure 11), but it picked up again in 2014 reaching 45%. Given that Florence is one of the biggest magnets in the region, the bed occupancy rate was slightly higher than the average, while the decline also less pronounced. In 2016, hotel occupancy in Florence reached 57%.73

72 Information retrieved from AirDNA.Co on 12/06/2017. The figure is a ratio of the total of available nights and the total of booked nights for 2016. 73 AirDNA data 17

Task 4 – Annex 6 - Market Case study – Florence

On AirBnB, according to platform data from 2016, guests stayed for 3.2 nights on average in Florence74. In comparison, the nightly rate for hotels in Italy was 375. Figure 11: Net occupancy rate of bedrooms in Tuscany

50,0

40,0

30,0

20,0

10,0

0,0 2012 2013 2014 2015

Source: Eurostat (Net occupancy rate of bed-places and bedrooms in hotels and similar accommodation (NACE Rev. 2, I, 55.1) by NUTS 2 regions (from 2012 onwards) [tour_occ_anor2])

The table below provides an overview of the findings presented in this section. Table 6: Summary overview of occupancy rates in Florence in 201676 No. Indicators Value Short-term occupancy rate for rooms/properties 54% (Florence) advertised online (AirBnB) A6 Short-term occupancy rate for hotel rooms 45% (Tuscany)

Average length of short-term rentals (AirBnB) 3.2 (Florence) A7 Average length of hotel stays 3 (Italy)

74 AirBnB (2016). Economic Impact Report Italy. Available at: https://italy.airbnbcitizen.com/new-study-airbnb-community-contributes-e3-4b-to-italian- economy/ 75 Average length of stay per guest in traditional accommodations in Italy: https://italy.airbnbcitizen.com/new-study-airbnb-community-contributes-e3-4b-to- italian-economy/ 76 Due to unavailability of statistics at the city level, the data available is presented: short-term occupancy rate for hotel rooms in Tuscany; and average length of hotel stays in Italy. 18

Task 4 – Annex 6 - Market Case study – Florence

3 Income and other tourism indicators

This section highlights the impact of the collaborative economy accommodation market on providers’ income and tourism in the city. In doing so, it aims to estimate the broader economic potential of the sector.

3.1 Income indicators

The revenues that Florence short-term accommodation providers earn from their collaborative economy activity are often additional to their main source of income. This section uses the income earned by typical AirBnB hosts as a proxy, given the limited data availability on other collaborative short-term rental platforms.

According to a report carried out by AirBnB, the total amount of economic activity brought by platform guests is EUR 169 million.77 Income from short-term rental activities amount to EUR 6,300 per year78 for the typical peer provider (median). Typical host on average rented 64 nights per listing in a year79.

Average revenues for AirBnB “entire place” listings fluctuate within the tourism season (Figure 12). Collaborative economy hosts, however, gain slightly more than traditional sector providers. Their revenue per room can be expected to be between EUR 30 and EUR 80, depending on the time of the year.80

Figure 12: Revenue for Airbnb entire place81

€ 90 € 80 € 70 € 60 € 50 € 40 € 30 € 20 € 10 € 0

Source: AirDNA data

The table below provides a brief overview of the income indicators identified in this section concerning AirBnB hosts in Florence.

Table 7: Summary overview of income indicators – Florence No. Indicators Value (EUR) Median income gained through short-term rental A8 6,300/year activities (AirBnB)

77 https://italy.airbnbcitizen.com/new-study-airbnb-community-contributes-e3-4b-to-italian-economy/ 78 Ibid. 79 Ibid. 80 AirDNA data 81 Entire Place ADR * Occupancy. Differing from the hotel industry, we consider entire place listings as a "room". 19

Task 4 – Annex 6 - Market Case study – Florence

3.2 Tourism indicators

In 2014, there were 2.56 million total stays in Florence with 2,080,240 hotel stays82 and 480,209 non-hotel stays83 with many tourists arriving from the US (as shown in Figure 13).84

Figure 13: 10 highest hotel stays in Florence by origin (2014)

Other Asia Russia Germany Brasil Spain UK France China Japan USA

0 50000 100000 150000 200000 250000 300000 350000 400000 450000

Source: Annuario Statistico del Comune di Firenze: http://annuario.comune.fi.it/dataset

2016 data on tourism arrivals and nights spent exist for AirBnB for Florence, and is taken here as a proxy for the broader collaborative short-term rental sector. In Florence, the two indicators sought, are the following: a) 2.08 million arrivals in tourist establishments in 2014, and 364,000 arrivals in AirBnB locations in 201685. b) 5.19 million nights spent in tourist establishments in 201486, and 1.16 million nights spent in AirBnB locations in 201687.

The table below summarises the main tourism indicators retrieved in this section.

Table 8: Summary overview of tourism indicators – Florence No. Indicators Value

Total number of tourists using AirBnB in 2016 364,000 B1 Total number of nights spent in AirBnB locations in 2016 1,16 million

Ratio of nights spent in AirBnB locations to nights spent in 22.4% traditional accommodation locations in 201688 (indicative) B2 Ratio of tourists using AirBnB accommodation to tourists using 17.4% traditional accommodation locations in 201689 (indicative)

82 Annuario Statistico del Comune di Firenze: http://annuario.comune.fi.it/dataset 83 Ibid. 84 Ibid. 85 https://italy.airbnbcitizen.com/new-study-airbnb-community-contributes-e3-4b-to-italian-economy/ 86 Annuario Statistico del Comune di Firenze: http://annuario.comune.fi.it/dataset 87 https://italy.airbnbcitizen.com/new-study-airbnb-community-contributes-e3-4b-to-italian-economy/ 88 Traditional accommodation data for 2014. 89 Traditional accommodation data for 2014. 20

Task 4 – Annex 6 - Market Case study – Florence

4 Impact on local communities

This section describes positive and negative implications of the collaborative economy accommodation offer on local communities.

4.1 Development of ancillary services

Collaborative economy tourism contributes to local economic development through increased spending on local businesses. In 2016, the Companies Register listed 136,676 companies in Florence, an increase of 1% in comparison with the previous year.90 At the national level, Florence is ranked 8th in terms of economic activity.

In 2013, the province of Tuscany was the 5th largest employer in the tourism sector in Italy, employing 72,000 workers91. The number of companies in accommodation and catering sector grew by 2% in 2015 and 4% in 2016.92 In terms of the number of businesses in the sector, Tuscany was in 4th place, having more than 14,000 companies, representing 8% of the national total93.

HomeExchange, in a 2013 study surveying its users, found that 67% of home exchangers in Italy prepare their own food (71% purchase organic food), 21% discover on their own, while 11% choose recommended by .94 This suggests that guests use local grocery shops and prefer to discover places by themselves, as opposed to choosing only well-treaded establishments. In addition, 27% of home exchangers in Italy participate in eco-tourism, while 88% say that environmentally friendly tourism is important.95

An extensive survey of Florence’s residents and businesses, taken in 2016, measured the social, cultural, economic and infrastructural impacts of tourism on the city.96 According to 75% of its respondents, tourism is an opportunity for new business development and job opportunities for residents. In addition, 74% agreed that tourism makes the city particularly attractive for investment.97 Given the important contribution of online collaborative short-term rental platforms in attracting tourism to the city in recent years, collaborative economy accommodation sector is a significant part of the picture.

4.2 Housing supply changes

There is no quantitative data available which would measure the impacts of collaborative short-term rental platforms on housing supply. However, according to the findings of Florence resident and business survey taken in 2016, increasing numbers of tourists has impacted the property market in the city.98 82% of respondents agreed that tourism causes a rise in property prices in Florence, while 64% of respondents thought that tourism causes residents to live outside the historic centre of Florence. Overall, according to respondents, growing tourist volumes compound housing supply by increasing prices and forcing residents outside the city centre.

90http://www.fi.camcom.gov.it/default.asp?idtema=1&page=informazioni&action=read&index=1&idtemacat=1&idcategoria=6460&open=1&idinformazione=30 995 91 Ibid. 92 Ibid. 93 Ibid. 94 HomeExchange (2013). My House is Yours. A Worldwide Study on Home Exchangers’ Profiles and Motivations. Available at: http://www.oits- isto.org/oits/files/resources/401.pdf 95 HomeExchange (2013). My House is Yours. A Worldwide Study on Home Exchangers’ Profiles and Motivations. Available at: http://www.oits- isto.org/oits/files/resources/401.pdf 96 ETOA, SCT & Life Beyond Tourism (2016) Il Turismo a Firenze: Il Punto di Vista dei Residenti. Comune di Firenze. 97 Ibid. 98 ETOA, SCT & Life Beyond Tourism (2016) Il Turismo a Firenze: Il Punto di Vista dei Residenti. Comune di Firenze. 21

Task 4 – Annex 6 - Market Case study – Florence

4.3 Inhabitants’ perception of collaborative short-term rental platforms

In 2016, an extensive survey of the residents of Florence measured their perceptions about the impact of tourism on the city.99 Respondents agreed that tourism:  “provides residents of Florence with opportunities to develop new contacts and cultural exchanges” (62%);  “promotes the preservation of historic palaces and other cultural sites in Florence” (61%);  “increases resident’s awareness of Florence as a city with heritage” (56%);  “promotes the development of culture, cultural activities and entertainment that also benefited the residents of Florence” (54%);  “strengthens the sense of belonging and pride of residents of Florence” (54%).

Crucially, the respondents did not think (68%) that tourism makes Florence less secure.100 Overall, growing tourism is perceived as providing not only economic benefits (section 4.1), but also boosts culture and strengthens identity of Florence. Given that collaborative short- term rental platforms have a significant presence in Florence, these results could also be applicable to the collaborative economy accommodation sector, but there is no record measuring it.

4.4 Impact on public services

In 2016, an extensive survey of the residents of Florence measured their perceptions about the impact of tourism on the city.101 Respondents agreed that tourism:  “causes a general increase in prices of goods and services for residents of Florence” (80%);  “causes congestion of urban spaces and shortage of services for residents of Florence” (61%);  In contradiction to the answers above, respondents did not think that “tourism takes away resources for other important projects for the city and the residents of Florence” (50%).

There is no record of impact on public services.

99 ETOA, SCT & Life Beyond Tourism (2016) Il Turismo a Firenze: Il Punto di Vista dei Residenti. Comune di Firenze. 100 Ibid. 101 Ibid. 22

Task 4 – Annex 6 - Market Case study – Florence

5 Future developments

On 24th of April 2017, the Italian Government introduced a new tax scheme for the collaborative economy in the accommodation sector. Article 4 of the new Financial Law102 specifies that the collaborative economy providers (only the peers and not professionals103) will be subject to a 21% flat tax rate. The online collaborative short-term rental platforms will be responsible for automatically collecting the money from peers and transferring it to the Italian Revenue Agency (i.e. sostituto d’imposta)104. The new tax scheme is effective since 1st of June 2017. Article 4 of the Financial Law also provides a definition of short- term letting: “A short-term lease for residential real estates - including also the cleaning services - made by a natural person (persona fisica), outside his business activity, signed directly or indirectly (i.e. trough real estate intermediaries or online platforms), with duration of not more than 30 days”.

102 (Disposizioni urgenti in materia finanziaria, iniziative a favore degli enti territoriali, ulteriori interventi per le zone colpite da eventi sismici e misure per lo sviluppo. (17G00063) (GU Serie Generale n.95 del 24-4-2017 - Suppl. Ordinario n. 20) 103 From a fiscal point of view there is a distinction between a lessor acting in his/her private capacity who carries out an occasional activity (short-term letting) renting out one room/apartment and a lessor acting in his/her professional capacity renting out more than one apartment. (Presidential Decree 131/1986 and Law 580/1993). The former would be considered “peer”, the latter “professional”. 104 http://www.gazzettaufficiale.it/eli/id/2017/04/24/17G00063/sg 23

Task 4 – Annex 6 - Market Case study – Florence

6 ANNEX 1: List of references

Reports: AirBnB. Overview of the AirBnB Community in Italy. Available at: https://www.AirBnBcitizen.com/wp- content/uploads/2016/05/overview_of_the_AirBnB_community_in_italy.pdf VVA Europe and Spark research Qquestionnaire. Study on the Assessment of the Regulatory Aspects Affecting the Collaborative Economy in the Tourism Accommodation Sector in the 28 Member States (580/PP/GRO/IMA/15/15111J). 21 April, 2017. ETOA, SCT & Life Beyond Tourism (2016) Il Turismo a Firenze: Il Punto di Vista dei Residenti. Comune di Firenze.

Articles: Freschi, A. L. (2017) “Tourism, the new regional law: consolidation Act on the regional tourism system” Regione Toscana. Available at: http://www.regione.toscana.it/-/turismo- la-nuova-legge-regionale-testo-unico-sul-sistema-turistico-regionale-

Official website and statistics: Official City of Florence’s website, providing information on governance and administrative aspects. Available at: http://en.comune.fi.it/administration/municipality/city_mayor.htm Official City of Florence’s website, providing information on governance and administrative aspects. Available at: http://en.comune.fi.it/administration/municipality/board_and_council.htm Official City of Florence’s website, providing information on governance and administrative aspects. Available at: http://en.comune.fi.it/administration/municipality/districts.htm Official City of Florence’s website, providing information on governance and administrative aspects. Available at: http://en.comune.fi.it/administration/housing/housing.html Official City of Florence’s tourism website, providing information on the tourist contact center. Available at: http://www.firenzeturismo.it/en/informazioni-utili-2/informazioni- turistiche-2/3119-contact-center-florence.html Official City of Florence’s tourism website, providing information on available accommodation in the city. Available at: http://www.firenzeturismo.it/en/tools-2.html Snapshot of HomeAway listings as of 26/05/2017. Available at: https://www.homeaway.co.uk/results/refined/keywords:florence/page:1 Snapshot of Wimdu listings as of 25/05/2017. Available at: http://www.wimdu.co.uk/florence Snapshot of 9Flats as of 25/05/2017. Available at: https://www.9flats.com/florence- florence-tuscany-italy Snapshot of HomeExchange listings as of 25/05/2017. Available at: https://www.homeexchange.com/en/search/Florence Snapshot of LoveHomeSwap listings as of 25/05/2016. Available at: https://www.lovehomeswap.com/location/italy/tuscany/florence Snapshot of Booking.com listings as of 25/05/2017. Available at: https://www.booking.com/city/it/florence.en- gb.html?label=socnet_fb_fp_20121019Florence

Snapshot of Tripadvisor listings as of 25/05/2017. Available at: https://www.tripadvisor.co.uk/Tourism-g187895-Florence_Tuscany-.html Annual Statistics of the Municipality of Florence. Available at: http://annuario.comune.fi.it/dataset

Legislation Extra-hotel Touristic Rental - Regional Law of the 20th of December 2016 No. 86, Testo unico del Sistema turistico regionale. Official Bulletin of the Tuscan Region no. 57 of 28.12.2016. Available at: http://www.consiglio.regione.toscana.it/upload/pdl/2016/pdl135_burt.pdf. Legislative Decree no. 23 of 14.03.2011. Available at: http://servizi.comune.fi.it/servizi/scheda-servizio/imposta-di-soggiorno Press release of the Council of Ministers no. 14 of 02.23.2017. Available at: http://www.regioni.it/news/2017/02/24/comunicato-stampa-del-consiglio-dei-ministri-n- 14-del-23-02-2017-501281/

European Commission

Study on the Assessment of the Regulatory Aspects Affecting the Collaborative Economy in the Tourism Accommodation Sector in the 28 Member States

Luxembourg, Publications Office of the European Union

2018 – 25 pages

ISBN 978-92-79-84011-1 doi: 10.2873/97716

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doi: 10.2873/97716