Destination marketing and the service-dominant logic: A resource-based operationalization of strategic marketing assets

Tourism Management 43 (2014) 91e102

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Tourism Management journal homepage: www.elsevier.com/locate/tourman

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 Texas State University, School of Family and Consumer Sciences, 101 FCS Building, San Marcos, TX 78666, USA c Lancaster University Management School, UK b

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

a b s t r a c t

Article history: Received 20 September 2013 Accepted 28 January 2014

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 servicedominant 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.

Keywords: Destination marketing The resource-based view of the firm Service-dominant logic Stakeholder marketing Strategic assets

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

* Corresponding author. Tel.: þ1 850 645 2710; fax: þ1 850 644 5565. E-mail addresses: [email protected] (N.D. Line), [email protected] (R.C. Runyan). 1 Tel.: þ1 512 245 2155; fax: þ1 512 245 3829. http://dx.doi.org/10.1016/j.tourman.2014.01.024 0261-5177/Ó 2014 Elsevier Ltd. All rights reserved.

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

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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 resources. 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 destination 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 threefold: First, we draw a series of parallels among the servicedominant logic of marketing (Vargo & Lusch, 2004), the stakeholder marketing movement (Bhattacharya & Korschun, 2008; Gundlach & Wilkie, 2010), and the resource-based view of the firm to propose a hierarchical classification of destination resources. Second, we explain the dynamic relationships among the resources within the proposed hierarchy. Finally, we provide support 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 literatures. From the management literature we utilize the resourcebased view of the firm (Barney, 1991) to provide a general framework 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 resources) 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 (organizations) 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 efficiently 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 nonsubstitutable (Barney, 1991). Despite the acceptance of RBV within the strategic management literature as a viable framework for explaining organizational performance (Crook, Ketchen, Combs, & Todd, 2008), the theory receives 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.

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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 contemporary perspectives pertaining to the nature and scope of marketing thought. Of particular consequence in making the theoretical link between RBV and SDL is the distinction among several types of resources. 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 operant 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 promotes the importance of intangible resources, stakeholder relationships, 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 parameters 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 destination 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 interactions 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 corresponding 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

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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 exception). 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 management perspective and, perhaps more importantly, at the organizational level. A second limitation to the contemporary perspective of destination 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 resources 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 imperfectly 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 between operand and operant resources (Vargo & Lusch, 2004), as well as among hierarchical levels of the operant resources themselves (Madhavaram & Hunt, 2007). Unfortunately, while the organization 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 classification 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 nature. 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 resourcebased 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 destination’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

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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 coordinate 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 servicedominant logic suggest that (1) fundamental differences exist between the (operand) destination resources that lie outside the control of a DMO and the (operant) destination management resources/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 subsequent 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 acknowledges the role of non-market stakeholders in the co-creation of value (Lusch, 2007; Lusch & Webster, 2011). Accordingly, proponents of the “stakeholder marketing movement” (Gundlach & Wilkie, 2010) have called for a more direct consideration of stakeholder 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 cocreated 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 resourcebased 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 creation 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 position 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 stakeholders: 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 competitiveness 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 resources 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 relatively 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 stakeholder 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 conceptualization 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

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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 proverbial “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 implement 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 higherlevel 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 distinctions 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 resources 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, political, 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 resources and capabilities with a higher net potential for the conference 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

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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 between an organization and its end-consumers or customers (Greenley et al., 2005; Hooley et al., 1998). Accordingly, customerbased 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 customerbased marketing assets include market knowledge, brand awareness, customer loyalty, and strategic relationships. Similarly, Urde (1999) addresses the specific potential for a brand to be developed 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 governments). In accordance with this framework, two types of alliancebased 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),

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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. Unfortunately, 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 alliancebased 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 development of two types of alliance-based assets, one reflecting a DMO’s relationship with its local government and another reflecting 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 relationships with the politicians responsible for allocating tax dollars 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 organizations 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 strategic marketing assets arising from the commingling of a DMO 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 industry. Industry-based assets are defined here as those assets that accrue to a DMO as a result of its ability to maintain favorable relationships with and among local tourism businesses. In addition to allying directly with its industry suppliers, DMOs must also facilitate a cooperative environment among the providers of their destination’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 organizations (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 industry cooperate for the good of the destination as a whole. Thus:

Proposition 3. Industry-based assets represent a unique set of strategic marketing assets arising from the commingling of a DMO 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 resources to create value and ultimately become a source of sustainable competitive advantage. In order to develop a full nomology of this process, however, an operational approach to the measurement 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 practitioner 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 classification of marketing assets and Kandemir et al.’s, 2006 operationalization 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 industry. 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 semistructured and were conducted in the tradition of the long

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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 Numerous industry handbooks reviewed including: DMAI Advocacy Toolkit; 2008 DMAI survey of DMO CEOs; DMAI Standard Performance Reporting Handbook; Yearly profile reports of DMOs 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 One marketing professor and four Ph.D. candidates reviewed the initial list of items for face validity, structure, and relevance to specified domain New list reviewed based on input from first discussion group and additional review of literature First depth interview conducted with a destination marketing professional (25 years experience) 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 Survey modified based on expert feedback and resubmitted to discussion group Seven additional interviews conducted per process outlined in body of text Internet survey consisting of all generated items. Posted in 3 DMAI discussion board forums (n ¼ 27).

Domain specification

Lit. review: Trade and Industry

Review of existing scales

Discussion group Discussion group Expert interview Expert review of items

Discussion group Expert interviews Pretest

interview (McCracken, 1988). When applicable, grand tour interview 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 generating 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 knowhow 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 process was followed for all three proposed constructs.

Domain specification

Item generation

Items revised; Items added Items revised Items revised; Items added Items revised; Items added

Items revised Items revised; Items added Items revised; Items deleted

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 examination 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.

3.2. Pretest 3.3. Data collection 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.

Like the data collected for the pretest, the data used for proposition testing were collected from a sample of destination marketing 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

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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 nonrespondents. The new cover letter indicated that no future mailings 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 pertaining 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

Table 2 Organizational/respondent information. Characteristic

n

%

Destination description Single city All cities in a single county Selected cities in a single county A multiple county region No response

73 89 23 33 5

33.0 40.3 10.4 14.9 2.3

Business models/governance structures Government body Government/private co-venture Government funding plus paying members Member supported with no government funds Other No response

55 37 63 11 50 7

24.9 16.7 28.5 5.0 22.6 3.2

Conference or convention center in destination No Currently planning/building one Yes, but not managed by our DMO Yes, managed by our DMO No response

99 7 90 21 6

44.8 3.2 40.7 9.5 2.7

Full-time employees 0e5 6e10 11e15 16e35 36 or more No response

114 47 19 21 13 9

51.6 21.3 8.6 9.5 5.9 4.1

Respondent role in DMO CEO/President/Executive Director Other No response

174 41 8

78.7 18.6 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.

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 processes, care was taken to minimize the potential effects of measurement 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 interviews discussed in the previous section. This process helped to ensure that the content of each item was presented in an unambiguous 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 samplebased 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 collection 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 independent 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 difference 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 discriminant 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

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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 conducted 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 measurement 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 firstorder 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 characteristics suggests that a unique set of stakeholder-based destination marketing assets exists across the organizational spectrum. The

99

Table 4 Validity assessment criteria and correlation matrix.

PBA IBA CBA a

CR

AVE

MSV

ASV

PBA

IBA

CBA

0.867 0.812 0.865

0.569 0.522 0.568

0.219 0.219 0.154

0.128 0.186 0.096

0.754a 0.468 0.194

0.722a 0.392

0.754a

Square root of AVE.

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 integration 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 theoretical 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 implications 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 development 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 constructs (Summers, 2001), the absence of quantitatively measurable constructs has hindered the progression of tourism theory. Contrasting 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

a

1.69 0.74 0.83 0.91 0.67 0.57

b .056 <.001 <.001 <.001 <.001 <.001

a .90 0.60 0.75 0.82 0.68

b .000 <.001 <.001 <.001 <.001

Customer-based assets (CBA) (a ¼ .86) CBA1: Our destination has a distinct brand image. (c.684) CBA2: Our destination’s brand is an important part of the reason that organized groups come to our area. (c.737) CBA3: Our destination’s brand is an important part of the reason that independent travelers come to our area. (c.810) CBA4: Our community is a well-established tourism destination. (c.641) CBA5: Upon visiting our destination, independent visitors are likely to revisit our destination in the future. (c.544)

5.17 5.43 4.83 5.23 4.66 5.70

1.27 1.62 1.64 1.64 1.73 1.23

Industry-based assets (IBA) (a ¼ .81) IBA1: The local tourism industry appreciates our organization’s contribution to the local economy. (c.541) IBA2: Tourism businesses in our destination cooperate with each other to access new markets. (c.662) IBA3: Tourism businesses in our destination share a common vision for our destination. (c.706) IBA4: Tourism businesses in our destination share a commitment to providing quality customer service. (c.602)

5.04 5.78 4.45 4.79 5.14

1.12 1.19 1.50 1.52 1.39

Politically based assets (PBA) (a ¼ .84) PBA1: Funding our organization is a priority for our politicians. (c.544) PBA2: The local government appreciates our organization’s contribution to the local economy. (c.718) PBA3: The local government understands the importance of tourism to our local economy. (c.731) PBA4: Our local government considers the impact that new legislation may have on our organization’s ability to achieve its mission. (c.704)

4.93 3.95 5.59 5.39 4.80

1.32 1.81 1.46 1.54 1.61

a b c

c2/df. RMSEA. Corrected item-total correlation.

a

1.93 0.58 0.84 0.84 0.78

b .065 <.001 <.001 <.001 <.001

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advancements that have been achieved via their empirical measurement, 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 constructs (such as the market-based assets construct conceptualized in this research) would also contribute to practical destination marketing. As previously discussed, destination marketers are increasingly 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 into these issues and their potential solutions. The present research suggests that the classical notions of firm performance 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 advantages 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 unsuccessfully 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 imbalance? 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 resources 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 relationships 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 directors 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 antecedent to organizational performance. However, these are propositions 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 cityand county-level destination marketing organizations, the constructs 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. Additionally, 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 marketing 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 operant nature of strategically valuable destination marketing resources. Although the present endeavor represents only a small step toward a more complete theoretical understanding of destination 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. References Amit, R., & Schoemaker, P. J. H. (1993). Strategic assets and organizational rent. Strategic Management Journal, 14(1), 33e46. Armstrong, J. S., & Overton, T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14(3), 396e402. Bagozzi, R. P. (1975). Marketing as exchange. Journal of Marketing, 39(4), 32e39.

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N.D. Line, R.C. Runyan / Tourism Management 43 (2014) 91e102 Nathan Line ([email protected]) 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 implications of stakeholder marketing for sustainable destination management.

Rodney C. Runyan ([email protected]) 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.