Full version

PICTURE
Pro-active management
of the Impact of Cultural Tourism
upon Urban Resources and Economies
Deliverable n° 13
Deliverable title
Impact of Cultural Tourism upon
urban economies
Annex 4: Bergen
FEEM
Task n° 1.4
Task Leader: FEEM
Task partners: FEEM, QUB, ARCCHIP
Authors: Elena Bellini, Barbara Del Corpo, Ugo Gasparino, William Malizia
(FEEM),
Siri Elvestad, Siri Sandtorv Heimark, Tone Merete Takvam
(OWHC, City of Bergen)
Date: January, 2007
The PICTURE project is financed by the European Commission, Sixth Framework Programme of
Research
Specific Programme: Integrating and strengthening the European Research Area
Activity: Specific activity covering policy-orientated research under “Policy support and anticipating
scientific and technological needs”
Priority 3. Underpinning the economic potential and cohesion of a larger and more integrated European
Union
Topic 3.6. The protection of cultural heritage and associated conservation strategies
Task 5: Cultural heritage and tourism. Contract n° SSP1-CT-2003-502491
Summary
This Annex presents the results obtained in the framework of the economic assessment of
tourism on the Norwegian case study of Bergen (Hordaland).
Due to the historical role of the sea in the economic development of the region,
Hordaland is Norway’s leading county in fish farming; small factories are mostly
specialized in the food industry related to fishery. Hordaland and Bergen play also a
leading role in Europe in the oil industry: 4/5 of the oil and gas produced in Norway, in
third place among the world’s leading net crude exporters, come from the fields off the
coast of Hordaland. Hordaland has also strong metallurgical and mineral industries.
Another important sector is represented by electronics, microwave communications and
satellite communications. Bergen offers over 115,000 jobs, with more than 20,000 small
and medium-sized businesses registered in the city itself. Tourism is a major sector of the
economy. The economic turnover pf tourism is estimated to 600 million. €a year. There
are approximately 1.3 million hotel nights a year and 6,000 people are employed in
activities related to tourism.
Bergen is a destination of cultural tourism, stressing on:

Art and history – the harbour bearing testimony of the history of the city and the
th
wooden houses dating from the early 19 . In 1979 UNESCO included the Bryggen
(the harbour) in the World Heritage List;

Nature and landscape – Bergen, “the Gateway to the Fjord”. The city is placed
between Sognefjord (the longest) and the Hardangenfjord (the most spectacular fjord);

Events – above all, the Bergen International Festival.
Cruise journeys dominate the picture of the peak season in Bergen. Tourists on cruise
visit Bergen for cultural or for leisure-environmental reason. The number of cruise ships
to Bergen has been constantly growing. Three cruise ships per day which stop 10 hours
on average, with a total of about 150,000 visitors per year.
This Annex is dedicated to a quantitative analysis of the economic impact of tourist
expenditures on the local economy of Bergen. After an introduction on the relevant
geographical and historical features of the municipality (Section 2), the economic
structure of Bergen and its surrounding region (Section 3), an analysis of the main
characteristics of tourism (in terms of attractions inventory, image of the city, typology of
tourism in terms of main features and motivation for trips) and its role, governance and
recent trends (Section 4), the deliverable presents (Section 5 and 6) the main results of the
application of the ‘three-step analysis’ for the assessment of the economic impact of
tourism on local economy presented in the Main Deliverable.
The analysis mainly aims at tracing the flow of tourist spending, in order to identify its
impact, e.g., on sales, income and employment (directly or indirectly driven by tourism).
The economic impact analysis focuses therefore on the actual flows of money related to
market transactions and is therefore only ‘a part of the whole story’.
2
In order to assess the economic impact:

a survey on tourists visiting Bergen was conducted (face-to-face interviews, performed
in the only peak period as, due to climatic conditions, tourism in the off-peak period is
rather negligible) to estimate the scale and variety of spending by different profiles of
tourists;

the spending patterns derived from the survey were then applied to an Input-Output
model of the Norwegian economy (and a re-scaled version, referring to the Hordaland
County) to quantify the effects on sales, incomes and employment.
As typical of any Input-Output based approach, the overall monetary effects of tourism
activity emerge as disaggregated over three components:
-
the direct impact (the total expenditure on the purchase of goods and services by
tourists – as emerged from the site-specific survey);
-
the indirect impact (the effects associated with the enhanced demand from ‘tourism
industries’ to local suppliers of goods and services);
-
the induced impact (the economic activity resulting from the additional consumer
spending, which takes place when the additional income earned directly or indirectly
by local households is spent).
The overall impact on economy is the sum of the direct, indirect and induced
contributions. By means of indirect and induced effects, changes in tourist spending can
impact virtually every sector of the economy in one way or another.
Although limited in perspective, a quantitative knowledge of the monetary impact
provides a basic ingredient towards the identification of the ‘most appropriate’ tourism
marketing and management strategies and should be taken in due consideration in
national, regional and municipal tourism planning.
3
Table of Contents
1
2
3
4
5
6
7
8
9
Introduction ................................................................................................................. 5
General information .................................................................................................... 6
2.1
Geography........................................................................................................... 6
2.2
History................................................................................................................. 7
The Economic structure .............................................................................................. 9
3.1
Economy in the County ...................................................................................... 9
3.2
Economy in the city of Bergen ......................................................................... 10
Tourism and the tourism industries........................................................................... 12
4.1
Tourism in Hordaland ....................................................................................... 12
4.2
Tourism in Bergen ............................................................................................ 13
4.2.1
Urban built heritage .................................................................................. 14
4.2.2
Natural heritage......................................................................................... 17
4.2.3
Urban intangible cultural heritage ............................................................ 18
4.2.4
Recent trends in tourism ........................................................................... 19
4.2.5
The tourism local policy ........................................................................... 22
The impacts of tourism on the urban economy ......................................................... 25
5.1
Scope and methodology.................................................................................... 26
5.1.1
Induced effects: closure with respect to households ................................. 29
5.1.2
Regional effects: re-scaling of the I-O matrix .......................................... 29
Bergen survey. Main findings ................................................................................... 31
6.1
Profiling tourists: qualitative analysis of the sample ........................................ 32
6.1.1
Cultural and non-cultural tourists in Bergen ............................................. 34
6.1.2
Cruising and non-cruising tourists in Bergen ........................................... 40
6.2
Direct impact of tourists’ expenditures in Bergen ............................................ 46
Economic impact ...................................................................................................... 58
7.1
Sale multipliers ................................................................................................. 59
7.2
Income and Employment multipliers................................................................ 63
Conclusions ............................................................................................................... 66
Bibliography ............................................................................................................. 69
4
1Introduction
This Annex reports the results of the case study on Bergen. The Annex is part of
Deliverable D13, Task 1.4.
Section 2 summarises the relevant geographical (including access and infrastructure) and
historical features of the municipality.
Section 3 discusses the economic structure of the city. It will provide an overview of
recent economic performance, e.g., in terms of unemployment rate and growth in GDP
and employment. It also describes the sectoral composition of the economy.
Section 4 firstly discusses the role of tourism and its importance, as perceived by local
actors (policy-makers, businesses, media, public at large), for future scenarios in the city
and in the surrounding region. Secondly, it analyses the main characteristics of tourism in
the city (attractions inventory, image of the city, recent trends in tourism growth,
typology of tourism in terms of main features and motivation for trips) and the policy
approaches to the development of local tourism.
Finally, Section 5 and Section 6 report and discuss the results of the three-step analysis
for the assessment of the economic impact of tourism on the local economy presented in
the Main Deliverable.
5
2General information
2.1 Geography
The city of Bergen is situated in the Hordaland County, in the south-west of Norway.
Hordaland confines to the north with the County of Sogn of Fjordane, to the east with the
Counties of Buskerud and Telemark, to the south with the County of Rogaland and to the
west it is surrounded by the North Sea.
The Hordaland County includes 33 municipalities with a population of more than
438,000 inhabitants, a total surface of 15,634 km² and a population density of just 28
inhabitants/km² (2002 census).
Figure 1: Norway counties
Source: Wikimedia Commons, http://en.wikipedia.org/wiki/Image:Norway_counties.svg
Bergen is the capital of western Norway and it is Norway’s second largest city. Bergen
has 243,960 inhabitants (October 2006), an area of 465 km² and a population density of
525 inhabitants/km². Bergen is a rather ‘multi-ethnic’ city: here foreign population
represents 7.6% of the residents. Among these, 5.6% do not come from western
countries. These data correspond to the national average, but are less compared to Oslo.
6
The County of Bergen thus lies between a group of mountains known collectively as de
syv fjell (“the seven mountains”) 1 and the sea, in an area characterized by spectacular
fjords and many small islands. More specifically, the city is placed between Sognefjord
(the longest) and the Hardangenfjord (the most spectacular) fjords. That is why the city is
often celebrated as the “Gateway to the fjords”.
Bergen’s climate is renowned for its plentiful rainfall (248 raining days were recorded in
2005). In average, it rains two out of three days, and there are long periods of
uninterrupted rain. The yearly average of precipitations is 2250 mm, three times over the
national average. Winters are very cold whereas summers are fresh. Nevertheless, in
comparison with the rest of the nation, the climate is rather mild and, thanks to the Gulf
Stream, Bergen has the privilege of being one of the warmest cities in Norway. Average
temperature ranges in fact from 20-25° C during summer and 0-5° C in winter. 10° C and
rain can happen both in January and July.
Concerning the transportation system and the access to the city, Bergen has an
International Airport (Flesland) with direct flights to many European cities. Every year
around 4 million air travellers pass through the Bergen Airport. The Bergensbanen
railways connect the city with the most important destinations in South Norway. Bergen
can be also easily reached by highway, which is free of charge. The highway E16 runs to
Voss, Valdred and Oslo. Along the coast, highway E39 runs south to Haugesund,
Stavanger and Kristiansand, and north to Forde, Alesund, Molde and Trondheim. Bergen
harbour is very dynamic: around 150,000 passengers land in Bergen every year. There are
frequent connections with Haugesund, Stavanger, Sognefjorden, Hirtshel in Denmark,
Newcastle in England, Torshan in the Far Oer Island and Reykjavik in Iceland.
2.2 History
Bergen was founded on the north side of the bay of Vǻ
gen by king Olaf III Kyrre, around
1070. In the past Bergen was in fact the political capital of Norway.
However, archaeological investigations over the last 15 years have proved evidence of
activity in Vǻ
gen prior to Olaf Kirre’
s time. The remains of a 10th century wharf have in
fact been found, besides large pits and traces of fields.
The city’s oldest urban development and financial centre throughout medieval times was
located on Bryggen (the quayside of Bergen). The oldest town was divided into two builtup areas, physically separated by a steep bluff. As the harbour basin was gradually
drained, the settlement expanded in a continuum along the east side of Vǻ
gen.
The harbour was already in that period one of the main factors of the town’s growth, and
through time it made Bergen one of Northern Europe’s most important ports. The city
became a natural nexus of the coastal trade with western and arctic Norway and
international maritime commerce. Commercial sailing vessels from the Faeroes, the
British Isles, the Baltic and continental North Sea ports moored on Vågen in front of the
wharves.
In 1349 the Black Death was brought to Norway by the crew of an English ship.
1
The first to name them “the seven mountains” was Ludvig Holberg (considered the founder of modern
Danish literature, writer and playwright, born in Bergen in 1684), inspired by the seven hills of Rome.
7
Around 1360 Bergen became one of the Hanseatic League’s four most important bureaus,
with the status of Kontor (i.e., Office) or commercial enclave. The German hanseatic
merchants lived in their own separate quarter of the town. Through the extraction of royal
privileges, the German merchants acquired control of Norwegian trade for the following
four centuries. However Bergen remained one of Europe’s most important ports, a
position it has held right up to our days. Fish dried in North Norway was the country’s
most important export commodity. On the other side, Norway imported weath from
England and the Baltic countries.
In the XV century the city was attacked several times by the Victual Brothers (pirats
involved in the naval wars between Danemark – supported by the Hanseatic League –
and Sweden); in 1429 they succeeded in burning the royal castle and much of the city.
Around the time of Reformation, the king forced the German merchants either to become
Norwegian citizens or to leave the country: the German influence started to diminish.
Therefore during the XVI and XVII centuries the Norwegian government gained stronger
control over domestic and international trade.
A major fire in 1702 destroyed most of the medieval wooden buildings. However, the
majority of the buildings were rebuilt generally on the old sites and frequently on the old
foundation walls.
Bergen retained its primary role over trade in Norway until 1789. On 17 October 1754,
the Norwegian Kontor was set up to replace the German Kontor. The old system
remained virtually unchanged, with the Norwegian Kontor adopting the Hanseatic
regulations and methods of trade and with German remaining the daily language.
Bergen remained the biggest city in the Nordic countries and Norway’s biggest city until
1850, when it was overtaken by Oslo. The disbanding of the Norwegian Kontor on 31
December 1899 signalled the end of an old and unique way of trading.
After the half of the XIX century the trade of stockfish was replaced by industrial
production. Bryggen became unsuited to the requirements of modern and rational
transportation and storage of goods. As a consequence, the harbour was gradually
modernized.
Between the second half of the XIX century and the First World War, some of the major
bank complexes were built along Vagsalmenning. The strong growth in trade and
industry resulted in an increase of population: from 17,000 inhabitants in 1855 to 103,500
inhabitants in 1920. The population of Bergen was outnumbered only by Oslo.
In 1916 part of the city centre was destroyed by a devastating fire. In addition to that in
1944, during the German occupation, a German warship anchored off the Bergenhus
fortress, filled it with explosive and blew it up. The city was also subject to some allied
bombing raids, aiming at German naval installations in the harbour. Many people were
killed and historic buildings damaged. However the centre of the city was reconstructed,
preserving the typical conformation of medieval buildings.
In 1972 Bergen was unified with neighbouring boroughs (Arna, Fana, Laksevåg and
Åsane), thereby abolishing its county status and getting its presents boundaries.
8
3The Economic structure
3.1 Economy in the County
The Hordaland County is characterized by a solid economy and a high standard of living.
It is one of richest counties of Norway.
Trade and industry in Hordaland is characterized by multiplicity. The county can boast a
wide variety of industries, mostly consisting of small or medium-sized companies, often
with long traditions of doing business internationally.
The economy is well developed in every sector: agriculture, industry and tertiary sector.
Hordaland is the leading county in fish farming. In 2003 155 fish farms in Hordaland
produced 94,121 tons of salmon and 17,147 tons of trout (19% of the total Norwegian
production of salmon and trout). More than 80% of the production is exported, the most
important markets being Denmark, France, Japan and Germany.
Large quantities of high-quality fruit is gathered from some 550,000 trees every autumn.
As the most important fruitgrowing county in Norway, Hordaland produces 1/3 of the
Country’s apples and pears, and 70% of the cherries (Hordaland City Council, 2004, pp.
4-5).
The county is also an industrial area, characterised by industries of different dimensions:
many small and medium enterprises, but also some big enterprises working in the field of
oil and gas extraction. Norway’s net export of crude oil and petroleum products is about 3
million barrels per day. This puts Norway in third place among the world’s leading net
crude exporters. 4/5 of the oil and gas come from the fields off the coast of Hordaland.
Bergen is in fact one of the biggest oil poles in the north of Europe. Hordaland has also
strong metallurgical and mineral industries producing ferrous alloys, aluminium, calcium
carbide, zinc and ilmenite. Beside these, small factories are specialized in the food
industry related to fishery. Another important sector is represented by electronics,
microwave communications and satellite communications.
Finally, tourism plays a major role (see below, p. 12).
Total 2003
Agriculture, hunting and forestry
Extraction of crude petroleum and natural gas
Manufacturing and Mining
Electricity, gas and water supply
Construction
Wholesale and retail trade, hotels and restaurants
Transport, storage and communications
Financial intermediation
Real estate, renting and business activities
Public administration and defence, compulsory social security
5,896
3,181
28,059
1,876
14,525
36,628
15,621
5,370
20,700
13,093
9
Education
Health and social services
Other social and personal activities
Unspecified
Hordaland county
18,539
41,786
7,852
1,254
214,380
Table 1: employment by sector in Hordaland. Employed persons 16-74 years old, 4th quarter 2003
Source: Hordaland City Council, 2004, p. 4
As regards to the sectoral composition of economy in 2003, 6% of the regional GDP was
represented by the primary sector. This record is lower than the national average, which
is 9%. In fact the county of Hordaland is mountainous and not much cultivable. By
contrast, the secondary sector plays a much more important role in the economy,
employing 22% of the total working population (higher record in respect to the national
average), mostly thanks to the manufacturing and mining subsection. In particular, about
28,000 persons (Table 1) are employed in the manufacturing industry in Hordaland (only
the neighbouring county of Rogaland employs more – 32,000).
Finally, Hordaland is a very important finance pole.
In recent years the Hordaland County has maintained a high standard of per capita GDP.
The county has indeed the highest per capita GDP in Norway (33,084 €), after the
counties of Oslo (64,708 €) and Rogaland (34,063 €).
3.2 Economy in the city of Bergen
The city reflects only partially the economic pattern of Hordaland.
Bergen is one of the largest agricultural areas in Hordaland.
The workers employed in the secondary sector are 18.9% (against 22% in the county). As
in the rest of the county, the most relevant industries are the fishing industry (aquaculture
and food), machinery and equipment, textiles, steelmaking and electrotechnical industry.
Moreover, Bergen is the main heliport for the connections with the oil platforms in the
North Sea. The seat is consequently the seat of industries working on oil, drilling and gas.
Bergen also has a strong research environment and a varied and high-tech industrial
sector.
As most of modern cities, Bergen has a tertiary vocation, absorbing 80.3% of the working
population. The city is seat of important banks and of Norway’s largest commercial TV
station headquarters (TV 2). Nearly 100 million tons of goods exported from the Bergen
region each year makes Bergen’s intermunicipal harbour Norway’s largest port (handling
more than 50% of all cargo handled in Norway in 2005) and the third in Europe. 40% of
Norway’s exports are created in the region with most income being generated by oil and
gas from the North Sea as well as the maritime and fishing industry.
Noteworthy is the well-established infrastructure between industry, research and
educational institutions, and government organisations. Here, there is an enormous
diversity of international level research expertise within the Bergen area, particularly in
10
the following fields: sustainable exploitation of marine resources, food safety and
traceability, aquaculture and fish health, environmental and ecological management, and
regulations and economy.
Bergen offers over 115,000 jobs, with more than 20,000 small and medium sized
businesses registered in the city itself. Unemployment rate is equivalent approximately to
4% (City of Bergen, 2006c).
11
4Tourism and the tourism
industries
4.1 Tourism in Hordaland
After some years with a stable market, in 2005 Norway participated in the international
growth in the tourist trade, overnight stop, transport and service. It is the home market
that increases most, followed by the English and the German.
Hordaland is one of most visited destinations in Norway. The capital Oslo, however, has
the leadership of tourist presence.
Hordaland is the third county in Norway (after the Counties of Oslo and Oppland) as
regards number of overnights in hotels and similar structures (
Table 2 ).
Hordaland
Oppland
Oslo
1995
of which
Norwegians
2004
of which
Norwegians
1,569,665
2,241,598
2,048,564
60.20%
60.09%
59.94%
1,749,664
1,846,130
2,742,274
63.61%
71.66%
62.21%
Table 2: overnights in Hordaland, compared to the most visited counties of Norway
Between 1995 and 2004 the county with the biggest positive gap in overnights
development is Oslo: the overnights in the 2004 are almost 2.8 millions, with an increase
of 34%. The increase in Hordaland County is inferior: about 180,000 units (+11.5%). The
Oppland county, on the other side, has inverted the trend. The decrease can be explained
by the decline of foreign tourism, after the boast linked to the Olympic Games
(Lillehammer, the county capital city, was the host city of the 1994 Olympic Winter
Games). Hordaland and Oslo, amongst all counties, show the bigger percentage of
foreign visitors, who represent about 37% of total presence. However, the percentage of
foreign tourists in Hordaland has only minimally increased between 1995 and 2004.
As regards the motivation for overnight stay (Table 3), in Hordaland 47% of total
overnight stays must be attributed to conference and work, compared to 61% in the Oslo
County. Such proportion has remained constant in the course of the last years. On the
contrary, in Oppland 80% of the visits take place for holidays and entertainment,
compared with 40% and 50% in Oslo and Hordaland, respectively. This is easily
explained by the fact that Oppland is mainly a winter sports resort.
12
Hordaland
Conference and
work
Holiday
Total
721,227
1995
Oppland
Oslo
2004
Oppland
Hordaland
435,998 1,409,564
815,748
848,438 1,805,600
639,000
1,569,665 2,241,598 2,048,564
Oslo
368,033 1,672,123
933,896 1,478,097 1,070,151
1,749,644 1,846,130 2,742,274
Table 3: motivation for overnight stays in Hordaland, Oppland and Oslo counties
Hordaland presents a high receptive capacity, even though the number of hotels is
decreasing (Table 4).
Difference
1995/2004
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
(%)
Hotels
Camping
sites
Dwellings
Other
107
41
110
41
110
44
115
57
114
55
109
55
109
53
103
51
100
49
103
48
-3.7%
+17%
-23
-23
-23
14
85
14
84
14
77
14
77
14
77
13
75
14
76
-+230%
Table 4: number of accommodation facilities per typology
Source: Statistikal Sentral Byra, 2005
Hotels of The Hordaland County are mainly small (1-74 rooms –
Table 5).
Number of rooms
Number of facilities
0-49
50-74
75-99
100-149
150-199
200 or more
Total
32
25
18
12
6
21
114
Table 5: hotels in Hordaland, 1999
4.2 Tourism in Bergen
Bergen is a destination of cultural tourism, stressing on:

Art and history (the harbour bearing testimony of the history of the city and the
wooden houses dating from the early 19th);
13

Nature and landscape (Bergen, “the Gateway to the Fjord”);

Events (above all, the Bergen International Festival).
In the following sections we will briefly describe Bergen’s main cultural tourism
attractions.
4.2.1 Urban built heritage
Bergen is well-known for the history of its harbour: the Bryggen. It encloses the
economic and cultural heritage of the city of Bergen, being the heart of city still today.
Thanks to its important historical role and to the spectacular wooden houses dating from
the early 19 th (still capable of transmitting a medieval feel to their visitors), in 1979
Bryggen was inscribed by the UNESCO in the World Heritage List. Today Bryggen is a
living illustration of the city’s history, with 61 protected buildings, covering about 13,000
2
m.
The Bryggen museum is based on the findings of the archaeological excavations carried
out in 1955 and 1972. Here the foundations of the oldest buildings in Bergen were found.
The museum displays ceramics, runic inscriptions, artefacts, etc.
But alarming problems are connected with the Bryggen site: the area is sinking, as the
houses are built on fillings. Bergen is particularly susceptible to rain and dramatic
climate. Both heavy rainfalls and spring tides can cause occasional floods at the Bryggen
site, affecting dramatically the buildings situated in the front. This adds to the already
existing tasks of protection of and of passing on of the cultural heritage and history of the
Bryggen site.
Figure 2: wooden houses at Bryggen
Source: Wikimedia Commons, http://en.wikipedia.org/wiki/Bergen
The Royal Residence in Bergen (Gamlehaugen) was the dwelling of the Norwegian King
when he officially visited the city. The building seems a Scottish castle and it was built in
1910 for the prime minister Christian Michelsen. Only in 1925 the government bought
the building and gave it to the King. Crown Prince Haakon lived there while studying at
the Naval Academy.
14
Figure 3: the Royal Residence
Source: Wikimedia Commons, http://en.wikipedia.org/wiki/Bergen
The Hakon’s hall is the largest and most impressive building of the royal residence in the
XIII century. Håkon’s Hall took its name from King Håkon Håkonsson, and was erected
between 1247 and 1261. It was built to host important celebrations of the monarchy and
the realm, but also for practical daily use. From the late Middle Ages onwards, Norway
was without a resident monarchy, so the original functions of the hall lapsed. In the 1520s
it was indeed used for storage purposes. But it was precisely this storage function which
allowed it to survive under various roof-forms, until about 1840, when it was
rediscovered for what it had originally been. In 1944 a German munitions ship exploded
in the harbour just below the building. The Hall caught fire, and it was so damaged that
only the walls remained. The present internal equipment of the building is the result of
the following restoration.
Near the Hakon’s hall is St. Mary Church, the oldest building of Bergen. It was built in
the first half of the XII century, and represents one of the most outstanding Romanesque
churches in the Country. The pulpit is the pride of the church and it is considered the
richest example of Baroque decorative art in Norway.
Bergen Art Museum is one of the largest art museums in Scandinavia. In three buildings
it offers a notable collection of Norwegian and international paintings from the XV to the
XX century. It is a large collection of the more renowned contemporary artists of Europe.
Here there are artworks by Paul Klee, Pablo Picasso, Miro, Kandinsky, Munch, and more.
In particular, the Rasmus Meyers Collection contains main works from Norwegian art
dating back to the XVIII century up to 1915 (such as J. C. Dahl, Tidemand and Gude,
Werensldold, Chr. Krogh), as well as a notable collection of Edvard Munch.
The Bergen Museum hosts an interesting collection of cultural history, with the
attestation of the Norwegian history from the prehistoric times to present, through the
medieval age. The museum includes archaeological artefacts, utensils, folk art objects
from urban and rural areas. There is also an extensive ethnographic collection from
various parts of the world. A large section is devoted to the Viking History; the museum
hosts many exhibitions on the Viking life stile in the past.
15
The Rosenkrantz Tower is a medieval building erected by the governor of the Bergen
Castle, Erik Rosenkrantz. It served as a combined residence and fortified tower to
Bergen. It offers an astonishing view on the seafront.
Figure 4: the Rosenkrantz Tower
Source: Wikimedia Commons, http://en.wikipedia.org/wiki/Bergen
The Hanseatic Museum is situated in one of the old trade houses at Bryggen. The
building is the only one in the area where the original furniture, dating back to the XVIII
and XIX centuries, has been preserved: in fact the area was destroyed many times by fire.
From 1360 until 1746 the Hanseatic League had in Bryggen its foreign office. The
tenements in Bergen consisted of several smaller trade houses, each run by a merchant
with a journeyman and apprentices. The Hanseatic merchants had both their living rooms
and their storage room in the same house. The museum shows how life was like in the
trade houses in the last years of the German Office.
The Bergen Cathedral (Domkirken) has a long and turbulent history: in fact this building
was destroyed many times by fire too. In 1150 the building was very small, and the
Franciscan friars were granted the use of the church. The building was heavily damaged
by fire in 1248, but the benevolent King Magnus gave the Franciscan friars a generous
donation, which enabled them to build a new beautiful church. Then, because of the
Lutheran Reforms the church was abandoned and ruined. Only in 1880 a great restoration
by the architects Christi and Blix gave the church its present shape.
A city, where the sea represents a fundamental element of life and development, cannot
lack a Maritime Museum. Bergen Maritime Museum is in the centre of Bergen. The
museum preserves the memory of seafaring in Bergen and describes (through an
interactive visit where it is possible to use library, photo service, ship register and films)
its development and importance. The museum also features a spectacular exhibition of
Viking ship models.
The Old Bergen Museum (Gamle Bergen) is an open air museum with more than 40
wooden houses, representative of Bergen architecture in the XVIII and XIX centuries.
The houses still have got the original furniture dating from the XVIII, XIX and XX
centuries, and give a picture of life in a small town with its dwellings and shops (baker,
barber, dentist, photographer, etc.).
16
Fantoft stave church (Fantoft stavkirke) is a reconstructed stave church in Fana, Bergen.
It was originally built in Fortun, a village near the eastern end of Sognefjord around 1150.
In the XIX century this church was threatened by demolition as were hundreds of other
stave churches in Norway. So, it was bought by consul F. Gade and saved by moving it in
pieces to Fantoft near Bergen in 1883. On the 6 June 1992 the church was totally
destroyed by arson. Reconstruction of an exact copy of the church was promptly initiated,
and finally completed in 1997.
Figure 5: Fantoft stave church
Source: Wikimedia Commons,
http://en.wikipedia.org/wiki/Fantoft_stave_church
Troldhaugen was, since 1885, the home of the composer Edvard Grieg (one of most
famous Norwegian composers of classical music) and his wife Nina. Grieg lived at
Troldhaugen for 22 years and composed many of his best-known works.
Very interesting, the Theta Museum is a secret room that hosted the partisans of the Theta
Group of the Resistance Movement during the occupation of Norway by the Nazis
between 1940 and 1945. The group consisted of young people aged between 19 and 22.
They aimed at establishing a connection with the Norwegian government in exile and
adopted other forms of resistance. For example, they gave the Allied information about
naval traffic along the coast.
Finally, the Norwegian Museum of Fisheries (Norges Fiskerimuseum) offers a look at
Norway’s fishing industry: the sea and its resources, territorial waters, management and
research, boats and equipment through the ages, whaling and sealing, fish farming and
products.
4.2.2 Natural heritage
Bergen is one of the most visited cities in Northern Europe also thanks to its natural
beauty: here the mountains meet the see, and Bergen is situated in between.
The seven mountains surrounding Bergen are famous for the possibility of practising
trekking and for the panorama that they offer. Every year, usually in May, the “Seven
17
Mountain Walk” takes place, a trekking walk along a 30 kilometres long route, reaching
2,200 metres of height.
But the city is mostly famous for its location, surrounded by fjords. In 2004 National
Geographic Travel Magazine named Norway’s fjords “the number one unspoiled travel
destination in the world”. Two among the fjords of Norway, the Geirangerfjord and the
Nærøyfjord, were inserted in 2005 on the UNESCO’s World Heritage List. For this
reason the city is reached by several cruise-ships, carrying tourists from all over the
world.
Figure 6: the Sognefjord
Source: Wikimedia Commons, http://en.wikipedia.org/wiki/Bergen
Fløibanen funicular takes, on an 8-minute ride, to the top of Mount Fløyen (320 m.a.s.l.),
offering a magnificent view over Bergen and the suburbs.
Bergen Aquarium is one of the finest and most extensive collections of marine fauna in
Europe. There are altogether more than 70 tanks, 3 outdoor pools with seals, penguins
and carps. The Aquarium extension contains a realistic nesting cliff, open plan
aquariums, new exhibition and a supervideograph/cinema.
4.2.3 Urban intangible cultural heritage
Bergen offers many cultural events in the course of the year, attracting to the city a large
number of visitors.
Bergen, the birthplace of Edvard Grieg, has one of the oldest symphony orchestras in
Europe, concerts, important festivals and musical happenings, including the well-known
Bergen International Festival.
The Bergen International Festival was founded in 1953 and, since then, it has focused on
presenting prominent international and Norwegian artists in the fields of classical music,
opera, chamber music, ballet, recitals, theatre, dance and performing arts. The festival
takes place every year over 12 days at the end of May. The attendance in 2002 reached
70,000 visitors for the indoor and outdoor events.
Meteor is a large biennial theatre festival, offering exciting performances featuring
national and international artists and theatre groups.
In June the Viking and medieval festival (Bjorgvin Marknad) takes place. It is located at
mount Fløyen. Here the tradition of the old Viking life style lives again. There are
18
historic exhibitions, lectures given by professors of History and also food prepared like
they did 1000 years ago.
Among the other events which deserve attention are: the Bergen International Film
Festival, representing one of the leading film festivals in Norway; the Bergen Fest, which
focuses on folk music and authentic American blues in particular, as well as R&B, funk,
gospel, rock and country; the Nordsteam festival, which offers the opportunity to bring
back the streets and harbour scene of the 1950s, with old cars, local passenger steamers
and veteran ships.
An interesting feature of Bergen’s life style is the Bergen Fish Market, which is a very
popular subject among photographers. With its colours, fish, souvenir, flowers and
handicraft it is a very picturesque place, the very hearth of the city pulses.
4.2.4 Recent trends in tourism
Tourism in Bergen is a mature tourism.
The economic turnover is estimated to 600 mln. €a year. There are approximately 1.3
million hotel nights a year and 6,000 people are employed in activities related to tourism.
Statistics made by Bergen Tourist Board are based on number of hotel nights in Bergen
city and do not include cruise tourists or day-visitors. Since 2000 there has been a
constant (with the exception of 2002) increase in the number of hotel nights in Bergen,
reaching about 210,000 in 2003 (Figure 7).
Figure 7: number of hotel nights. In thousands
Source: Bergen Tourist Board
In 2005 overnight stays in hotels showed a marked growth, both in the peak season and in
the entire year. In 2004 the number of guest nights had risen by 5.8%, whereas in 2005
there was an increase of 6.3%, equivalent to 74,052 guest nights. This positive
performance puts Bergen above both the national average and the average of the four
Counties in the Fjord Norway region. Norwegian guest nights rose by 7.3%, foreigners’
19
guest nights by 4.6%. The increase in the high season was 4.6%; excellent the dynamic in
the low season (January-April, October-December), showing an increase of 56% (City of
Bergen, 2006a).
According to the Bergen Tourist Board, Great Britain, Germany and USA are the main
foreign markets during the summer season from May to September (Table 6).
Nationalities
Number of visitors (%)
Norway
64.8%
Great Britain
5.3%
Germany
4.9%
USA
4.7%
Spain
2.2%
France
1.9%
Italy
1.4%
Netherlands
1.2%
Other Europe
2.9%
Table 6: top ten visitors’ Country of origin to Bergen
Visitors from USA and Japan have been stable, while the visitors from China and Russia
have increased in numbers.
A large number of the Norwegian visitors come on business trips, either meetings or
conferences. The Norwegians are almost the only visitors during winter.
Cruise tourists dominate the picture of visitors at Bryggen during the peak season, which
lasts from April through September. The Bergen harbour is indeed Scandinavia’s most
visited cruise harbour. Bergen has one of the highest cruise passenger rates in Northern
Europe. The port of Bergen welcomes more than 150,000 cruise ship passengers every
summer. The main cruise port in Bergen is “Skoltegrunnskaien”, located near Bryggen.
Statistics from the Bergen Tourist Board show that in 2004 225 cruise ships visited
Bergen harbour. The total number of passengers was 157,263. In 2005 there was an
increase in the number of ship arrivals: 245 cruise ships visited Bergen in 2005 and the
number of passengers increased to over 190,000 (Table 7). The number of cruise ships
has increased by 158% in ten years (1995-2005) and the number of passengers by 267%.
The rapid growth in the cruise industry is evident above all when looking at the number
of passengers, which has almost duplicated in 5 years (2000-2005).
Year
Ships
1990
1991
1992
100
128
112
Passengers
--47,365
20
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
159
164
155
139
152
160
138
172
195
192
210
225
245
77,838
76,868
71,187
69,146
73,895
84,216
85,363
99,881
105,422
124,783
136,650
157,263
190,130
Table 7: cruise calls at Bergen harbour
Source: City of Bergen, 2006d
The most visited attractions are Fløibanen (the Funicular), Bergen Aquarium,
Troldhaugen (Edward Grieg museum) and the Hanseatic Museum. We must not forget
the Fish Market and Bryggen (Table 8). The tourist activities at the Bryggen site are
concentrated in the summer season (May-September). Within these months 597,321
people visited the site in 2005 2. In the autumn and winter months the site is more or less
empty with hardly any activity at all.
Attractions
1 Fløibanen Funicular
2 Bergen Aquarium
Visitors in year 2003
1,096,404
(estimate) 200,000
3 Edvard Grieg’s home Troldhaugen
86,560
5 Bergen Art Museum
6 Hanseatic Museum
73,158
48,769
7 Bryggen Museum
40,182
8 Håkon’s Hall
9 Fantoft Stave Church
37,733
36,000
10 Old Bergen
26,428
Table 8: Bergen’s most visited attractions in 2003
Source: City of Bergen, 2006b
2
Between July and August 2005, when the PICTURE survey was carried out, the number of visitors at
Bryggen ranged between 4,000 to nearly 9,000 visitors per day, causing big congestion problems.
21
4.2.5 The tourism local policy
Bergen Tourist Board is a common body for promoting the City of Bergen as a tourist
destination. The Tourist Board has approximately 397 members, among which is of
course the City of Bergen; almost every company within the tourist trade are members.
There are 70 partners that are involved with accommodation, all from 5 star hotels to
B&B, 97 restaurants and cafés, 18 companies working with transport, 15 travelling
agents, 150 shops and companies that deliver goods to the tourist industry, 7 art galleries
and 28 museums.
The goal of the Bergen Tourist Board is to promote Bergen as a positive tourist
destination trough coordinating all parties that work in different sectors of the tourist
industry.
The Bergen Tourist Board employs 150 people, and has 4 main departments:

Tourist information centre

Department for recreation and leisure

Conference Department

Bergen Guide Service.
Improving Bergen as a tourist destination is done through strategic planning and
organising. In 2003 the Bergen Tourist Board presented a new Strategic plan for the
period 2003-2007, which followed the Strategic plan for the period 1996-2001.
The vision expressed in the Strategic Plan is that Bergen shall become one of the leading
tourist destinations in Europe. The tourist industry shall be based on quality, positive
experience and be economically sound.
To reach this goal, a number of strategies have been developed:

To increase number of visitors in the off-peak season

To increase the quality of the visit to Bergen, by coordinating all parties involved

To stimulate and strengthen tourist board members’ profits and competition through
information and marketing of Bergen, both nationally and internationally.
The Bergen Tourist Board activities cover:

Public-related information and profiling

Media service

Targeted marketing towards conference organizers

Trade-related marketing towards the holiday and leisure market

Product co-ordination and development

Management of Tourist Information Offices

Promotion of guide services through Bergen Guide Service

Study Norway – Technical Visits.
22
Information is available in various formats, such as:

The Official Bergen Internet Site (www.visitBergen.com)

Bergen Presentation Brochure (available in 7 languages)

The Official Guide to Bergen and the Region (Norwegian, English, German and
French)

Conference and Congress Presentation Brochure (Norwegian, English)

Handbook for the Bergen Card (Norwegian, English, German)

The Official Bergen City Map

Bergen Parking Map

Bergen & the fjords, day excursions (incl. map)

Information Brochure for Bergen Guide Service.
The Bergen Card (lasting 24 or 48 hours) offers free bus travel within the city limits, free
admittance to most museums and attractions, as well as discounts on a variety of cultural
and sightseeing attractions and parking.
The organization of the Bergen Tourist Board has proven very successful. It has been
possible to:

Pool the economic resources for marketing Bergen

Coordinate the marketing of Bergen, presenting the city’s unambiguous and unique
character (the “Bergen profile” – Bergen is promoted as a good city to live in, to work
in and to visit)

Increase hospitality

Promote festivals and other cultural activities

Improve the guide service through education of the official guides who are employed
in the Bergen Guide Service

Present most of the relevant tourist information on one web site

Offer coordinated and correct information in tourist brochures, guide books, etc.
The focus on the quality of the tourist offer and experience was already developed on the
occasion of the selection of Bergen as European City of Culture for 2000 (together with
other 8 cities – Avignon, Bologna, Brussels, Cracow, Helsinki, Prague, Reykjavik and
Santiago de Compostela). Bergen 2000 (an independent foundation established ad-hoc
for organising the event) program covered both the city and the region. The programme
started on 17 of February 2000 and ended on 3 of December 2000; the regional program
was concentrated to the summer months. The final program had three main focuses:

Contemporary arts from small and medium-sized producers

Community based (often non-professional) cultural expression

A regional program over much of Western Norway.
23
There were a total of 1000 projects with 5000 performances, 150 exhibitions, 180 open
air events and 50 seminars and school projects. Apart from the increased visibility in the
media and appraisal of the city by its visitors, «the cultural year gave cultural life a
chance to show what could be made possible with extra money. The success of the
program has been followed up by the city. The cities cultural budget has permanently
been higher than in 2000 (including support for Bergen 2000) since 2002. The year has
also strengthened local political support for arts and culture and the experiences are the
foundation of a new generation of ambitions plans» (City of Bergen, 2005).
Today Bryggen is one of the most visited cultural tourist sites in Norway. In order to
preserve its historical values and the authenticity of the site, the Bryggen project has been
established. The partners in the project are Foundation Bryggen, which owns half of the
buildings, the owners of the other houses, the City of Bergen with the Heritage
Management Office, the Regional Heritage Management Office and the National
Directorate of Heritage Management. The project is mainly financed by the State.
24
5The impacts of tourism
on the urban economy
The present chapter presents a quantitative estimation of the economic impact of tourist
expenditure in Bergen. As underlined in Stynes (1999), an economic impact analysis is
finalized (and restricted) to tracing the flows of spending associated with tourism
activities in a region, in order to identify, typically, the changes in sales, income and
employment (directly or indirectly driven by tourism).
Economic impact analysis focuses therefore uniquely on the actual flows of money
related to market transactions.
As clearly emerged from the PICTURE Project, economic impact analysis is only ‘a part
of the whole story’ (although an essential one). As a matter of facts, tourism-related
activities lead to multifaceted effects on the local community and its ‘quality of life’, as
well as to a variety of associated economic consequences that are not taken into account
in a market transaction based ‘economic impact analysis’ (e.g., the direct costs incurred
by tourism businesses, government costs for infrastructure to better serve tourists,
‘congestion’, environmental degradation and other tourism-related costs borne by
individuals in the local community). Therefore it has to be clearly distinguished between
an ‘economic impact analysis’ and a more general ‘cost-benefit analysis’ – being well
aware that an economic impact analysis, by itself, provides a rather narrow and often onesided perspective on the impacts of tourism. Community decisions over tourism often
involve debates between industry proponents touting tourism economic impacts (benefits)
and detractors emphasizing tourism costs. An economic impact analysis emphasizes the
monetary benefits of tourism (and it has therefore to be counterbalanced by
environmental, social, cultural and/or fiscal impact studies, which generally tend to focus
more on the negative impacts connected to tourism activities). From this point of view,
economic impact analysis represents a compulsory essential element, but for the
decisional framework to be balanced, it has to be integrated in a broader ‘cost/benefit
analysis’ of the effects of tourism. Sound decisions rest on a balanced and objective
assessment of both benefits and costs and an understanding of those who benefit from
tourism and those who pay for it.
Although limited in perspective, a quantitative knowledge of the monetary impact
provides a basic ingredient towards the identification of the ‘most appropriate’ tourism
marketing and management strategies and represents an important consideration in
national, regional and municipal tourism planning. Communities need to understand the
relative importance of tourism to their region, including the monetary contribution of
tourism to economic activity in the area.
25
5.1 Scope and methodology
A variety of methods, ranging from ‘pure guesswork’ to ‘complex mathematical models’,
have been used to estimate the economic impacts. The following Table, adapted from
Stynes (1999), presents few of them, in order of increasing degree of sophistication.
Level
Spending patterns
Local economy
Judgment
Expert judgment
Expert judgment to estimate multipliers
2
Use or adjust spending averages from
studies of a similar area/market
Use or adjust aggregate tourism
spending multipliers from a similar
region/study
3
Adjust spending that is disaggregated
within particular spending categories &
segments
Survey random sample of visitors to
estimate average spending by segment
& spending category
1
4
Primary data
Use sector-specific multipliers from
published sources
Use an Input-Output model of the
region’s economy
Table 9: methodological approaches for the estimation of economic impacts, ordered by levels of
complexity - adapted from Stynes (1999)
Although in some cases good judgment or existing data may be more accurate than a
specific survey, particularly if the survey has a low response rate, small sample size and
measurement and sampling procedures that do not guarantee a representative sample or
reliable measurements, for the case study of Bergen, the ‘most advanced procedure’
based on primary data (Level 4, in Table 9), has been implemented:

a survey of tourists visiting Bergen was conducted (face-to-face interviews) in order to
estimate the scale and variety of spending by different profiles of tourists;

the spending patterns derived from the survey were then applied to an Input-Output
model of the Norwegian economy (and a re-scaled version, referring to the Hordaland
County) to quantify the effects on sales, incomes and employment.
As typical of any Input-Output based approach, the overall monetary effects of tourism
activities emerge as disaggregated over three components (see the main body of
PICTURE Deliverable 13 for more details):

the direct impact, i.e., the total expenditure on the purchase of goods and services by
tourists – as emerged from the site-specific survey. The direct impact typically
concerns very specific economic sectors, such as: lodging, restaurant, entrance fee to
cultural attractions, amusement, retail trade, transportation – that are referred to as
‘tourism industries’;

the indirect impact, i.e., the effects associated with the increase of demand from
‘tourism industries’ to local production factors and to other sectors of the local
26
economy. This in turn results in further production and employment in businesses
located in the region of concern, as local suppliers buy local production factors and
locally produced goods and services. The degree of magnitude of these indirect effects
is governed by the extent to which business firms in the area supply each other with
goods and services (inter-industrial linkages). In general, the smaller the scale of the
economy, the weaker are the connections between the local producers and a higher
percentage of the direct tourist expenditures will “leak” out of the geographic area
under study (imports). For example, the indirect effects related to the direct
expenditures of tourists staying overnight in hotels are the production changes
resulting from various rounds of re-spending of the hotel industry's receipts in other
backward-linked industries (i.e., industries supplying products and services to hotels).
Changes in sales, jobs and income in the linen supply industry, for example, represent
indirect effects of changes in hotel sales. Businesses supplying products and services
to the linen supply industry represent another round of indirect effects, eventually
linking hotels to varying degrees to many other economic sectors in the region;

the induced impact is the change in economic activity resulting from the additional
consumer spending, which takes place when the additional income earned directly or
indirectly from the incoming tourists is spent. Additional residents’ income is partially
spent in locally supplied goods and services providing a further impetus to local
economic activity. For example, hotel and linen supply employees - supported directly
or indirectly by tourism - spend their income in the local region for housing, food,
transportation, and the usual array of household product and service needs. The sales,
income, and jobs that result from household spending of added wage, salary, or
proprietor’s income are induced effects (see Section 5.1.1).
The overall impact on economy is the sum of the direct, indirect and induced
contributions. The effect of tourism on the local economy is mainly influenced by two
key factors:

the characteristics and the spending patterns of the local tourists, affecting the direct
impact on the economy. Essential features here include: the reason for travel, the
length of stay, the accommodation chosen, etc.;

the characteristics of the ‘tourism industries’ and of the local economy. Key features
here include the shares of ‘tourism industries’ that are locally-owned, as well as the
ability of local economy to satisfy the demand of ‘tourism industries’ (the more likely
the more diversified and interlinked is the local economy). The magnitude of indirect
and induced effects (the so-called “secondary effects”) depends on the propensity of
businesses and households in the region to purchase goods and services from local
suppliers. If ‘tourism industries’ and their suppliers are locally owned, the
remunerations (profits, rent and wages) tend to stay locally and the local community
will strongly benefit from them.
By means of indirect and induced effects, changes in tourist spending can impact
virtually every sector of the economy in one way or another.
By expressing the overall impact (direct + indirect + induced) in terms of a multiple of
the direct impact alone, several summary measures, known as Input-Output ‘multipliers’,
can be defined. The most frequently used types of Input-Output multipliers are those that
27
estimate the effects of exogenous changes on: sales in the sectors of the economy, income
earned by households and employment expected to be generated because of these new
sales and this additional income (see the main body of PICTURE Deliverable 13 for more
details). The notion of multipliers rests therefore upon the relationship between the initial
effect of an exogenous change and the total effect of that change: the multipliers
encapsulate the impact of tourism in the region of interest and capture the secondary (i.e.,
indirect and induced) effects of visitor spending, showing the wide range of sectors in the
local community that benefit from tourism.
In terms of multipliers, the economic impact can be generally expressed as:
Economic Impact = Number of Tourists · Average Spending per Tourist · Multiplier
In the framework of this Annex, we limited ourselves to a preliminary estimation of the
Average Spending per different profiles of tourists as well as to a determination of sale,
income and employment Multipliers (see Section Errore. L'origine riferimento non è
stata trovata. and Section 7.2, respectively). Due to the relatively high uncertainty
intrinsic to the results (and the average spending patterns in particular – as the limited
available resources didn’t allow to interview a statistically representative sample of
visitors), no attempt is done either to extrapolate these findings in terms of overall
economic impacts or to use these results to forecast the economic impact of future
tourism scenarios and policies. Data obtained from the model can however be used by
local decision makers, e.g., to identify tourist expenditure in their area, understand the
value of different tourist types to the area, isolate the likely monetary benefits of a
potential tourism development, determine how different sectors of local economy will
directly or secondarily benefit from tourism activities (and which inter-industrial linkages
should be reinforced in order to increase the monetary benefits), model the impact of
tourism on local additional income and employment and support decision making in
order to work out how the impact on local economy could be maximised (in a kind of
cost/benefit analysis).
Furthermore, it has to be remembered that an ‘impact analysis’ based on the Input-Output
formulation, tends to concentrate on changes expected to occur in the short run (e.g., next
tourist season). There are, however, several other long-term categories of economic
impacts that are not typically covered by an Input-Output analysis. Stynes (1999)
mentions, for example:

changes in prices (tourism can sometimes inflate the cost of housing and retail prices
in the area)

changes in the quality and quantity of goods and services (tourism may lead to a wider
array of goods and services available in the area - of either higher or lower quality than
without tourism)

changes in property and other taxes (taxes to cover the cost of local services may be
higher or lower in the presence of tourism activity)

economic dimensions of ‘social’ and ‘environmental’ impacts.
28
Potential long-term effects driven by tourism on local economy have been discussed in
details in the main body of the Deliverable 13. When longer-term and/or broader changes
are examined (or when dealing with projections and forecasting), the economic structure
of the city cannot be generally treated as ‘frozen’ and induced adjustments can become of
primary importance (e.g., ‘displacement effects’, see Deliverable 13). One has always to
remember that Input-Output models rely on a number of assumptions (see Deliverable
13), and therefore their results shouldn’t be quoted ‘out of contest’.
5.1.1 Induced effects: closure with respect to households
As mentioned in the previous Section, the monetary economic impact of tourism
activities on a local economy, can be generally described as the sum of three additive
contributions: the direct, the indirect and the induced effects. From a methodological
point of view, the inclusion of induced effects means to pass from a ‘simpler’ InputOutput model that is ‘open with respect to households’ (i.e., that allows the evaluation of
only direct and indirect effects) to a ‘more complex’ model that is ‘closed with respect to
households’ (see the Deliverable 13 for a ‘didactical’ and critical discussion). The
‘closure with respect to households’ takes into account that households earn incomes in
payment for their labour to production processes, and, as consumers, they spend their
income in rather well patterned ways. Consequently, an increase in the amount of labour
needed (driven by an additional number of visiting tourists) will lead to an increase in the
amount spent by the households for consumptions. In other words, although households
tend to purchase goods for final consumption, the amount of their purchases is related to
their income, which depends on the sales of each of the economic sectors. Thus, in the
formulation of the Input-Output analysis, the household sector could be moved inside the
technically interrelated table, that is, to make it one of the ‘endogenous’ sectors. This is
known as closing the model with respect to households. From a technical point of view,
this is implemented by including an additional row and an additional column, related to
the new household sector (the necessary data are available from the Norwegian Statistical
Office3), in the Input-Output matrix. The additional row represents wages and salaries
received by households from each economic sector in payment for their labour services
(showing how its output, i.e. labour service, is used as an input by the various sectors).
The additional column shows the structure of the household purchases distributed across
the economic sectors (i.e., the consumption pattern). The last element, at the intersection
between the additional row and the additional column, represents the household
purchases of labour services.
5.1.2 Regional effects: re-scaling of the I-O matrix
Typically, the Input-Output table is available at scales (usually at national level) that are
bigger than the one of interest for the local application. Several approaches have been
proposed in order to adjust (re-scale) the original Input-Output model in order to reflect
the peculiarities of a sub-region.
From a conceptual point of view, there are two basic features of a local economy that
influence the characteristics of an Input-Output analysis at sub-regional scale:
3
Cfr. http://www.ssb.no/english.
29

firstly, although the data in the original Input-Output table are obviously some kind of
averages of data from individual producers who are located in specific regions, the
structure of production in a particular sub-region may be identical to or may differ
markedly (e.g., due to ‘economic specialization’) from that recorded in the available
Input-Output matrix;

secondly, it is generally true that the smaller the area of concern, the more dependent
the economy will become on trade with ‘outside’ the area (i.e., exports and imports
across the region’s border) – both for the sales of regional outputs and purchases of
inputs needed for local production.
With respect to the Bergen case study, an Input-Output table was available from the
Statistical Office (http://www.sbb.no/english) at national scale (i.e., its straightforward
implementation would allow the estimation of the impact of tourism in Bergen on the
Norwegian economy). In order to complement this analysis with an estimation of the
impact on local economy (Hordaland county), we decided to re-scale the Input-Output
matrix by using auxiliary data. A series of alternative procedures, at different levels of
complexity, have been proposed in literature for re-scaling an I-O matrix: a recent PhD
Thesis by Bonfiglio (2006) was dedicated at the illustration and critical review of a large
variety of alternatives. We have opted for the implementation of the ‘Flegg Location
Quotient’4. This methodology, in order to re-scale the Input-Output matrix, makes use of
the number of employees engaged in each economic sector (in this specific case, in
Norway and in the Hordaland economy, respectively), as well as of empirically derived
factors. Data about employment in Hordaland were taken, for an aggregated set of
economic macro-sectors, from Hordaland County Council (2004).
4
See, e.g., Bonfiglio (2006) and references herein.
30
6Bergen survey. Main
findings
Tourists spend their money to buy certain goods and services. These initial tourist
expenditures, generally directed to very specific sectors of the economy, which we have
labelled as ‘tourism industries’ (i.e., lodging, restaurant, retail trade, entrance fee to
cultural attractions, amusement, local transportation, etc.), represent additional revenues
for these activities and correspond to the driving term for the further impact on local
economy (i.e., indirect and induced effects). The extent and characteristics of the total
economic impacts will therefore reflect the magnitude and composition of the initial
tourist expenditures (the Input-Output is a linear model, that is, under the approximation
of the model, if the tourism expenditures are doubled also the impacts will double).
It is therefore an essential step in the procedure to be able to obtain a detailed assessment
of the ‘average spending patterns’ (disaggregated on different classes of ‘tourism
industries’ or on different economic sectors).
For the Bergen case study, expenditure patterns have been derived from a specific
Questionnaire (compiled through face-to-face interviews), embedded within a more
comprehensive site-specific survey. As the main concern of the Bergen case study was to
examine whether the tourist traffic at the World Heritage Site of Bryggen, situated in the
City of Bergen, had any major impact on the built environment and the preservation of
Bryggen, the survey took place at the Bryggen site itself (the main part of the interviews
took place in the Bryggestredet, the open area at the back of the Bryggen site).
Due to climatic reasons, in Bergen, tourism is limited to a well-defined seasonal window
(from April through September). Contrary to the other two Mediterranean case-studies
(Elche, Spain and Syracuse, Italy) the contribution of off-season winter tourism is totally
negligible: the site is practically empty with hardly any activity at all. Consequently, in
this ‘pilot study’, no seasonal variations were considered and the survey was conducted in
a single campaign, undertaken at the ‘peak’ of the tourism season (essentially in July and
August, 2005 – Monday to Friday). Since 1979, when Bryggen was listed on the
UNESCO World Heritage List, there has been a steady increase in the number of tourists.
In addition to that, tourism patterns are changing. Tourists in general, but specifically
visitors to museums and historic buildings on heritage trails, come in waves, in coaches,
and often have limited time before leaving for the next destination. This leads to a short
but heavy impact on the environment, and a cycling of these impacts occurs through out
the day as successive waves of tourists enter he site. The pattern described above is very
obvious at the Bryggen site.
Due to the limited available resources, in this ‘pilot study’, a total number of 161
questionnaires related to the economic assessment could be collected through face-to-face
interviews. It is essential to underline that, from a statistical point of view, the survey is
considerably undersized. For example, the European Cities Tourism Research and
Statistics Working Group (2004) recommends that 1,500-2,000 interviews should be
31
carried out in a single city for the survey to be considered representative. Furthermore,
the choice of Bryggestredet and timing (peak of the tourist season), as well as other
aspects of the survey, made a ‘random sample’ impossible (i.e., the main parameters that
characterize the interviewed population are not necessarily representative of the tourist
flux in Bergen). This is mainly due to language barriers (the interviewers spoke
Norwegian, English and German), the timing of the survey at the peak of the tourists
season (Norwegian tourists tend to avoid this period of the year, if possible, as Bryggen is
perceived as ‘overcrowded’), the location (a large number of Norwegian visitors come on
business trip and will normally not visit tourist sites on ‘working hours’) and practical
difficulties in accessing and interviewing the large number of tourists on guided tours –
people travelling on their own were not in the same hurry as people travelling in
organized groups and therefore more willing to be interviewed (with the consequence that
cruise and package tourists tend to be underrepresented, while tourists who travel on their
own or in semi-package tours tend to be over represented in the sample). The derivation
of spending patterns for different tourist profiles should therefore be seen mainly as a
practical demonstration of the methodology and as a ‘preliminary assessment’, more
intended to study trends and behaviour of different typologies of tourists rather than
representing a reliable quantitative evaluation.
6.1 Profiling tourists: qualitative analysis of the sample
As spending can widely differ across the different kinds of tourists and due to the limited
representativeness of the interviewed population, a segmentation approach has been used,
aiming to capture systematic differences in spending. Key tourist profiles were
introduced (e.g., day-tripper, cruising, cultural, recreational, etc.) and, based on the
sample of the available Questionnaires, average levels and compositions of expenditure
evaluated for each tourism segment.
A qualitative analysis of the sample represents an important basis for the interpretation of
the differences in tourists’ expenditures and offers useful elements for a wider description
of tourists’ behaviour.
In our questionnaire (see Annex 1 to D13), the most relevant factors of discrimination
among different typologies of tourists, for the analysis of the respective patterns of
expenditure and expenditure levels, have been identified as follows:

Reason

Motivation

Tour/unique destination

Organisation of the travel

Length of stay

Accommodation

Expenditure level

Activities

Age
32

Education

Employment

Income.
Reason refers to the reason for travelling
relatives, business travel or other reasons.
answering “Holiday” were asked to explain
Bergen (Motivation), that is the destination’s
or leisure).
to Bergen: holiday, visits to friends and
Among all the interviewed people, those
what was the specific reason for choosing
cultural heritage or other attractors (culture
An important element for evaluation of the economic impact on the economy is
represented by the organisation of the travel, i.e. whether the visitor is self-organised or
on the contrary bought a package tour. Linked to this element is the decision of the tourist
to visit only Bergen or, on the contrary, to stop in Bergen only for a fraction of its travel
including also other – distant or neighbouring – destinations (Tour/unique destination).
This provides information about the level of attractivity of the destination.
The length of stay is essential to distinguish between tourists and non-tourists (whom we
will refer to as “day-trippers”). In fact, according to the Tourism Society in the UK
tourism is «the temporary short-term movement of people to destinations outside the
places where they normally live and work, and activities during their stay at these
destinations; it includes movement for all purposes, as well as day visits and excursions»
(Richards G., 1996, p. 21). Similarly, the WTO definition of tourism includes «the
activities of persons during their travel and stay in a place outside their usual place of
residence, for a continuous period of less than one year, for leisure, business or other
purposes» (World Tourism Organization, 1993). Thus, WTO clarifies the tourist activities
and establishes temporal limits. In addition, while the Tourism Society only mentions day
visitors and excursionists, WTO establishes a distinction between day
visitors/excursionists and tourists in a narrow sense: ‘excursionists’ stay less than 24
hours at their destination, and only travellers who stay overnight can be defined as
‘tourists’. Moreover, this is a key factor in the analysis of the economic impact of
different typologies of visitors. For instance, tourists staying for the day are likely to
spend a smaller share of total expenditure in locally produced goods.
Accommodation is again another important factor of economic impact: hotels are more
expensive than, for instance, campsites. Moreover, as we have already anticipated, the
ownership – whether local or not – of the accommodation chosen is a fundamental factor
affecting the indirect impact on the economy.
The activities done during the period of stay (cultural recreation, entertainment, shopping,
etc.) allow for the distinction between cultural and non-cultural tourists, as well as
between two broad types of cultural tourists. As a consequence of a marked change in the
profile of cultural tourists since the late 1980s, Richards (1996) distinguishes between the
“specific cultural tourist”, for whom visiting cultural sites and attractions is the primary
reason for the journey; and “general cultural tourists”, who take in cultural tourism as part
of their broader interest in holidaying. Together with the motivation for travelling, the
activities done explain much of the intangible effect of tourism on the destination. For
33
example, tourists travelling for cultural reasons usually put a different level of pressure
on natural and cultural resources than, e.g., ‘sun&beach’ tourists.
Finally, there are a series of statistical data about age, education, employment and income
that can explain both the interest in culture and the level of expenditure of the visitor.
To sum up, the economic impact of tourism and the consequences for the urban quality of
life vary deeply according to the typology of tourist involved.
Before presenting the main findings as regards profile and behaviour of the most
interesting typologies of visitors identified in Bergen with the help of the questionnaires,
we would like to resume here the main features of tourism in Bergen.
First of all, Bergen is a destination of cultural tourism, stressing on:

Art and history (the harbour bearing testimony of the history of the city and the
wooden houses dating from the early 19th);

Nature and landscape (Bergen, “the Gateway to the Fjord”);

Events (above all, the Bergen International Festival).
A very interesting feature of Bergen is then represented by the cruise industry. Visitors
coming on cruise could be driven by cultural interest as well as by pure leisure. They
form a significant portion of the total number of yearly visitors in Bergen.
6.1.1 Cultural and non-cultural tourists in Bergen
In the present paragraph we will analyse the survey sample according to the visitors’
motivation, distinguishing between two groups: culture-driven tourists and other visitors.
It must be underlined that only the interviewed people who had answered “Holiday” to
the question about the reason for travelling to Bergen had to answer to the question about
their motivation for choosing the destination. As a consequence, the number of
respondents to the question motivation is only 140, and not 161.
Among the 140 respondents, culture-driven visitors are 126, i.e., 90%; the remaining 10%
is represented by visitors driven by other reasons, e.g. leisure.
Figure 8 shows the results of the crossing between motivation and tour/unique
destination. Both groups of visitors mostly visit Bergen as part of a tour; the percentage is
equal to 100% for non-cultural tourists. Only 18% of the cultural tourists declared Bergen
was the main destination of their travel.
34
Percentage of Tourists
100%
CULTURE
OTHER
80%
60%
40%
20%
0%
YES
NOT
Tour/unique destination
Figure 8: results of the Bergen questionnaire (motivation, tour/unique destination)
The majority of tourists visiting Bergen are self-organised. Only 26% of cultural tourists
bought a package tour, compared with 43% of non-cultural tourists (Figure 9).
Percentage of Tourists
80%
CULTURE
70%
OTHER
60%
50%
40%
30%
20%
10%
0%
SELF-ORGANIZED
PACKAGE
Organisation
Figure 9: results of the Bergen questionnaire (motivation, organisation)
A very fundamental element in our analysis is represented by the length of stay of visitors
to Bergen. Figure 10 shows that, even though the majority of the respondents are staying
overnight, day-trippers represent 35% and 43% of cultural and non-cultural tourists,
respectively.
35
Percentage of Tourists
70%
60%
CULTURE
OTHER
50%
40%
30%
20%
10%
0%
DAY-TRIPPER
TOURIST
Length of stay
Figure 10: results of the Bergen questionnaire (motivation, length of stay)
Cultural tourists also present a longer period of stay, about 2 days and 2 nights, very
similarly to the behaviour of other-motivated tourists (Figure 11 and Figure 12).
Figure 11: number of days and nights spent in Bergen for cultural tourists. The red lines correspond
to the mean values
Figure 12: number of days nights spent in Bergen for non-cultural (other-motivated) tourists. The
red lines correspond to the mean values
36
70%
CULTURE
60%
OTHER
50%
40%
30%
20%
10%
ow
ns
hi
p
fr
ie
nd
s
ow
nf
la
t
re
n
t fl
at
ho
st
el
ca
m
B
&
ps
it e
B
0%
ho
te
l
Percentage of Tourists
For the 90 cases that stay overnight, the accommodation structure has been analysed
(Figure 13). Non-cultural tourists prefer hotels, whereas cultural tourists are divided into
two main subgroups: of tourists staying in hotels and of tourists preferring campsites, that
is less expensive accommodation, with a consequent lower expenditure level.
Accommodation
Figure 13: results of the Bergen questionnaire (motivation, accommodation)
Percentage of Tourists
Looking at the data about age (Figure 14), the difference between the two groups is
evident: cultural visitors are younger than non-cultural ones. In fact, almost 33% of
cultural visitors are 26 to 35 years old, showing percentages for the other classes of age
never higher than 20%. On the other hand, in the case of cultural visitors all classes of
age are represented, and there are also over 65-year-old respondents. Non-cultural tourists
are, on the contrary, middle-aged.
40%
CULTURE
OTHER
30%
20%
10%
0%
18-25
26-35
36-45
46-55
56-65
>65
Age
Figure 14: results of the Bergen questionnaire (motivation, age). Respondents had to be of age
Both groups of respondents hold a degree, with a certain prevalence of cultural tourists
(Figure 15).
37
Percentage of Tourists
60%
CULTURE
OTHER
50%
40%
30%
20%
10%
0%
grammar
school
high school
college
graduate
post
graduate
Education
Figure 15: results of the Bergen questionnaire (motivation, education)
80%
CULTURE
OTHER
60%
40%
20%
ot
he
r
ife
ho
us
ew
pl
oy
ed
un
em
ed
re
t ir
em
pl
oy
ed
0%
st
ud
en
t
Percentage of Tourists
Contrary to our expectations, employment status is not found to be a discriminant
element for distinguishing between the two types of respondents (Figure 16).
Employment
Figure 16: results of the Bergen questionnaire (motivation, employment)
On the contrary, the data about income turned out to be more significant (Figure 17).
Although around 30% of both groups of respondents declared a family income higher
than 55.000 €per year, the percentage is higher for non-cultural tourists. In general, noncultural tourists have got an above the average income (45-55,000 €and over). It should
be however underlined that this question was felt particularly personal; as a consequence,
30 cultural visitors out of 126 refused to answer, as well as 3 non-cultural visitors out of
14.
38
Percentage of Tourists
40%
CULTURE
OTHER
30%
20%
10%
0%
<15
15-25
25-35
35-45
45-55
>55
Income
Figure 17: results of the Bergen questionnaire (motivation, income). Data expressed in thousand €
The following table (Table 10) resumes the features of cultural visitors in Bergen.
The Cultural Tourist:

is mobile
- short visits, in several different cities in the course
of the same journey
- length of stay is on average 2 days and 2 nights

is self-organized

 stays in hotel or in a campsite

is young
26-35 years old

holds a degree

is employed

has got an average income
<15 or 25-45,000 €/year
Table 10: the cultural tourist’s profile
The almost universal caricature of the stereotypical Heritage tourist (the so-called
‘Baedeker/ Michelin tourist’) is aged 45-65, with higher than average disposable income,
education, and travel experience, holidaymaking independently in a group of two and
staying in hotel accommodation. But a different typology of cultural tourists is emerging:
the so-called ‘Lonely Planet’ or ‘Rough Guide’ tourists. These are young people, aged
20-30, with a different and lower patterns of expenditure of course, staying in
inexpensive bed and breakfast or other accommodation facilities, which may have useful
advantages for spreading the benefits of tourism both economically and spatially, as this
kind of facilities are often owned by local people (Ashworth G. J., 2004, p. 6). This is
confirmed by ECT & WTO (2005). City cultural tourists «tend to be predominantly
female, highly educated with professional or managerial occupations and relatively high
incomes […]. Although older cultural tourists do tend to undertake more cultural
activities and spend more during their city trips, cultural tourism in cities is an activity
followed by all age groups, with the peak age group in terms of participation lying
between 20 and 30» (p. 34).
39
The findings about cultural visitors in Bergen confirm the feature of the stereotypical
cultural tourist (self-organised, staying in hotel, high level of education), except for the
income level, but at the same time confirms the evolution in the cultural tourism market:
an important part is represented by young people, staying in less expensive
accommodation facilities.
To conclude, considering the importance of cruises for Bergen’s economy, the means of
transport used by the visitors have been analysed (Figure 18). Cultural tourists choose
other means of transport, different from cruise ships, to go to Bergen.
Percentage of Tourists
80%
CRUISING
NON-CRUISING
60%
40%
20%
0%
CULTURE
OTHER
Means of transport
Figure 18: results of the Bergen questionnaire (motivation, means of transport)
In the following paragraph, the behaviour of Bergen visitors coming on cruise will be
analysed.
6.1.2 Cruising and non-cruising tourists in Bergen
In the present paragraph we will analyse the survey sample according to the means of
transport used by Bergen’s visitors. More specifically, among all the possible means of
transport used by Bergen’s visitors (airplane, car, bus, etc.), we are interested in analysing
cruise ships market.
In our sample, cruisers represent about 27% of the respondents. From statistical data
about tourism in Bergen in the peak tourist season, we know that cruise tourists are a very
large part of the total visitors. In our sample, cruise tourists are underrepresented. This is
mostly due to the fact that a large number of cruise tourists are on guided tours, and it is
practically impossible to interview tourists on guided tours, as they are often are on a
hurry and are not free to stop in a place without the whole group 5.
Figure 19 shows the results of the crossing between means of transport and tour/unique
destination. As we have already seen analysing the attractivity of Bergen towards
cultural/non-cultural tourists, also cruising and non-cruising visitors mostly visit Bergen
as part of a tour. Less than 10% and 26% of cruising and non-cruising visitors declared
5
For a deep discussion of the representativeness our the sample see PICTURE Deliverable 34, written by
OWHC, City of Bergen, which resumes the methodology and findings of the different survey carried out by
the PICTURE project partners in Bergen.
40
Bergen was the main destination of their travel. The data confirm that Bergen is
perceived as “the gateway to the fjords”.
Percentage of Tourists
100%
CRUISING
NON-CRUISING
80%
60%
40%
20%
0%
YES
NOT
Tour/unique destination
Figure 19: results of the Bergen questionnaire (means of transport, tour/unique destination)
The majority of tourists visiting Bergen are self-organised. However, about 60% of
cruising tourists bought a package tour, whereas 88% of non-cruising tourists organised
the trip on their own (Figure 20).
Percentage of Tourists
100%
CRUISING
NON-CRUISING
80%
60%
40%
20%
0%
SELF-ORGANISED
PACKAGE
Organisation
Figure 20: results of the Bergen questionnaire (means of transport, organisation)
A very fundamental difference between the two groups is evident in Figure 21; cruising
tourists are essentially day-trippers (in fact, cruise ships stop in Bergen only 10 hours on
average), whereas the other group of visitors stay overnight. More precisely, cruising
visitors have a length of stay of 1.1 nights, compared with the mean permanence of noncruising tourists, which is equivalent to 2.6 nights (Figure 22).
41
Percentage of Tourists
80%
70%
CRUISING
NON-CRUISING
60%
50%
40%
30%
20%
10%
0%
DAY-TRIPPER
NON DAY-TRIPPER
Length of stay
Figure 21: results of the Bergen questionnaire (means of transport, length of stay)
Figure 22: number of nights spent in Bergen for ‘cruising’ vs. ‘non-cruising’. The red lines
correspond to the mean values
For the 108 cases that stay overnight, the accommodation structure has been analysed
(Figure 23). Non-cruising tourists prefer hotels or the less expensive campsites, whereas
cruising tourists came to Bergen by their own ship, where they sleep or stay in hotel. This
53% of cruising tourists staying in hotel are, in reality, staying on the cruise ship
(included here in the category “hotel”) or in shore hotels, often arranged by the tour
operator as part of the package tour.
42
CRUISING
NON-CRUISING
50%
40%
30%
20%
10%
ow
ns
h
ip
nd
s
fr
ie
nf
la
t
ow
at
el
re
n
t fl
ho
st
te
am
ps
i
c
B
&
B
0%
ho
te
l
Percentage of Tourists
60%
Accommodation
Figure 23: results of the Bergen questionnaire (means of transport, accommodation)
Percentage of Tourists
Cruising has been found to appeal to a relatively broad range of tourists of all ages and
interests (although there is still a general misconception that cruising is mainly for
wealthy and/or older people). It can be observed only a slight prevalence of the age class
56-65 (Figure 24). On the contrary, non-cruising tourists are mostly young people, aged
26-35.
40%
CRUISING
NON-CRUISING
30%
20%
10%
0%
18-25
26-35
36-45
46-55
56-65
>65
Age
Figure 24: results of the Bergen questionnaire (means of transport, age). Respondents had to be of
age
Cruising tourists tend to possess higher levels of education: higher percentage of
respondents who hold a degree, in comparison with non-cruising tourists, even though
PhD-holders are more numerous among non-cruising visitors (Figure 25).
43
Percentage of Tourists
70%
CRUISING
60%
NON-CRUISING
50%
40%
30%
20%
10%
0%
grammar
school
high school
college
graduate
post
graduate
Education
Figure 25: results of the Bergen questionnaire (means of transport, education)
80%
CRUISING
NON-CRUISING
60%
40%
20%
ot
h
er
w
ife
h
ou
se
pl
oy
ed
u
ne
m
ed
re
t ir
pl
oy
ed
em
ud
en
t
0%
st
Percentage of Tourists
As cruising tourists tend generally to be older than non-cruising ones, although both
groups of respondents are mostly employed people, over 20% of cruising tourists have
already retired from work, while for non-cruising visitors this percentage is below 10%
(Figure 26).
Employment
Figure 26: results of the Bergen questionnaire (means of transport, employment)
As regards income, it should be again underlined that this question was felt particularly
personal; as a consequence, 15 cruising visitors out of 43 refused to answer, as well as 26
non-cultural visitors out of 118. Anyway, from the available data, we can see that in the
cruisers’ salary distribution, top incomes (i.e., more than 55,000 €/year) tends to be
somewhat over-represented, but a relatively high percentage of cruisers is also
characterized by medium-low incomes, in particular in the interval, 15,000 ÷ 25,000
€/year (Figure 27). The fact that most of the interviewed tourists had a high income
verifies that Norway is an expensive country to travel in.
44
Percentage of Tourists
40%
CRUISING
NON-CRUISING
30%
20%
10%
0%
<15
15-25
25-35
35-45
45-55
>55
Income
Figure 27: results of the Bergen questionnaire (means of transport, income). Data expressed in
thousand €
To summarize, cruisers in Bergen are mainly driven by cultural interest. Nevertheless,
they are not particularly interested in Bergen and visit also other destination in the course
of a tour. Cruising tourists are mostly shore-dependent for food only; they are more
interested in sightseeing and in less than 50% of the cases visit a museum; they are more
interested in shopping than in buying local crafts. As a consequence, in addition to the
fact that their length of stay is measured in hours, local tourist expenditure is minimal and
is frequently claimed to be less than the local costs incurred in receiving such tourists.
Cruise tourists cause congestion and a not evenly spread impact, with disadvantages for
the resident community. On the other hand, his presence is soft: less environmental
impacts (consumption of natural resources such as water, rubbish).
In the case of Bergen, anyway, this type of tourism doesn’t seem to be compatible with
the cultural image and the rich heritage the destination could and would like to
communicate.
In this ‘pilot study’, some of the tourists’ profiles where characterized by a relatively low
number of available questionnaires: it has to be noticed again that, from a statistical point
of view, samples of at least 50-100 visitors are typically recommended, within each
tourism segment, for the analysis to be ‘robust’. Due to the moderately low number of
Questionnaires, averaged spending patterns could only be determined together with
relatively large ‘confidence intervals’. The only way to obviate this shortcoming (and
therefore decrease the uncertainty that originates from the use of a limited number of
questionnaires to determine the spending pattern), is to increase the number of
questionnaires (a stratified sampling, based on the results reported in this ‘pilot study’,
could also be efficiently implemented, instead of a pure random sampling, in an eventual
second phase).
45
6.2 Direct impact of tourists’ expenditures in Bergen
The spending estimates are probably the most important part of the economic impact
analysis. For the different profiles used in the segmentation, they capture the amount of
money brought into the region by each tourist. Input-Output analysis (and/or the use of
‘ad hoc’ multipliers) only refers to the ‘amplification’ of the initial spending through
‘secondary’ (i.e., indirect and induced) effects. As noted by West (1999), in an economic
impact study the important thing to consider is not the size of the multiplier but the
magnitude of the total impact on sales, income and employment: a small multiplier can
correspond to a large total impact and a large multiplier to a small impact on the economy
depending on the size of the initial tourist expenditures (i.e., the amount of money
brought into the region by tourism). Although multiplier values are a useful indicator, one
has to bear in mind that they ‘only show relativities’.
In extracting spending patterns from a Survey, some technical and conceptual difficulties
could arise particularly in relation to the presence of all-inclusive packages. In the case
of ‘package tours’, a large percentage of the money paid by the visitor could actually
accrue to airlines, coach operators, travel agents outside the holiday regions and never
even enter the area of concern (this is particularly relevant for holidays overseas). In
order to be able to estimate the spending that actually impacted on local economy, the
process of face-to-face interviews, in the case of ‘package tourists’, didn’t limit itself to
the request of the aggregated global cost of the ‘holiday package’: for example, in the
implemented Survey, package tourists were asked for a complementary set of
‘disaggregated’ information - in particular on the kind of accommodation, on the
consumption of food and beverages and on the services provided by the package (e.g.,
hotel, restaurants on board in case of cruises, etc.).
From a statistical point of view, the problem related to the treatment of ‘holiday
packages’ is a kind of (constrained) imputation of missing values (i.e., ‘filling the holes’
in a data matrix). We opted for a particularly simple treatment: the missing entries for
‘package tourists’ were imputed on the basis of the characteristics emerged from the face
to face interviews, as well as general information collected from the interviewed ‘nonpackage tourists’. For example, if from an interview emerged that a ‘package-tourist’
spent a night in hotel, the direct impact for accommodation for this tourist was estimated
by extracting a random value from the distribution of the accommodation costs sustained
by all ‘non-package’ tourists who also spent a night in hotel. Knowing, in most cases, the
daily per capita cost of the package, the aforementioned imputation procedure could be
corrected, by assigning higher expenditures to package tourists with higher per capita
daily costs.
Although rather empirical in nature, we believe that the procedure - in its simplicity - is
adequate for the problem at hand and that the overall results would not be substantially
affected by the particular way in which ‘holiday packages’ are treated (only about ¼ of
the available questionnaires, 39 out of 161, refers to ‘package tourists’). However, the
implemented procedure should not be viewed as a ‘magic black box’: in the post-analysis
of the results it has to be remembered that for ‘package tourists’ essentially a (data
driven) ‘best guess approach’ has been used and, consequently, results related to this
kind of tourists will be characterized by higher uncertainties.
46
The results of the survey are shown in Figure 28, for the different spending categories
treated in the Questionnaire (expenditures of ‘package tourists’, imputed through the
aforementioned procedure, are also included in the Figure). One can notice the presence
of few ‘outliers’, and the relatively high variability of the daily per capita spending (that
reflects the heterogeneity of tourists). The spending category ‘transport in’ refers to the
mobility costs for local transportation in the Bergen region (e.g., taxis, public transports,
rental cars, gasoline). On the opposite, the transportation costs to reach and leave the
destination (e.g., airplane/train/coach or fixed auto expenses) were excluded from the
impact analysis, as they were considered to have been most likely made in the tourist’s
residence area, rather than in the area of concern.
Two leading spending categories emerge from Figure 28: the main contribution to the per
tourist daily spending appears to be related to the accommodation (if the tourist happens
to spend the night in Bergen) and the food (and beverages) costs.
The high scattering in the accommodation costs is better analyzed in Figure 29, which
clearly shows how the variability mainly reflects the choice made by the tourists. For
tourists spending the night in Bergen, alternative with no accommodation costs are also
detected – for those staying in their ‘second house’, for those visiting friends, or for
cruisers who spend the night on board (as will be better discussed later, the case of
cruising is a rather particular kind of tourism, as it can be organized in such a way that
most spending accrues directly to the cruise organizer, with only a minor impact on local
economy).
47
Figure 28: results of the Bergen questionnaire (global data, all interviews). The figure shows the daily
per capita expenditure disaggregated over the spending classes used in the Questionnaire. The points
in the graphs are randomly jittered along the y-axis, in order to avoid overlapping and making the
plot more readable
Figure 29: results of the Bergen questionnaire (global data). The figure shows the per night, per
capita expenditure for selected types of accommodation. Apart from the shown results, zero
accommodation costs are assigned to tourists staying in their ‘second house’, visiting friends, or for
cruiser spending the night on board (as, in this specific case, accommodation costs are not expected to
directly accrue to local economy)
In order to better analyze the spending patterns (daily and total, i.e., over the whole
length of stay in Bergen), several tourist profiles have been introduced, as reported in the
following Table:
Daily
Total
Number of
expenditure per expenditure per
Questionnaires
capita
capita
organization: package/non-package
package
non-package
39
122
51.4 €
45.4 €
71.1 €
148. €
43
118
46.0 €
47.2 €
78.6 €
148. €
127
13
46.9 €
41.1 €
110. €
109. €
4
15
140
75.3 €
40.9 €
46.1 €
404. €
164. €
110. €
cruising/non-cruising
cruising
non-cruising
motivation: cultural or other
culture
other
main reason for travelling
business
friends
holiday
48
football match
accompanying husband on business
1
1
118. €
62.1 €
235. €
1119. €
52
109
33.2 €
53.4 €
33.2 €
175. €
8
153
47.6 €
46.8 €
147. €
128. €
161
46.9 €
129. €
day-tripper/non-day-tripper
day-tripper
overnight-stay tourist
nationality
Norwegian
foreigner
‘generic tourist’ [all questionnaires]
Table 11: the number of available questionnaires and the estimation of the average per capita, daily
and total (i.e., over the whole length of permanence in the Bergen region) expenditure - for each of
the tourist profiles used in the ‘segmentation’
From the Table above, it can seen how, for several profiles, the number of available
questionnaire is very limited: only 4 questionnaires for ‘business tourists’, only 8
Norwegian tourists being interviewed, also cruise tourists and package tourists are
underrepresented. Similarly to what we explained for cruisers (see page 18), although
visitors travelling on a package tour represent a very important part of the total visitors to
Bergen (as, according to statistical data, cruisers represent the most important group in
the peak tourist season and the majority of them travels on package tours), it is very
difficult to interview visitors on package tour as they are in a hurry and less willing to be
6
interviewed than self-organised tourists. The same is true for people on business .
The consequent lack of representativeness (we remember that, from a statistical point of
view, 50-100 questionnaires are typically recommended, within each tourism segment)
could therefore limit the ‘robustness’ of the related conclusions: it couldn’t be excluded,
with a reasonable amount of certainty, that the differences observed between two
different profiles of tourists could just reflect a ‘statistical artefact’ originating from the
variability intrinsic to any random sampling procedure.
As well as in the daily and total per capita amount, differences can be observed for the
spending pattern. As can be noticed from Table 11, dissimilarities in behaviour across the
different tourist profiles are more evident for the total per capita expenditure than for the
daily one. This is a consequence of the fact that different kinds of tourists tend to be
characterized by different length of stay in Bergen. The length of stay emerges therefore
as a fairly significant parameter, in the profiling of ‘typical’ categories of tourists.
6
For a deep discussion of the representativeness our the sample see, again, PICTURE Deliverable 34.
49
Figure 30: per capita spending patterns for different profiles of tourists, as derived from the Bergen
Questionnaires
Figure 31: same as Figure 30 but for different tourists’ profiles
Due to the restricted number of available Questionnaires, as well as due to the substantial
variability of the spending behaviour (see, e.g., the considerable scattering in Figure 28),
50
any quantitative conclusion drawn from the present analysis will be accompanied by an
intrinsic uncertainty. As in any analysis of survey data, it is therefore essential to consider
if the number of available data allows ‘robust’ and ‘significant’ (from a statistical point
of view) conclusions.
A graphical illustration of the typical uncertainty related to the determination of the
average expenditures for accommodation and food and beverages – the two most
relevant categories taken into account in the determination of the spending pattern (see
Figure 30 and Figure 31) – is reported in Figure 32.
Figure 32: empirical inference of the ‘confidence levels’ with which the average value of the per
capita daily expenditure for ‘food and beverages’ (left side) and the per capita per night
accommodation expenditure (right side) are estimated. The red line refers to the average value. No
segmentation has been used; all 161 available questionnaires are taken into account and equally
weighted (but the evaluation of the average expenditure per night per capita includes only those
tourists spending at least one night in Bergen)
For the two cases depicted in Figure 32, the following confidence intervals can be
determined, through the application of non-parametric bootstrap resampling techniques:
‘generic tourist’ [all questionnaires]
Food and Beverages [per day, per capita]
95% confidence interval
90% confidence interval
80% confidence interval
Accommodation [per night, per capita]
95% confidence interval
90% confidence interval
80% confidence interval
Minimum value Average value Maximum value
15.5 €
13.8 €
16.4 €
14.2 €
16.9 €
14.6 €
17.3 €
23.8 €
20.4 €
27.2 €
21.1 €
26.5 €
22.0 €
25.6 €
51
Table 12: average values and confidence intervals intrinsic to the determination of the per capita
daily expenditure for ‘food and beverages’ and the per capita per night expenditure for
accommodation (‘generic tourist, all 161 questionnaires taken into account)
The quantities reported in Table 12 could be interpreted in the following way: e.g., the
average value of the daily per capita spending for ‘food and beverages’, as estimated
from the 161 ‘randomly sampled’ questionnaires, is 15.5 €. Furthermore, from the
available dataset it can be stated, roughly speaking, ‘with 95% probability of not
committing a mistake’, that the true mean will be included within the interval 13.8 €÷
16.4 €(more precisely: if several samples of 161 questionnaires were randomly collected
from the distribution of the incoming tourists and, similarly to Figure 32 and Table 12, a
95% confidence interval computed for each of the randomly selected sets, in the long run
about 95% of these estimated confidence intervals would contain the true mean). This
definition is extended in an obvious way to cover the case of 90% and 80% confidence
intervals, also reported in Table 12.
The width of the confidence intervals reflects both the variability of the measured data
(the larger the variability, the larger the confidence interval) as well as the number of the
collected samples (the lower the number, the larger the confidence interval).
Complementary to the estimations for a ‘generic tourist’, as reported in Table 12,
confidence intervals can also be calculated for single tourist profiles and spending
categories. Survey data related to specific ‘tourist profiles’ (i.e., subclasses of the original
161 questionnaires, see Table 11) will tend to be characterized by higher ‘uncertainties’
(as a consequence of the smaller number of available questionnaires), however, generally
speaking, this tendency is likely to be counterbalanced by the higher homogeneity (i.e.,
the reduced variability) in the spending behaviour of tourists belonging to the same
profile.
It is however essential to find out which combinations of tourist profiles can be
discriminated in a statistically significant way, within the limits implicit to the present
study (it has to be noticed that profiles that are not found to be ‘significantly different’ in
the present survey could, in principle, be found to be distinguishable if the number of
questionnaires is increased – i.e., if the discriminatory power of the survey improved).
The question we want to answer is therefore: “which tourist profiles present a
significantly different behaviour in their daily and/or total per capita spending?”. In order
to approach this problem in a transparent and objective way, a statistical test has to be
applied. As the most common assumption of a normal distribution of spending is not
supported by experimental data (see e.g. Figure 28, which tends to present ‘tails’ in the
distributions of tourist expenditures), we opted for a non-parametric standard statistical
test: the Wilcoxon Rank Sum Test. The test compares two sets of data and express the
eventual disparity between the two medians, evaluated from the two sets, in terms of a pvalue7.
7
The p-value answers this kind of question: “if the difference between the medians of two sampled
populations were zero, what is the chance that a random collection of samples (in a number equal to that of
the available Questionnaires) would result in a median difference as far from zero as that observed for the
analyzed data?”. In simpler words, if the p-value is ‘sufficiently small’, one can be ‘relatively sure’ that the
medians of the two datasets really differ. If this is not the case, it should be concluded that on the basis of
52
The standard conventional threshold of significance used to justify a claim as a
statistically significant effect is p-value < 0.05 (i.e., the term statistically significant has
become synonymous with p-value < 0.05). We will also adopt this convention.
Daily
Total
Number of expenditure per expenditure per
Questionnaires
capita
capita
p-value
p-value
organization: package/non-package
package vs. non-package
39 vs. 122
.200
.008
43 vs. 118
.629
.014
127 vs. 13
.747
.768
4 vs. 15
4 vs. 140
15 vs. 140
.027
.062
.719
.027
.006
.092
52 vs. 109
.000
.000
8 vs. 153
.953
.029
cruising/non-cruising
cruising vs. non-cruising
motivation: cultural or other
culture vs. other
main reason for travelling
business vs. friends
business vs. holiday
friends vs. holiday
day-tripper/non-day-tripper
day-tripper vs. stay-night(s)
nationality
Norwegian vs. foreigner
Table 13: p-values associated with the Wilcoxon Rank Sum Test. p-values smaller than 0.10 are
highlighted in boldface, those smaller than 0.05 (conventional threshold of significance) in red
From Table 13 it emerges that, in terms of per capita daily spending, the several profiles
of tourists tend to be characterized by expenditures that are ‘relatively similar’.
Significant differences are only observed in relation with:

day trippers vs. tourists spending the night in Bergen (as can be expected, as the cost
for accommodation represents one of the most relevant items in the spending pattern,
see Figure 28, Figure 30 and Figure 31);

‘business tourists’, that in the Survey appear to be characterized by relatively high
8
daily expenditures (see also Table 11) .
An example of the comparison of the per capita daily expenditure by two classes of
tourists (package vs. self-organized) is reported in Figure 33. For this specific
comparison, the Wilcoxon Rank Sum Test brings to a p-value of 0.20 (see Table 13), i.e.,
the difference between the medians shouldn’t be judged as ‘significant’ for these two
profiles of tourists (as long as the convention p-value < 0.05 has been adopted).
the available data it is not possible to discriminate between the value of the medians in the two datasets
(and, consequently, they should be treated as ‘indistinguishable’ in this respect).
8
However it has to be noticed that only 4 questionnaires are available for this profile of tourists, so that the
generality and representativeness of this conclusion is at least ‘questionable’.
53
Figure 33: comparison between the daily per capita spending of ‘package’ and ‘non-package’ tourists
(the red lines refer to the mean value)
The general situation changes substantially if the analysis is done on per capita total
spending (i.e., per capita expenditures over the whole length of stay in Bergen – see right
column in Table 13). The fact that in most cases the medians of the daily per capita
expenditures were found not to be significantly apart, while those of the total per capita
spending appeared to be significantly different, strongly suggests that the source of
dissimilarity between the different tourist profiles is more related to the different length
of stay than to different spending behaviours.
As already anticipated, Figure 34 shows the length of stay for the case of ‘cruising’ and
‘non-cruising’ tourists, where it emerges rather clearly that ‘non-cruising’ tourists have a
tendency to stay in Bergen for longer time intervals. It is mainly this disparity in the
length of stay, which causes the total spending of the two tourist profiles to be
significantly different (see Table 13).
Figure 34: number of nights spent in Bergen for ‘cruising’ vs. ‘non-cruising’, the red lines
correspond to the mean values
The same is true, e.g., for the ‘package’ and ‘self-organized’ tourists (shown in Figure
35). The significant differences in the per capita total spending – reported in Table 11 –
find, also in this case, their origin in the crucial dissimilarity in the average length of
stay.
54
Figure 35: same as Figure 34 but for ‘package’ and ‘non-package’ tourists
From the analysis reported in Table 11 and Table 13, it emerges therefore that:

self-organized tourists tend to spend more, during their whole stay in Bergen, than
‘package tourists’;

cruising tourists have a significantly lower total expenditure than their counterparts;

the total expenditure of business tourists is confirmed to be significantly high, not only
in terms of daily spending but even if the spending over the whole duration of the stay
in Bergen is taken into account;

tourists spending at least one night in Bergen have, as can be obviously expected, a
bigger economic impact than day-trippers;

the interviewed Norwegian tourists tend to be characterized by significantly higher
total spending than tourists coming from abroad;

no peculiar behaviour can instead be established in the spending characteristics of
cultural tourists, nor in daily neither in total expenditures9.
Although cruise visitors do not necessarily avail themselves of local ‘on shore’
accommodations, their average per capita daily spending is found to be comparable to
that of ‘non-cruising’ tourists (see Table 13). This implies that the minor spending in
accommodation is compensated by higher expenditures in other items, as can be seen in
Figure 30. However, when reasoning in terms of the per capita economic impact over the
whole length of stay, cruise tourists are found to bring on average less money than their
non-cruising counterparts. The main reason for this behaviour is that cruise tourists tend
to stay a shorter time in Bergen, than the other tourist profiles, see Figure 34.
Consideration about the impact of cruises should, however, require pieces of information
that trespass the aim of this Annex. We have been focusing uniquely on onshore spending
of cruise tourists in Bergen. However industry wide, cruise ship spending comes from a
variety of other sources (see, e.g., Moloney, 2004):
7
However it has to be noticed that Bergen is perceived as a ‘cultural goal’, that is nearly all the interviewed
tourists – over 90% – declare ‘cultural experience’ to be the major driving reason for travel to Bergen.
55

the ships’ crew would also have an impact on Bergen economy, as part of the crew
will have ‘shore leave’ for at least some time during a ship’s visit. Per capita
expenditures by crew members are, however, considered to be relatively low,
compared to per capita expenditures of cruise passengers;

in the course of a cruise stopover, each cruise ship incurs a number of auxiliary
expenditures. These include, e.g., vessel spending (the amount the cruise lines pay for
fuel, food and provisions, agency fees, line handling, garbage removal, sludge
removal, water, ship repairs/parts, etc.), harbour dues, pilotage and other port charges.
In common with expenditures by passengers and crew, these expenditures might
provide a beneficial contribution to the local economy;

other intangible benefits might accrue in the host region from cruise ship business; one
of such benefits is the enhanced return to the region of passengers who have
previously visited the area on cruise ships. The International Cruise Market Monitor
(1996), estimates that up to “50% of all cruisers expect to return to the areas they
have visited on a cruise”.
However, taken as a whole, the cruise industry is not necessarily a “cash cow.” It does
come with its own multifaceted array of costs, as e.g. those mentioned in Regan and
Prisloe (2004): advertising and marketing expenses for the port; organization of shuttle
coaches from the harbour to the tourist attractions and consequent congestion, crowding
and pollution; construction and maintenance of piers and terminals; potential demand on
local health care system for passengers needing medical attention; environmental hazards
(e.g., ship discharges); increased costs for infrastructure, port security and other services.
This is just a ‘sample’ of the level of complexity that has to be approached in a site
specific ‘cost/benefit’ kind of analysis. This is, however, outside the aims of the present
Annex and we will therefore go back to our initial task: an Input-Output analysis of the
monetary economic impact.
In order to implement the Input-Output analysis, the expenditures evaluated over the
spending categories used in the Questionnaire (i.e., accommodation, food and beverages,
transport in, entertainment, culture, shopping, crafts and other retail trade) have to be
transposed into relevant sectors of the economic classification used by the Statistical
Office in the formulation of the Input-Output table. Due the limited information on the
items bought by tourists during their stay in Bergen, the conversion is done by taking into
account only the four following economic sectors:

52 - retail trade, except for motor vehicles, motorcycles; repair of personal and
household goods;

55 - hotels and restaurants;

60 - land transport; transport via pipelines;

92 - recreational, cultural and sporting activities.
The conversion from the spending categories used in the Questionnaire into the economic
sectors used by the Input-Output is implemented as follows:
56
52
55
60
92




weight · food and beverages + shopping + crafts + other retail trade
(1 - weight) · food and beverages + accommodation
transport in
entertainment + culture
where weight is a parameter that refers to the fraction of the ‘food and beverages’
expenditure that is purchased at retail trades, consequently, (1 – weight) is the
complementary fraction that is consumed at hotels and restaurants. A value of the
parameter weight very close to .5 was estimated on the basis of auxiliary information
contained in the questionnaires (i.e., where and how breakfast, lunch, dinner and other
eventual meals were consumed).
It has also to be noticed how the economic classification routinely used by European
Statistical Offices tends to be rather adequate for the description of the industrial
component of economy (about 20-30 sectors are related to manufactory activities) but
appears to be relatively poor with respect to tourism related analysis. For examples, no
distinction is done between hotels (accommodation) and restaurants (food and beverages)
and, with a particular focus on cultural tourism, between cultural and
recreational/sporting activities.
57
7Economic impact
A basic information, collected by Statistical Offices and released in the form of InputOutput tables, concerns the flow of products from each economic sector considered as a
producer to each other economic sector considered as a consumer. One of the main
fascinations of the Input-Output approach is the ability to take consistently into account
this complex network of interdependences between the different sectors of the economy
of concern.
In its most usual implementation, the Input-Output model relies on the existence of an
exogenous spending (i.e., an external independent ‘driving term’): one of the most
common uses of Input-Output techniques is the assessment of the effects on economy that
are induced by a specific type of external demand. In our case, the basic kinds of
transactions that constitute the exogenous spending are those related the expenditures of
the variety of tourists visiting the region of concern. In the present Annex, we are mainly
concentrating on a kind of normalized impact on local economy, i.e., that driven by the
average total spending (i.e., over the entire length of stay in Bergen) of a single
hypothetical tourist. If necessary, the normalized results can be re-scaled by means of:
Economic Impact = Number of Tourists · Average Total Spending · I-O Multiplier
where Number of Tourists corresponds to the number of additional tourists that are
expected to be attracted in the region of concern, the Average Total Spending reflects the
per capita tourist expenditure over the whole length of stay in Bergen (as empirically
derived, for several tourist profiles, in Table 11, or as estimated on the base of policy
considerations) and the I-O Multiplier reflects the property of local economy (and will be
the main subject of the present Section)10.
If, for example, one were interested in the estimation of the potential economic impact
originating from the implementation of a specific tourism policy focussed in attracting
more tourists in the region, one could opportunely ‘re-scale’ the Number of Tourists. On
the other hand, if one were interested in the monetary impact of policies aimed at the
selection of particular profiles of tourists or at incrementing their length of stay in
Bergen, the Average Total Spending, would be the most natural parameter to be ‘rescaled’ in this kind of ‘what-if’ exercise. In contrast, policies dedicated to the
improvement of the inter-linkages among the local enterprises would have mainly an
11
impact on the value of the I-O Multipliers .
A quantitative global analysis of the monetary economic impact of tourism spending
requires therefore an estimation of Number of Tourists to the region (eventually
Alternatively, the Average Daily Spending could have been used instead of the Average Total Spending,
in case the main interest were the estimation of the economic benefits related to a tourist spending one
more day in Bergen.
11
One has however to remember that, due to the linear approximation intrinsic to the Input-Output
approach, the magnitude of the Input-Output Multipliers will depend uniquely on the pattern of spending
and on the characteristics of local economy. If the exogenous spending is doubled (i.e., if the number of
tourists, or the average daily spending or the length of stay is doubled), the I-O Multiplier would remain
unaffected and the estimated impact on local economy will also simply double.
10
58
disaggregated over the segmentation used to capture the special characteristics of the
different tourist profiles), of the Average Total Spending and of the I-O Multipliers.
Estimates or projections of tourist activity could come from a demand model or some
systems for measuring the levels of tourism activity in the area. However developed,
carefully designed measurements of tourist activity and a proven demand model are the
very foundations of meaningful global quantitative analysis. This step also is usually the
weakest link in most tourism impact studies, as few regions have accurate counts of
tourists, let alone good models for predicting changes in tourism activity or separating
local visitors from outside the region.
As already mentioned, we will however limit the scope of this Annex to an estimation of
the incremental economic impact related to a single additional tourist. Use will be made
of the spending patterns derived, in Section 2.2, for different tourist ‘profiles’ (e.g.,
cruising vs. non-cruising), from the site-specific Questionnaires. These normalized results
could, however, be importunately extrapolated to forecasting or global analysis if future
projection or assumptions about the actual the Number of Tourists were available.
7.1 Sale multipliers
A sale multiplier is defined as the total value of production (in all sectors of economy)
that is necessary to satisfy an exogenous unitary increment in the local tourist spending
(i.e., a 1 €increase in the tourism-related final demand). The value assumed by the sale
multiplier can be useful in selecting policy strategy: e.g., if a local government were
trying to determine in which sector of the economy to spend an additional €(or whatever
amounts), comparison of sale multipliers would allow to identify where this spending
would have the greatest impact in terms of total €value of sales generated throughout the
local economy. If maximum total sale effects were the exclusive goal of government
policy, it would always be rational to invest in the sector (or to attract those profile of
tourists) whose sale multiplier was the largest (of course, there might well be other
reasons, as taking into account strategic factors, equity, capacity constraints for sectoral
12
production, etc.) .
The effects on the output of the Norwegian economy driven by the total spending of a
‘generic tourist’ during his/her stay in Bergen are shown in Figure 36. It can be noticed
that the direct expenditure (in blue in the figure) accrues to a limited number of economic
sectors (precisely, the four sectors selected as representative of ‘tourism industries’ in the
Input-Output modelling) and is then ‘more equally’ re-distributed, across the interlinked
economic sectors, through the various passages in the chain of suppliers (i.e., indirect
effects, represented in the figure through a colour scale ranging from red to yellow).
Several sectors (e.g., 70 - Real estate services, 74 - Other business services and 15 - Food
products and beverages) though, under the hypothesis of the modelling, not directly
impacted by tourism spending, receive a distinctive indirect benefit from tourism, as they
12
Note, however, that under the assumptions of Input-Output methodology, sale multipliers may overstate
the effect on the economy if some sectors are operating at or near capacity and hence some of the needed
new inputs would have to be imported to the economy and/or outputs from some sectors would be shifted
from exports to inputs in the economy. This kind of consequences will assume even more importance in
local models (i.e., at municipality or County scale).
59
are ‘tightly interlinked’ with the ‘tourism industries (i.e., these sector play a dominant
role in the ‘chain of suppliers’ of the ‘tourism industries’).
The consequences of the redistribution of the direct spending across the economy become
even more evident if induced effects are included, Figure 37. As reported in Section
5.1.1, by closing the Input-Output matrix with respect to households, the additional
induced effects of household income generation through payments for labour services and
the associated consumer expenditures on goods produced by the various sectors are
captured in the model. The results are shown in Figure 37, which clearly shows
incremental benefits for both the local economy and the private households (the impact
on salaries will be the topic of Section 7.2).
60
Figure 36: economic impact on Norwegian economy from the total expenditure of a ‘generic’ tourist
in Bergen. The direct expenditures (i.e., the money directly spent from the average tourist and
accruing to the ‘tourist industries’) are shown in blue (4 sectors are taken into account as
representative of ‘tourist industries’). The indirect effects are additionally added by using a fading
colour scale: in red are shown the effects related to the ‘first round’ through local economy (i.e.,
suppliers of ‘tourist industries’), in orange the effects of the ‘second round’ (i.e., suppliers of
suppliers of ‘tourist industries’), and so on. Each round (or ‘ripple’) through local economy is smaller
than the previous one, as part of the money tends to ‘leak out’ from the geographic area being
studied. While building I-O Multipliers, Input-output models consider and sum up all these successive
rounds of spending
Figure 37: same as Figure 36, but including direct, indirect and induced effects (and, on the left side of
the figure, the ‘new’ economic sector 95 – Private households’, now treated as endogenous)
As explained in details in the main body of the PICTURE Deliverable 13, the global
impact of tourism on economy can be condensed into opportunely defined indicators,
known as Input-Output multipliers. The sale multiplier, including indirect and induced
effects, is usually estimated taking into account the total sale effect over the original N
economic sectors only (i.e., not including the new ‘private household’ sector). This
multiplier is also sometimes indicated as the truncated sale multiplier.
61
Sale multipliers (impact of a tourist in Bergen on the Norwegian economy) are reported
in Table 14. They are a-dimensional quantities that give an account of the sales, which
are driven by an unitary spending from a visiting tourist. For example a sale multiplier of
1.59 means that a tourist spending of 1 €causes, in the whole economy, a series of
interlinked sales summing up to 1.59 €(i.e., 1 €as direct and 0.59 €as indirect and/or
induced).
Sale Multiplier
Sale Multiplier
[indirect effects]
[indirect and induced effects]
[impact on households excluded]
1.59
1.56
1.62
1.56
1.55
1.60
1.61
1.62
1.56
1.68
1.56
1.60
1.56
1.57
2.44
2.38
2.56
2.35
2.34
2.48
2.52
2.53
2.36
2.71
2.35
2.48
2.38
2.38
package
non-package
cruising
non-cruising
culture
other
business
friends
holiday
day-tripper
stay-night(s)
Norwegian
foreigner
‘generic tourist’ [all questionnaires]
Table 14: sale multipliers on Norwegian economy for different profiles of tourists
As can be seen from Table 14, the sale multipliers for the different profiles of tourists are
rather similar. The resemblance remains relatively high also when the effect on sales is
analyzed in terms of the four economic sectors that tend to be stimulated by the tourist
spending (i.e., the ‘tourism industry’; see Table 15).
Sale Multiplier
Sale Multiplier
[indirect and induced effects]
[indirect effects]
[impact on households excluded]
52 - Retail trade services [except of motor vehicles
and motorcycles; repair services of personal and household goods]
55 - Hotels and restaurants services
60 - Land transport [transport via pipelines services]
92 - Recreational, cultural and sporting services
1.78
3.04
1.44
1.59
1.61
2.01
2.33
2.43
Table 15: same as Table 14, but with reference to the economic sector where the direct expenditure
occurs (‘tourism industries’)
Among these four sectors, ’52 – Retail trade service’ appears to be the ‘most efficient’ in
‘amplifying’ the tourist spending, while ’55 – Hotels and restaurants services’ appears to
have a ‘lower efficiency’ in ‘exciting’ the local economy.
62
After the re-scaling of the Input-Output matrix to the Hordaland County (see Section
5.1.2), regional sale multipliers can also be estimated, as reported in the following Table:
Sale Multiplier
package
non-package
cruising
non-cruising
culture
other
business
friends
holiday
day-tripper
stay-night(s)
Norwegian
foreigner
‘generic tourist’ [all questionnaires]
Sale Multiplier
[indirect effects]
[indirect and induced effects]
[impact on households excluded]
1.19
1.19
1.21
1.18
1.18
1.20
1.21
1.21
1.19
1.23
1.19
1.20
1.19
1.19
1.29
1.28
1.32
1.27
1.27
1.30
1.31
1.31
1.27
1.34
1.27
1.30
1.28
1.28
Table 16: same as Table 14, but here the impact of tourism in Bergen is estimated at the regional
scale of the Hordaland County (and not at the national Norwegian scale)
It can be noticed that, as expected, the multipliers at regional scale are considerably
smaller than those related to the impact on the economy at national scale. As discussed in
more detail in the main body of the PICTURE Deliverable 13, the extent of indirect and
induced effects depends both on the size of the region under study as well as on the
strength of the inter-relationships between the different sectors of the economy of
concern. Generally speaking, the smaller the area of concern, the faster the initial direct
expenditure may ‘leak’ out of the study area, causing weaker indirect and induced effects
and consequently smaller I-O multipliers.
7.2 Income and Employment multipliers
As the name implies, income multipliers attempt to translate the impacts of changes in
final demand spending into changes in income received by households (i.e., labour
supply), rather than translating the final demand changes into total value of sectoral sales
as the previously reported multipliers.
The income multipliers, similar to the sale multipliers, are relatively ‘insensitive’ of the
tourist profiles. For the different profiles, the income multipliers tend to vary in the
following ranges:
impact on Norwegian economy related to direct and indirect effects
impact on Norwegian economy related to direct, indirect and induced effects
impact on Hordaland economy related to direct and indirect effects
0.37 ÷ 0.51
0.54 ÷ 0.75
0.29 ÷ 0.41
63
impact on Hordaland economy related to direct, indirect and induced effects
0.32 ÷ 0.44
Table 17: ranges of variation of income multipliers related to tourism in Bergen
Finally, from the relationships between the value of the output of a sector and the
employment in that sector (in terms of employees per €worth of output), it is possible to
estimate an employment multiplier. Contrary to the sale and income multiplier, the
employment multiplier is a dimensional indicator, expressed as the increase in the
number of employees driven by an additional spending. The values reported in Table 18
refer to additional employees per 1 million €additional tourism expenditure.
package
non-package
cruising
non-cruising
culture
other
business
friends
holiday
day-tripper
stay-night(s)
Norwegian
foreigner
‘generic tourist’ [all questionnaires]
Employment Multiplier
Employment Multiplier
[indirect effects]
[indirect and induced effects]
Norway
13.3
12.6
14.7
12.3
12.2
14.2
14.3
14.3
12.3
16.3
12.4
13.8
12.6
12.7
Hordaland
11.1
10.5
12.5
10.2
10.1
12.0
12.1
12.0
10.3
13.9
10.3
11.7
10.5
10.6
Norway
18.4
17.5
20.4
17.1
16.9
19.5
19.7
19.8
17.2
22.6
17.2
19.2
17.5
17.6
Hordaland
11.7
11.1
13.2
10.8
10.7
12.7
12.7
12.7
10.9
14.6
10.9
12.3
11.1
12.3
Table 18: ranges of variation of employment multipliers related to tourism in Bergen. The
multipliers are expressed as the number of additional employees driven by an increment in tourism
expenditure of 1 million €
The increase in variability (in particular with respect to the sale multipliers) is mainly a
consequence of the different ‘labour intensity’ of the ‘tourism industries’. As can be
noticed from Table 19, the Sector ‘52 – retail trade services’ is characterized by a
relatively high labour intensity and, consequently, tourist profiles whose spending pattern
(in terms of percentage of total spending) insists on this sector will be characterized by
higher employment multipliers.
Employment Multiplier Employment Multiplier
[indirect effects]
[indirect and induced effects]
Norway
Hordaland
Norway
Hordaland
52 - Retail trade services
[except of motor vehicles
and motorcycles; repair services of personal and household goods]
20.8
18.1
28.4
19.1
55 - Hotels and restaurants services
60 - Land transport [transport via pipelines services]
8.7
9.9
7.0
8.1
12.2
14.3
7.4
8.7
64
92 - Recreational, cultural and sporting
services
10.5
7.9
15.5
8.3
Table 19: same as Table 18, but with reference to the economic sector where the expenditure occurs
65
8Conclusions
Economic impact analysis focuses on the actual flows of money related to market
transactions. It reflects how tourists contribute to local economy, as they purchase goods
and services in that economy and its scope is therefore quite different from a ‘more
general’ cost/benefit analysis.
Estimates of the economic impact of tourism spending (and its ‘ripple’ effects) are most
accurately made through Input-Output analysis. Purchases of goods and services that are
made from suppliers outside the area of concern are considered to be ‘leakages’ and are
not included in the economic impact estimates. The direct spending of tourists visiting the
geographic area of concern (the so-called direct effect, mainly accruing to the ‘tourist
industries’) sets off successive rounds of spending (or ‘ripples’) by the supplying
industries and services (the so-called indirect effect). Each succeeding round of spending
tends to be smaller than the preceding one, as money gradually ‘leaks’ out of the
geographic area being studied. In parallel to the increment in sales, local employment and
consequently the locally earned wages and salaries would also increase. These increased
earnings will be spent locally, for the most part, thereby producing even more spending in
the region (the induced effect).
Input-output models sum up all these successive rounds of spending, thus allowing the
estimation of a total spending, or output, impact. In the Input-Output framework, the total
impact equals the direct spending plus the indirect effect plus the induced effect.
Estimates of the total income and employment generated are calculated in a similar way.
In the present Annex, an analysis of the economic impact of tourism activities in Bergen
has been presented. The analysis is based on the aforementioned Input-Output
methodology (discussed in details in the framework of PICTURE Deliverable 13).
Expenditure pattern data, extracted from an on-site survey for different profiles of
tourists, have been inputted into an Input-Output model in order to estimate the changes
in local final demand resulting from the expenditures of tourists. In essence, the model
adds to the direct effects (as estimated from the Survey), the successive rounds of interindustry expenditures (indirect effect), plus the changes in local household spending
resulting from the wages and salaries generated by tourism (induced effect). The
economic impact on sales, income and employment has been assessed at both national
scale (Norway – original Input-Output matrix), as well as regional scale (Hordaland
County – re-scaled Input-Output matrix).
Contrary to the other two Mediterranean PICTURE case studies (Syracuse and Elche) in
the case of Bergen, it is not easy to tell apart ‘cultural’ from ‘leisure/sun&beach’ tourists.
Almost all tourists coming to Bergen perceive themselves as attracted by its cultural,
natural and environmental assets and a clear counterpart does not seem to exist. A clear
distinctiveness is on the contrary represented by cruising visitors, and that is also why we
focused on this form of tourism.
Also with respect to the daily and total per capita expenditures, no significant
differences are found between cultural tourists and visitors brought to Bergen by other
66
motivations. The data presented in the previous pages show that ‘culturally motivated’
visitors have an average daily spending (46.9 €, just as the ‘generic tourist’ – see Table
11), higher than that of a ‘non-cultural’ tourist. In particular, the cultural tourist spends
more than a non-cultural tourist for all expenditure items (transport in the destination,
shopping, food, entertainment, crafts and of course cultural visits), except
accommodation and other retail trade (see Figure 30). On the contrary, the total spending
(i.e., over the whole length of stay in Bergen) is below-the-average (110 €compared with
129 €of the generic tourist), very similar to the one of a non-cultural tourist and the same
as a generic “holiday tourist” (see Table 11). This shows how ‘culturally motivated’
tourists tend to be ‘more mobile’, staying for shorter times in one single location.
As a consequence of the shorter length of stay in Bergen, both the indirect and the
induced impacts of a cultural tourist on the Norwegian economy (during its stay in
Bergen) are the lowest among the impacts of the different typologies of visitors (see
Table 14). After having rescaled the Input-Output matrix to the Hordaland County, the
contribution to the economy of the cultural tourists is comparable with that of other
typologies of visitors, although remaining among the lowest (see Table 16). This also
translates in a lower support to employment than the other typologies of visitors (see
Table 18).
In the Bergen case-study, the total number of face-to-face interviews was restricted to
161, due to the limited available resources. It is important to underline that, from a
statistical point of view, the number of collected Questionnaires is relatively small.
Consequently, the results reported in this Annex should be seen as a preliminary ‘pilot
assessment’: their importance being mainly a study of trends and behaviour of different
typologies of tourists rather than an evaluation of quantitative reliable results.
Anyway, even though the economic impact of cultural tourism, during his/her staying in
Bergen, seems to be inferior to that of other typologies of tourism, it shouldn’t be
forgotten that cultural tourism is part of a number of synergies including local economic
development, environmental conservation, the enhancement of heritage and cultural
production, and even the senses of identity and well-being of local communities. In
addition to that, cultural tourists are expected to have lower local costs and more spread
benefits over local business activities; thus contributing more clearly to the economic,
cultural and political benefit of local communities.
From our pilot study, it emerges that the average spending of the intercepted tourists
visiting Bergen is not particularly high, despite the fact that Norway is well known to be
one of the most expensive destinations in Europe. This is due, above all, to the fact that
the length of stay is relatively low for each of the analysed tourist profiles.
Bergen seems to be affected, if possible more than other destinations, by one of the most
typical phenomena related to cultural tourism development in European cities: the great
fragmentation of holidays, which multiplies short visits (see, among other, Cabrini,
2003). Cultural tourists are “sophisticated tourists”, always in search of different and
undiscovered backgrounds and locations. This fact implies that return visits are rather
unusual. «Every visit would be a unique experience» (Malta Tourism Authority, 2002, p.
6): tourists have pre-marked sites and ‘work of art’ that must be visited if the place is to
be authentically experienced. Once ‘collected’, a repeat visit becomes superfluous and the
67
‘collection’ must be expanded elsewhere. Ironically the more unique the heritage
experience, the less likely it is to be re-visited.
As a consequence, policies aiming at extending tourists’ permanence (except for cruisers,
whose length of stay and behaviour depend from the features of the cruise industry), as
well as at attracting both first time and repeat visitors, might be improved.
Cultural (mega) events and festivals, for instance, offer interesting opportunities for city
destinations in attracting both first time and repeat visitors (ECT & WTO, 2005).
According to an Internet poll carried out in 2004 by ECT (ECT & WTO, 2005, p. 37 and
101), cultural festivals and events are perceived by 88% of the respondents as important
reasons for cultural tourists to choose to specifically visit a place. The destination must be
perceived as original and dynamic, and always changing. But before launching different
cultural tourism activities, it is important to reflect on the importance of authenticity. The
risk is the creation of events and activities thought to attract the tourist, with no/little link
with the local culture, and consequent loss of local identity.
68
9Bibliography
Ashworth G. J. (2004), The blue - grey transition: heritage in the reinvention of the
tourism resort, Faculty of Spatial Sciences, University of Groningen (NL).
Bonfiglio A. (2006), A Sensitivity Analysis of the Impact of CAP Reform. Alternative
Methods of Constructing Regional I-O Tables, University of Marche, Ancona, Italy,
http://associazionebartola.univpm.it/pubblicazioni/phdstudies/phdstudies1.pdf.
Cabrini L. (2003), Cultural Tourism: Opportunities and Challenges, presentation at the
European Forum of the World Heritage Cities, Luxembourg.
City of Bergen (2005), Bergen’s successful City Of Culture in the year 2000,
http://www.bergen.kommune.no/kultur/Eng._oppsummering_2005.doc.
City of Bergen (2006a), 2005 was an excellent year for the tourism industry in Bergen,
Press
release,
11
January
2006,
http://www.visitbergen.com/pdf/Press%20release%2011%20Jan%202006.pdf.
City
of
Bergen
(2006b),
Additional
http://www.visitbergen.com/pdf/Cruise_Port_Information_additional.doc.
City
of
Bergen
(2006c),
Bergen
http://www.bergen.kommune.no/info_/ekstern/engelsk/.
City
of
Bergen
(2006d),
Cruise
calls
http://www.visitbergen.com/pdf/Cruise_statistics.pdf.
at
information,
in
brief,
Bergen
Harbour,
European Cities Tourism Research and Statistics Working Group (2004), Proposal for a
questionnaire design for tourism visitor surveys in European cities,
http://www.europeancitiestourism.com,
http://tourmis.wu-wien.ac.at/material/eurocitymanual.pdf.
ETC – European Travel Commission and WTO – World Tourism Organization (2005),
City Tourism & Culture. The European Experience, ETC Research Report n° 2005/1,
Brussels.
Hordaland County Council (2004), Hordaland. The Central County of Western Norway,
http://www.hordaland.no/upload/Forsida/Dokument/BrosjyreEnglish051.pdf.
Wild G P (1996), International Cruise Market Monitor, Quarterly Commentary and
Analysis, 2 (4).
Malta Tourism Authority (2002), Strategic Plan 2002-4, Valletta.
Moloney R. (2004), The Economic Contribution of the Port of Cork’s Cruise Ship
Business to Ireland – An Input-output Analysis, Business Briefing: Global Cruise,
http://www.touchbriefings.com/pdf/858/moloney.pdf.
Regan W. M. and Prisloe M. R. (2004), The Economic Impact of a Cruise Ship Visit on
Connecticut’s Economy, Department of Economic & Community Development, Hartford,
69
Connecticut,
http://www.ct.gov/ecd/lib/ecd/crusie_ship_in_new_london_eia_3.19.04_.pdf.
Richards G. (1996), Cultural Tourism in Europe, CABI, Wallingford, http://www.atlaseuro.org/pages/pdf/cultural%20tourism%20in%20europe.PDF.
Stynes D. (1999), Economic Impacts of Tourism, Michigan State University,
http://www.msu.edu/course/prr/840/econimpact/pdf/ecimpvol1.pdf.
West G. R. (1999), Notes On Some Common Misconceptions In Input-Output Impact
Methodology, Discussion Papers Series 262, University of Queensland, Australia,
http://eprint.uq.edu.au/archive/00000414/01/DP262Oct99.pdf.
World Tourism Organization (1993), Recommendations on Tourism Statistics, WTO,
Madrid, in: Richards G. (1996), Cultural Tourism in Europe, CABI, Wallingford.
70