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The purpose of this paper is to analyze the dynamic competitive profile of Istanbul and to
compare it to ten other European cities by using a multidimensional approach.
International Journal of Culture, Tourism and Hospitality Research
Assessing Istanbul competitiveness: a multidimensional approach
Valeria Minghetti Federica Montaguti
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Valeria Minghetti Federica Montaguti, (2010),"Assessing Istanbul competitiveness: a multidimensional approach", International J ournal of
Culture, Tourism and Hospitality Research, Vol. 4 Iss 3 pp. 228 - 240
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Assessing Istanbul competitiveness:
a multidimensional approach
Valeria Minghetti and Federica Montaguti
Abstract
Purpose – The purpose of this paper is to analyze the dynamic competitive pro?le of Istanbul and to
compare it to ten other European cities by using a multidimensional approach.
Design/methodology/approach – Starting from a review of existing competitiveness models, the
paper develops a methodology that takes into account the complex shifting nature of the network of
‘‘mobilities’’ interacting within and around the destination.
Findings – The proposed approach proves to be effective in designing a dynamic competitive pro?le of
every city and in identifying the factors that drive competitiveness within and between different
competitive clusters of cities.
Originality/value – The newapproach presents several original elements, since it embeds the evolution
of the system of diverse intersecting tourism and non tourism ‘‘mobilities’’ that characterize an urban
destination, and integrates different dimensions and disciplinary points of view.
Keywords Tourism, Cities, Competitive strategy, Europe
Paper type Research paper
Introduction
Visiting cities is an ever-growing tourismactivity in Europe. Also thanks to the enlargement of
the European Union, urban tourism ?ows for different purposes (visit to attractions, events,
business, etc.) are expanding at a faster rate than tourism in general (European Travel
Commission, 2008). Traditional cultural cities are places that were not created for tourism
development and where tourism has established itself within the changing economic, social
and cultural environment. Tourism activities interact with other urban functions as part of a
system of overlapping ?ows and relationships (Laws, 1993).
Besides, cities are places in motion, nodes of dynamic networks of different physical and
virtual ‘‘mobilities’’ (Urry, 2007) – tourists, residents, businesses, capitals, culture,
knowledge, etc. – that constantly reshape the urban space, the organization of tourism
and non-tourismpractices and the city image and brand. Fromthis point of view, not only the
tourism performance of a city depends on the attractiveness of core resources (historic,
cultural, etc.) and the quality of tourism-related facilities, but also on the evolution of these
networked ‘‘mobilities’’. This development implies building a model that explicitly considers
all these aspects.
The article analyzes the dynamic competitive pro?le of Istanbul in comparison to other ten
European cities (Venice, Florence, Rome, Barcelona, Bruges, London, Paris, Prague, Seville
and Vienna) – a pro?le developed according to a multidisciplinary and multidimensional
approach taking into account the evolution of this system of diverse intersecting tourism and
non tourism ‘‘mobilities’’. The approach and the results obtained derive from a
research-work the Tourism Competitiveness Department of the Italian Government
commissioned to CISET. The study aimed at developing a benchmark analysis by
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VOL. 4 NO. 3 2010, pp. 228-240, Q Emerald Group Publishing Limited, ISSN 1750-6182 DOI 10.1108/17506181011067619
Valeria Minghetti is a senior
researcher and
Federica Montaguti is a
researcher, both based at
CISET, Venice, Italy.
Received December 2009
Revised January 2010
Accepted March 2010
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comparing the competitiveness of the three most famous Italian art cities (Florence, Rome
and Venice) with the other eight given European cities.
After having de?ned the concept of ‘‘city to play’’ and the role that tourism ‘‘mobilities’’ and
other ‘‘mobilities’’ have in analyzing the tourismperformance of a city, the paper presents the
methodology used for the analysis and the multidimensional approach developed for
monitoring the competitiveness of an urban destination. Starting from these elements, the
article then outlines the dynamic competitive pro?le of Istanbul and of the other cities. Four
common development and evolution patterns (‘‘clusters’’) have been identi?ed, showing
how Istanbul positions itself in comparison to the European cities analyzed. The ?nal section
draws conclusions, and provides indications for future research.
De?ning a ‘‘city to play’’: the role of tourism and other ‘‘mobilities’’
According to recent studies, cities and destinations are transforming themselves from
‘‘space of places’’ to ‘‘space of ?ows’’ (Castells, 2000; Manente, 2000), in nodes of a
complex network of relationships among different kinds of spatial and virtual ‘‘mobilities’’ at
local and global level (see Figure 1). Spatial mobility is determined by a variety of factors,
such as increasing/decreasing population, migrations, growth in transport services and
travels, changes in urban economic structure and visitor ?ows. Its evolution also implies that
cities themselves are constantly ‘‘on the move’’, as these transformations entail the
creation/destruction of infrastructures, business and service centers, hotels, etc. How
residents, workers and tourists move within the city is also evolving, according to the spatial
Figure 1
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reorganization of the city, and the location of old and new attractions. Besides physical
‘‘mobilities’’, there are also many different virtual ‘‘mobilities’’. characterizing the cities –
capitals, investments, information, knowledge, but also ideas, memories, images, etc.
(Figure 1). The spread of information and communication technologies accelerates the
growth of these ‘‘mobilities’’.
Tourism is a component of this complex system of ‘‘mobilities’’. In the last decades, the
dramatic development of tourism ?ows and practices has heavily affected the pattern of
urban growth as well as the internal geography of destinations. In this and other ways,
tourism ‘‘mobilities’’, both physical and virtual, in?uence the dynamic development of other
‘‘mobilities’’. At the same time, non-tourism ‘‘mobilities’’ (e.g. growth of foreign investments,
settling down of creative industries, reorganization of the urban space, success of books or
?lms set in the city) impact on the development of city tourism (emerging of new leisure
segments, expansion of business tourism, etc.). They affect how tourists – or potential
tourists – move in the city, how they perceive it, what they do and see there (Bærenholdt
et al., 2004).
Consequently, cities can be seen as a dynamic ‘‘place of movement’’ (Hetherington, 1997;
see also Crouch, 2000). They are not ?xed and immobile objects, but ‘‘places to play’’,
‘‘produced through the multiple networked ‘mobilities’ of capital, persons, objects, signs and
information’’ (Sheller and Urry, 2004, p. 6; see also Coleman and Crang, 2002; Haldrup,
2004). Therefore, the challenge to become a ‘‘city to play’’ – or to hold this role – and then
become a ‘‘city in play’’ relies on the continuous and evolving interaction among tourism and
other kind of activities.
The performance of a city depends on the evolution of this system of diverse intersecting
‘‘mobilities’’. How the city moves or is mobilized through various global networks of
economic, cultural, fashion, and tourismrelationships, affects its competitiveness and image
(see also Ritchie and Crouch, 2003, p. 245). This has a major impact on ‘‘people’s decisions
to visit the city, to buy its products and services, to do business or relocate there’’ (Anholt,
2006, p. 2). On the other side, the growth of the tourist interest in the city and the
strengthening of the urban tourist brand affects its attractiveness as a place to live, work,
study, invest and so on.
Analyzing city competitiveness. Towards a multidimensional approach
The methodology used
The role of ‘‘mobilities’’ interplay has an important impact on measuring the tourism
competitiveness of an urban destination. As ‘‘tourist activities are not so separate from the
places that are visited’’ (Sheller and Urry, 2004, p. 5), and locations are continuously ‘‘made
and remade by the performances of tourists and workers, image and heritage, the latest
fashions’’ (Sheller and Urry, 2004, p. 1), capital and information, the competitiveness
analysis requires the adoption of a multidimensional approach. This perspective should take
into account the shifting con?gurations of tourism and non-tourism ‘‘mobilities’’, and assess
the role of each mobility and of a single factor in determining the success of the destination.
The main issue is to identify an alternative to traditional metrics that helps to measure the
tourismcompetitiveness of a ‘‘city to play’’, as ‘‘the ‘mobilities’ paradigminvolves newkind of
methods [. . .] ‘on the move’’’ (Urry, 2007, p. 39).
From this point of view, the set of cities identi?ed by the Italian Government for the study and
analyzed in this paper, represented a good testing ?eld. They are a heterogeneous set of
urban destinations – considering their position within the local political, economic and social
networks and the stage in their urban and tourism life-cycle. Their visitors generally do not
look for cultural tourism only (e.g. visits to museums and monuments), but also for other
activities (e.g. events, business and congress, shopping, wine and food tasting). The
brands of these cities are important not only to attract tourists, but also investments, capitals
and businesses.
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A review of the literature on existing models de?ning the destination competitiveness (Dwyer
and Kim, 2003; Enright and Newton;, 2004; Gooroochun and Sugiyarto, 2005; Maggi and
Croce, 2005; Ritchie et al., 2001; World Economic Forum, 2008) highlighted that the main
indicators used by these models were not so effective in designing competitive pro?les or in
identifying the determinants of competitiveness for these cities. The models generally
consider the destination as a tourism attraction, a relatively given and ?xed system, that is a
separate object from demand and from other ‘‘mobilities’’ networks. They apply metrics that
take into account a number of comparative and competitive factors essentially based on the
amount of resources and attractions, the stock of infrastructure and the characteristics and
quality of service facilities available at the destination. The models only partially consider
and investigate the effects on competitiveness deriving from the dynamic interaction
between demand and supply and between tourism and non tourism ‘‘mobilities’’.
A four-step research plan was therefore developed. The ?rst step was to describe and
analyze the cities’ pro?le and their appeal, according to their different features (urban,
socio-economic, innovative aspects, characteristics of tourism demand and supply, image
and brand, etc). A group of variables/indicators were then identi?ed. The indicators were
used to classify every city and frame into different competitive models, according to the
aspects investigated above. Starting from these variables, a meaningful set of summary
indicators were selected, suitable to group cities presenting similar or comparable
characteristics in a number of competitive clusters. Finally, the competitiveness of each city
within and among clusters was assessed.
The new approach developed aims at integrating the effects of the different kind of shifting
‘‘mobilities’’ in de?ning and assessing the competitive pro?le of the destination. In more
detail, the methodology:
1. provides a dynamic perspective of the city, allowing researchers to assess its actual and
future performance according to a number of quantitative and qualitative indicators;
2. analyzes the competitiveness of a city according to the competitive set identi?ed. As
stated by Enright and Newton, ‘‘speci?c tourism destinations are not competitive or
uncompetitive in the abstract, but versus competing destinations’’ (Enright and Newton,
2004, p. 781);
3. takes into account tourists’ behavior and perceptions (activities done/experiences lived
while in the city) as a dimension of the destination competitiveness and not only as an
outcome of competitiveness;
4. considers the signi?cance and variety of core resources and attractors and not only of
their physical amount. ‘‘The mere counting of the number of museums and historical sites
[. . .] may well mask the quality of these attractions- something that is often the primary
appeal to visitors’’ (Ritchie et al., 2001, p. 6); and
5. ?nally, the approach assesses the role of other ‘‘mobilities’’ and the city positioning in
global networks, as factors de?ning the city development and potential, and its capacity
to subsequently attract quali?ed investors, professionals and tourists (OECD, 2006).
Since these elements affect the city brand, integrating traditional competitiveness models
with those assessing features, brand equity, and strength of destinations/places brand
becomes essential.
The data collection
In de?ning the items to be assessed, the indexes adopted by the different approaches
analyzed from the literature were taken into account, and in particular those included in the
layers of the Ritchie and Crouch model (Ritchie and Crouch, 2003). Some aspects were not
– or partially – included since they were considered irrelevant (e.g. climate) or not signi?cant
(accessibility) for the group of top urban destinations studied. In the end, more than 90 items
were identi?ed, and assessed for each city in two different ways.
Various sources were checked to build the set of quantitative and qualitative variables and
indicators to be used to design the different competitive pro?les. The method combines the
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desk analysis of secondary sources (e.g. statistical data on tourism demand and supply,
visitors’ surveys, city development and marketing plans, etc.) with an e-mail survey carried
out with a group of about thirty international urban tourism experts and managers of city
tourist of?ces. The purpose of this survey was to appraise the items identi?ed according to
the insight they have of the whole group of cities analyzed (for experts) or of the city they
work for (for tourist of?ce managers), from different point of views.
The adoption of an expert approach mediates between supply-side and demand-side
measurements (Wo¨ber, 2006). On the one hand, tourism experts and managers have
professional knowledge of the cities analyzed, the characteristics and potentialities of local
tourismsupply and the role of different ‘‘mobilities’’. On the other, ‘‘experts judgments are often
applied because they indirectly represent the opinions of the consumers’’ (Gearing et al.,
1974, in Grabler, 1997, p. 148). In addition, since urban tourism experts are asked to judge
each relevant aspect for all cities in a row, this methodology allows researchers to obtain a
ranking of cities according to each aspect analyzed and then to compare its performance.
In order to obtain the desired empirical data, an ad hoc questionnaire was constructed
itemizing the factors that were postulated to in?uence the city competitive pro?le. In
particular, experts and city managers were asked to give their opinions on the following
aspects:
B the urban and economic pro?le of the city (current economic role and potential, quality of
urban services and environment, level of traf?c and tourism congestion, environmental
policies);
B the pro?le and behavior of tourism demand (importance of repeaters and same-day
visitors for both domestic and international market; variety of socio-demographic
segments in both markets; variety of activities done/experiences lived by tourists);
B the resonance and variety of core resources and attractors (monuments, museums,
events, shopping facilities, etc.);
B the variety/quality of accommodation supply and its capacity to meet the needs of
different expenditure pro?les;
B the price competitiveness (tourist prices’ perception and general cost of living);
B the city brand (pulse/vivacity, presence, outstanding attributes and personality); and
B the use of technology in marketing and selling the city (howeasy it is for a tourist to arrange
a stay in the city using the websites of the local tourist board and of private operators).
The survey analyzed more than 90 items through 13 questions. For each item, experts were
asked to give a score to each city using a ?ve-point Likert scale. The meaning of each scale
point was adapted according to the factors/items to be analyzed.
The summary indicators
The analysis of hard data collected from secondary sources and of soft data deriving from
the experts’ survey allowed to create a meaningful set of simple or weighted summary
indicators useful to identify the competitive pro?le of each city and then group them into
competitive clusters with similar characteristics.
The indicators chosen are representative of all the main aspects investigated (urban and
economic structure, pro?le and behavior of tourism demand, resonance of core resources
and attractors, accommodation supply, prices and brand and image). They provide a
dynamic pro?le of the city (not only a picture of the ‘‘state of the art’’ but also some future
perspectives), and are those that better emphasize the similarities and differences between
cities. Furthermore, they help to identify the city pro?les and to compare them within and
among clusters. Table I shows the nine indicators used, their meaning and how they have
been calculated.
Three indicators are demand-related (international market, visitors mix and experience mix),
three refer to local supply (resources, accommodation and prices), two to city image and
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brand (presence and pulse) and the last one to the economic structure and future
development of the city (potential). In particular, presence, pulse and potential indicators
embed the impacts of other ‘‘mobilities’’ on tourism and, speci?cally, the effects of the
evolution of the urban space and structure and of local lifestyle on the city’s identity and the
perceptions tourists have of the place. One indicator out of nine derives from statistical data
(the role of international tourism demand). The other indicators represent qualitative
variables of city competitiveness, derived from the empirical analysis by elaborating, for
each factor identi?ed, the judgments given by experts on a number of correlated items.
Istanbul’s competitive pro?le
The competitive models identi?ed
A spider plot chart combining the selected indicators was used to describe the competitive
pro?le of Istanbul and of the other cities investigated (see Figures 2 to 5). Normalized values
(0-1) were calculated in order to obtain a comparable range of values for all quantitative and
Table I Competitiveness indicators for cities to play
Indicator Meaning Calculation
Role of international tourism demand Importance of international tourists on total
tourism in the city
Share of foreign arrivals on total arrivals
(hard data)
Variety of socio-demographic
segments
Capacity of the city to attract different
demand segments (e.g. school trippers,
18-24 years old people, etc.)
Weighted mean of scores given by experts
to the importance (number and intensity) of
each socio-demographic segment on both
domestic and international markets
Variety of tourist
activities/experiences offered to
tourists
Capacity of the city to offer a varied range of
activities/experiences to tourists (i.e. how
many activities offered are done by tourists)
Weighted mean of scores given by experts
to the importance (number and intensity) of
each speci?c activity/experience offered to
both domestic and international tourists
Signi?cance of core resources and
attractors
The most important resources/attractors the
city is famous for (i.e. the capacity of the city
to promote its resources/attractors)
Simple mean of scores given by experts to
the signi?cance (variety and resonance) of
different kinds of resources/attractors
Competitiveness of accommodation
supply
Capacity of accommodation supply to meet
the requirements of clients with different
expenditure budget (luxury, upper,
average, budget, young
people/backpackers)
Simple mean of scores given by experts to
the capacity of accommodation supply to
satisfy each expenditure pro?le listed
(presence and judgment on price/quality
ratio)
Relative cost of the city for tourists Whether the city is more expensive or
cheaper for tourists than for residents (cost
for tourists v. cost of living)
Score obtained by comparing the scores
given by experts to the perceived cost of the
city for tourists and for residents
Presence of the city The city’s international role and standing in
the last 30 years
Simple mean derived from the scores given
by experts to the contribution the city has
given to the world in the last 30 years,
according to a number of aspects (e.g.
culture, style)
Pulse of the city The appeal of the city, that is the presence
of a vibrant urban lifestyle as part of city’s
brand image
Simple mean derived from the scores given
by experts to vivacity of city life both at
daytime and at night
Potential of the city The city’s future contribution and potential Simple mean derived from the scores given
by experts to the contribution each city
might give in the future in different areas
(culture, design, lifestyle, etc.) and to the
economic and educational opportunities it
offers/will offer (potential of the city and
foreseen contribution in each area)
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qualitative indicators. The polygonal area derived by linking these values represents the
city’s competitive pro?le.
The comparison of different pro?les leads to the identi?cation of four common development
and evolution patterns (clusters), showing how Istanbul positions itself in comparison to the
European cities analyzed. The distinguishing characteristics of each cluster and of each city
within the cluster are brie?y discussed herewith.
The ultimate cities. The ?rst cluster groups four cities, two global metropolitan areas (London
and Paris) and two large cities (Rome and Barcelona) (Figure 2). The shape of the polygonal
area characterizing each of them shows that they have a more or less balanced competitive
pro?le. These cities generally compete on many tourist markets (business, conventions, city
breaks, cultural tourism, events, etc.) and are characterized by a wide range of signi?cant
Figure 2 The ‘‘ultimate’’ cities
Figure 3 The ‘‘picture’’ cities
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resources and attractions (monuments, events, link to famous people, business centers,
etc.).
London and Paris are highly charismatic and lively cities and they will probably strengthen
their role in the near future. Here, tourism and other activities are all components of a
complex project of urban development. Rome presents a lower performance in comparison
to others with regards to two indicators (potential of the city and variety of tourist
activities/experiences). Although the ‘‘Eternal city’’ has acquired a pro?le similar to London
and Paris – thanks to a number of initiatives promoted by the Municipality in the last few
years – the process is not complete yet. The issue is whether the city will be able to maintain
this new role in the near future (potential).
The presence of Barcelona in this cluster is the result of a recent development, which has no
roots in a far consolidated historic role, but is the result of a strong cultural and economic
Figure 4 The ‘‘new old’’ city
Figure 5 The ‘‘young trendy’’ cities
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regeneration and a wide scale re-organization of the urban space that began after the end of
Franco’s regime (Degen, 2004). An international public acknowledged the rebirth in 1992
and, since then, tourism, economics, culture, sport and fashion networks continuously feed
and mobilize Barcelona’s ‘‘renaissance’’. This rebirth positions the city in the highest ranks
among the big capitals of urban tourism.
The picture cities. The second cluster includes three traditional art cities (Venice, Florence
and Bruges), which show a more stretched competitive pro?le (Figure 3). These cities are
generally specialized on few segments/products (basically, cultural sightseeing) and
tourism seems to play a driver role in their pro?le in comparison to other urban ‘‘mobilities’’.
Although they are powerful tourist brands, strongly attracting international demand, their
presence in other global networks has not been so signi?cant in the last 30 years and this
consideration has probably affected the experts’ perception of an almost static urban
lifestyle (pulse). Unlike the previous cluster, these are cities able to ‘‘play’’ mainly their tourist
performance, and experts do not foresee any change for the future.
The new old city. The third cluster includes Vienna only. The city appears characterized by
an extensive transformation phase, which creates a unique competitive pro?le (Figure 4).
While the behavior of some indicators (variety of segments and experiences, pulse, role of
international tourists) highlights a similarity with the pro?les of cluster 2, the performance of
others (competitiveness of accommodation, presence, potential, etc.) suggests an evolution
comparable to pro?les of cluster 1, which is due to changes in non-tourism ‘‘mobilities’’
(internationalization of the economy, growth of foreign investments, spread of innovative and
creative industries).
The young trendy cities. The fourth cluster includes Istanbul and two other emerging urban
tourist destinations, presenting a varied competitive pro?le: Prague and Seville (Figure 5).
The common points of their performances are low values for the variety of the tourist
experiences offered, the signi?cance of core resources and the city presence at
international level – which highlight a similarity with cluster 2, but also the high value
attributed to the pulse of the city, as for pro?les in cluster 1.
Generally, all these cities still have a less established role as global tourist destinations, in
comparison to cities of clusters 1 and 2. Nevertheless, the rapid development of tourist ?ows
in the last years, especially in Istanbul and Prague, seems to be the result of their perceived
‘‘youth’’ and liveliness and, in the case of Istanbul, also of the growth of other urban
‘‘mobilities’’ related to business and culture.
The determinants of competitiveness: tourism v. non tourism ‘‘mobilities’’
In a dynamic perspective, Istanbul and each city analyzed not only competes with the others
included in the same group (competition within a cluster), but also with cities grouped in
other patterns (competition between clusters). The main determinants of competitiveness
analyzed show the cities where tourism ‘‘mobilities’’ have a crucial role in their evolution, and
the cities where the evolution of other non tourism ‘‘mobilities’’ is generally the driver of
change also for tourism.
The ?rst group includes Venice and Bruges. These cities are characterized by a sluggish
social and economic environment, where the evolution of tourism trends and behavior
(especially international ?ows) has an important role in de?ning the use of urban spaces and
the development and costs of services at local level (Figure 5). Nevertheless, although these
cities are acknowledged all around the world for their urban and architectural structure, other
kinds of local tourism resources and attractions seem to be less promoted than in other
urban destinations analyzed. In addition, the experts consider the quality of accommodation
not appropriate to meet the requirements of clients having different expenditure budgets.
The development of new investments and economic opportunities, and the settlement of an
advanced service industry would be important actions to re-launch these destinations and
balance the role of tourism, stimulating, at the same time, the development of new tourism
market segments (e.g. business and congress).
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The second group of cities include Istanbul, Barcelona, London, Paris and Vienna (Figure 6).
The urban, social and economic development that has characterized these cities in the past
years is expected to continue in the near future, in particular in Istanbul and Vienna. It
represents an important driver also for tourism, since it can stimulate the creation of new
attractions and of new market segments (see Figure 7).
According to this approach, Istanbul’s pro?le shows that the city will possibly evolve towards
a cluster 1 pro?le, heading to compete in the set with London, Paris, and Barcelona.
Figure 6 Cities where tourism mobilities have a crucial role in their evolution
Figure 7 Cities where non tourism mobilities also affect tourism evolution
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In fact, there are many signs of an extensive ‘‘mobilization’’ of the city through various
networks. For example, according to the results of an international survey on leading
business cities, the managers of many international major companies acknowledged
Istanbul as one of the most important emerging business locations (Cushman and
Wake?eld, 2007). The intensive plans developed to renovate and revitalize some urban
areas and enhance the local transport network, along with the incentives to real-estate
companies interested in investing in hotels and congress venues, are rede?ning some city
spaces. Moreover, Istanbul is the 2010 European Capital of Culture, and this event has
stimulated the restoring of the historical heritage and the development of a marketing and
communication plan to promote the cultural identity of the city.
As for Vienna, its ability to compete with big metropolitan areas will depend on how the
evolution of the local economic environment (with a strong focus on innovation) and the
political role played by the city will contribute to rede?ne its image and then its identity as a
city to play. In between of these two groups there are Rome, Florence, Prague and Seville. In
these cities, the role of tourism and non-tourism ‘‘mobilities’’ is more balanced, although the
weight they will assume in the near future is not clear yet.
Conclusion and indications for future research
Analyzing the competitiveness of a tourism destination and of a city in particular, requires a
systemic approach that takes into account the complex shifting nature of the network of
‘‘mobilities’’ interacting within and around the destination. This approach should also embed
the relativity of the competitive space of a destination and the circular cause-effect
relationships between tourists and destinations.
The proposed methodology offers both theoretical and practical bene?ts for tourism
research and city policy-makers. In its experimental application to the analysis of Istanbul
and other European cities, it proves to be effective in designing a dynamic competitive
pro?le of every city, framing a number of competitive models and identifying the role of
different ‘‘mobilities’’ in driving competitiveness within and between clusters. As the spider
plots of Istanbul, Barcelona and Vienna demonstrate, this approach appears to be very
sensitive to changes in one or more indicators, giving prompt feedback about the evolving
impact of tourism and non-tourism changes. It also embeds a future perspective, since the
performance of the indicators highlight the city’s potential to evolve towards another pro?le
within the same cluster or to another competitive cluster.
This framework also offers practical implications for city policy- makers and stakeholders
involved. The methodology provides a user-friendly and effective tool for monitoring the city
performance and benchmarking its results in comparison to a set of competing urban
destinations. However, this potential of the framework does not suggest that, at this stage of
development, the results obtained provide an unambiguous tool to analyze the destination’s
competitiveness. Further research will be required to re?ne the approach and test it on a
larger and/or different group of destinations. Additional studies should be devoted to how
the factors produced by the dynamic networking between tourism and non-tourism
‘‘mobilities’’ can combine together at a given moment to create a successful destination.
A note of caution should be added when considering the features of the methodology used.
Unlike other models of tourism destination competitiveness, its non-deterministic and
relative nature implies that no ?xed list of factors and items has been given once and for all.
Researchers have to adapt or rede?ne the set of indicators to be used according to the
different kind of destinations and tourist markets they are analyzing, which entails a longer
scouting stage and deeper knowledge of the tourist market and the destinations to be
studied. Moreover, the approach requires that researchers adopt a multidimensional and
multidisciplinary perspective, which implies the ability to identify a number of meaningful
aspects and variables from several branches of knowledge and to identify the best indicator
to measure each of them.
Considering speci?cally the method for data collection used, a caveat concerns the use of
the experts’ judgment. While assessing a group of destinations according to a number of
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different features could be quite an easy task when top urban tourist destinations are
considered, dif?culties arise with less studied or visited cities or tourist resorts. Such cases
might require, for example, using a larger number of experts or selecting a different group
according to each aspect investigated (e.g. the urban pro?le, the characteristics of core
resources). However, this solution could create some problems as a coherent picture may
not emerge when elaborating the data all together.
Despite these caveats, the framework proposed represents the ?rst step towards the
development of a more systemic approach to destination competitiveness analysis and of
more complete metrics, also applicable to non urban destinations. In its ?rst testing, the
methodology proves to provide reliable and signi?cant results, even in relation to a group of
top urban destinations, which could have challenged the traditional methods in many ways.
Future developments will focus on better de?ning the set of information used, and on
studying the interactions among the variables in determining the competitiveness of the
destination, that is the system rules rather than the factors only. Outlined this way, the
methodology would allowto foresee with higher likelihood howa given destination will evolve
in a speci?c competitive space and therefore its competitiveness.
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About the authors
Valeria Minghetti is senior researcher at CISET- Ca’ Foscari University (Venice). She has
more than 15 years’ experience in teaching, researching and writing on tourismsubjects and
has worked on a number of projects for important national and international organisations
(Eurostat, European Commission, WTO, etc.). Her main research interests include tourism
demand analysis, the economic impact of tourism, the interconnections between tourism
and transport and the diffusion of innovation technologies in the tourism industry. Valeria
Minghetti is the corresponding author and can be contacted at: [email protected]
Federica Montaguti is researcher at CISET- Ca’ Foscari University (Venice). In recent years
she has worked speci?cally on destination planning and management and on the analysis of
destination competiveness and brand. She is also involved in the management and tutorship
of the Master programme in economics and management of tourism, and she teaches in
other Master and undergraduate programmes.
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This article has been cited by:
1. Marco Cucculelli, Gianluca Goffi. 2016. Does sustainability enhance tourism destination competitiveness? Evidence from
Italian Destinations of Excellence. Journal of Cleaner Production 111, 370-382. [CrossRef]
2. Chien-Min Chen, Sheu-Hua Chen, Hong-Tau Lee, Tsung-Hsien Tsai. 2016. Exploring destination resources and
competitiveness–A comparative analysis of tourists' perceptions and satisfaction toward an island of Taiwan. Ocean & Coastal
Management 119, 58-67. [CrossRef]
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doc_100409528.pdf
The purpose of this paper is to analyze the dynamic competitive profile of Istanbul and to
compare it to ten other European cities by using a multidimensional approach.
International Journal of Culture, Tourism and Hospitality Research
Assessing Istanbul competitiveness: a multidimensional approach
Valeria Minghetti Federica Montaguti
Article information:
To cite this document:
Valeria Minghetti Federica Montaguti, (2010),"Assessing Istanbul competitiveness: a multidimensional approach", International J ournal of
Culture, Tourism and Hospitality Research, Vol. 4 Iss 3 pp. 228 - 240
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Assessing Istanbul competitiveness:
a multidimensional approach
Valeria Minghetti and Federica Montaguti
Abstract
Purpose – The purpose of this paper is to analyze the dynamic competitive pro?le of Istanbul and to
compare it to ten other European cities by using a multidimensional approach.
Design/methodology/approach – Starting from a review of existing competitiveness models, the
paper develops a methodology that takes into account the complex shifting nature of the network of
‘‘mobilities’’ interacting within and around the destination.
Findings – The proposed approach proves to be effective in designing a dynamic competitive pro?le of
every city and in identifying the factors that drive competitiveness within and between different
competitive clusters of cities.
Originality/value – The newapproach presents several original elements, since it embeds the evolution
of the system of diverse intersecting tourism and non tourism ‘‘mobilities’’ that characterize an urban
destination, and integrates different dimensions and disciplinary points of view.
Keywords Tourism, Cities, Competitive strategy, Europe
Paper type Research paper
Introduction
Visiting cities is an ever-growing tourismactivity in Europe. Also thanks to the enlargement of
the European Union, urban tourism ?ows for different purposes (visit to attractions, events,
business, etc.) are expanding at a faster rate than tourism in general (European Travel
Commission, 2008). Traditional cultural cities are places that were not created for tourism
development and where tourism has established itself within the changing economic, social
and cultural environment. Tourism activities interact with other urban functions as part of a
system of overlapping ?ows and relationships (Laws, 1993).
Besides, cities are places in motion, nodes of dynamic networks of different physical and
virtual ‘‘mobilities’’ (Urry, 2007) – tourists, residents, businesses, capitals, culture,
knowledge, etc. – that constantly reshape the urban space, the organization of tourism
and non-tourismpractices and the city image and brand. Fromthis point of view, not only the
tourism performance of a city depends on the attractiveness of core resources (historic,
cultural, etc.) and the quality of tourism-related facilities, but also on the evolution of these
networked ‘‘mobilities’’. This development implies building a model that explicitly considers
all these aspects.
The article analyzes the dynamic competitive pro?le of Istanbul in comparison to other ten
European cities (Venice, Florence, Rome, Barcelona, Bruges, London, Paris, Prague, Seville
and Vienna) – a pro?le developed according to a multidisciplinary and multidimensional
approach taking into account the evolution of this system of diverse intersecting tourism and
non tourism ‘‘mobilities’’. The approach and the results obtained derive from a
research-work the Tourism Competitiveness Department of the Italian Government
commissioned to CISET. The study aimed at developing a benchmark analysis by
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VOL. 4 NO. 3 2010, pp. 228-240, Q Emerald Group Publishing Limited, ISSN 1750-6182 DOI 10.1108/17506181011067619
Valeria Minghetti is a senior
researcher and
Federica Montaguti is a
researcher, both based at
CISET, Venice, Italy.
Received December 2009
Revised January 2010
Accepted March 2010
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comparing the competitiveness of the three most famous Italian art cities (Florence, Rome
and Venice) with the other eight given European cities.
After having de?ned the concept of ‘‘city to play’’ and the role that tourism ‘‘mobilities’’ and
other ‘‘mobilities’’ have in analyzing the tourismperformance of a city, the paper presents the
methodology used for the analysis and the multidimensional approach developed for
monitoring the competitiveness of an urban destination. Starting from these elements, the
article then outlines the dynamic competitive pro?le of Istanbul and of the other cities. Four
common development and evolution patterns (‘‘clusters’’) have been identi?ed, showing
how Istanbul positions itself in comparison to the European cities analyzed. The ?nal section
draws conclusions, and provides indications for future research.
De?ning a ‘‘city to play’’: the role of tourism and other ‘‘mobilities’’
According to recent studies, cities and destinations are transforming themselves from
‘‘space of places’’ to ‘‘space of ?ows’’ (Castells, 2000; Manente, 2000), in nodes of a
complex network of relationships among different kinds of spatial and virtual ‘‘mobilities’’ at
local and global level (see Figure 1). Spatial mobility is determined by a variety of factors,
such as increasing/decreasing population, migrations, growth in transport services and
travels, changes in urban economic structure and visitor ?ows. Its evolution also implies that
cities themselves are constantly ‘‘on the move’’, as these transformations entail the
creation/destruction of infrastructures, business and service centers, hotels, etc. How
residents, workers and tourists move within the city is also evolving, according to the spatial
Figure 1
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reorganization of the city, and the location of old and new attractions. Besides physical
‘‘mobilities’’, there are also many different virtual ‘‘mobilities’’. characterizing the cities –
capitals, investments, information, knowledge, but also ideas, memories, images, etc.
(Figure 1). The spread of information and communication technologies accelerates the
growth of these ‘‘mobilities’’.
Tourism is a component of this complex system of ‘‘mobilities’’. In the last decades, the
dramatic development of tourism ?ows and practices has heavily affected the pattern of
urban growth as well as the internal geography of destinations. In this and other ways,
tourism ‘‘mobilities’’, both physical and virtual, in?uence the dynamic development of other
‘‘mobilities’’. At the same time, non-tourism ‘‘mobilities’’ (e.g. growth of foreign investments,
settling down of creative industries, reorganization of the urban space, success of books or
?lms set in the city) impact on the development of city tourism (emerging of new leisure
segments, expansion of business tourism, etc.). They affect how tourists – or potential
tourists – move in the city, how they perceive it, what they do and see there (Bærenholdt
et al., 2004).
Consequently, cities can be seen as a dynamic ‘‘place of movement’’ (Hetherington, 1997;
see also Crouch, 2000). They are not ?xed and immobile objects, but ‘‘places to play’’,
‘‘produced through the multiple networked ‘mobilities’ of capital, persons, objects, signs and
information’’ (Sheller and Urry, 2004, p. 6; see also Coleman and Crang, 2002; Haldrup,
2004). Therefore, the challenge to become a ‘‘city to play’’ – or to hold this role – and then
become a ‘‘city in play’’ relies on the continuous and evolving interaction among tourism and
other kind of activities.
The performance of a city depends on the evolution of this system of diverse intersecting
‘‘mobilities’’. How the city moves or is mobilized through various global networks of
economic, cultural, fashion, and tourismrelationships, affects its competitiveness and image
(see also Ritchie and Crouch, 2003, p. 245). This has a major impact on ‘‘people’s decisions
to visit the city, to buy its products and services, to do business or relocate there’’ (Anholt,
2006, p. 2). On the other side, the growth of the tourist interest in the city and the
strengthening of the urban tourist brand affects its attractiveness as a place to live, work,
study, invest and so on.
Analyzing city competitiveness. Towards a multidimensional approach
The methodology used
The role of ‘‘mobilities’’ interplay has an important impact on measuring the tourism
competitiveness of an urban destination. As ‘‘tourist activities are not so separate from the
places that are visited’’ (Sheller and Urry, 2004, p. 5), and locations are continuously ‘‘made
and remade by the performances of tourists and workers, image and heritage, the latest
fashions’’ (Sheller and Urry, 2004, p. 1), capital and information, the competitiveness
analysis requires the adoption of a multidimensional approach. This perspective should take
into account the shifting con?gurations of tourism and non-tourism ‘‘mobilities’’, and assess
the role of each mobility and of a single factor in determining the success of the destination.
The main issue is to identify an alternative to traditional metrics that helps to measure the
tourismcompetitiveness of a ‘‘city to play’’, as ‘‘the ‘mobilities’ paradigminvolves newkind of
methods [. . .] ‘on the move’’’ (Urry, 2007, p. 39).
From this point of view, the set of cities identi?ed by the Italian Government for the study and
analyzed in this paper, represented a good testing ?eld. They are a heterogeneous set of
urban destinations – considering their position within the local political, economic and social
networks and the stage in their urban and tourism life-cycle. Their visitors generally do not
look for cultural tourism only (e.g. visits to museums and monuments), but also for other
activities (e.g. events, business and congress, shopping, wine and food tasting). The
brands of these cities are important not only to attract tourists, but also investments, capitals
and businesses.
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A review of the literature on existing models de?ning the destination competitiveness (Dwyer
and Kim, 2003; Enright and Newton;, 2004; Gooroochun and Sugiyarto, 2005; Maggi and
Croce, 2005; Ritchie et al., 2001; World Economic Forum, 2008) highlighted that the main
indicators used by these models were not so effective in designing competitive pro?les or in
identifying the determinants of competitiveness for these cities. The models generally
consider the destination as a tourism attraction, a relatively given and ?xed system, that is a
separate object from demand and from other ‘‘mobilities’’ networks. They apply metrics that
take into account a number of comparative and competitive factors essentially based on the
amount of resources and attractions, the stock of infrastructure and the characteristics and
quality of service facilities available at the destination. The models only partially consider
and investigate the effects on competitiveness deriving from the dynamic interaction
between demand and supply and between tourism and non tourism ‘‘mobilities’’.
A four-step research plan was therefore developed. The ?rst step was to describe and
analyze the cities’ pro?le and their appeal, according to their different features (urban,
socio-economic, innovative aspects, characteristics of tourism demand and supply, image
and brand, etc). A group of variables/indicators were then identi?ed. The indicators were
used to classify every city and frame into different competitive models, according to the
aspects investigated above. Starting from these variables, a meaningful set of summary
indicators were selected, suitable to group cities presenting similar or comparable
characteristics in a number of competitive clusters. Finally, the competitiveness of each city
within and among clusters was assessed.
The new approach developed aims at integrating the effects of the different kind of shifting
‘‘mobilities’’ in de?ning and assessing the competitive pro?le of the destination. In more
detail, the methodology:
1. provides a dynamic perspective of the city, allowing researchers to assess its actual and
future performance according to a number of quantitative and qualitative indicators;
2. analyzes the competitiveness of a city according to the competitive set identi?ed. As
stated by Enright and Newton, ‘‘speci?c tourism destinations are not competitive or
uncompetitive in the abstract, but versus competing destinations’’ (Enright and Newton,
2004, p. 781);
3. takes into account tourists’ behavior and perceptions (activities done/experiences lived
while in the city) as a dimension of the destination competitiveness and not only as an
outcome of competitiveness;
4. considers the signi?cance and variety of core resources and attractors and not only of
their physical amount. ‘‘The mere counting of the number of museums and historical sites
[. . .] may well mask the quality of these attractions- something that is often the primary
appeal to visitors’’ (Ritchie et al., 2001, p. 6); and
5. ?nally, the approach assesses the role of other ‘‘mobilities’’ and the city positioning in
global networks, as factors de?ning the city development and potential, and its capacity
to subsequently attract quali?ed investors, professionals and tourists (OECD, 2006).
Since these elements affect the city brand, integrating traditional competitiveness models
with those assessing features, brand equity, and strength of destinations/places brand
becomes essential.
The data collection
In de?ning the items to be assessed, the indexes adopted by the different approaches
analyzed from the literature were taken into account, and in particular those included in the
layers of the Ritchie and Crouch model (Ritchie and Crouch, 2003). Some aspects were not
– or partially – included since they were considered irrelevant (e.g. climate) or not signi?cant
(accessibility) for the group of top urban destinations studied. In the end, more than 90 items
were identi?ed, and assessed for each city in two different ways.
Various sources were checked to build the set of quantitative and qualitative variables and
indicators to be used to design the different competitive pro?les. The method combines the
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desk analysis of secondary sources (e.g. statistical data on tourism demand and supply,
visitors’ surveys, city development and marketing plans, etc.) with an e-mail survey carried
out with a group of about thirty international urban tourism experts and managers of city
tourist of?ces. The purpose of this survey was to appraise the items identi?ed according to
the insight they have of the whole group of cities analyzed (for experts) or of the city they
work for (for tourist of?ce managers), from different point of views.
The adoption of an expert approach mediates between supply-side and demand-side
measurements (Wo¨ber, 2006). On the one hand, tourism experts and managers have
professional knowledge of the cities analyzed, the characteristics and potentialities of local
tourismsupply and the role of different ‘‘mobilities’’. On the other, ‘‘experts judgments are often
applied because they indirectly represent the opinions of the consumers’’ (Gearing et al.,
1974, in Grabler, 1997, p. 148). In addition, since urban tourism experts are asked to judge
each relevant aspect for all cities in a row, this methodology allows researchers to obtain a
ranking of cities according to each aspect analyzed and then to compare its performance.
In order to obtain the desired empirical data, an ad hoc questionnaire was constructed
itemizing the factors that were postulated to in?uence the city competitive pro?le. In
particular, experts and city managers were asked to give their opinions on the following
aspects:
B the urban and economic pro?le of the city (current economic role and potential, quality of
urban services and environment, level of traf?c and tourism congestion, environmental
policies);
B the pro?le and behavior of tourism demand (importance of repeaters and same-day
visitors for both domestic and international market; variety of socio-demographic
segments in both markets; variety of activities done/experiences lived by tourists);
B the resonance and variety of core resources and attractors (monuments, museums,
events, shopping facilities, etc.);
B the variety/quality of accommodation supply and its capacity to meet the needs of
different expenditure pro?les;
B the price competitiveness (tourist prices’ perception and general cost of living);
B the city brand (pulse/vivacity, presence, outstanding attributes and personality); and
B the use of technology in marketing and selling the city (howeasy it is for a tourist to arrange
a stay in the city using the websites of the local tourist board and of private operators).
The survey analyzed more than 90 items through 13 questions. For each item, experts were
asked to give a score to each city using a ?ve-point Likert scale. The meaning of each scale
point was adapted according to the factors/items to be analyzed.
The summary indicators
The analysis of hard data collected from secondary sources and of soft data deriving from
the experts’ survey allowed to create a meaningful set of simple or weighted summary
indicators useful to identify the competitive pro?le of each city and then group them into
competitive clusters with similar characteristics.
The indicators chosen are representative of all the main aspects investigated (urban and
economic structure, pro?le and behavior of tourism demand, resonance of core resources
and attractors, accommodation supply, prices and brand and image). They provide a
dynamic pro?le of the city (not only a picture of the ‘‘state of the art’’ but also some future
perspectives), and are those that better emphasize the similarities and differences between
cities. Furthermore, they help to identify the city pro?les and to compare them within and
among clusters. Table I shows the nine indicators used, their meaning and how they have
been calculated.
Three indicators are demand-related (international market, visitors mix and experience mix),
three refer to local supply (resources, accommodation and prices), two to city image and
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brand (presence and pulse) and the last one to the economic structure and future
development of the city (potential). In particular, presence, pulse and potential indicators
embed the impacts of other ‘‘mobilities’’ on tourism and, speci?cally, the effects of the
evolution of the urban space and structure and of local lifestyle on the city’s identity and the
perceptions tourists have of the place. One indicator out of nine derives from statistical data
(the role of international tourism demand). The other indicators represent qualitative
variables of city competitiveness, derived from the empirical analysis by elaborating, for
each factor identi?ed, the judgments given by experts on a number of correlated items.
Istanbul’s competitive pro?le
The competitive models identi?ed
A spider plot chart combining the selected indicators was used to describe the competitive
pro?le of Istanbul and of the other cities investigated (see Figures 2 to 5). Normalized values
(0-1) were calculated in order to obtain a comparable range of values for all quantitative and
Table I Competitiveness indicators for cities to play
Indicator Meaning Calculation
Role of international tourism demand Importance of international tourists on total
tourism in the city
Share of foreign arrivals on total arrivals
(hard data)
Variety of socio-demographic
segments
Capacity of the city to attract different
demand segments (e.g. school trippers,
18-24 years old people, etc.)
Weighted mean of scores given by experts
to the importance (number and intensity) of
each socio-demographic segment on both
domestic and international markets
Variety of tourist
activities/experiences offered to
tourists
Capacity of the city to offer a varied range of
activities/experiences to tourists (i.e. how
many activities offered are done by tourists)
Weighted mean of scores given by experts
to the importance (number and intensity) of
each speci?c activity/experience offered to
both domestic and international tourists
Signi?cance of core resources and
attractors
The most important resources/attractors the
city is famous for (i.e. the capacity of the city
to promote its resources/attractors)
Simple mean of scores given by experts to
the signi?cance (variety and resonance) of
different kinds of resources/attractors
Competitiveness of accommodation
supply
Capacity of accommodation supply to meet
the requirements of clients with different
expenditure budget (luxury, upper,
average, budget, young
people/backpackers)
Simple mean of scores given by experts to
the capacity of accommodation supply to
satisfy each expenditure pro?le listed
(presence and judgment on price/quality
ratio)
Relative cost of the city for tourists Whether the city is more expensive or
cheaper for tourists than for residents (cost
for tourists v. cost of living)
Score obtained by comparing the scores
given by experts to the perceived cost of the
city for tourists and for residents
Presence of the city The city’s international role and standing in
the last 30 years
Simple mean derived from the scores given
by experts to the contribution the city has
given to the world in the last 30 years,
according to a number of aspects (e.g.
culture, style)
Pulse of the city The appeal of the city, that is the presence
of a vibrant urban lifestyle as part of city’s
brand image
Simple mean derived from the scores given
by experts to vivacity of city life both at
daytime and at night
Potential of the city The city’s future contribution and potential Simple mean derived from the scores given
by experts to the contribution each city
might give in the future in different areas
(culture, design, lifestyle, etc.) and to the
economic and educational opportunities it
offers/will offer (potential of the city and
foreseen contribution in each area)
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qualitative indicators. The polygonal area derived by linking these values represents the
city’s competitive pro?le.
The comparison of different pro?les leads to the identi?cation of four common development
and evolution patterns (clusters), showing how Istanbul positions itself in comparison to the
European cities analyzed. The distinguishing characteristics of each cluster and of each city
within the cluster are brie?y discussed herewith.
The ultimate cities. The ?rst cluster groups four cities, two global metropolitan areas (London
and Paris) and two large cities (Rome and Barcelona) (Figure 2). The shape of the polygonal
area characterizing each of them shows that they have a more or less balanced competitive
pro?le. These cities generally compete on many tourist markets (business, conventions, city
breaks, cultural tourism, events, etc.) and are characterized by a wide range of signi?cant
Figure 2 The ‘‘ultimate’’ cities
Figure 3 The ‘‘picture’’ cities
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resources and attractions (monuments, events, link to famous people, business centers,
etc.).
London and Paris are highly charismatic and lively cities and they will probably strengthen
their role in the near future. Here, tourism and other activities are all components of a
complex project of urban development. Rome presents a lower performance in comparison
to others with regards to two indicators (potential of the city and variety of tourist
activities/experiences). Although the ‘‘Eternal city’’ has acquired a pro?le similar to London
and Paris – thanks to a number of initiatives promoted by the Municipality in the last few
years – the process is not complete yet. The issue is whether the city will be able to maintain
this new role in the near future (potential).
The presence of Barcelona in this cluster is the result of a recent development, which has no
roots in a far consolidated historic role, but is the result of a strong cultural and economic
Figure 4 The ‘‘new old’’ city
Figure 5 The ‘‘young trendy’’ cities
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regeneration and a wide scale re-organization of the urban space that began after the end of
Franco’s regime (Degen, 2004). An international public acknowledged the rebirth in 1992
and, since then, tourism, economics, culture, sport and fashion networks continuously feed
and mobilize Barcelona’s ‘‘renaissance’’. This rebirth positions the city in the highest ranks
among the big capitals of urban tourism.
The picture cities. The second cluster includes three traditional art cities (Venice, Florence
and Bruges), which show a more stretched competitive pro?le (Figure 3). These cities are
generally specialized on few segments/products (basically, cultural sightseeing) and
tourism seems to play a driver role in their pro?le in comparison to other urban ‘‘mobilities’’.
Although they are powerful tourist brands, strongly attracting international demand, their
presence in other global networks has not been so signi?cant in the last 30 years and this
consideration has probably affected the experts’ perception of an almost static urban
lifestyle (pulse). Unlike the previous cluster, these are cities able to ‘‘play’’ mainly their tourist
performance, and experts do not foresee any change for the future.
The new old city. The third cluster includes Vienna only. The city appears characterized by
an extensive transformation phase, which creates a unique competitive pro?le (Figure 4).
While the behavior of some indicators (variety of segments and experiences, pulse, role of
international tourists) highlights a similarity with the pro?les of cluster 2, the performance of
others (competitiveness of accommodation, presence, potential, etc.) suggests an evolution
comparable to pro?les of cluster 1, which is due to changes in non-tourism ‘‘mobilities’’
(internationalization of the economy, growth of foreign investments, spread of innovative and
creative industries).
The young trendy cities. The fourth cluster includes Istanbul and two other emerging urban
tourist destinations, presenting a varied competitive pro?le: Prague and Seville (Figure 5).
The common points of their performances are low values for the variety of the tourist
experiences offered, the signi?cance of core resources and the city presence at
international level – which highlight a similarity with cluster 2, but also the high value
attributed to the pulse of the city, as for pro?les in cluster 1.
Generally, all these cities still have a less established role as global tourist destinations, in
comparison to cities of clusters 1 and 2. Nevertheless, the rapid development of tourist ?ows
in the last years, especially in Istanbul and Prague, seems to be the result of their perceived
‘‘youth’’ and liveliness and, in the case of Istanbul, also of the growth of other urban
‘‘mobilities’’ related to business and culture.
The determinants of competitiveness: tourism v. non tourism ‘‘mobilities’’
In a dynamic perspective, Istanbul and each city analyzed not only competes with the others
included in the same group (competition within a cluster), but also with cities grouped in
other patterns (competition between clusters). The main determinants of competitiveness
analyzed show the cities where tourism ‘‘mobilities’’ have a crucial role in their evolution, and
the cities where the evolution of other non tourism ‘‘mobilities’’ is generally the driver of
change also for tourism.
The ?rst group includes Venice and Bruges. These cities are characterized by a sluggish
social and economic environment, where the evolution of tourism trends and behavior
(especially international ?ows) has an important role in de?ning the use of urban spaces and
the development and costs of services at local level (Figure 5). Nevertheless, although these
cities are acknowledged all around the world for their urban and architectural structure, other
kinds of local tourism resources and attractions seem to be less promoted than in other
urban destinations analyzed. In addition, the experts consider the quality of accommodation
not appropriate to meet the requirements of clients having different expenditure budgets.
The development of new investments and economic opportunities, and the settlement of an
advanced service industry would be important actions to re-launch these destinations and
balance the role of tourism, stimulating, at the same time, the development of new tourism
market segments (e.g. business and congress).
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The second group of cities include Istanbul, Barcelona, London, Paris and Vienna (Figure 6).
The urban, social and economic development that has characterized these cities in the past
years is expected to continue in the near future, in particular in Istanbul and Vienna. It
represents an important driver also for tourism, since it can stimulate the creation of new
attractions and of new market segments (see Figure 7).
According to this approach, Istanbul’s pro?le shows that the city will possibly evolve towards
a cluster 1 pro?le, heading to compete in the set with London, Paris, and Barcelona.
Figure 6 Cities where tourism mobilities have a crucial role in their evolution
Figure 7 Cities where non tourism mobilities also affect tourism evolution
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In fact, there are many signs of an extensive ‘‘mobilization’’ of the city through various
networks. For example, according to the results of an international survey on leading
business cities, the managers of many international major companies acknowledged
Istanbul as one of the most important emerging business locations (Cushman and
Wake?eld, 2007). The intensive plans developed to renovate and revitalize some urban
areas and enhance the local transport network, along with the incentives to real-estate
companies interested in investing in hotels and congress venues, are rede?ning some city
spaces. Moreover, Istanbul is the 2010 European Capital of Culture, and this event has
stimulated the restoring of the historical heritage and the development of a marketing and
communication plan to promote the cultural identity of the city.
As for Vienna, its ability to compete with big metropolitan areas will depend on how the
evolution of the local economic environment (with a strong focus on innovation) and the
political role played by the city will contribute to rede?ne its image and then its identity as a
city to play. In between of these two groups there are Rome, Florence, Prague and Seville. In
these cities, the role of tourism and non-tourism ‘‘mobilities’’ is more balanced, although the
weight they will assume in the near future is not clear yet.
Conclusion and indications for future research
Analyzing the competitiveness of a tourism destination and of a city in particular, requires a
systemic approach that takes into account the complex shifting nature of the network of
‘‘mobilities’’ interacting within and around the destination. This approach should also embed
the relativity of the competitive space of a destination and the circular cause-effect
relationships between tourists and destinations.
The proposed methodology offers both theoretical and practical bene?ts for tourism
research and city policy-makers. In its experimental application to the analysis of Istanbul
and other European cities, it proves to be effective in designing a dynamic competitive
pro?le of every city, framing a number of competitive models and identifying the role of
different ‘‘mobilities’’ in driving competitiveness within and between clusters. As the spider
plots of Istanbul, Barcelona and Vienna demonstrate, this approach appears to be very
sensitive to changes in one or more indicators, giving prompt feedback about the evolving
impact of tourism and non-tourism changes. It also embeds a future perspective, since the
performance of the indicators highlight the city’s potential to evolve towards another pro?le
within the same cluster or to another competitive cluster.
This framework also offers practical implications for city policy- makers and stakeholders
involved. The methodology provides a user-friendly and effective tool for monitoring the city
performance and benchmarking its results in comparison to a set of competing urban
destinations. However, this potential of the framework does not suggest that, at this stage of
development, the results obtained provide an unambiguous tool to analyze the destination’s
competitiveness. Further research will be required to re?ne the approach and test it on a
larger and/or different group of destinations. Additional studies should be devoted to how
the factors produced by the dynamic networking between tourism and non-tourism
‘‘mobilities’’ can combine together at a given moment to create a successful destination.
A note of caution should be added when considering the features of the methodology used.
Unlike other models of tourism destination competitiveness, its non-deterministic and
relative nature implies that no ?xed list of factors and items has been given once and for all.
Researchers have to adapt or rede?ne the set of indicators to be used according to the
different kind of destinations and tourist markets they are analyzing, which entails a longer
scouting stage and deeper knowledge of the tourist market and the destinations to be
studied. Moreover, the approach requires that researchers adopt a multidimensional and
multidisciplinary perspective, which implies the ability to identify a number of meaningful
aspects and variables from several branches of knowledge and to identify the best indicator
to measure each of them.
Considering speci?cally the method for data collection used, a caveat concerns the use of
the experts’ judgment. While assessing a group of destinations according to a number of
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different features could be quite an easy task when top urban tourist destinations are
considered, dif?culties arise with less studied or visited cities or tourist resorts. Such cases
might require, for example, using a larger number of experts or selecting a different group
according to each aspect investigated (e.g. the urban pro?le, the characteristics of core
resources). However, this solution could create some problems as a coherent picture may
not emerge when elaborating the data all together.
Despite these caveats, the framework proposed represents the ?rst step towards the
development of a more systemic approach to destination competitiveness analysis and of
more complete metrics, also applicable to non urban destinations. In its ?rst testing, the
methodology proves to provide reliable and signi?cant results, even in relation to a group of
top urban destinations, which could have challenged the traditional methods in many ways.
Future developments will focus on better de?ning the set of information used, and on
studying the interactions among the variables in determining the competitiveness of the
destination, that is the system rules rather than the factors only. Outlined this way, the
methodology would allowto foresee with higher likelihood howa given destination will evolve
in a speci?c competitive space and therefore its competitiveness.
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About the authors
Valeria Minghetti is senior researcher at CISET- Ca’ Foscari University (Venice). She has
more than 15 years’ experience in teaching, researching and writing on tourismsubjects and
has worked on a number of projects for important national and international organisations
(Eurostat, European Commission, WTO, etc.). Her main research interests include tourism
demand analysis, the economic impact of tourism, the interconnections between tourism
and transport and the diffusion of innovation technologies in the tourism industry. Valeria
Minghetti is the corresponding author and can be contacted at: [email protected]
Federica Montaguti is researcher at CISET- Ca’ Foscari University (Venice). In recent years
she has worked speci?cally on destination planning and management and on the analysis of
destination competiveness and brand. She is also involved in the management and tutorship
of the Master programme in economics and management of tourism, and she teaches in
other Master and undergraduate programmes.
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