Market structures strategy and innovation in tourism sector

Description
This study aims to add to the existing body of knowledge the link between market structures,
strategy and innovation by applying the diagnostic test of the integrated model of innovation, and also
present the results of an empirical study applied to tourism in a small open economy. The study uses an
archetype and the market outcome resulting from the innovation strategies pursued to compare
similarities and differences according to a firms’ geographical location to identify innovative patterns in
tourism firms.

International Journal of Culture, Tourism and Hospitality Research
Market structures, strategy and innovation in tourism sector
Luisa Margarida Cagica Carvalho Soumodip Sarkar
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To cite this document:
Luisa Margarida Cagica Carvalho Soumodip Sarkar , (2014),"Market structures, strategy and innovation in tourism sector",
International J ournal of Culture, Tourism and Hospitality Research, Vol. 8 Iss 2 pp. 153 - 172
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Lan-Lan Chang, Kenneth F. Backman, Yu Chih Huang, (2014),"Creative tourism: a preliminary examination of creative
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Rodoula Tsiotsou, Vanessa Ratten, (2010),"Future research directions in tourism marketing", Marketing Intelligence &
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Antónia Correia, Metin Kozak, J oão Ferradeira, (2013),"From tourist motivations to tourist satisfaction", International J ournal
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Market structures, strategy and
innovation in tourism sector
Luisa Margarida Cagica Carvalho and Soumodip Sarkar
Luisa Margarida Cagica
Carvalho is an Assistant
Professor at the
Department of Social
Sciences and
Management, Open
University of Portugal,
Oeiras, Portugal and
Researcher at the Center
for Advanced Studies in
Management and
Economics (CEFAGE),
University of Évora, Évora
Portugal. Soumodip
Sarkar is an Associate
Professor at the
Department of
Management, University
of Évora, Évora, Portugal
and CEFAGE, University
of Évora, Évora, Portugal.
Abstract
Purpose – This study aims to add to the existing body of knowledge the link between market structures,
strategy and innovation by applying the diagnostic test of the integrated model of innovation, and also
present the results of an empirical study applied to tourismin a small open economy. The study uses an
archetype and the market outcome resulting from the innovation strategies pursued to compare
similarities and differences according to a ?rms’ geographical location to identify innovative patterns in
tourism ?rms.
Design/methodology/approach – The study applies a multivariate analysis using a data set
consisting of survey responses from 158 Portuguese ?rms.
Findings – The ?ndings indicate links between service, market structures and innovation strategies
considering geographical agglomeration of ?rms in a small economy, and also different innovation
trajectories and positions in the model.
Research limitations/implications – The results of this study are generalizable to a dynamic industry
context of tourism ?rms operating in a small open economy, such as Portugal.
Practical implications – The results suggest that managers need to attend to intangible resources,
such as marketing and human resources and their links with innovation and performance, particularly in
the case of service ?rms.
Originality/value – The paper highlights the role of intangible resources, especially marketing and
human resources, in tourism?rms. Geographical location also in?uences the ?rm’s strategy and results.
Keywords Strategy, Innovation, Tourism, Portugal, Market structures, Service sector
Paper type Research paper
Introductory note
Innovation emerges as a driver of economic growth and prosperity in several countries
(Stockdale, 2002; Fagerberg and Godinho, 2004;OECD, 2013) and at a micro level,
innovation is a source of competitive advantage for ?rms. It is also considered a key source
for improved output performance of the service sector (Van Ark et al., 2003). In the
European Union (EU; Metka and Gallouj, 2012), implementation of the competitiveness
growth strategy Horizon 2020 is dominated by services and requires exploitation of the
broad innovation potential that combines technological and non-technological innovations
and the problem-solving approach. In fact, the service sector plays a fundamental role in
developed economies, the share of services on average accounting for 72.7 per cent of
gross domestic product (GDP) in EU27 in 2011, with substantial differences across
member states (e.g. Romania: 52.6 per cent, Germany: 66.2 per cent, Greece: 79.3 per
cent and Luxembourg: 94.7 per cent; Eurostat, 2012). According to the EU Competiveness
Report (European Commission, 2011, p. 11), in the last 15 years,
[. . .] the EU economy has become ever more service oriented with the weight of manufacturing
sectors shrinking to 20 per cent of the total value added. This structural change has important
consequences for the EU research and innovation system as the growing weight of the services
sectors, which have a lower R&D intensity, offsets in most EU Member States recent increases
in the research-intensity of manufacturing sectors.
Received 6 May 2013
Revised 11 September 2013
19 November 2013
19 March 2014
Accepted 27 March 2014
DOI 10.1108/IJCTHR-05-2013-0031 VOL. 8 NO. 2 2014, pp. 153-172, © Emerald Group Publishing Limited, ISSN 1750-6182 INTERNATIONAL JOURNAL OF CULTURE, TOURISM AND HOSPITALITY RESEARCH PAGE 153
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The same report suggests empirical evidence of direct and indirect effects of services and
service innovation on growth, employment and competitiveness of the economy (European
Competitiveness Report, 2011).
There has been increasing research recently on service sector innovation (Sundbo, 2001,
2007; Sundbo et al., 2007; Gallouj, 2002; Schianetz et al., 2007; Miles, 2005; Hjalager,
2002; Carvalho, 2008). In this context, while several authors indicate that innovation in
services and innovation in manufacturing are closely related, other authors discover a
difference between them (Sundbo, 2007; Pires et al., 2008). Table I presents a framework
considering different perspectives concerning evolutionary approaches to research on
service sector innovation.
However, a greater effort is required to systematize the complex nature of innovation in
services and its economic impact (Gago and Rubalcaba, 2007). In the case of innovation
in tourism, research can still be considered to be in its infancy. This study aims to contribute
towards creating and developing research into innovation applicable to the tourism sector.
It intends to use an integrated model (Sarkar, 2005, 2007) as a framework of analysis that
would allow future research and help scholars understand various issues related to market
structures, strategy and innovation in the tourism sector. In this paper, we provide a
framework of analysis in a four-quadrant model that captures the essence of the external
environment, knowledge intensity and the cost advantages of tourism ?rms.
Innovation search for a de?nition
The Lisbon Strategy threw a major challenge to EU countries to transform this economic
space into the most competitive economic region. This goal was to be met through
Table I Services innovation: a framework
Assimilation vs demarcation approaches
Assimilation As resulting from technology adoption and use,
overlooking the non-technological aspects of
processes creating novelty
Demarcation or service-oriented
approaches
Trying to account for the speci?city of service
products and sector compared to those related
to manufacturing
Theoretical vs empirical approaches
Theoretical or conceptual Analysis of the role of technical change and its
effects on structural change in sector
composition of economies towards services and
aggregate growth has yet to be developed. This
approach is also known as neo-Schumpeterian
perspectives
Empirical or appreciative Fragmentation and lack of comparability of
empirical evidence of innovation in services has
often made it dif?cult to generalise contributions
in this domain to the entire sector
Typological vs analytical approaches
Typological Typologies aim to reduce the variety of
information by systematising and labelling it
Analytical Aim to disassemble the evidence into
components to demarcate innovation in services
from traditional innovation studies in order to
account for speci?city of service products by
trying to provide new analytical tools
Demand vs supply-oriented approaches
Demand Consider the client’s involvement in the
innovative process
Supply Emphasise the adoption of technology and its
impacts on productivity
Source: Gallouj and Savona, 2010, adapted
PAGE 154 INTERNATIONAL JOURNAL OF CULTURE, TOURISM AND HOSPITALITY RESEARCH VOL. 8 NO. 2 2014
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investment in human capital, innovation and entrepreneurship. Consequently, innovation
and research have a crucial role to play in improving ?rm competitiveness.
Schumpeter (1934) explicitly introduced the economic impact of innovation in 1934 when
he described innovation as the development of new products, new processes, new
markets and new sources of raw materials or new ways to shape industrial organization.
Schumpeter introduced in the ?eld of economics the concept of creative destruction as a
source of a new economic cycle and related innovation to economic growth. The role of
innovation in economic development has received attention from other authors in this area
(Nelson and Winter, 1982a, 1982b).
Additionally, the innovation literature highlights different approaches, such as the
economics of industrial innovation (Freeman, 1991), R&D and innovation (Arrow, 1962),
differences across industries (Pavitt, 1984) and the role that ?rm-level capacities play in
innovation and learning (Cohen and Levinthal, 1989, 1990).
According to Kline and Rosenberg (1986), innovation is a complex social phenomenon.
The process through which innovations emerge does not follow a linear path, being
characterized by complex feedback mechanisms and interactive relations. Hollenstein
(2000) also considers the innovation process to be a complex phenomenon, one that
includes several stages starting from basic research through to accessing the market with
new products and the introduction of new production techniques within the ?rm.
Innovation in services
The service sector is the largest productive sector in most Organization for Economic
Cooperation and Development (OECD) economies. Recently, several authors have
focused their research on services (Sundbo, 2001, 2007; Sundbo, 2007, 2007; Gallouj,
2002; Schianetz et al., 2007; Miles, 2005; Hjalager, 2002; Carvalho, 2008). However,
research in this area is fraught with dif?culty, and the diversity of activities included in the
service sector makes it dif?cult even to de?ne what a service is. Services were initially
classi?ed as non-productive activities. Some economists describe service products as
“anything sold in trade that could not be dropped on your foot” (Hauknes, 1998, p. 6).
Table II summarizes items that contribute towards the de?nition of innovation in services.
Table II Innovation in services: looking for a de?nition
Service innovations are often small adjustments to
procedures and thus incremental and rarely
radical. Service innovation processes are normally
very practical
Sundbo and Gallouj (1999)
The introduction of signi?cantly new products and
services or implementations of signi?cantly
improved processes
Licht, et al. (1999)
Service innovation is by de?nition
multidimensional. Compared to, for example,
manufacturing, service innovation is characterized
by much greater emphasis on the organizational
dimension of innovation (new service concepts,
new client interface and new delivery systems)
rather than technological options
Van Ark et al. (2003)
Service innovation is mainly an incremental
process that includes two components:
Carvalho (2008)
A non-technological component, dependent on
intangible human resources, organizational
structure and factors that can add value to
customer service (marketing, distribution
channels, etc.);
A technological component that is nowadays
inseparable from the ?rst component, and which
depends on technology, especially ICT
VOL. 8 NO. 2 2014 INTERNATIONAL JOURNAL OF CULTURE, TOURISM AND HOSPITALITY RESEARCH PAGE 155
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Service sector innovation implies changes in many elements, and sometimes it is dif?cult
to separate process from product innovation. Whether it is a new service product, a new
procedure for producing or delivering, a new organizational form or introduction of new
technology, in “most cases cannot be stored, it must be produced in the momentum of
consumption” (Gronroos, 1990).
The Community Innovation Survey (CIS) proposed a de?nition of technological innovation
based on the Oslo Manual (OECD, 1997). This de?nition in the case of services refers to the
implementation of new or signi?cantly improved services, service production or delivery
methods. Consequently, new or improved services are considered as innovation when their
characteristics are completely new or signi?cantly improved qualitatively or in terms of
performance and technologies used. However, new or signi?cantly improved production
methods involve changes in equipment, as well as in the technologies used to implement
new or signi?cantly improved services. These changes are generally related to machinery,
equipment and software upgrading (Or?la-Sintes et al., 2005). This approach is linked to
the reverse product cycle proposed by Barras (1986, 1990), where information
technologies (ITs) play a fundamental role in service innovation. Barras (1986, 1990)
argues that incremental innovation precedes a period of agitation and that this period of
agitation is punctuated by discontinuity through a new service offering. Improvements in
the ef?ciency of delivering existing services lead to quality improvements, in the end
yielding new service offerings. Hence, periods following incremental innovation (i.e. after
the adoption of a standard sub-service) should lead to an increased level of sub-service
variation, which should result in a new service. Barras’s (1986, 1990) framework linked
service innovation with ITs. However, for those services where interactivity appears to be
more relevant, such as tourist accommodation, this pattern could well diverge. In the case
of hospitality business, it involves the use of technologies generally embodied in new
machinery, equipment or software (technological assets) (Or?la-Sintes et al., 2005). The
next section discusses theoretical approaches to innovation in tourism. Table III
summarizes different studies of service innovation in different service sub-sectors.
Innovation in tourism
Despite the importance of and the connection between the two, the study of innovation in
tourism remains in its infancy (Sarkar and Carvalho, 2005). Also, Hjalager (2010) argues for
empirical evidence about innovation in tourism. The reasons for the paucity of research are
various. First of all, the de?nition of tourism as a “product” involving a combination of many
elements creates dif?culties in the development of empirical studies. In fact, tourism
products can include tangible or/and intangible elements. For instance, a destination can
be identi?ed via a number of suppliers, such as hotels, restaurants, entertainment ?rms,
car-hire ?rms and tourism guides. Moreover, tourism is not just based on the production of
goods or services. Several intangible characteristics are embodied in individuals. The
sociological and cultural features of the local population as well as a tourist’s behaviour can
in?uence the tourism experience. Weiermair (2006) de?nes the tourism product as an
experience. Other dif?culties are related to the characteristics of tourism products due to
the simultaneity of production and consumption (Weiermair, 2006) and also coterminality
(Miles, 2005).
The tourism sector, as in services, in general, is characterized by a high degree of
heterogeneity. For instance, hotel complexes with golf courses cannot be compared to
family-run guest-houses or small restaurants. Some studies on innovation and
entrepreneurship ?nd that hotels and restaurants have a lower rate of survival; they are
typically establishments with a very low entry barrier, thus making it easy to establish new
?rms on a non-innovative basis (Sundbo and Gallouj, 1999). Innovation research in tourism
reveals different approaches, for instance, some studies focus on measurement of
innovation (Pikkemaat and Peters, 2005; Volo, 2005), others on patterns of innovation
PAGE 156 INTERNATIONAL JOURNAL OF CULTURE, TOURISM AND HOSPITALITY RESEARCH VOL. 8 NO. 2 2014
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(Hjalager, 2002; Hjalager, 2010; Weiermair, 2006; Or?la-Sintes, et al., 2005), and yet others
on the analysis of the determinants of innovation (Jones, 1996; Walder, 2005; Ottenbacher
and Gnoth, 2005; Pikkemaat, 2008).
The market characteristics of the sector with a high degree of competitiveness oblige ?rms
to innovate as a condition to stay on top of the competition (Hall and Williams, 2008).
However, tourism ?rms have a greater dif?culty in “protecting” innovation, and so it is easier
for competitors to imitate new practices. This triggers a constant challenge to innovate and
hold on to a competitive advantage (Porter, 1998). Associated with the notion of
competitive advantage, productivity is linked to quality and production ef?ciency. As a
result, tourism ?rms that invest in quality and product diversi?cation are generally more
competitive. Additionally, alterations in quality can contribute to a more appropriate price
strategy. Consequently, innovation is crucial to reducing production costs, enhancing
marketing and providing product value (Weiermair, 2006).
Table III Research on service innovation: remarks and results by sub-sector
Author(s)
De?nition/methodological
contributions Sector Main ?ndings
Barras (1986, 1990) Reverse life cycle model ICT The cycle of innovation in services as
the reverse of the traditional cycle
established in the manufacturing
sector
Miles (1993, 2005) Qualitative typologies and
sector speci?c case studies
Knowledge Intensive Business
Services
Relates the key features of service
activities (speci?cities and
heterogeneity) to traditional statistical
classi?cations. Contributes to study of
the knowledge base of some service
activities
Gallouj (2007) Sector speci?c analysis Large-scale retailing Innovative behaviour in retailing is
more complex than the mere
introduction of technological systems
Windrum and Garcia-Goñi
(2008)
Characteristic-based
de?nition of products as a
theoretical device for model
innovation
Public health services Boundary between goods and
services is becoming more blurred
Caccomo and
Solonandrasana, (2001);
Dejellal and Gallouj, (2008)
Qualitative evidence includes
complex services that
combine a number of
elementary services
Tourism Tourism is a mix of complex goods
and services, de?ned as temporal
sequences of market goods and
services (transport, accommodation,
catering, attractions and visits) with
public goods and services (heritage
and cultural sites, natural reserves,
transport and signalling infra-
structures, tourist of?ces)
Evangelista (2000) Quantitative typologies and
empirical analysis of
innovation based on large-
scale surveys, mainly CIS
Services in general, excluding
public services. Country and
cross-country studies in
Europe
First quantitative typology based on
Italian CIS
Tether and Tajal (2008);
Abreu et al. (2009); Gallouj
and Savona (2010)
The latest CIS based analyses
con?rm the prosperity and variety of
innovation patterns in services and
the important role played by non-R&D
innovation expenditure. The
signi?cance of cooperation in service
innovation (open modes of
innovation), also relying on high-level
skills and particularly the type of
human capital. Highlighting the role of
organizational innovation as an
important side effect of the
introduction of innovative services on
the market
VOL. 8 NO. 2 2014 INTERNATIONAL JOURNAL OF CULTURE, TOURISM AND HOSPITALITY RESEARCH PAGE 157
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The way to achieve these results should not be through reducing costs by paying low
wages. Tourism industries in many cases absorb the less-skilled and the unemployed. This
attribute, mainly in small- and medium-sized enterprises (SMEs), can jeopardize innovation
in the sector. However, competitiveness and adaptation of the tourism sector to new market
environments depends on investment in the quality of staff and managers (OECD, 2002).
In fact, the speci?cities of the tourism sector in?uence innovation, and some studies point
to the potential for greater innovation activity in this sector (Hjalager, 2002; Sundbo et al.,
2007).
The tourism sector has recently been in?uenced by several factors, three of which can be
included in the study of innovation in tourism:

First, globalization implies deregulation and increased competition in the tourism sector
(Weiermair, 2006). The number of tourists has steadily increased, and they have easy
access to more regions/markets. Tourism consumption has grown, extending the sector
to new economies. Therefore, in this context, ?rms and tourist destinations have to
adapt to the new situation and develop strategies to improve or maintain a competitive
advantage.

Second, the tourist pro?le has changed. Tourists are more experienced and informed.
Information and communications technology (ICT) facilitates access to information and
contributes to the demand for alternative and more sophisticated products (Stamboulis
and Skayannis, 2003). Tourists nowadays are more independent, and they tend to
organize their holidays themselves.

Third, sustainability is essential to gaining competitive advantage. Tourism ?rms must
be managed with attention to the economic, social and environmental dimensions.
Three factors, globalization, experienced demand and sustainability, must be considered
in an organization’s strategy to achieve competitive advantages.
Several authors argue that competitiveness in tourism is mainly dependent on innovation to
achieve lower costs and higher quality outputs (Chadee and Mattsson, 1996; Ottenbacher
and Gnoth, 2005). Nevertheless, tourism ?rms operate in different sectors such as
transportation, accommodation, leisure or intermediation, and the innovation behaviour of
each tourism ?rm would also differ (Or?la-Sintes and Mattsson, 2009). In the case of
hospitality ?rms, Jones (1996) suggests that innovation takes the form of a stepwise
process due to the in?uence of customer-contact personnel. In this case, new service
design and testing requires the input of prospective customers and also active cooperation
of the operating personnel who would ultimately be delivering the service. Moreover,
Camisón and Monfort-Mir (2012) argue that diffusion of innovation among services and
tourism ?rms is characterized by a low propensity for the development of new products and
processes. Nevertheless, extant literature does not empirically test the singular pattern of
tourism innovation in comparison to manufacturing and services in general.
Additionally, Ottenbacher and Gnoth (2005) proposed nine factors that support successful
service innovation by hotel managers: market selection; strategic human resource
management; training of employees; market responsiveness; empowerment; behaviour-based
evaluation; marketing synergy; employee commitment and tangible quality. Or?la-Sintes
and Mattsson (2009) conclude that innovation behaviour in the hotel industry relates
innovation types to determinants such as the service provider and customer competences,
market drivers and the impact of innovation on performance. Grissemann et al. (2013)
identi?ed ?ve ?rm-internal dimensions in?uencing innovation behaviour in hospitality ?rms:
employee involvement, customer participation, ITs, innovation management and innovation
networks. The same study also reveals that innovations in hotels’ service area and hotels’
IT area were in?uenced by employee involvement, customer participation, innovation
management and ITs.
PAGE 158 INTERNATIONAL JOURNAL OF CULTURE, TOURISM AND HOSPITALITY RESEARCH VOL. 8 NO. 2 2014
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While there has been and continues to be an increasing trend to study innovation in
tourism, particularly in hospitality, it is accompanied by some controversy, and there has
been little in the way of a business model that enables understanding of the broad factors
in?uencing innovation in this sector. The next section proposes a framework applied to the
service sector that can help analyze different organizational archetypes, innovation factors
and consequences in the tourism sector.
Integrated model
The diversity of approaches to studying innovation has generated countless typologies and
now model speci?cations depending upon the focus of study (Sarkar, 2007). Despite an
increasing volume of literature on innovation behaviour, the innovation process is still poorly
understood (Coombs et al., 1996), with still no precise prescription for successful
innovation (Rothwell, 1992). In fact, the literature on management (strategy) offers a wide
array of quite simple and intuitive models of strategy (as well as organizational
management). The majority of these models offer insights on designing effective strategy,
and their virtue often lies in their simplicity and intuitive appeal. However, these models are
seldom analytical or robust, lacking any behavioural relationship between the variables
under study (Sarkar, 2007, p. 31).
The integrated innovation model (Sarkar, 2005, 2007) ?lls a major gap in the understanding
of innovation dynamics, by connecting market forces, sustainability and outcomes in an
intuitive yet rigorous framework. It is a model for understanding ?rm and market dynamics,
as it relates to innovation, enhanced by the different strands of literature on industrial
organization, management and innovation. It is an integrated approach which allows the
academic, management consultant and manager alike to understand where a product (or
a single product ?rm) is located in an integrated innovation space and why it is so located,
which then provides valuable clues as to what to do when designing strategy. Application
of an integrated model to the tourism sector allows analyzes of a wide range of market
dynamics, as illustrated below.
The model describes a product (or a single product ?rm) in four dimensions: an external
market dimension, a dimension on strategic orientation and two outcome dimensions.
These four dimensions together de?ne four spaces: an archetypal space, a strategy space,
an outcome space and a market space. In conjunction, these four spaces describe the
integrated innovation space.
In the ?rst and north-east quadrant, which describes the archetypal space (Figure 1), the
external market dimension in which a ?rm operates is represented by the degree of
competitive market pressure on the horizontal axis. A product or ?rm located further to the
right is under increasing competitive pressure, often represented by an increase in the
number of ?rms in the industry. The vertical axis in the archetypal space measures a ?rm’s
strategic orientation. In the innovation context (of the general framework), the strategic
orientation is an innovation–product differentiation strategy.
Moving anti-clockwise (Figure 1), the strategy space gives the trade-off between a ?rm’s
strategic orientation and market return. While the archetypal space describes a ?rm
according to the coordinates of an external (market)–internal (strategic) relationship, the
strategy space de?nes its market outcome with respect to its strategic orientation. The
second quadrant, therefore, describes a strategy space where the two variables of
innovation and market outcome are connected via a behavioural relationship.
The market outcome of the ?rm in its competitive environment can be variously represented
by a variable such as sales, market share, margins or pro?ts, with a westward or outward
movement away from the origin representing an increased level of market share (or other
outcome variable). The model suggests a generic pay-off function represented by upward
sloping concave surfaces. These curves represent the return fromactivities associated with
a given degree of market pressure, between the strategic orientation pursued and the
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outcome of that strategy. It posits a positive relationship between strategic orientation
(innovation/product differentiation) and the resulting market share in the industry. These
curves are the innovation–pay-off (IP) curves. The exact curvature or elasticity of these IP
functions is industry speci?c. These IP curves, associated with a given degree of market
pressure, can shift temporally due to different factors including evolving product and labour
market conditions, technological changes and (disruptive) innovation.
Hence, the coordinates of a product in the strategy space give the market outcome the ?rm
enjoys in a given competitive environment, which is the result of the degree of innovation
or product differentiation pursued. Ceteris paribus, a higher level of product differentiation
by a ?rm, would lead to an increase in market outcome (sales, market share or pro?ts). The
third quadrant describes the outcome space, but in an effort to keep the model simple, we
choose only one variable to represent a ?rm’s outcome, given its strategic orientation
(innovation strategy). This space maps market outcome, which is measured by sales,
market share or pro?ts, onto itself via the 45° line. This device enables us in the ?nal
southeast quadrant to study the correspondence between returns and competitive
pressure. Later on in this outcome space, we shall describe a behavioural relationship
between two important market outcome variables, market share and pro?ts.
The fourth quadrant maps the external environment to market returns for a given strategic
orientation (innovation). This is the market space, which locates the market outcome for a
given degree of competitive pressure. The market outcome of the product (single product
?rm) is, in turn, related to the degree of product innovation/differentiation via the integration
of the strategic space and the outcome space.
Figure 1 The integrated innovation space: archetypal, strategy, outcome and the
market space
45º
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Outcome Space (QIII) Market Space (QIV)
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Figure 1 below illustrates the case of two ?rms, Firms 1 and 2. Firm 1 faces a fairly
competitive environment and in its effort to stand above the crowd, offers a more
differentiated product.
A ?rm could be described and positioned in one of the following archetypes in the
archetypal space: wolf (high differentiation and low competition), fox (high differentiation
and competition), bear (low differentiation and competition) and sheep (low differentiation
and high competition).
The methodological approach
This part of the study presents an empirical study as applied to tourism ?rms.
Methodology
This research uses factorial analysis of principal component analysis (PCA) on a data set
composed of 158 Portuguese ?rms in the tourism sector. The sample was collected in 2010
using the electronic addresses of Portuguese tourism ?rms registered in the Portugal Travel
Guide. The questionnaire was sent to key informants (more details about data collection
and characterization in the next section). The questionnaire includes 29 questions to be
responded in a scale between 0 and 10. According to Sarkar (2007), this scale allows more
intuitive answers. These tourism ?rms are drawn from different segments in the hospitality
and tourism sector, including hotels, guest-houses and car-hire ?rms.
PCA is a statistical method involving a mathematical procedure that transforms a number
of possibly correlated variables (in this case, 29 variables from the questionnaire
developed by Sarkar, 2007) into a number of uncorrelated variables called principal
components, related to the original variables by an orthogonal transformation. This
transformation is de?ned in such a way that the ?rst principal component has as high a
variance as possible (that is, accounting for as much of the variability in the data as
possible), and each succeeding component, in turn, has the highest variance possible
under the constraint of being orthogonal to the preceding components. PCA is sensitive to
the relative scaling of the original variables. This methodology has an exploratory and
con?rmatory value (Hair et al., 1998), and this allows collecting the three components by
using statistical methods from the axes of the ?rst quadrant of the model, called quadrant
of archetypes (Sarkar, 2005, 2007). The scale used (from 0 to 10) was designed to elicit
intuitive responses.
The variables of the integrated model are grouped into three categories (X axis – market
pressure, Y axis – product differentiation and Z axis – market performance). The ?rst
dimension of the model (X) refers to the perception of the ?rm’s own attitude towards the
market, the second (Y) concerns the ?rm’s behaviour and the third dimension (Z) refers to
the results. PCA uses an oblimin rotation (“similar or orthogonal rotations, except that
oblique rotations allow correlated factors instead of maintaining independence between
rotated factors”; Hair et al., 1998, p. 110) and a pairwise comparison. “The scale of
reliability presents the proportion of variance attributable to the true score of the latent
variable. (. . .) Internal consistency is typically equated with Cronbach’s (1951) coef?cient
alpha” (DeVellis, 2003, p. 29) for each of the six factors extracted through determination of
Cronbach’s ? (“Alpha is de?ned as the proportion of a scale’s total variance attributable to
a common source, presumably to the true score of a latent variable underlying the items”;
DeVellis, 2003, p. 31).
Data characterization
This section presents a general characterization of our sample. Table IV illustrates the
distribution of ?rms by size, showing that the majority of these ?rms are small- and
medium-sized.
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Table V presents the ?rms’ distribution by region. The greatest number of ?rms is located
in Lisbon and the south of the country (Algarve), the most important tourism destinations in
the country.
Multivariate analysis: PCA
This section presents the PCA and consequently the factors extracted.
Table VI illustrates the ?rst factor. Based on the integrated model, this factor is named
“Firms’ position based on marketing” because of the inclusion of variables included in
marketing strategy. This factor groups questions 4, 5, 6, 7 and 8 and is connected to
marketing strategy. It highlights the non-technological dimension of innovation in the
tourism sector (Table VII).
Factor 2 forms a group of four items from the Z axis (market performance). This factor does
not allow identi?cation of sub-dimensions in Z. When considering the tourism sector, this is
justi?able given the interrelationship between Factors 1 and 2 (Table VIII).
Factor 3, sustainability of services in the market, includes a set of items related to human
resources, which again highlights the importance of non-technological factors in tourism
Table IV Distribution of ?rms by size
Size Proportion (per cent)
Small and medium ?rms 78
Large ?rms 2
Table V Distribution of ?rms by region
Region Proportion (per cent)
Lisbon 30
South – Algarve 37
North 7
Centre 3
Islands – Azores and Madeira 5
Questions left unanswered 18
Table VI Factor 1. Firms’ position based on marketing
Items Average SD Impact factor
Correlation total
of item
With regard to new markets: our objective at the moment is simply
to survive; we are always trying to expand and explore new
market opportunities [Z3] 7.3 1.66 0.352 0.808
Our clients are: disappointed and may easily switch to
competitors’ products if we are not careful; they are very satis?ed
with what we have to offer [Z10] 7.2 1.53 0.523 0.723
Our products enjoy: less prestige than those of our competitors;
much greater prestige than those of our competitors [Y7] 7.1 1.45 0.354 0.634
Our products are: not dependent on any protection; protected by
patent/copyright/some form of special knowledge [Y6] 7.6 1.54 0.608 0.772
Our product: is de?ned as having: standard, modular attributes;
specialized features that are often proprietary [X9] 6.5 2.22 0.273 0.618
We believe that we offer clients products that are: inferior to
competitors’ products; better than competitors’ products [Y2] 6.8 1.65 0.482 0.675
Our clients pay: less for our products than for our competitors’
products; more for our products than for our competitors’
products [Y3] 7.4 1.50 0.604 0.765
Cronbach’s ? ? 0.813
Variance explained ? 70 per cent
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?rms. Tacit knowledge of human resources is a differentiating factor. This factor is situated
on the Y axis of the integrated model (Table IX).
The PCA resulted in three factors (Factors 4, 5 and 6). Factor 4 concerns entry barriers,
turbulence and product homogeneity as relevant factors. Market structure justi?es the
situations of perfect competition (the sheep archetype in the model) and monopoly (tending
towards the bear archetype), justifying a lower allocation of resources to innovation
(Table X).
Factor 5 is very important with regards to the level of competition. Tourism ?rms reveal a
higher segmentation according to tourism product (sun and beach, meetings, incentives,
conventions and exhibitions [MICE], short breaks, city breaks, nature, etc.) (Table XI)
The last factor, bargaining power, includes items connected to the bargaining power of
customers, which increases in the case of individual customers due to the growing option
of online booking and sales. ICT has increased transparency in the market. Information now
available about ?rms makes it easy for individual clients to choose according to price.
Table VII Factor 2. Entrepreneurial performance
Items Average SD Impact factor
Correlation total
of item
Our market share is: low and under great pressure; high
and stable [Z1] 5.7 1.83 0.523 0.731
Our margins before taxes are: small and under pressure;
comfortable and above the industry average [Z6] 5.1 1.87 0.399 0.677
We are: concerned with our low sales; satis?ed with the
regular increments of sales [Z8] 4.7 2.11 0.652 0.765
In order to maintain our market position: we do not need
great investments in technology or personnel; we have to
invest constantly in new ideas and technology [Z7] 6.4 1.77 0.543 0.654
Cronbach’s ? ? 0.703
Variance explained ? 34 per cent
Table VIII Factor 3. Sustainability of services in the market
Items Average SD Impact factor
Correlation total
of item
Our products: are not dif?cult to copy; not easily duplicated
by other ?rms [Y10] 6.5 1.97 0.432 0.645
Our services: are not dif?cult to replicate if we do nothing;
are not easily replicated [Y5] 6.3 2.01 0.553 0.871
Our services can be de?ned as having: standard attributes;
a great many special attributes [Y1] 5.4 1.42 0.633 0.762
Cronbach’s ? ? 0.602
Explained variance ? 21 per cent
Table IX Factor 4. Market structure
Items Average SD Impact factor
Correlation total
of item
Our market is characterized by: low turbulence in terms of entry
or exit of ?rms; new ?rms are constantly entering the market
and, in general, there is high market turbulence [X5] 6.1 2.01 0.621 0.734
Our consumers: are obliged to use our services due to a lack of
alternatives; have many alternatives to our service [X6] 5.9 2.12 0.528 0.732
Our market is characterized by: dif?culty of entry for new
competitors; ease of entry for new competitors [X4] 4.9 2.31 0.586 0.711
Cronbach’s ? ? 0.571
Explained variance? 26 per cent
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Tourism ?rms in archetypes of an integrated model
This section shows Factors 1 (a ?rm’s position based on marketing), 3 (sustainability of
services) and 4 (market structure) archetypes of an integrated model. Factors 1 and 3
belong to differentiation (Y axis) and Factor 4 belongs to market pressure (the X axis
identi?ed three factors, the choice of Factor 4 is justi?ed by statistical reliability) (X axis).
Figure 1 allows for ?rms to be positioned within the archetypes according to the PCA
presented in the last section.
Figure 3 presents Factors 1 (a ?rm’s position based on marketing) and 4r (market
structure). It identi?es 117 ?rms as belonging to the fox archetype, 33 ?rms to the wolf
archetype, ?ve ?rms to the bear archetype and three ?rms to the sheep archetype. These
positions suggest that when the strategy of differentiation/innovation is based on marketing,
?rms show high competitive positioning in the market.
Figure 3 presents the archetypes with reference to Factors 3 (sustainability of service in the
market) and 4 (market structure). In this case, it is possible to identify 85 ?rms as belonging
to the fox archetype, 29 ?rms to the wolf archetype, 16 ?rms to the sheep archetype and 18
?rms to the bear archetype. The positioning also suggests the importance of intangible
resources, such as human resources.
A comparison of Figure 2 with Figure 3 allows us to draw the following conclusion: most
?rms are positioned as the fox archetype (74 per cent in Figure 2 and 53 per cent in Figure
3). However, Figure 3 has a more balanced distribution of ?rms among the four archetypes,
with a high number of ?rms in archetypes of lower differentiation (bear and sheep) and a
small number of ?rms in the sheep archetype category (3 per cent in Figure 2 and 11 per
cent in Figure 3). Based on the theoretical approach of the integrated model,
Schumpeterian entrepreneurs are mainly situated in the wolf archetype category and could
also include some in the fox archetype category in which ?rms try to innovate to succeed
in the marketplace. However, it is important to note that ?rms are mainly positioned on a
0-10 scale in high values (mainly ?5). This ?nding raises some questions: could it be that
some wolves are actually foxes? Additionally, how many foxes are really sheep in disguise?
Table X Factor 5. Competition
Items Average SD Impact factor
Correlation total
of item
Our competitors: are not as good as we are; are powerful
and highly organized [X2] 5.1 1.93 0.368 0.601
Our market is characterized by: few competitors; many
competitors [X1] 7.3 1.95 0.614 0.648
In terms of the functionality of our product: there is no
substitute in the market; there are many substitutes [X3] 6.9 1.81 0.562 0.733
Cronbach’s ? ? 0.578
Explained variance ? 20 per cent
Table XI Factor 6. Bargaining power
Items Average SD Impact factor
Correlation total
of item
Our prices are: not under pressure, indeed, price is not the
buyer’s principal decision variable; are always under great
pressure [X10] 7.2 2.02 0.671 0.838
When establishing prices for our services, we have:
imposed our prices on our customers; lowered prices to
amounts that customers are willing to pay [X8] 6.9 2.01 0.678 0.823
Cronbach’s ? ? 0.508
Explained variance ? 14 per cent
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Tables XII and XIII present how the ?rms are distributed by archetypes with regard to Y –
marketing and Y – sustainability of services in markets.
Analyzing by region allows us to identify that the highest number of ?rms in the wolf
archetype category are in the Lisbon region and in the south of Portugal, which are the main
tourism destinations in Portugal. These results suggest the possibility of an entrepreneurial
clustering of the sector, which permits the reduction of uncertainties, access to resources,
know-how and networks.
Figure 2 Archetypes (Y – marketing)
L Degree of competitive pressure H
BEAR
WOLF FOX
SHEEP
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33
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5
Figure 3 Archetypes (Y – sustainability of services in the market)
L Degree of competitive pressure H
BEAR
WOLF FOX
SHEEP
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29
26
18
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Discussion
The empirical model and the results achieved corroborate the importance of the use of
more behavioural approaches in the relationship variables under study (Sarkar, 2007),
mainly in heterogeneous and multidimensional sectors such as tourism. Applying an
integrated model to the tourism sector allows analysis of a wide range of market dynamics,
illustrated in several dimensions or factors of the multidimensional analysis.
Factor 1 “Firms’ position based on marketing” grouped a set of variables included in
marketing strategy and highlights the importance of marketing strategy in service ?rms and
entrepreneurial strategy (Guido et al., 2011). Regarding Factor 2, “Entrepreneurial
performance”, some studies reveal that improvements in a ?rm’s performance are
dependent on customer relationship management and the existence of an entrepreneurial
culture that promotes innovation and marketing (Brendan and Graham 2002; Siwan and
Rowley, 2010; Kohtamäki, et al., 2012). Factor 3, “Sustainability of services in market” again
highlights the importance of non-technological factors in tourism ?rms. Other studies also
refer to the importance of non-technological forms of innovation, such as professional
know-how, brands and design, which then play a major role (Decelle, 2004). Camisón and
Monfort-Mir (2012) indicate that tourism ?rms are less technically innovative than
manufacturing and other service ?rms and that they present mainly incremental innovations
based on earlier available knowledge within the organization, permitting imitators and
adapters to prevail over the genuine innovators. Jacob et al. (2003) also found that Balearic
hotels mainly launch non-technological innovations that change organizational, delivery
and work processes. With Factor 3, tacit knowledge of human resources is considered as
a differentiating factor in our results. Tacit knowledge is not easily codi?ed, may not be
formally identi?ed and can be acquired only through practice (Buckley and Ollenburg,
2013). This variable is understudied in the tourism sector (Singh and Hu, 2008). Factor 4,
“Market structures”, includes entry barriers, turbulence and product homogeneity as
relevant factors. These factors are identi?ed in other studies in which the entry and exit of
?rms are very frequent (OECD, 2002; Carvalho, 2008). The theoretical approach developed
by Comanor (1987) concerning relationship between barriers to entry and innovation
concludes that when barriers to entry are lower, the incentive to innovate is also small,
as the pro?tability of innovations soon disappears, while when the barriers to entry are
higher, the incentive to innovate tends to decrease. Factor 5, “Competition”, con?rms
the sectoral segmentation and also takes into consideration demand-driven features,
particularly spending per customer (Dolnicar, 2004; Mok and Iverson, 2000; Pizam and
Reichel, 1979; Spotts and Mahoney, 1991; Woodside et al., 1987). And the last factor,
Factor 6 “Bargaining power” considers items connected to customers’ bargaining
Table XII Tourism ?rms by archetypes (Y – marketing)
Archetypes Firms
Sheep 3
Wolf 33
Fox 117
Bear 5
Total 158
Table XIII Tourism ?rms by archetypes (Y – sustainability of services in market)
Archetypes Firms
Sheep 26
Wolf 29
Fox 85
Bear 18
Total 158
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power. Tourism ?rms have at least two types of customers: tour operators, who have a
high bargaining power, and customers, who usually have less bargaining power.
However, data reveal that the bargaining power of individual clients has recently seen
an increase as a result of the growing option of online booking and sales. Information
now available about ?rms makes it easy for individual clients to choose according to
price. In fact, social media have been widely adopted by travellers to search, organize,
share and annotate their travel stories and experiences through blogs and microblogs
(e.g. Blogger and Twitter), online communities (e.g. Facebook, RenRen and
TripAdvisor), media sharing sites (e.g. Flickr and YouTube), social bookmarking sites
(e.g. Delicious), social knowledge sharing sites (e.g. Wikitravel) and other tools in a
collaborative way (Xiang and Gretzel, 2010; Leung et al., 2013) and improve indirectly
the bargaining power of individual customers.
Summarizing, the PCA allows six components to be identi?ed. These components could be
situated within the dimensions of the integrated model. Although Factor 1 includes the X, Y
and Z variables, in our view respondents interpreted this as the Y dimension. The
multivariate analysis con?rms the importance of intangible resources, especially marketing
and human resources, in tourism ?rms. However, it is important to note that this research
follows an empirical approach (Gallouj and Savona, 2010), and it could be dif?cult to
generalize the contributions of this study to the entire service sector.
Concluding remarks
In recent years, there has been increasing research on service sector innovation. However,
it is possible to point out to different perspectives, while several authors indicate that
innovation in services and manufacturing are closely related, other scholars establish a
difference between them. Additionally, research into innovation in tourism is at an early
stage. This study aims to contribute towards creating and developing research into
innovation as applied to the tourism sector, where validation is necessary. The
characteristics of the tourism sector, such as the heterogeneity and dispersion of activities
in nature, time and space, make empirical analysis dif?cult. This analysis does not intend
to portray an extensive picture of all the questions involved in the study of the tourism
sector. Nevertheless, because it is based on a reliable statistical database, and also based
on a theoretical model tested on other sectors including the service sector, it allows
analyzes of the dynamics of innovation in tourism from a more sensitive and behavioural
approach. The study uses archetypes and the market outcome resulting from the
innovation strategies that have been pursued. This research also compares similarities and
differences according to ?rms’ geographical location to identify innovative patterns in
tourism ?rms.
The empirical study using PCA allows the identi?cation of six components. These
components could be situated within the dimensions of the integrated model. Although
Factor 1 includes X, Y and Z variables, it is of our view that respondents interpreted them
as Y. The multivariate analysis con?rms the importance of intangible resources, especially
marketing and human resources, in tourism ?rms.
A complementary approach allows the positioning of ?rms in the ?rst quadrant of this
integrated model (archetype axes) and suggests that most ?rms in the sample perceived
themselves to be in the fox category in both tested cases. These ?rms invest via greater
effort with this differentiation based on marketing. Geographical location in Lisbon and the
south of Portugal seem to be relevant factors in making the values ?5 in the Y axis. The
?ndings highlight the links between service, market structures and innovation
strategies, considering geographical agglomeration of ?rms in a small economy, as well
as different innovation trajectories and positions in the model according to the
geographical distribution.
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The study also identi?es the link between services, market structures and innovation
strategies considering geographical agglomeration of ?rms in a small economy, as well as
factors that determine the competitiveness of tourism ?rms. This study could provide a
more sensitive approach to studying innovation in tourism and facilitate intuitive modelling
that could be used by managers and consultants. The situational analysis provided by this
research is related to a theoretical relationship, considering a set of relevant variables and
its virtue lies in the practical approach to situational analysis.
The main managerial implications highlight the importance of managers’ attention to
intangible resources, such as marketing and human resources and their link to innovation
and performance. It is also important that managers perceive the increased bargaining
power of individual clients as a result of the growing option of online booking and sales.
Another clue provided by the results suggests the possibility of an entrepreneurial
clustering of the sector, which permits the reduction of uncertainties, access to resources,
know-how and networks.
In terms of public policy, this research suggests that development of this sector is
facilitated by the density of activities in a region to create a critical mass. It also
highlights the need for public policies that enhance entrepreneurial cooperation and
the promotion of common programmes crucial to the development of competences in
the ?elds of organizational management, human resources and marketing applied to
tourist destinations.
From an academic point of view, this research provides a holistic understanding of
innovation. From this perspective, innovation is in?uenced by external environmental
factors that in?uence strategic decisions and by intangible resources, especially marketing
and human resources. The last factors have a special role in the competitiveness of tourism
?rms. Geographical location also in?uences ?rms’ strategy and results.
Future studies could investigate further why geography/regions in?uence tourism ?rms’
innovativeness and how public policies could in?uence innovation in tourism from a
regional perspective. The authors believe that this research marks an important step in
developing innovation research in the tourism sector.
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About the authors
Luísa Margarida Cagica Carvalho is an Assistant Professor at the Open University
(Portugal) and Researcher at the CEFAGE, University of Évora. She received her PhD in
Management from the University of Évora (Portugal). She is the author of several articles in
scienti?c journals, international conferences, books and book chapters. Her current
research interests are in the areas of entrepreneurship, innovation, internationalization and
the service sector. Luísa Margarida Cagica Carvalho is the corresponding author and can
be contacted at: [email protected]
Soumodip Sarkar is a noted economist and management researcher. He is an Associate
Professor at the Department of Management, University of Évora, Portugal, where he was
the Dean of the Doctoral School, Institute for Advanced Studies and Research (IIFA) till
2014. His research interests are entrepreneurship and innovation, and at the university, he
is the coordinator of the Program in Entrepreneurship and Innovation.
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