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Destination marketing and the service-dominant logic:
A resource-based operationalization of strategic marketing assets
Nathaniel D. Line a,*, Rodney C. Runyan b,c,1
a
Florida State University, Dedman School of Hospitality, B4113 University Center, 288 Champions Way, Tallahassee, FL 32306, USA
b
Texas State University, School of Family and Consumer Sciences, 101 FCS Building, San Marcos, TX 78666, USA
c
Lancaster University Management School, UK
h i g h l i g h t s
The resource-based view is considered within the context of destination marketing.
The service-dominant logic is used to construct a destination resource hierarchy.
Three stakeholder-based categories of strategic marketing assets are identified.
A DMO’s market-based assets are operationalized as a second-order latent construct.
The implications of this construct for future research are discussed.
a r t i c l e i n f o
Article history:
Received 20 September 2013
Accepted 28 January 2014
Keywords:
Destination marketing
The resource-based view of the firm
Service-dominant logic
Stakeholder marketing
Strategic assets
a b s t r a c t
Despite the popularity of the resource-based view of the firm as a theoretical mechanism for the
explanation of organizational performance, this framework has received surprisingly little attention
within the context of destination marketing organizations (DMOs). The purpose of this research is to
enhance extant perspectives of destination competitiveness by considering the destination marketing
function from the dual theoretical lenses of the resource-based view of the firm and the service-
dominant logic of marketing. In particular, this research focuses on the resource classification schemas
underpinning these two frameworks and proposes a conceptual extension of their core phenomena to
the domain of destination marketing. Within this discussion, a conceptual and operational definition of
competitive market-based assets is proposed. This multifaceted construct is discussed as a potential
outcome of market-oriented destination marketing and as an antecedent to DMO performance.
Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction
Destinations are recognized as the primary unit of analysis in
the domain of tourism research (Pike Page, 2014), and as such,
destination marketing organizations (DMOs) have taken on
increased importance for tourism scholars. Depending on the view
one takes, the DMO is either a marketing organization, responsible
for driving business to the destination (Gartrell, 1992; Pike Page,
2014), or it is a management organization, providing leadership and
direction for the multifaceted tourism system (Murphy Murphy,
2004). Regardless of whether one sees the penultimate function
of these organizations as management or marketing, DMOs are a
key component of destination success (Bornhorst, Ritchie,
Sheehan, 2010; Ford Peeper, 2008). In this paper, we take the
position that while marketing is the core function of a DMO (Pike
Page, 2014), stakeholder management (e.g., leadership, direction,
coordination and management of a destination’s value-proposition
across stakeholders) is likewise an essential facet of strategic
destination marketing. Utilizing prevailing theoretical lenses from
the management and marketing literature, we develop our position
by proposing and operationalizing a latent conceptualization of
strategically valuable destination marketing assets emanating from
key stakeholder markets.
Destination marketing organizations are unique as they exert
little control over many of the resources they must leverage to
achieve success. That is, DMOs control neither the destination
infrastructure (e.g., roads, transportation, etc.) nor the privately
owned suppliers of the tourism product (e.g., lodging, dining, retail,
etc.). Lack of resource control notwithstanding, DMOs are still in
* Corresponding author. Tel.: þ1 850 645 2710; fax: þ1 850 644 5565.
E-mail addresses: nline@fsu.edu (N.D. Line), rcr56@txstate.edu (R.C. Runyan).
1
Tel.: þ1 512 245 2155; fax: þ1 512 245 3829.
Contents lists available at ScienceDirect
Tourism Management
journal homepage: www.elsevier.com/locate/tourman
http://dx.doi.org/10.1016/j.tourman.2014.01.024
0261-5177/Ó 2014 Elsevier Ltd. All rights reserved.
Tourism Management 43 (2014) 91e102

charge of managing their destination’s value proposition. Without
the ability to control the product or its attributes, however, DMO’s
must create value by coordinating the efforts of those stakeholders
that directly control the destination’s core and supporting re-
sources. But how do DMOs act strategically if they do not control
(and therefore cannot directly deploy) destination resources?
Pike and Page (2014) suggest that the quintessential goal of all
DMOs is sustained destination competitiveness and that to attain
this requires the cultivation of resources that can build competitive
advantage. Thus, given the networked makeup of the destination
marketing industry (Ford, Wang, Vestal, 2012; Wang Xiang,
2007), the ultimate challenge for DMOs is to facilitate resource
interaction and combination across destination stakeholders.
While the strategic importance of interorganizational resource
interaction is a relatively new course of academic inquiry (e.g.,
Baraldi, Gressetvold, Harrison, 2012), the structure of the desti-
nation marketing industry suggests the utility of such a framework.
Unfortunately, because a unifying theoretical framework that
clearly identifies the sources of sustainable competitive advantage
for DMOs has yet to be achieved, tourism research has fallen behind
the more general streams of marketing research in its ability to
measure the organization-level latent phenomena associated with
successful implementations of the marketing concept. In light of
this important theoretical gap, the purpose of this paper is three-
fold: First, we draw a series of parallels among the service-
dominant logic of marketing (Vargo Lusch, 2004), the stake-
holder marketing movement (Bhattacharya Korschun, 2008;
Gundlach Wilkie, 2010), and the resource-based view of the
firm to propose a hierarchical classification of destination re-
sources. Second, we explain the dynamic relationships among the
resources within the proposed hierarchy. Finally, we provide sup-
port for this framework by developing conceptual and operational
definitions of a DMO’s market-based assets through the formal
scale development process (Churchill,1979). This multidimensional
construct is discussed as a potential outcome of market-oriented
destination marketing and as an antecedent to DMO performance.
2. Conceptual framework
If the DMO is an organization that functions in both marketing
and management capacities (Bornhorst et al., 2010), approaches to
construct development must likewise draw from prevailing
perspectives in both the marketing and the management litera-
tures. From the management literature we utilize the resource-
based view of the firm (Barney, 1991) to provide a general frame-
work of how resources are identified and leveraged by a firm to
create competitive advantage and long-term success. Within this
general framework, a more specific model of the DMO is derived
through the incorporation of two separate theories of marketing:
the service-dominant logic (SDL) (Constantin Lusch, 1994; Vargo
and Lusch, 2004) and market orientation (Kohli Jaworski, 1990;
Narver Slater, 1990). This model demonstrates the strategic
paths by which the DMO acts upon resources outside of its control
(i.e., operand resources) using its own resources (i.e., operant re-
sources) to create a higher-order (composite) resource base (see
Madhavaram Hunt, 2007). We propose that this process results in
the development of a set of market-based assets that facilitate the
achievement of a DMO’s ultimate goal, sustained destination
competitiveness. Fig. 1 synthesizes these distinct constructs and
provides an overview of the framework used to propose and
operationalize the multidimensional market-based assets
construct.
2.1. RBV, SDL and destination marketing organizations: an
integrated framework
The resource-based view (RBV) of the firm seeks to explain the
sources of long-term organizational success (Barney, 1991; Peteraf,
1993; Wernerfelt, 1984). Under the assumption that firms (orga-
nizations) are fundamentally heterogeneous in terms of resources
and capabilities, the resource-based view posits that long-term
financial success accrues to those organizations that most effi-
ciently and effectively deploy resource endowments in the
marketplace (Peteraf, 1993). Such resources may be tangible or
intangible (Barney, 1991) and can have varied sources of origin
(Hooley, Broderick, Möller, 1998). In order for a resource to
contribute to the creation of a sustainable competitive advantage,
however, it must be valuable, rare, inimitable, and non-
substitutable (Barney, 1991).
Despite the acceptance of RBV within the strategic management
literature as a viable framework for explaining organizational per-
formance (Crook, Ketchen, Combs, Todd, 2008), the theory re-
ceives surprisingly little attention within the context of destination
marketing organizations (DMOs). One potential reason for the
Fig. 1. An SDL-based hierarchy of destination marketing resources.
N.D. Line, R.C. Runyan / Tourism Management 43 (2014) 91e10292

dearth of RBV-focused research in the tourism and destination
marketing literature is that, until recently, scholars have considered
the tenets of marketing thought fundamentally incompatible with
those of the resource-based view (see Srivastava, Fahey,
Christensen, 2001). However, the shift in marketing thought from
a goods- or product-centered dominant logic to a service-centered
dominant logic (Constantin Lusch, 1994; Lusch Webster, 2011;
Madhavaram Hunt, 2007; Vargo Lusch, 2004) has helped to
bridge the gap between the resource-based view and contempo-
rary perspectives pertaining to the nature and scope of marketing
thought.
Of particular consequence in making the theoretical link be-
tween RBV and SDL is the distinction among several types of re-
sources. Within the SDL framework, Constantin and Lusch (1994)
refer to resources as either operand or operant. Briefly, operand
resources are possessed of a relatively low level of utility until
imbued with value via the deployment of a higher-order set of
operant resources. A key feature of the SDL is the notion that op-
erant resources (as opposed to operand resources) stand as the
locus of a sustained competitive advantage (Vargo Lusch, 2004).
We propose that this concept is particularly salient in the tourism
industry, as destinations have become increasingly homogenized
(Crouch, 2011) and operand resources (e.g., sun, sand, historical,
water, etc.) are increasingly seen as substitutable. In terms of the
resource-based view, because substitutable resources are certainly
not rare and lose value based on consumer perceptions (Peteraf,
1993), such resources cannot be leveraged for sustainable
competitive advantage (Barney, 1991). Accordingly, the SDL pro-
motes the importance of intangible resources, stakeholder re-
lationships, and the co-creation of value (Lusch Webster, 2011;
Vargo Lusch, 2004) within the marketing function.
Among the most important canons of the SDL paradigm is the
contention that value is no longer created merely through the
expression of a firm-level value proposition to the market but via
the interactions of the focal firm/organization with a broad set of
external stakeholders (Lusch Webster, 2011). This shift away from
a product-centered dominant logic to an emphasis on relationships
among networked actors raises some important questions in the
field of destination marketing: For example, given the unique pa-
rameters associated with the marketing of destinations (as opposed
to the marketing of tangible goods), what is the nature of the
operand/operant resource dichotomy within the domain of desti-
nation marketing? Likewise, what is/are the locus/loci of value
creation in the destination marketing function, and what are the
potential sources of competitive advantage that arise from in-
teractions between the DMO and its stakeholder markets? Finally,
what are the potential benefits of a market-oriented approach to
destination marketing, and how should these relationally based
constructs be organized, conceptualized, and operationalized? The
following sections address these critical issues, culminating in set
of propositions pertaining to the dimensional structure of such a
construct.
2.2. Destination competitiveness
The increasingly competitive conditions in the contemporary
market for destinations (Pike Ryan, 2004) have facilitated a cor-
responding interest in the identification of the destination-level
factors associated with destination competitiveness. Within this
stream of research, a number of classification schemata have been
proposed that identify a multitude of attributes associated with
destination competitiveness (e.g., Crouch, 2011; Dwyer, Mellor,
Livaic, Edwards, Kim, 2004; Enright Newton, 2004; Ritchie
Crouch, 2003). The majority of this research, however, has been
conducted at the level of the destination with relatively little
discrimination between the destination itself and the organizations
charged with marketing and managing the destinations (see
Bornhorst et al.’s, 2010 qualitative study for an important excep-
tion). As a result, while there has been progress toward the goal of
identifying what a competitive destination looks like in terms of its
overall attribute structure, relatively less is known about the
sources of these competitive advantages from a strategic manage-
ment perspective and, perhaps more importantly, at the organi-
zational level.
A second limitation to the contemporary perspective of desti-
nation competitiveness is that it lacks a hierarchical approach to
resource classification. In general, resources refer to the tangible
and intangible factors that contribute to improved efficiency and/or
effectiveness in the provision of some market offering (Barney,
1991). However, resource-based theory holds that not all re-
sources contribute to the development of a competitive advantage
in the same way (Amit Schoemaker, 1993; Barney, 1991; Hooley
et al., 1998; Hunt Morgan, 1995; Srivastava, Shervani, Fahey,
1998). Acknowledging that firm resources are homogenous and
imperfectly mobile, Barney (1991) stipulated that in order to be
considered as a source of sustainable competitive advantage, a
resource must be valuable, rare, imperfectly imitable, and imper-
fectly substitutable.
This resource-based approach to competitive advantage is an
integral component of the service-dominant logic. Similar to the
resource-based view, the SDL distinguishes between resources
based on the ability to confer competitive advantage. Building on
resource-based theory, proponents of the SDL differentiate be-
tween operand and operant resources (Vargo Lusch, 2004), as
well as among hierarchical levels of the operant resources them-
selves (Madhavaram Hunt, 2007). Unfortunately, while the or-
ganization of these RBV- and SDL-based theoretical phenomena
have contributed greatly to the advancement of marketing thought,
tourism research has been slow to apply these frameworks.
In order to fully understand the manifestations of these classi-
fication schemata in the context of destination marketing, it is first
necessary to take a closer look at the differences between operand
and operant resources. First, in terms of establishing an RBV-based
resource classification system of destination marketing resources,
the stipulation that operand resources must be acted upon in order
to confer value is perhaps the most important distinction. However,
a second essential feature of operand resources is their basal na-
ture. Operand resources are common and, of themselves, are
possessed of a relatively low degree of marginal utility (Constantin
Lusch, 1994). Considered within the terminology of the resource-
based view, operand resources do not represent a strong source of
sustainable competitive advantage because they are abundantly
available at the aggregate level, are largely substitutable, and can be
imitated relatively easily. As such, many commonly acknowledged
destination attributes such as physiography and climate, culture,
heritage/history, activity mix, infrastructure, and superstructure (cf.
Dwyer et al., 2004; Ritchie Crouch, 2003) can be seen as operand
resources. While these resources are necessary for the production
of a DMO’s market offering, the increasing homogenization of
destinations (Crouch, 2011) has rendered these attributes highly
substitutable in many product categories (e.g., sun and sand, urban,
etc.) (Usakli Baloglu, 2011).
Additionally, DMOs have relatively limited control of a desti-
nation’s operand resources. These organizations control neither the
destination’s infrastructure nor the private suppliers of the tourism
product. Likewise, a DMO does not own the natural and historical/
heritage-based resources that play such a critical role in many
destinations’ competitive positions (Dwyer et al., 2004; Enright
Newton, 2004). Because many of these core and supporting
destination-level resources are largely beyond the direct control of
N.D. Line, R.C. Runyan / Tourism Management 43 (2014) 91e102 93

the DMO, it is difficult to deploy them advantageously without
combining them with other resources (cf. Madhavaram Hunt,
2007). Recalling that operant resources are employed to act on
operand resources (and other operant resources) to create value
(Vargo Lusch, 2004), the capabilities that allow a DMO to coor-
dinate its operand resources into a value-proposition can be seen as
the operant locus of value creation in the destination marketing
function. As discussed in the following section, these capabilities
are the essence of a market orientation (Day, 1994).
2.3. Market orientation and stakeholder marketing
As applied to destinations, the principles of the service-
dominant logic suggest that (1) fundamental differences exist be-
tween the (operand) destination resources that lie outside the
control of a DMO and the (operant) destination management re-
sources/capabilities that are used to imbue the operand resources
with utility and value; and (2) the value of a DMO to a destination
lies in its ability to deploy resources outside of its direct control to
the destination’s economic advantage (cf. Ford Peeper, 2008). To
accomplish such a task requires consideration not only of customer
needs, but also the needs of the public and private stakeholders of
the destination’s tourism product (Fyall Garrod, 2005; Murphy
Murphy, 2004; Sheehan, Ritchie, Hudson, 2007; Wang, 2008).
Thus, in order to be truly market-oriented, a DMO must go beyond
the traditional customer-centric notion of “the market” (i.e., Kohli
Jaworski, 1990; Narver Slater, 1990). In addition to visitors, extant
research on destination stakeholders suggests the existence of at
least two additional stakeholder markets with which a DMO must
interact in order to be successful e the local government and the
local tourism industry. As follows, stakeholder theory and the
closely related tenets of stakeholder marketing are introduced as a
justification for this expanded view of DMO market orientation. In
turn, this discussion forms the basis for the proposal (and subse-
quent operationalization) of a DMO’s strategic marketing assets.
In contrast to traditional input-output models of the firm,
stakeholder theory argues that managers should be concerned not
only with competitors and customers, but with all actors that
possess a legitimate interest in the firm’s activities (Donaldson
Preston, 1995; Freeman, 1984). While the formal application of
stakeholder theory to the field of marketing is a relatively new
phenomenon, historical propositions concerning the nature and
scope of marketing thought suggest that customers are but one
market for which the tenets of the marketing concept apply
(Bagozzi, 1975; Hunt, 1976; Kotler, 1972).
As discussed above, the service-dominant logic explicitly ac-
knowledges the role of non-market stakeholders in the co-creation
of value (Lusch, 2007; Lusch Webster, 2011). Accordingly, pro-
ponents of the “stakeholder marketing movement” (Gundlach
Wilkie, 2010) have called for a more direct consideration of stake-
holder issues within the context of strategy development (e.g.,
Bhattacharya Korschun, 2008, Ferrell, Gonzalez-Padron, Hult,
Maignan, 2010; Lusch Webster, 2011). Stakeholder marketing
suggests that, in addition to crafting marketing strategy based on
customer- and competitor-level information (Kohli Jaworski,
1990; Narver Slater, 1990), firms must also consider how their
activities will affect all parties that hold a stake in their business
practices and/or the outcome of these practices. In advocacy of
stakeholder marketing, Smith, Drumwright, and Gentile (2010) go
so far as to warn against the potential onset of a “new marketing
myopia” which ignores the emergence of salient non-customer
stakeholder markets that have come to wield significant power
over business activities and firm performance. Thus, in contrast to
the customer-centric, value-proposing dominant logic of Lusch and
Webster’s (2011) “era two” conceptualization of the marketing
concept, stakeholder marketing identifies more strongly with the
contemporary paradigm (i.e., era three) whereby value is co-
created across stakeholders in an effort to maximize both
customer and stakeholder value.
Importantly, the confluence of marketing and stakeholder
management can likewise be interpreted in terms of the resource-
based view. Day (1994) suggests that a market-based approach to
strategy is driven by a specific set of managerial capabilities. In
terms of the RBV framework, strategic capabilities such as a market
orientation can be viewed as resources that contribute to the cre-
ation of sustained competitive advantage (Hooley et al., 1998;
Teece, Pisano, Schuen, 1997). Likewise, if the scope of what
constitutes a market orientation is extended to include a wider
range of organizational stakeholders, stakeholder theory provides a
basis for the explication of stakeholder relationships as a source of
such an advantage. Thus, by combining stakeholder theory’s posi-
tion concerning the importance of external stakeholders with the
RBV-based position that stakeholder relationships represent rare
and inimitable resources (Dyer Singh, 1998), advocates for
stakeholder marketing are not unreasonable in suggesting that the
marketing concept plays a role in the cultivation of such resources
(Bhattacharya Korschun, 2008).
The above principles of stakeholder marketing are particularly
germane to the domain of destination marketing. Because DMOs
control very few of the resources necessary for sustaining a
competitive advantage in the overall market for destinations,
managers and executives of these organizations are charged with
the difficult task of adding value to a product that is ultimately
delivered by a broad set of autonomous external stakeholders.
While a number of stakeholders have been identified within the
general destination marketing function, three external groups
continually emerge as the most important destination stake-
holders: customers (group and independent), industry suppliers
(especially hoteliers), and politicians (e.g., Ford Peeper, 2008;
Park, Lehto, Morrison, 2008; Sheehan Ritchie, 2005; Sheehan
et al., 2007).
Recalling the previous discussion of destination competitive-
ness and resource hierarchies, we suggest that (1) if a destination’s
core and supporting resources represent a set of operand resources
and (2) if the owners, suppliers, and end consumers of these re-
sources represent a destination’s stakeholders, then a DMO’s
orientation toward these stakeholders can be said to represent an
operant-level resource. Furthermore, because a DMO can be rela-
tively more (or less) oriented toward any one stakeholder group,
we suggest that a corresponding operant-level orientation should
likewise be acknowledged vis-à-vis each stakeholder market.
Madhavaram and Hunt’s (2007) hierarchy of operant resources
identifies each of these individual orientations as a basic operant
resource (BOR); but, like operand resources (albeit in a different
way and for different reasons), these BORs are also a relatively weak
source of sustainable advantage.
When combined, however, BORs (e.g., market-specific stake-
holder orientations) form a higher-order composite operant resource
(COR) (Madhavaram Hunt, 2007). Because CORs are relatively
more difficult to acquire and/or develop, they are often a stronger
source of sustainable competitive advantage than are BORs. Thus,
for destination marketers, we suggest that a market orientation
represents a capability-level, composite operant resource reflected
by three first-order, stakeholder-specific orientations: a customer
market orientation, a political market orientation, and an industry
market orientation.
In the case of destinations, the multi-stakeholder conceptuali-
zation of market orientation proposed above is positioned as the
operant resource that imbues the destinations’ core and supporting
resources with utility. Thus, while a DMO may not directly control

its core and supporting resource base, it can still deploy its fixed
operand resources, via its operant capabilities, in a strategically
competitive manner. The degree to which competitive advantage is
sustained, however, depends on the extent to which marketing
across stakeholders is a part of the DMO’s strategic posture. While
the essence of competitive advantage is still locked in the prover-
bial “black box” of RBV theory (Priem Butler, 2001; Sirmon, Hitt,
Ireland, 2007), prior research suggests that a more tangible
outcome of a given strategic orientation is the stock of strategic
assets the organization possesses (Greenley, Hooley, Rudd, 2005).
These assets are more difficult to develop but are also a more
powerful (and sustainable) source of competitive advantage. We
refer to these as relational market-based assets. In the following
sections we develop these market-based assets conceptually and
provide an operational structure for each.
2.4. Market-based assets
Like resources, assets “enable the firm to generate and imple-
ment its efficiency and effectiveness in the marketplace”
(Srivastava et al., 1998, p. 4). However, assets can be distinguished
from resources based on their relative complexity. In general, assets
are defined as bundles of resources and capabilities that can be
leveraged to gain competitive advantage (Srivastava et al., 2001).
Additionally, assets typically must be generated over a period of
time (Amit Schoemaker, 1993). Returning to Madhavaram and
Hunt’s (2007) hierarchy of resources, assets represent a higher-
level resource resulting from the combination of multiple
operand resources, CORs, and/or BORs over time; and the more
assets are bundled together, the more sustainable is the resultant
competitive advantage (Runyan, Finnegan, Gonzalez-Padron,
Line, 2013).
Returning to the opening discussion, Fig. 1 synthesizes the dis-
tinctions among a destination’s core/supporting operand resources,
operant resources/capabilities, and assets adopted in the current
research endeavor. As discussed, operand resources are assumed to
be heterogeneous across destinations. For destinations, such re-
sources may be tangible or intangible and include the natural/
historically based resource endowments of the destination; the
climate; the physical infrastructure; the local culture (particularly
its acceptance of visitors); and the individual skills and knowledge
of the tourism industry stakeholders in the destination. Although
these resources are beyond the direct control of the DMO, they can
still be leveraged to create competitive advantages when deployed
in tandem with the appropriate operant resource(s) (Madhavaram
Hunt, 2007). As seen in Fig. 1, the combination of customer, po-
litical, and industry orientations forms a composite operant
resource, and when this COR is deployed in coordination with a
destination’s operand resources, the result is a bundling of re-
sources and capabilities with a higher net potential for the con-
ference of sustainable competitive advantage. This is the definition
of a market-based asset.
Like resources and capabilities, assets can be grouped according
to the functional source of their origination (e.g., organizational,
financial, legal, marketing, etc.) (Hooley et al., 1998). Though a
number of asset categories have been identified, applications of
RBV in the field of marketing research have emphasized the
importance of market-based assets in particular. Market-based
assets represent a distinct type of strategic asset that “arise(s)
from the commingling of the firm with entities in its external
environment” (Srivastava et al., 1998, p. 2). Although these assets
are largely intangible, their rare and inimitable nature affords them
a potentially enhanced ability to facilitate a sustainable competitive
advantage. This potential is realized through the organization’s
ability to co-create value through stakeholder marketing via a
DMO’s marketing capabilities (i.e., a market orientation). These
capabilities can be seen as the “glue” that binds operand resources
together (Day, 1994) to ultimately form the more strategically
valuable market-based assets. When these core resources are
bound together in this way, the bundling effect provides the
foundation for a resource-based competitive advantage that may
otherwise not be achieved (Madhavaram Hunt, 2007).
2.5. Relational market-based assets
Relational market-based assets are defined as the “outcomes of
the relationship between a firm and key external stakeholders
including distributors, retailers, end customers, other strategic
partners, community groups and even government agencies”
(Srivastava et al., 1998, p. 5). Within the proposed framework, a
market orientation represents the antecedent condition on which
such “outcomes” are based, while relational market-based assets
represent the outcomes themselves. However, because (1) multiple
types of market-based assets exist (Hooley et al., 1998) and (2)
organizations vary in their orientations across stakeholder markets
(Greenley et al., 2005), three distinct types of market-based assets
are proposed (customer-based assets, industry-based assets, and
politically based assets) each of which is derived from a DMO’s
relationship with a specific stakeholder market.
2.5.1. Customer-based assets
Customer-based assets arise from positive relationships be-
tween an organization and its end-consumers or customers
(Greenley et al., 2005; Hooley et al., 1998). Accordingly, customer-
based marketing assets are often discussed under the auspices of
relationship marketing (Sheth, Sisodia, Sharma, 2000; Srivastava
et al., 2001). For example, Doyle’s (2001) examples of customer-
based marketing assets include market knowledge, brand aware-
ness, customer loyalty, and strategic relationships. Similarly, Urde
(1999) addresses the specific potential for a brand to be devel-
oped into a strategic asset. Taking a more fine-grained approach,
Greenley et al. (2005) distinguish customer-based assets such as
brand-awareness, firm reputation, and customer relationships from
alliance-based assets such as market access and access to strategic
partners’ resources.
Within the context of DMOs, customer-based assets such as
crafting a differentiable destination image (Hankinson, 2005) and
maintaining positive relationships with customers (Pike, Murdy,
Lings, 2011) are increasingly being attributed to what the present
research defines as market-oriented behaviors. Other desirable
customer-based assets such as loyalty and repeat visitation are also
likely to rely on the extent to which a DMO keeps up with changing
needs and preferences of its target markets (Pike et al., 2011). As
such, activities geared toward better understanding and satisfying
visitor needs likely play an important role in the development of a
sustained competitive advantage. Thus:
Proposition 1. Customer-based assets represent a unique set of
strategic marketing assets arising from the commingling of a DMO
with its visitor stakeholder markets.
2.5.2. Alliance-based assets
In contrast to customer-based marketing assets, alliance-based
marketing assets reflect relationships among the organizations
that make up what Sheehan et al. (2007) refer to as the destination
promotion triad (DMOs, industry suppliers, and local govern-
ments). In accordance with this framework, two types of alliance-
based marketing assets are proposed: industry-based assets and
politically based assets. While these specific types of alliance-based
assets are unique to destination marketing (Palmer Bejou, 1995),

they are, in many ways, analogous to existing conceptualizations of
alliance-based assets in the general business literature. For
example, Hooley et al. (1998) discuss alliance-based assets in terms
of networks and alliances. Such assets include market access,
knowledge sharing, and access to financial resources (Greenley
et al., 2005). Similarly, Kandemir, Yaprak, and Cavusgil (2006)
operationalize an alliance network performance construct. Unfor-
tunately, while these constructs have been validated in general
marketing contexts, neither construct sufficiently captures the
unique complexities of destination marketing.
Unlike customer-based marketing assets that can be attributed
to understanding customers and competitors, a DMO’s alliance-
based marketing assets arise out of interactions with its industry
and political stakeholders. As such, the destination promotion triad
(Sheehan et al., 2007) can be viewed as a de facto cross-sectional
alliance between the DMO, the local government, and the
tourism industry (also see Wang Xiang, 2007). Accordingly, each
DMO has two potential alliance partners and a distinct relationship
with each partner. These relationships are the basis for the devel-
opment of two types of alliance-based assets, one reflecting a
DMO’s relationship with its local government and another reflect-
ing its relationship with the local tourism industry.
Politically based assets refer to those assets that accrue to a DMO
as a result of the ability of its managers to maintain favorable re-
lationships with the politicians responsible for allocating tax dol-
lars to the organization. The degree to which a DMO successfully
markets itself to its community and the politicians who represent
that community can have a major impact on the level of political
support the DMO receives (Destination Travel Foundation
Revent LLC, 2011; Gretzel, Fesenmaier, Formica, O’Leary, 2006).
Without continuously communicating the value of their organiza-
tions to the local community/government, DMOs risk losing the
support of the politicians that fund their organizations (Destination
Marketing Association International Foundation Karl Albrecht
International, 2008; Gretzel et al., 2006). In addition to losing
funds, adverse government regulation and policy decisions can also
severely hamper a DMO’s ability to fulfill its mission (Ford Peeper,
2008). By contrast, with a strong advocacy platform, DMOs can help
to ensure that when funding and policy decisions are made, these
decisions are considered in terms of the potential impact on the
local tourism industry and the DMO. The importance of the political
stakeholder market to destination marketing suggests that:
Proposition 2. Politically based assets represent a unique set of
with its political stakeholder markets.
A second type of alliance-based marketing asset arises from the
commingling of the DMO with entities in the local tourism in-
dustry. Industry-based assets are defined here as those assets that
accrue to a DMO as a result of its ability to maintain favorable re-
lationships with and among local tourism businesses. In addition to
allying directly with its industry suppliers, DMOs must also facili-
tate a cooperative environment among the providers of their des-
tination’s tourism product (Fyall Garrod, 2005). According to a
2008 survey of DMO CEOs, building partnerships among local
stakeholders was one of the most commonly reported value
propositions that CEOs wanted to be associated with their organi-
zations (DMAIF Karl Albrecht International, 2008). Thus, for
DMOs the goal is not to ally with any one firm per se, but to promote
an atmosphere of cooperation among all tourism firms in its
jurisdiction by building a consensus for its value proposition. In
these terms, industry support for the firm’s mission can also be
seen as a type of alliance-based asset to the extent that the
numerous (and often competing) firms in the local tourism in-
dustry cooperate for the good of the destination as a whole. Thus:
Proposition 3. Industry-based assets represent a unique set of
with its industry stakeholder markets.
Together, Propositions 1e3 suggest the existence of a specific
and measurable set of assets that correspond to each of the primary
stakeholder markets toward which a DMO may be oriented. These
assets can be seen as the outcomes of a DMO’s ability to leverage
stakeholder relationships to act upon a destination’s operand re-
sources to create value and ultimately become a source of sus-
tainable competitive advantage. In order to develop a full nomology
of this process, however, an operational approach to the mea-
surement of these constructs is essential.
3. Methods
In order to test the propositions developed in the previous
section, three constructs were developed, each reflecting the assets
inherent to a specific stakeholder market. According to Churchill’s
(1979) methodology, the first step in the process for developing
marketing constructs is specification of a construct’s domain via an
in-depth review of the literature for the purposes of defining the
construct(s) of interest. Having specified the domain of strategic
destination marketing assets in the previous section, the remaining
steps in Churchill’s construct development process are discussed as
follows.
3.1. Generation of sample items
The second step in the construct development process is the
generation of a sample of items reflective of the phenomenon in
question as specified by its theoretical domain and corresponding
conceptual definition. Churchill (1979) provides several examples
of productive techniques for generating items including discussion
groups, expert interviews, and reviews of academic and practi-
tioner literature. All of these techniques were employed in the
operational explication of market-based assets. Table 1 provides a
description of the techniques used for item generation.
To begin, items reflective of customer- and alliance-based assets
were drawn from existing operationalizations of conceptually
similar constructs (e.g., Greenley et al.’s, 2005 operational classifi-
cation of marketing assets and Kandemir et al.’s, 2006 operation-
alization of alliance network performance). Each existing item was
reviewed for face validity as well as the degree to which its overall
structure was methodologically sound (e.g., no double-barreled
questions, ambiguous wording, etc.). The initially generated list of
items was then modified according to the process outlined in
Table 1. Because changes were made to the running list of items
reviewed in each successive step, the wording of items in the final
list was often quite different from the original source. However,
each time a modification was made, the new item was reviewed to
ensure that it still tapped the appropriate conceptual domain.
A particularly important part of the item generation phase was
the insights generated from conducting interviews with experts in
the field of destination marketing. In order to ensure that items
generated to measure the aforementioned latent constructs were
relevant to the practice of destination marketing (Lindell
Whitney, 2001), a series of interviews were conducted with DMO
managers and executives in a southeastern U.S. state for which
tourism is recognized as the second largest revenue producing in-
dustry. Participants (and interview content) were selected in
accordance with the tenets of theoretical sampling (Glaser, 1978) so
as to ensure a sufficiently broad representation of the phenomena
inherent to the proposed constructs. The interviews were semi-
structured and were conducted in the tradition of the long

interview (McCracken, 1988). When applicable, grand tour inter-
view techniques were also employed (Spradley, 1979). Interview
data were transcribed and subsequently analyzed to identify
recurring themes within each construct’s conceptual domain
(Strauss Corbin, 1998).
The interview data were then used to further modify the running
list of items and to determine the extent to which new items would
need to be added to each scale so as to sufficiently cover the
respective conceptual domains of each construct. For example,
while Greenley et al. (2005) was a logical starting point for gener-
ating items reflective of customer- and alliance-based marketing
assets, many of Greenley et al.’s (2005) original items were not
contextually valid to the domain of destination marketing. Their
operationalization of alliance-based assets, for example, includes
items measuring “access to strategic partner’s managerial know-
how and expertise” and “shared technology”, neither of which
appropriately reflect the domain of politically based assets in the
field of destination marketing. Because the existing items were
deemed theoretically irrelevant, it became necessary to develop
new items appropriate to the domain of destination marketing. By
attending to the emergent themes from the professional interviews,
new items could be crafted in such a way as to remain consistent
with the previously discussed conceptual domain of market-based
assets in general, and alliance-based assets in particular. This pro-
cess was followed for all three proposed constructs.
3.2. Pretest
The next step in the construct development process is to reduce
(or purify) the list of items generated in the previous steps via a
pretest of the questionnaire on a subset of the intended population
from which the final sample will be taken. In order to pilot test the
measures, a survey was posted in three discussion forums (the
Marketing Forum, the Research Forum, and the General Topics
Forum) on the website of the main trade organization for the
destination marketing industry, Destination Marketing Association
International (DMAI). Following the process outlined by Dillman,
Smyth, and Christian (2009), the opportunity to complete the
survey was posted three times with two week intervals between
postings. As an incentive to complete the survey, respondents were
given the opportunity to enter into a drawing to win a $200 Visa
gift card.
The pretest data were used to assess the internal consistency of
the measurement items and to test the factor structure of each
latent construct. Internal consistency was measured via an
assessment of Cronbach’s alpha, which measures how well a set of
generated items reflects a construct’s domain (Peter, 1979). The
reliability of individual measurement items was tested via an ex-
amination of the change in alpha when each item was deleted.
Items causing alpha to drop below .7 were reviewed for face validity
and, if deemed outside of the construct’s domain, were not
included in the final measurement instrument (Nunnally, 1967).
Upon establishing internal consistency for each construct, factor
analyses were conducted in order to assess the underlying factor
structure. Items reflective of each construct were analyzed via a
principal components analysis (PCA) with varimax rotation. The
results of this analysis were used to further reduce the potential
measurement items for each construct using the cutoff criteria
recommended by Hair, Black, Babin, Anderson, and Tatham (2006).
In total, six items were deleted. Of the remaining 21 items, 20 met
Hair et al.’s (2006) factor loading criteria for practical significance
(.5). The sole item not meeting this criterion met the minimum
standard for inclusion (.3). Following the initial reduction, a second
PCA was then conducted, resulting in a three-factor solution
explaining 55.5% of the variance in the model. Upon completion of
the pretest data analysis, the purified list of items was then
compiled into a new survey instrument to be used in final stage of
data collection.
3.3. Data collection
Like the data collected for the pretest, the data used for prop-
osition testing were collected from a sample of destination mar-
keting executives and managers. However, unlike the pretest, data
used for testing the propositions were collected via a mail survey
(see Dillman et al., 2009). The list of measurement items were
organized into a hard-copy survey, and mailed to sample of 600
DMO executives in 28 randomly selected U.S. states along with a
self-addressed, postage-paid return envelope. The sample was
drawn from a database of 1200 U.S.-based DMOs of varying size and
organizational structure. Due to resource constraints, only half the
database was sampled. Rather than spreading out the 600 sampled
organizations across all 50 states, 25 states were randomly selected,
and the DMOs from those states in the database were included in
Table 1
Domain specification and item generation.
Technique Description Outcome
Lit. review: Academic Numerous scholarly articles reviewed in the fields of marketing, strategy,
management, and tourism
Domain specification
Lit. review: Trade and Industry Numerous industry handbooks reviewed including: DMAI Advocacy Toolkit;
2008 DMAI survey of DMO CEOs; DMAI Standard Performance Reporting
Handbook; Yearly profile reports of DMOs
Domain specification
Review of existing scales Items from existing scales reviewed for face validity within the context of
specified domains. When necessary, existing items were adapted so as
to reflect each construct as specified
Item generation
Discussion group One marketing professor and four Ph.D. candidates reviewed the initial list
of items for face validity, structure, and relevance to specified domain
Items revised; Items added
Discussion group New list reviewed based on input from first discussion group and additional
review of literature
Items revised
Expert interview First depth interview conducted with a destination marketing professional
(25 years experience)
Expert review of items List of items compiled into survey form: Two destination marketing professionals
at the 2011 NTA conference were asked to take this survey and provide verbal
interpretations of the items as they responded
Discussion group Survey modified based on expert feedback and resubmitted to discussion group Items revised
Expert interviews Seven additional interviews conducted per process outlined in body of text Items revised; Items added
Pretest Internet survey consisting of all generated items. Posted in 3 DMAI discussion
board forums (n ¼ 27).
Items revised; Items deleted

the sample. Because the total number of organizations in the 25
state sampling frame did not reach the full 600 organizations
sought for this study, additional states were added to the sample
until the total number of organizations reached 600. This brought
the total number of states sampled to 28.
Because the unit of analysis for this research is the organization,
only one respondent per organization was asked to complete the
survey. As an incentive to complete the survey, a newly minted $1
gold coin was affixed to the cover letter explaining the survey
process. Additionally, participants were given the option to request
an executive summary of the findings. A total of 106 surveys were
returned in the two weeks following the initial mailing (17.7%
response rate).
The initial mailing was followed by two subsequent mailings.
Two weeks after the first survey was mailed, a follow-up postcard
was sent to non-respondents reminding them of the opportunity to
participate in the research and advising them that another copy of
the survey would be mailed to them in two weeks time. In response
to the postcard mailing, another 54 responses were received. Two
weeks after the postcard was sent, a second copy of the survey and
a modified cover letter were mailed to the remaining non-
respondents. The new cover letter indicated that no future mail-
ings would be received. In the four weeks following the final
mailing, 62 responses were received bringing the respondent total
to 222 (for an overall response rate of 37.0%). Information per-
taining to the respondents and their organizations can be seen in
Table 2.
Because of the rigor of the data collection process, missing data
in returned questionnaires was extremely rare. Of the 3774 relevant
points of data returned, only 10 entries were missing. Because
missing values represented a mere .002% of the data collected,
missing values were imputed according to the series mean.
3.4. Common method biases
Throughout the scale development and data collection pro-
cesses, care was taken to minimize the potential effects of mea-
surement error attributable to the methodology and not the true
participant scores of the latent phenomena under investigation.
First, several techniques were employed to minimize the incidence
of common rater effects (Podsakoff, MacKenzie, Lee, Podsakoff,
2003). The survey length was kept to a minimum to reduce the
potential effects of transient mood states. Potential acquiescence
issues were addressed by inserting reverse coded items into the
survey to ensure that respondents would not simply revert to
“agreeing” with questions before carefully reading item content
(Dillman et al., 2009; Podsakoff et al., 2003).
Second, care was taken to reduce biases resulting from specific
properties of the items themselves. Most importantly, each item
was carefully constructed based on the content of the expert in-
terviews discussed in the previous section. This process helped to
ensure that the content of each item was presented in an unam-
biguous manner and expressed in terminology appropriate to the
population of interest (Lindell Whitney, 2001). Additionally, each
section of the questionnaire began with an identification of key
terms relevant to each item block to further achieve a maximum
level of item comprehension on behalf of the respondent (Lindell
Whitney, 2001).
A final source of potential bias inherent to all forms of sample-
based data collection is attributable to the possibility that those
who respond to a survey are significantly different than those who
do not respond. The data collection process was designed so that an
estimate of non-response bias could be obtained (Armstrong
Overton, 1977). Each time a survey was returned, the response
was immediately coded relative to the corresponding data collec-
tion round (i.e., each response was coded as either a one, a two, or a
three). These groups were then used to conduct a series of inde-
pendent sample t-tests to determine the extent to which the means
of early respondents were significantly different than those of the
later respondents. These tests were conducted for all observed
variables.
With respect to the three respondent groups, all pairwise
comparisons were analyzed. First, response group one was
compared with response group two. Finding no significant differ-
ence between these two groups (p .05), response group two was
then compared with response group three. Again, no significant
differences were identified in the mean structure between the two
respondent groups (p .05). Finally, response group one was
compared with response group three (a between-group response
lag of one month). The differences between these two groups were
also insignificant across all variable comparisons (p .05). The
failure to identify significant differences across the respondent
categories suggests that the incidence of non-response bias in the
data collection process was minimized.
3.5. Results
The data collected in the final sample were submitted to checks
of both reliability and construct validity. Upon establishing internal
consistency of the measures (Cronbach’s a), confirmatory factor
analyses (CFAs) were conducted in order to verify the factor
structure of each construct and to assess convergent and discrim-
inant validity. In the first step of the analysis, all constructs were
subjected to individual CFAs. For each first-order construct, an
initial CFA was conducted with all measurement items specified as
Table 2
Organizational/respondent information.
Characteristic n %
Destination description
Single city 73 33.0
All cities in a single county 89 40.3
Selected cities in a single county 23 10.4
A multiple county region 33 14.9
No response 5 2.3
Business models/governance structures
Government body 55 24.9
Government/private co-venture 37 16.7
Government funding plus paying members 63 28.5
Member supported with no government funds 11 5.0
Other 50 22.6
No response 7 3.2
Conference or convention center in destination
No 99 44.8
Currently planning/building one 7 3.2
Yes, but not managed by our DMO 90 40.7
Yes, managed by our DMO 21 9.5
No response 6 2.7
Full-time employees
0e5 114 51.6
6e10 47 21.3
11e15 19 8.6
16e35 21 9.5
36 or more 13 5.9
No response 9 4.1
Respondent role in DMO
CEO/President/Executive Director 174 78.7
Other 41 18.6
No response 8 3.6
State Breakdown: AL-5, FL-2, GA-12, MN-7, MO-9, MS-5, MT-4, NC-12, ND-5, NE-3,
NJ-1, NM-1, NV-3, NY-7, OH-21, OK-7, OR-22, PA-18, SC-4, SD-3, TN-11, TX-24, UT-1,
VA-12, WA-1, WI-8, WV-10, WY-1.

reflective indicators of the proposed latent factor. Based on the
overall fit and analyses of the standardized regression estimates,
items were deleted from each specification in a stepwise manner to
identify the effect of the omitted items on the fit of the model. Each
time an item was deleted, a chi-square difference test was con-
ducted to assess changes in model fit resulting from the inclusion/
omission of that item. When the deletion of an item resulted in a
significant increase in model fit, the better fitting model was
adopted, and the omitted item was not included in subsequent
analyses. As a result of this final purification, a further 8 items were
omitted from further analysis. The resulting factor structure along
with the means and standard deviations of the final set of mea-
surement items can be seen in Table 3.
Next, in order to test for full construct validity (i.e., convergent
and discriminant validity), average variance extracted (AVE) was
calculated in the manner advocated by Fornell and Larcker (1981).
Table 4 shows the critical ratio (CR), AVE, maximum shared squared
variance (MSV), and average shared squared variance (ASV) for
each construct. The correlation matrix (with the square root of AVE
on the inter-construct diagonal) is also provided. For all variables,
CR AVE 0.5, providing strong evidence of convergent validity
for each construct in the model (Hair et al., 2006). Additionally, the
AVE for each construct is greater than both the ASV and MSV with
no two constructs correlating over .5. These results provide strong
evidence of discriminant validity among the constructs (Hair et al.,
2006).
Finally, in order to test the overall proposition that all three first-
order constructs are reflective of the same underlying latent factor,
a second-order market-based assets construct was specified. The
second-order specification included a total of 32 parameters. Using
Kline’s (2005) convention of a minimum of 5e6 observations per
parameter, the size of the data sample (n ¼ 222) is likely not a
source of bias in either the second-order specification or the
measurement model that was specified to calculate AVE. The
second-order specification (a ¼ .85), was a relatively good fit to the
data (c2
¼ 129.7, df ¼ 62 [c2
/df (CMIN) ¼ 2.093]; RMSEA ¼ .071;
CFI ¼ .947; TLI ¼ .933) with all standardized regression estimates
significant (p .001) and positive as proposed.
In summary of the results, the analysis of data collected from
more than 220 DMO’s with widely varying organizational charac-
teristics suggests that a unique set of stakeholder-based destination
marketing assets exists across the organizational spectrum. The
empirical support for the proposition of this construct and its
dimensional structure has the potential to affect both the theory
and practice of destination marketing in several important ways. In
the following section, potential implications of these findings are
discussed.
4. Discussion
In a general sense, the value of this research lies in the inte-
gration of RBV’s exogenous notion of value creation with the
endogenous notion of competitive advantage championed by the
proponents of stakeholder marketing and the service-dominant
logic. However, our research makes a more specific contribution
to tourism scholarship by situating the explanation of this theo-
retical intersection within the unique contexts of the destination
marketing environment. Thus, perhaps most importantly, this
research can be seen as a starting point for the further exploration
of these well-established theoretical frameworks within the
domain of destination marketing. As follows, we discuss the im-
plications of such a trajectory for tourism scholarship providing
examples of potentially important avenues for future research.
The most significant contribution of this research is the devel-
opment of a new construct for the empirical investigation of both
RBV- and SBL-based conceptual frameworks from a tourism
perspective. Currently, the dearth of empirically measurable
organization-level constructs in the field of destination marketing
research has rendered the formation of strategically based
construct nomologies essentially impossible; and because the
advancement of theory rests on the development of sound con-
structs (Summers, 2001), the absence of quantitatively measurable
constructs has hindered the progression of tourism theory. Con-
trasting this to the abundance of organizational constructs found in
the management and marketing literature and the theoretical
Table 3
Measurement scale properties: first-order specifications.
Constructs and indicators Mean Std. dev. Std. est. p
Customer-based assets (CBA) (a ¼ .86) 5.17 1.27 a
1.69 b
.056
CBA1: Our destination has a distinct brand image. (c
.684) 5.43 1.62 0.74 .001
CBA2: Our destination’s brand is an important part of the reason that organized groups come to our area. (c
.737) 4.83 1.64 0.83 .001
CBA3: Our destination’s brand is an important part of the reason that independent travelers come to our area. (c
.810) 5.23 1.64 0.91 .001
CBA4: Our community is a well-established tourism destination. (c
.641) 4.66 1.73 0.67 .001
CBA5: Upon visiting our destination, independent visitors are likely to revisit our destination in the future. (c
.544) 5.70 1.23 0.57 .001
Industry-based assets (IBA) (a ¼ .81) 5.04 1.12 a
.90 b
.000
IBA1: The local tourism industry appreciates our organization’s contribution to the local economy. (c
.541) 5.78 1.19 0.60 .001
IBA2: Tourism businesses in our destination cooperate with each other to access new markets. (c
.662) 4.45 1.50 0.75 .001
IBA3: Tourism businesses in our destination share a common vision for our destination. (c
.706) 4.79 1.52 0.82 .001
IBA4: Tourism businesses in our destination share a commitment to providing quality customer service. (c
.602) 5.14 1.39 0.68 .001
Politically based assets (PBA) (a ¼ .84) 4.93 1.32 a
1.93 b
.065
PBA1: Funding our organization is a priority for our politicians. (c
.544) 3.95 1.81 0.58 .001
PBA2: The local government appreciates our organization’s contribution to the local economy. (c
.718) 5.59 1.46 0.84 .001
PBA3: The local government understands the importance of tourism to our local economy. (c
.731) 5.39 1.54 0.84 .001
PBA4: Our local government considers the impact that new legislation may have on our organization’s
ability to achieve its mission. (c
.704)
4.80 1.61 0.78 .001
a
c2
/df.
b
RMSEA.
c
Corrected item-total correlation.
Table 4
Validity assessment criteria and correlation matrix.
CR AVE MSV ASV PBA IBA CBA
PBA 0.867 0.569 0.219 0.128 0.754a
IBA 0.812 0.522 0.219 0.186 0.468 0.722a
CBA 0.865 0.568 0.154 0.096 0.194 0.392 0.754a
a
Square root of AVE.

advancements that have been achieved via their empirical mea-
surement, it is likely that tourism research could gain from the
development of a similar bevy of valid and reliable organizational
constructs. Operationally defining market-based assets is a first
step in this direction.
In addition to the intrinsic theoretical value of this research, the
development of marketing- and management-based tourism con-
structs (such as the market-based assets construct conceptualized in
this research) would also contribute to practical destination mar-
keting. As previously discussed, destination marketers are increas-
ingly searching for ways to remain both relevant and competitive in
the contemporary marketing environment (DMAIF Karl Albrecht
International, 2008; Gretzel et al., 2006). The development of a
unique theory of destination marketing, replete with measurable
constructs and empirically testable hypotheses, would provide
distinctive insight intothese issues and their potential solutions. The
present research suggests that the classical notions of firm perfor-
mance espoused in the resource-based view of the firm combined
with the contemporary perspectives of the service-dominant logic
and stakeholder marketing are a worthwhile place to start.
In terms of strategic planning, the connection between operand
and operant resources advocated in this research suggests that
DMOs should focus on creating higher order, composite operant
resources. Because the creation of sustainable competitive advan-
tages is a complex inter-organizational process, all members of the
destination promotion triad (Sheehan et al., 2007) should recognize
that many operand resources within a tourist destination are
neither rare nor unique enough to endow competitive advantage in
isolation. As such, stakeholders must allow (and provide support
for) the DMO to acquire and develop its own composite resource
base. These may take the form of knowledge, skills, organizational
culture, or experience.
Additionally, the market-based assets scale may serve as a tool
for DMOs to measure their own success in creating the sort of
composite operant resources that can imbue independently owned
operand resources with utility. Similarly, this instrument could be
used to identify areas of potential improvement when it comes to
stakeholder marketing. For example, if a destination is unsuccess-
fully competing with another destination on the same type operand
resource base (e.g., sun and sand), could an enhanced political
orientation potentially be a way to address this competitive imbal-
ance? Would a stronger set of political market-based assets help to
get a bond issue through to improve local infrastructure? Or, would a
stronger set of industry-based assets, characterized by collaborative
marketing initiatives, increase demand for the destination?
In sum, our theoretical framework demonstrates how previously
identified issues within the destination marketing literature, often
portrayed as separate and difficult to connect, can (and should) be
connected from a strategic perspective. In terms of the RBV, the
destination resources controlled by privately owned hospitality and
tourism firms are not necessarily valuable in the aggregate. In order
for a destination to be successful, DMOs must leverage these re-
sources appropriately. Likewise, in terms of the SDL, our framework
suggests that the successful DMO is one that can bring to bear its
operant resources to leverage those operand resources it does not
control. Our research provides destination marketers with a
framework and an operational approach to this process.
With an operationalized scale to measure market-based assets,
scholars may now conduct empirical research into causal re-
lationships ex ante and post hoc acquisition and/or deployment of
these assets. Understanding these relationships would help to
answer a number of important questions raised by the present
research. For example, concerning leadership, does changing di-
rectors and/or overall strategic focus towards a market orientation
lead to stronger alliances with tourism-focused firms and thus
improved performance? Are some market-based assets more
important than others in maintaining the relationships inherent to
the destination promotion triad? How does the deployment of (for
example) political market-based assets affect performance when
deployed in conjunction with weak customer market-based assets?
Can highly developed DMO-level operant resources make up for
less highly refined (or weaker) operand resources at the destination
or firm levels? We believe that these are all research questions
heretofore not empirically addressable, but are now quantifiable
via the market-based asset scale developed herein.
4.1. Limitations
One of the most significant limitations of this study is that while
the analyses suggest preliminary evidence of convergent and
discriminant validity, we stop short of assessing the nomological
validity of the market-based assets construct. Recalling Fig. 1, the
implications of the proposed RBV- and SDL-based framework are
that market-based destination marketing assets result from a
market-oriented approach to destination marketing and are ante-
cedent to organizational performance. However, these are propo-
sitions that must be formally hypothesized and empirically tested.
Thus, an essential area of future research is the exploration of these
and other constructs that either affect or are affected by a DMO’s
market-based asset structure. Such research would lend strength to
the construct from a validity standpoint as well as contribute to the
continued advancement of tourism theory.
A second limitation of this research is attributable to sample
population. Because the scope of this research includes only city-
and county-level destination marketing organizations, the con-
structs developed herein should not be unduly generalized outside
of these contexts. That is, while the measurement items are content
valid within the context of the sample population, these items may
need to revised, and the construct dimensionality reviewed, before
considering the phenomenon at a state or national level. Addi-
tionally, because DMOs vary in roles and organizational structure
internationally, the constructs developed in this research should be
tested for cross-cultural measurement invariance before they are
applied outside of the United States.
4.2. Conclusion
The purpose of this research was to enhance extant perspectives
of destination competitiveness by considering destination mar-
keting from the dual theoretical lenses of the service-dominant
logic and the resource-based view of the firm. The result was the
development of a multidimensional construct reflecting the oper-
ant nature of strategically valuable destination marketing re-
sources. Although the present endeavor represents only a small
step toward a more complete theoretical understanding of desti-
nation marketing, it is the hope of the researchers that this
contribution will stimulate further consideration of the importance
of construct development in this process.
Acknowledgement
The authors would like to thank Dr. Youcheng Wang for his
assistance in the data collection phase of this project.
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Nathan Line (nline@fsu.edu) is an assistant professor in the
Dedman School of Hospitality at Florida State University. His
primary research interests include collaborative destination
marketing and stakeholder engagement. These interests
have led him to become increasingly interested in the im-
plications of stakeholder marketing for sustainable desti-
nation management.
Rodney C. Runyan (rcr56@txstate.edu) is Professor and
Director of the School of Family and Consumer Sciences,
Texas State University, and Visiting Professor of Marketing
at Lancaster University. His primary research areas are
strategy, research methodology, and entrepreneurship.
These interests include investigating how entrepreneurial
strategies impact tourist destinations.

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