Market-Oriented Destination Marketing

Abstract

As competition among destinations has intensified, researchers have increasingly advocated for a market-oriented approach to destination marketing. Unfortunately, the unique stakeholder structure of the destination marketing environment precludes a direct application of the traditional market orientation paradigm to this domain. Accordingly, the purpose of this research is to empirically develop an operational definition of the market orientation construct that can be applied to destination marketing organizations. Based on the tenets of stakeholder theory, this research proposes a multiple-stakeholder view of the marketing concept and develops its attendant operational construct. Referred to herein as a multistakeholder market orientation (MSMO), this construct is proposed and operationalized as reflective of the extent to which a destination marketing organization (DMO) implements the marketing concept across the stakeholder spectrum. The nomological validity of this construct is established by testing the effect of the proposed MSMO construct on DMO performance.

Keywords

destination marketing market orientation stakeholder theory construct development

Introduction

The contention that firms must identify and satisfy customer needs more effectively than their competitors has long been a hallmark of the marketing concept (Drucker 1954). Market orientation is conceptualized as the extent to which a firm capitalizes on this process (Day 1994; Kohli and Jaworski 1990; Narver and Slater 1990). Over the last two decades, the development of a market orientation has been a core concept in marketing strategy and has consistently been demonstrated to positively affect organizational performance across a number of industry- and firm-specific conditions (see Liao et al. 2011). Additionally, multiple meta-analytic studies support the contention that a market orientation is a critical determinant of organizational performance (e.g., Cano, Carrillat, and Jaramillo 2004; Kirca, Jayachandran, and Bearden 2005).

Despite widespread consideration of the importance of a market orientation across a number of industry and firm types (Liao et al. 2011), very little research has been conducted concerning its potential application to destination marketing organizations (DMOs). Unfortunately, because the market orientation phenomenon has yet to be addressed within this context, effective implementations of market-oriented practices within the DMO have been slow (Pike 2004). Nonetheless, the changing communication landscape (Ford and Peeper 2007), the increasing need for customer engagement (King 2002), shrinking budgets (Williams, Stewart, and Larson 2011), and the threat of new sources of competition (Gretzel et al. 2006) have led to increasing calls for a market-oriented approach to destination marketing (e.g., Line and Runyan 2014).

Recognizing these issues, Bieger, Beritelli, and Laesser (2009) argue that, in order to successfully adapt to the current marketplace, DMOs must “transform themselves into modern, market-oriented service centers” (p. 309). But what is market-oriented destination marketing? Is it sufficient to say that destination marketers should simply be customer- and competitor-focused as the traditional paradigm suggests? Or do the complexities of the destination marketing function compel a deeper understanding of what it means to implement the marketing concept in this environment?

Interestingly, although the importance of a market-oriented approach to destination marketing has been tacitly acknowledged (e.g., Fyall and Garrod 2005; Line and Runyan 2014; Medlik and Middleton 1973; Pike 2004; Ritchie 1996), an overt account of this construct is conspicuously absent in the tourism literature. Because existing conceptualizations of a market orientation focus exclusively on customer and, to a lesser extent, competitor engagement (Kohli and Jaworski 1990; Narver and Slater 1990), ignoring other potentially important organizational stakeholders (Ferrell et al. 2010), we propose that the current conceptual approaches to the market orientation phenomenon are not generalizable to the multistakeholder destination marketing environment. Thus, while there has been increasing interest in the manifestation of the market orientation construct in the field of destination marketing, an integrative account of the operational structure of this construct is nonexistent.

This is not to say that scholars have ignored the importance of stakeholder management in the destination marketing literature. In fact, a number of studies have endeavored to provide an account of the salient actors in the destination marketing environment (e.g., visitors, tour groups, industry constituents, political/governing entities, and competitors) (see Park, Lehto, and Morrison 2008; Sheehan and Ritchie 2005). Likewise, research has been conducted concerning the extent to which DMOs are strategically oriented toward such stakeholders. For example, Pike, Murdy, and Lings (2011) explored the concept of a visitor relationship orientation (see also Murdy and Pike 2012), while d’Angella and Go (2009) considered the extent to which DMOs implement the marketing concept within the context of tourism industry stakeholders. Similarly, Sheehan, Ritchie, and Hudson (2007) considered this phenomenon within the context of destination governance. Taken together, such research has identified numerous stakeholder markets toward which a DMO may (or may not) be oriented. Unfortunately, no construct exists to measure the extent to which DMOs engage in what Buhalis (2000) refers to as balancing the strategic objectives of these stakeholders.

The lack of an integrative construct to measure the market orientation phenomenon within the context of destination marketing is of potential concern given Line and Runyan’s (2014) contention that a market-oriented approach to stakeholder management is essential to the development of strategic assets and sustainable competitive advantage. Moreover, the recent emphasis on collaborative destination marketing (e.g., Fyall and Garrod 2005; Pike and Page 2014; Wang and Xiang 2007; Wang and Krakover 2008) suggests the increasing need for the identification (and operationalization) of a construct that captures the extent to which DMOs adhere to and implement the marketing concept across the stakeholder spectrum. Pike and Page (2014) put forth precisely this sentiment in their recent critique of the extant literature on collaborative destination marketing strategy. Their assessment of this topic suggests that “what has been lacking to date is the development of a comprehensive model drawing together the key themes [of collaborative strategy], with which to guide practitioners through the minefield that is the attempted implementation of altruistic collaborative strategies with the myriad of stakeholders holding differing vested interests” (p. 211).

We suggest that one reason that such a model is nonexistent is that the constructs inherent to such a model have not been explicitly conceptualized and/or operationalized. As such, the purpose of this research is to propose and operationalize a conceptualization of the market orientation construct within the specific context of the destination marketing environment. We refer to this construct herein as a multistakeholder market orientation (MSMO). Within the context of destination marketing, MSMO is defined as a set of organizational behaviors reflective of an organization-wide commitment to total value creation by (1) understanding and reacting to the needs of salient stakeholder markets and (2) generating and communicating relevant information across those markets. Using Churchill’s (1979) method for developing marketing constructs, a multidimensional conceptualization of MSMO is proposed and empirically validated using data collected from a sample of small to medium-sized DMOs in the United States. The nomological validity of this construct is then established by testing the effect of the proposed MSMO construct on DMO performance.

Conceptual Background

Market Orientation

Kotler’s (1972) proposal of a generic concept of marketing suggested that the principles of marketing need not necessarily be restricted to the product marketplace. Rather, Kotler suggested that marketing should be viewed as applicable to all entities (or publics) with which a firm transacts. In accordance with this generic conceptualization of marketing, the American Marketing Association (AMA 2015) defines marketing as “the activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and society at large”. Interestingly, however, while the definition of marketing has been updated to reflect the ongoing shifts in the nature and scope of marketing thought, the fundamental operational construct reflective of the marketing concept (i.e., a market orientation) has remained unchanged since its inception.

Broadly speaking, a market orientation is reflective of the extent to which the marketing concept is implemented by an organization (Kirca, Jayachandran, and Bearden 2005; Liao et al. 2011; Narver and Slater 1990). Over the past 20 years, empirical research within this stream has been a central component of marketing scholarship. However, prior to its operational specification, the market orientation concept was mainly deployed as a differentiating mechanism used to characterize firms whose primary focus was satisfying the customer, as opposed to optimizing production (i.e., a production orientation) or maximizing sales (i.e., a sales orientation). As such, the term market orientation was, for many years, little more than a subjective descriptor of the contemporary conventional wisdom concerning the practical nature and scope of the marketing concept and was accompanied by very little empirical substance (Narver and Slater 1990).

The ambiguity of such an important component of marketing thought was problematic for marketing scholars because without a definitive theoretical basis for its conceptualization, the empirical utility of the market orientation construct was limited. Noting these issues, scholars began to more formally consider the theoretical origins and implications of the philosophies underlying the implementation of the marketing concept. These efforts resulted in two theoretically similar (though operationally distinct) conceptualizations of a market orientation: Narver and Slater’s (1990) cultural approach (i.e., the MKTOR scale) and Jaworski and Kohli’s (1993) activities approach (i.e., the MARKOR scale; see also Kohli and Jaworski 1990).

Despite their disparate conceptual foundations, scholars are in general agreement that both approaches tap the same theoretical domain (Oczkowski and Farrell 1998). Using one or the other approach, myriad studies have been conducted connecting a market orientation to a wide variety of antecedents and outcomes. However, despite the proliferation of MKTOR and MARKOR as the dominant operational approaches to measuring market orientation for the purposes of empirical research, the application of these two approaches has not gone unchallenged. Critics of the traditional paradigm suggest that, because market orientation is operationalized as a function of customer- and/or competitor-oriented reactions and behaviors, the conceptual domain of the phenomenon itself is unduly restrictive and overly narrow in focus (e.g., Ferrell et al. 2010; Greenley, Hooley, and Rudd 2005; Matsuno and Mentzer 2000). Such critics further contend that although customer- and competitor-level information are important components of strategic marketing decisions, a number of equally important stakeholder markets play a role in decisions related to the implementation of the marketing concept (Greenley, Hooley, and Rudd 2005). Depending on the industry, examples of such stakeholder markets include, but are not limited to, employees, investors/shareholders, suppliers, community groups/NPOs, universities, and governments (Ferrell et al. 2010; Matsuno and Mentzer 2000; Slater and Narver 1999).

Unfortunately, although such groups are often acknowledged in strategy development processes, stakeholder issues are typically approached from the view of the customer rather than from a broader social context (Ferrell et al. 2010) and are not included at all in the traditionally accepted conceptualizations and measurements of market orientation. By implication then, market-level transaction/exchange appears to remain the central tenet of the marketing concept (at least at an operational level), implying that a market orientation is achieved only within the strategic context of product-market actors (i.e., customer and competitors). But if the basic phenomenon of marketing is indeed the transaction (Kotler 1972), why then does a market orientation emphasize only the generation, dissemination, and reaction to market-level information? Is it not possible to bring to bear the tenets of marketing within the context of transactions with (and among) other stakeholders for the purpose of creating value?

Contemporary scientific perspectives suggest that while a customer focus is undoubtedly central to the marketing concept, the creation of customer value should be expanded beyond a customer-centric focus. In particular, both the service-dominant logic (Vargo and Lusch 2004) and the developing tenets of stakeholder marketing (Bhattacharya and Korschun 2008) suggest that (1) an organization has the potential to create value through all of its transactions, regardless of the transacting partner (Lusch and Webster 2011), and (2) the extent to which the marketing concept is applied to these transactions should accordingly be reflected in the conceptualization of the organization’s market orientation. Stated more simply, the construct representing the extent to which the marketing concept is implemented should include dimensionality beyond the typical customer- and competitor-based factors. We suggest that this concept can best be understood as a multistakeholder market orientation. As follows, we develop this construct within the context of both the service-dominant logic of marketing and the closely related tenets of the stakeholder theory of the firm. We then connect the attendant concepts to the domain of destination marketing.

The Service-Dominant Logic

The currently accepted market orientation paradigm emerged in a time period in which marketing was viewed as customer-oriented and value-proposing (Lusch and Webster 2011). Recently however, marketing scholars have acknowledged yet another evolution in contemporary marketing thought. Proponents of this new perspective, referred to as the service-dominant logic of marketing (Vargo and Lusch 2008), maintain that neither firm nor customer can unilaterally dictate the notion of value. Instead, this newest shift in marketing thought posits that value is achieved via the exchange of operant resources such as knowledge, information, and skills, rather than through the exchange of operand resources in the form of tangible goods/materials (Vargo and Lusch 2004). The service-dominant logic suggests that rather than merely being created by the producer, value is cocreated through the interaction of a firm with its customers, competitors, and other salient stakeholders (Lusch and Webster 2011). Additionally, the service-dominant logic holds that the goal of value creation is less about maximizing customer value than it is about maximizing the organization’s collective value vis-à-vis the full range of its salient stakeholders.

As such, the service-dominant logic takes a systems approach to value creation. Likewise, the primary metaphor of this framework is not “the organization” but the “network” (Lusch and Webster 2011, 130). The service-dominant logic–based network metaphor is central to the current perspective of the destination marketing environment, where multiple complex entities contribute to the value creation process in distinct, but equally essential, ways (Cabiddu, Lui, and Piccoli 2013; Cooper, Scott, and Baggio 2009; Gummesson 2014; Mistilis, Buhalis, and Gretzel 2014). It should be recognized that value at a destination is created and achieved through the collection of a discrete service provider network owing to the nonsequential production process of products and services. This is different from the traditional value chain concept that transforms inputs into outputs following a more linear and sequential process (Porter 1985). Thus, at the destination level, the logic of value creation is characterized by the linking together of complementary business units, managing the horizontally linked production process, and coordinating production and consumption activities simultaneously with relatively less little upstream or downstream production. In this value creation network, the destination plays a mediating role between providers of the various primary activities and support activities in value creation by maximizing the supply-side externalities within the destination. As such, the value configuration of each business in the destination is embedded in the destination’s value network (Katz and Shapiro 1985). Though it can be argued that each individual business unit has its own discrete value configuration, the effect of externalities arising from operating within a destination context constitutes an interactive value configuration process in which each business unit has to meet the standards and expectations of the network as an equal partner.

Stakeholder Marketing

The emphasis that the service-dominant logic places on maximizing stakeholder value is rooted in the stakeholder theory of the firm (Freeman 1984). Stakeholder theory, as a descriptive mechanism, suggests that organizations are “a constellation of cooperative and competitive interests possessing intrinsic value” (Donaldson and Preston 1995, 66). In these terms, any cooperative or competitive interest that can affect (or can be affected by) an organization’s activities can be considered a stakeholder of that organization (Clarkson 1995). Although customers and competitors fit the traditional conceptualization of a stakeholder, stakeholder theory suggests the existence of numerous other salient actors in a firm’s marketing environment (Freeman 1984). Within the general business literature, groups such as shareholders, investors, and community groups (Ferrell et al. 2010; Greenley and Foxall 1997) have been identified that fit the definition of a stakeholder.

Given the potential for stakeholder groups to influence managerial decision making, marketing researchers are increasingly acknowledging the importance of taking a stakeholder perspective in the conceptualization of a market orientation (Ferrell et al. 2010; Greenley and Foxall 1998; Greenley, Hooley, and Rudd 2005; Lusch 2007). The theoretical intersection of the market orientation paradigm and stakeholder theory is embodied by the stakeholder marketing movement (Gundlach and Wilkie 2010). In contrast to traditional perspectives, stakeholder marketing mandates that companies “look beyond customers as the sole target of marketing activities” (Bhattacharya 2010, 1). Accordingly, the core philosophies of stakeholder marketing include both a consideration of multiple stakeholder interests in the design of marketing strategy and an understanding of marketing’s impact across the stakeholder spectrum (Bhattacharya 2010).

Conceptualized as such, the tenets of stakeholder marketing pose some serious challenges to the extant conceptualizations of a market orientation. Most significantly, we suggest that if marketing has in fact moved to a networked model of value creation with a fundamental goal of maximizing total value for all stakeholders (Lusch and Webster 2011), the customer- and competitor-centric conceptualizations of a market orientation proposed by Narver and Slater (1990) and Kohli and Jaworski (1990) simply cannot account for the complexities of the new paradigm. Thus, while information generation, dissemination, and reaction are still key to maximizing value for customers (Kohli and Jaworski 1990), no longer can this information come only from “the market,” nor can it be used simply for the creation of customer value. Instead, information must be generated and disseminated across stakeholders for the purpose of value creation in toto. This is the essence of an MSMO in a general sense as well as an essential component of what is developed below as a market-oriented approach to destination marketing.

Destination Marketing

The above suggests that when it comes to destination marketing, the conceptualization of a market orientation must go beyond the typical customer- and competitor-based approaches (i.e., Kohli and Jaworski 1990; Narver and Slater 1990). Because DMOs operate in a highly networked marketing environment characterized by a wide variety of stakeholders (each of which may have a unique set of opinions regarding the role of tourism in the community), a DMO’s marketing strategy must consider all such stakeholders in order to achieve organizational success (Ford and Peeper 2008; Park, Lehto, and Morrison 2008). A synthesis of the existing perspectives of destination stakeholders suggests that in addition to customers and competitors, two other stakeholder constituencies should be considered in the operationalization of a DMO’s MSMO, the tourism industry and the local political structure (inclusive of both politicians and residents). As such, market-oriented destination marketing is operationally specified herein as a second-order factor composed of five first-order dimensions.

Figure 1 identifies the five salient stakeholder constituencies inherent to the destination marketing environment: independent/transient travel, group travel, competitors, the tourism industry, and political entities. These five groups were drawn from an in-depth review of the predominant conceptualizations of DMO stakeholder structure, including (but not limited to) Crouch’s (2011) conceptual model of destination competitiveness; Ford and Peeper’s (2008) comprehensive book on DMO management; Line and Runyan’s (2014) conceptualization of destination marketing assets, Sheehan and Ritchie’s (2005) salient stakeholder categorization schema; Sheehan, Ritchie, and Hudson’s (2007) destination promotion triad; and Wang and Xiang’s (2007) theoretical framework of collaborative destination marketing. Importantly, these five stakeholder constituencies reflect Bornhorst, Ritchie, and Sheehan’s (2010) findings concerning the key stakeholder actors that determine and define the success of a destination.

Figure 1.

Multistakeholder market orientation.

As reflected in Figure 1, the MSMO concept revolves around five salient, but also dynamic (Beritelli, Bieger, and Laesser 2014), stakeholders: independent customers, group travel, competitors, industry stakeholders, and local political interests. From an operational perspective, independent customers refer to nongroup travel in all forms, including transient visitors, visiting friends and relatives (VFR), and stopover visitors. Group travel can be defined as various organized group travel, including MICE, SMERF organizations, tour operators and their clients, and meeting/event planners. Competitors are represented by all other destinations or entities with which a DMO competes either directly or indirectly for visitors. Industry stakeholders include any private organizational entities such as hotels, restaurants, and transportation companies that benefit from the tourism activities in a destination. Last but not least, political stakeholders refer to all governmental entities that exert influence on the operational activities of a DMO as well as a destination. Such political constituents may include residents and interest groups at a local destination (e.g., Jordan 2015). The figure suggests that an MSMO, characterized by a strategic orientation toward these five stakeholder constituencies, results in the development of a competitive advantage for the DMO as well as the destination it represents.

Methods

The first step in the process for developing marketing constructs is specification of a construct’s domain (Churchill 1979). This is typically accomplished via a review of the literature for the purposes of defining the construct of interest. In addition to specifying the domain of a proposed construct, Churchill (1979) mandates that researchers “have good reasons for proposing additional new measures given the many available for most marketing constructs of interest” (p. 67). Having satisfied this imperative in the literature review, the remaining steps in the scale development process are discussed as follows.

Generation of Sample Items

Items reflective of MSMO were developed via an iterative process involving multiple stages of item generation and revision. Items from existing scales (including the MARKOR, MKTOR operationalizations of a market orientation and several other conceptualizations of nonprofit market orientation; e.g., Modi and Mishra 2010; Shoham et al. 2006) were reviewed and revised for application within the domain of destination marketing. Each time an item was added or revised, the running list of reflective measurement items was reviewed by the primary researcher as well as by a group of business academics with diverse backgrounds (tourism, marketing, management, and strategy). This group met once per week over a period of five weeks as the list was being developed to discuss the items from both theoretical and methodological perspectives.

The resultant list of items was then considered from a practitioner standpoint to ensure that destination marketing professionals would interpret each item correctly. To accomplish this, the full list of measurement items was organized into a hard copy survey and presented to a small sample of destination marketing executives attending the National Tour Association Conference. The primary researcher sat with each respondent as he/she took the survey and asked the respondent to provide verbal feedback to each item as they were responding. The survey was again revised based on the practitioner feedback and resubmitted to the academic discussion group for additional consideration.

Field Interviews and Specification of Dimensionality

Following the generation of items from existing literature, a round of field interviews was conducted to allow for the organic development of the dimensional structure of the proposed MSMO construct. Interview content and selection of participants were conducted according to tenets of grounded theory (Strauss and Corbin 1998). Theoretical sampling of participants and interview content (Glaser 1978) allowed for the emergence of recurring themes related to the process of destination marketing. The themes identified in the qualitative analyses were used to develop the dimensional structure of the proposed MSMO construct and to ensure that the list of reflective items signified a sufficiently broad representation of the thematic developments (Lindell and Whitney 2001). The analysis of interview data yielded the five-factor conceptualization of the MSMO construct as proposed in the literature review (and depicted in Figure 1).

Pretest

To further purify the instrument and test for factor structure, a pretest was posted in three discussion forums (the Marketing Forum, the Research Forum, and the General Topics Forum) on the Destination Marketing Association International (DMAI) website. The invitation to participate in the pretest was posted three times in each forum with two week intervals between postings (Dillman, Smyth, and Christian 2009). The pretest data were used to assess the internal consistency and the factor structure of each first-order dimension of the proposed MSMO construct. Upon confirming the internal consistency of each of the five first-order constructs, factor analyses were conducted in order to better understand the structure of each proposed first-order construct. Items reflective of each dimension of the MSMO construct were analyzed via a principal components analysis (PCA) with varimax rotation. Initially, the PCA was conducted without specifying the number of dimensions (Hair et al. 2006). Analysis of the eigenvalues and the resulting scree plot suggested a five-factor structure with 65% of variance explained. Using this information, a second PCA was conducted specifying a five-factor solution corresponding to the dimensionality identified through the grounded theoretical analysis of the qualitative data and the literature review. The results of this analysis were used to further reduce the scale items. Items loading onto multiple factors were deleted, as were items that loaded heavily onto constructs outside of their theoretically specified domain.

Main Data Collection

The data used for the final stage of construct validation were collected from a large sample of destination marketing executives and managers in the United States. A questionnaire containing the final set of measurement items was mailed to a total of 600 DMOs in the United States. Each mailed survey was addressed to the director (or top manager) of the organization along with a self-addressed, postage-paid return envelope. The preliminary mailing was followed by two subsequent requests for participation (Dillman, Smyth, and Christian 2009), resulting in a total of 222 complete responses (a 37% response rate). However, because the vast majority of the responding organizations employed 30 or fewer people, responses from organizations employing over 30 people (n = 16) were eliminated from the analysis. Thus, the final sample (n = 206) can be seen as representative of small and medium-sized DMOs only. Additional information pertaining to the respondents and their organizations can be seen in Table 1.

Table 1.

Organizational/Respondent Information.

Characteristic	n	%
Destination description
Single city	66	32.0
All cities in a single county	88	42.7
Selected cities in a single county	20	9.7
A multiple county region	31	15.0
Total number of other nonregional DMOs in county
0	129	62.6
1	24	11.7
2	14	6.8
3	12	5.8
4 or more	16	7.8
Business models/governance structures
Government body	53	25.7
Government/private coventure	37	18.0
Government funding plus paying members	55	26.7
Member supported, with no government funds	11	5.3
Other	47	22.8
Full-time employees
0–5	114	55.3
6–10	47	22.8
11–15	19	9.2
16–20	9	4.4
21–25	6	2.9
26–30	6	2.9
Respondent role in DMO
CEO/President/Director	169	82.0
Other	33	16.0

Note: DMO = destination marketing organization; Statewise breakdown: AL, 5; FL, 2; GA, 12; MN, 6; MO, 9; MS, 5; MT, 4; NC, 11; ND, 5; NE, 3; NJ, 1; NV, 2; NY, 7; OH, 20; OK, 7; OR, 22; PA, 17; SC, 3; SD, 3; TN, 10; TX, 20; UT, 1; VA, 11; WA, 1; WI, 8; WV, 10; WY, 1.

Common Method Biases

Throughout the scale development and data collection processes, several important steps were taken to minimize the potential effects of methodologically based measurement error. First, care was taken to minimize potential biases attributable to the structural properties of the measurement items. As discussed above, all items were developed in accordance with the content generated in the practitioner interviews. This process helped to ensure that the content of each item was presented unambiguously and expressed in terminology that would be meaningful to the respondent population (Lindell and Whitney 2001). Additionally, because it was important to maintain consistency across the interpretation of the technical terminology used in the items, each section of the questionnaire began with a brief definition of key terms relevant to that section. In addition to maintaining consistency, the explicit identification of key terms helped to further optimize item comprehension among respondents to the survey (Lindell and Whiney 2001).

Another potential source of bias results from the possibility that the context in which an item is presented may generate artificial covariance due to some relationship with other contextually relevant items (i.e., items in the same scale). Two techniques were used to minimize item context effects. First, the number of scale points measuring each item was held constant across scale types. This prevented respondents from having to adjust their scaling schema across inconsistent inter-item scale intervals. Second, while items from similar constructs were generally presented in groups, items were occasionally intermixed between groups to ensure that inter- and intraconstruct correlations were not artificially affected as a result of item placement (Podsakoff et al. 2003).

A final source of potential bias is attributable to the possibility that the DMO executives who responded to the survey are significantly different than those who did not respond. In order to account for nonresponse bias, returned surveys were coded according to the corresponding round of data collection. Thus, all responses were coded as a one, a two, or a three, depending on when they were received. Using these three groups, a series of independent sample t tests were conducted for all observed measurement items. For all pairwise comparisons, the between-group differences were not significant (p > .05). These results indicate a consistency across respondent groups and a minimization of the incidence of nonresponse bias.

Data Analysis

The data collected in the final sample were used to assess the psychometric properties of the developed scales. First, a measurement model was specified inclusive of all five first-order constructs (χ² = 362.9, df = 160 [χ²/df = 2.27]; root mean square error of approximation [RMSEA] = .079; comparative fit index [CFI] = .90; Tucker–Lewis index [TLI] = .89). The resulting factor structure of each first-order dimension of MSMO can be seen in Table 2, which demonstrates sufficient reliability for all the five constructs (α = .79, .82, .81, .90, and .78 for ICO, GTO, CMO, ISO, and PSO, respectively). Additionally, Table 2 shows the means, standard deviations, and standardized parameter estimates for all items reflective of each dimension of the proposed construct. As seen in the table, all parameter estimates were significant at the .05 level, providing preliminary evidence of convergent validity. Additionally, while the size of the sample precluded Kolmogorov-Smirnov analyses, analyses of the Q-Q plots for each of these variables provided evidence of a multivariate normal distribution (Hair et al. 2006).

Table 2.

Measurement Scale Properties: Multistakeholder Market Orientation.

Constructs and Indicators (7-Point Likert-Type Scaling)	Mean	Standard Deviation	StandardEstimate	p
Independent Customer Orientation (ICO) (α = .79)	5.36	1.54
ICO1: Our organization conducts (or sponsors) research to identify the reasons that independent travelers visit our destination.	4.72	2.07	0.644	<.001
ICO2: Understanding the needs of the independent travel market is an important part of our organization’s strategic planning process.	5.82	1.52	0.706	<.001
ICO3: Our organization understands the tourism-related needs of the independent travelers that visit our destination.	5.50	1.29	0.773	<.001
ICO4: Our strategic objectives are designed to ensure that our destination meets the tourism-related needs of the independent travelers that come here.	5.41	1.29	0.768	<.001
Group Travel Orientation (GTO) (α = .82)	5.21	1.57
GTO1: Understanding the needs of the group travel market is an important part of our organization’s strategic planning process.	5.47	1.59	0.722	<.001
GTO2: Our organization understands the tourism needs of the organized groups that visit our destination.	5.58	1.33	0.801	<.001
GTO3: Our organization conducts (or sponsors) research to identify new opportunities for attracting organized groups to our destination.	4.30	1.94	0.742	<.001
GTO4: Our organization works with the local tourism industry to understand the needs of the group travel market.	5.50	1.41	0.806	<.001
Competitor Orientation (CMO) (α = .81)	4.23	1.73
CMO1: Our managers regularly discuss our competitor’s strengths and weaknesses.	4.32	1.66	0.748	<.001
CMO2: Employees with different responsibilities share information about our competitors with each other.	4.77	1.67	0.667	<.001
CMO3: Our organization conducts (or sponsors) research to better understand our competitors’ target markets.	3.40	1.78	0.696	<.001
CMO4: Our organization shares relevant information about our competitors with the local tourism industry.	4.42	1.80	0.787	<.001
Industry Stakeholder Orientation (ISO) (α = .90)	5.90	1.26
ISO1: Our managers understand the local lodging industry’s expectations of our organization.	5.97	1.14	0.669	<.001
ISO2: Our organization actively seeks feedback about our marketing activities from the local lodging industry.	5.72	1.34	0.897	<.001
ISO3: Meeting with representatives of the local lodging industry to discuss our organization’s strategy is an effective use of our managers’ time.	5.84	1.34	0.773	<.001
ISO4: Our organization appreciates input from the local lodging industry when setting strategic objectives.	6.16	1.09	0.788	<.001
ISO5: Our organization seeks input from the local lodging industry when setting strategic objectives.	5.79	1.41	0.872	<.001
Political Stakeholder Orientation (PSO) (α = .78)	5.32	1.54
PSO1: Our organization appreciates input from local politicians when setting strategic objectives.	5.21	1.56	0.589	<.001
PSO2: Our organization communicates the local political leadership’s position regarding the role of tourism in our community to our industry stakeholders.	5.36	1.52	0.85	<.001
PSO3: Our organization facilitates the flow of relevant information from our local government to the local tourism industry.	5.38	1.53	0.777	<.001

Note: χ² = 362.9, df = 160; root mean square error of approximation = .079; comparative fit index = .90.

In order to formally test for convergent and discriminant validity, average variance extracted (AVE) was calculated in the manner advocated by Fornell and Larcker (1981). Table 3 shows the critical ratio (CR), AVE, maximum shared squared variance (MSV), and average shared squared variance (ASV) for each first-order dimension of the proposed MSMO construct. The correlation matrix is also provided (with the square root of AVE on the diagonal). 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, providing strong evidence of discriminant validity among the constructs (Hair et al. 2006).

Table 3.

Validity Assessment and Correlation Matrix.

	CR	AVE	MSV	ASV	ICO	GTO	CMO	ISO	PSO
ICO	0.79	0.53	0.23	0.17	0.73^a
GTO	0.84	0.59	0.41	0.31	0.48	0.77^a
CMO	0.81	0.53	0.41	0.22	0.38	0.64	0.73^a
ISO	0.90	0.65	0.32	0.24	0.41	0.57	0.43	0.80^a
PSO	0.78	0.56	0.31	0.22	0.39	0.54	0.38	0.55	0.75^a

Note: CR = critical ratio; AVE = average variance extracted; MSV = maximum shared squared variance; ASV = average shared squared variance.

Square root of AVE.

Upon establishing the soundness of the measurement model, the final task was to confirm the second-order structure of MSMO. Using the specifications for each dimension developed in the first-order analyses (and specified in the measurement model), a CFA was conducted specifying the second-order structure of MSMO. This specification demonstrated an acceptable fit to the data (χ² = 371.7, df = 165 [χ² /df = 2.25]; RMSEA = .078; CFI = .90; TLI = .89). Likewise, all path estimates were positive and significant (p < .05). The results of these analyses support the proposed factor structure of MSMO.

In order to ensure that the demonstrated fit of the model was attributable to the structure of the data and not an artifact of the ratio of the sample size (206) to the number of parameters in the measurement model itself (50), a confirmatory factor analysis of the MSMO construct was conducted using composite variables. Following the process outlined by Yuan, Bentler, and Kano (1997), composite variables were created by averaging the measurement items reflective of each factor. The resultant five indicators were then specified as reflective of a single latent construct (MSMO), and submitted to a confirmatory factor analysis (χ² = 8.91, df = 5 [χ²/df = 1.78]; RMSEA = .062; CFI = .98; TLI = .97). The resultant fit indices suggest that the model is still viable even with a much larger ratio of sample responses (206) to free parameters (16) (Kline 2005).

Nomological Validity: MSMO and DMO Performance

An essential part of the market orientation framework is the well-documented connection between the adoption of a market orientation and enhanced firm performance. Because MSMO represents an extension of the existing market orientation paradigm, an implied corollary to the proposed framework is that MSMO should likewise impact DMO performance in a positive manner. Thus, in order to demonstrate the nomological validity of the proposed market-oriented approach to destination marketing, we sought to test a preliminary hypothesis that MSMO, operationalized within the context of destination marketing, should positively affect DMO performance.

To test this hypothesis, a performance construct was included in the questionnaire. The performance construct was measured subjectively via four items designed to capture several aspects of DMO performance (α = .93). Measurement items were developed following the same process accounted for above concerning the development of MSMO. These measurement items and their properties (means, standard deviations, and factor loadings) can be seen in Table 4. Participants responded to these items on a 7-point scale anchored by “less successful than planned” and “more successful than planned.” The referent time frame was the previous three years.

Table 4.

Measurement Scale Properties: Destination Marketing Organization Performance.

Indicators	Mean	Standard Deviation	Standard Estimate	p
Progress toward long-term goals	5.02	1.18	0.74	<.001
Meeting expectations of local tourism industry	5.29	1.12	0.91	<.001
Meeting expectations of community leadership	5.33	1.24	0.87	<.001
Achieving intended economic impact	5.39	1.15	0.80	<.001

Note: χ²/df = 2.53; root mean square error of approximation = .036; Tucker–Lewis index = .997; comparative fit index = .999.

In order to test the hypothesis of a positive relationship between MSMO and DMO performance, a structural equation was specified with a parameter linking the second-order specification of MSMO with the first-order specification of DMO performance (χ² = 474.9, df = 246 [χ² /df = 1.93]; RMSEA = .067; CFI = .92; TLI = .90). In the specified structural model, all path estimates were significant and positive, including the parameter linking MSMO to DMO performance (see Figure 2). Thus, we find support for the hypothesized relationship between MSMO and DMO performance.

Figure 2.

Multistakeholder market orientation and performance.

It is important to note here that the relationship between MSMO and performance accounted for in this research hinges on the assumption that self-reported responses to subjective survey material can provide an accurate measurement of organizational performance. While there is some evidence that subjectively derived measurements are acceptable representations of an organization’s performance (Dess and Robinson Jr. 1984; Venkatraman and Ramanujam 1986), there is still a possibility that because of social desirability biases, subjective measures of performance may be artificially inflated. Rather than merely assuming that the subjective measurements of DMO performance obtained from the respondents are an appropriate representation of each organization’s performance, a post hoc analysis was conducted to determine the extent to which these subjective measurements of performance correlate with an objective measurement of performance.

In order to conduct this analysis, a secondary data set was acquired from Smith Travel Research (STR). For destinations, one of the most valuable pieces of STR data is hotel demand numbers, calculated as the total number of hotel rooms sold in a given destination in a given time frame. When considered over time, changes in hotel demand represent the extent to which a DMO has been successful in increasing visitor demand for its destination. Thus, while DMOs do not influence supply- or revenue-based hotel metrics, these organizations presumably have a direct effect on aggregate demand for a destination. As such, a measurement of the change in destination-level hotel demand was developed as an objective measurement of DMO performance.

This metric was calculated for all responding destinations for which the corresponding data were available. Overall, STR was able to provide aggregate demand data for 157 (76.2%) of the 206 responding destinations. For each of these destinations, STR provided monthly aggregate demand data from 2008 to 2012. These data represent the total number of hotel rooms sold for each month in each responding destination. Because the subjective assessment of performance solicited in the survey was a measurement of performance over the previous three years (i.e., 2009–2011), the STR data were used to calculate yearly aggregate demand from 2008 to 2011. Then, for each focal year (2009–2011), the change in aggregate demand from the previous year was calculated by dividing demand in the focal year by the previous year’s demand. This number was subtracted by 1 and multiplied by 100 to create a +/– percentage indicator of yearly change in demand. The percentage change in demand for each focal year was then summed to yield a composite three-year change in demand index for each destination. Calculating the performance variable in this way ensures that, although each responding destination is subject to a unique set of environmental parameters regarding size, budget, baseline demand, etc., the final metric reflects a standardized measurement of performance.

This composite number was used as the objective correlate. The corresponding subjective correlate was calculated as an average of the respondents’ scores for the four latent variables reflective of the DMO’s performance relative to its strategic plans over the previous three years (see Table 4). Thus, to the extent that a DMO’s strategic plan emphasizes maintaining/enhancing destination demand (an assumption of the model), the subjective measurement of performance should be positively correlated with yearly aggregate demand trends. The results of this analysis indicated that the subjective measurement of performance was significantly correlated with the objective measurement of performance (r = .157; p < .05). Thus, while statistical constraints preclude an inclusion of the objective correlate in the structural model, the positive (albeit small) correlation between the subjective measurement of performance and a corresponding objective measurement is crucial to establishing the nomological validity of the MSMO construct. Specifically, this finding supports the contention that (1) subjective measures can accurately assess DMO performance and (2) the positive relationship identified between MSMO and performance is externally valid.

Discussion

Market-oriented destination marketing is not a new idea. Indeed, references to this phenomenon are widespread throughout the tourism and destination marketing/management literature. However, despite the application of market orientation to myriad operational contexts in both the for-profit and nonprofit domains, the construct has never been formally conceptualized within the context of destination marketing. As such, the primary contribution of the present endeavor is the extension of the market orientation paradigm (along with its implications regarding organizational performance) to the specific context of destination marketing.

Broadly speaking, the results of this research suggest that, just as market orientation affects firm performance in traditional product markets, the adoption of a conceptually expanded but theoretically analogous strategic orientation by a DMO will likewise result in increased organizational performance. Given the importance of the market orientation construct within the general business literature over the previous quarter century (Kirca, Jayachandran, and Bearden 2005), the extension of this phenomenon to destination marketing has the potential to usher in a new stream of DMO research. Because both MSMO and its DMO-based operationalization are situated within the context of well-established theoretical perspectives, future research can use the extensive and richly diverse stream of extant market orientation research as a framework to assess the extent to which MSMO affects other important constructs in the DMO performance nomology.

Thus, the task for tourism scholars is to continue to expand the theoretical understanding of this construct by testing its relationships with organizational constructs beyond what is considered in the present research. For example, exploring the effects of MSMO on phenomena such as creativity, innovation, organizational learning, and visitor satisfaction represent promising areas for extending the framework. However, because these constructs have been conceptualized in noncongruent industry contexts, tourism scholars must continue to develop industry-specific operationalizations of these constructs.

Practical Implications

Having made a theoretical case for the construct itself, it is likewise important to address the implications of the MSMO framework for collaborative destination marketing. According to the framework espoused in the present research, the penultimate function of a DMO is to coordinate a value proposition across a broad set of external stakeholders in the marketing environment. In these terms, an MSMO represents the extent to which a DMO possesses the set of capabilities necessary to coordinate the interests of the actors in the marketing environment. While the value delivery network of every DMO is unique in terms of the specific composition of stakeholder relationships, it is the nature of these relationships in toto that determines its ability to be successful in the marketplace.

The DMO’s role in establishing and maintaining partnerships with and among destination stakeholders is an essential part of the value creation function (Wang 2008). Unfortunately, however, because stakeholders do not always value the role of the DMO in the local economy, it cannot be assumed that just because an alliance exists, the relationships among its members necessarily represent a source of competitive advantage (Palmer and Bejou 1995; Parmigiani and Rivera-Santos 2011). Indeed, research suggests that considerable variation exists in the extent to which DMOs positively relate to their alliance partners, and vice versa (Sheehan and Ritchie 2005). Ford and Peeper’s (2008) qualitative study of DMO managers provides support for this position in their conclusion that a lack of what the present research refers to as an MSMO is often associated with less successful DMO performance.

As such, the premise of this article is that because MSMO represents an orientation to all salient actors in the value creation process, the implementation of such a posture is positively related to organizational performance. That is, like a market orientation, MSMO reflects a set of strategic organizational capabilities (cf. Day 1994; Foley and Fahy 2009). To the extent that the capabilities associated with managing stakeholder relationships are both sustainable and difficult to duplicate (Dyer and Singh 1998), such capabilities can be assumed to contribute to the creation of a sustainable advantage in much the same way as the customer- and competitor-oriented capabilities conceptualized by both Narver and Slater (1990) and Kohli and Jaworski (1990). As such, the conceptual logic underpinning the proposed MSMO construct suggests that the capabilities associated with maintaining favorable stakeholder relationships can appropriately be identified as a sustainable source of competitive advantage to the extent that such relationships help avoid the strategic drift that occurs when DMOs lose sight of forces in the external environment (Dwyer et al. 2009).

Accordingly, MSMO mandates that the traditional customer-centric view of a market orientation must be combined with an orientation toward other stakeholders if it is to contribute to the development of a sustainable competitive advantage. Within the context of destination marketing, this means that a DMO must also communicate its customer-focused value proposition across the stakeholder spectrum in order to coordinate the delivery of that proposition (cf. Buhalis 2000). If a DMO’s value proposition is communicated to both the suppliers of the tourism product and the political entities that represent the destination as a whole, and all parties act in a unified manner relative to the implementation of this proposition, assets such as brand equity (Pike 2007), repeat visitation (Morais and Lin 2010), visitor loyalty (Velázquez, Saura, and Molina 2011), and target market loyalty (McKercher and Guillet 2011) are more likely to develop than would be the case in the absence of such coordination (Line and Runyan 2014).

Limitations

As is the case with all research, there are several limitations inherent to this study that must be acknowledged. In this section, these limitations are addressed in terms of their potential effects on the research findings. Additionally, the potential for these limitations to inform future research is considered.

One of the primary limitations of this research is attributable to the sampling frame. The sampling process resulted in data from 27 U.S. states. As such, there are 23 states that are not represented in the analysis. This presents a potential problem of the generalizability of the findings. Future research could lend additional insight into this issue by conducting state-specific examinations of the research findings. For example, instead of focusing on DMOs throughout the United States, future research could take a census of all DMOs in a particular state (or small subset of states) and attempt to replicate these findings over a smaller sampling area.

Another sampling-based limitation is attributable to the sample population. The sample population for this research was city, county, and small-region DMOs. Thus, the framework developed in this research cannot be generalized to state and/or national DMOs. While the MSMO phenomenon is applicable to such organizations from a conceptual standpoint, state- and national-level DMOs are subject to different industry parameters than their more localized counterparts. Accordingly, state- and nation-specific operationalizations of MSMO may need to be developed. Similarly, because the present research was only concerned with DMOs and destinations in the United States, there is also the potential for future research to extend this research to other countries. Extensions of MSMO to other countries could also be used to assess cross-cultural measurement invariance.

Additionally, it is important to note that the proposed MSMO construct is conceptualized as reflective rather than formative. As such, the proposed dimensionality should not be seen as necessarily exhaustive, particularly when it comes to larger-size organizations. While large DMOs would likely exhibit orientations toward a similar group of stakeholders as conceived of in this research, such organizations may need to consider other types of stakeholders not accounted for in the above conceptualization of MSMO. For example, stakeholders such as film studios (and other major media outlets), search engines, research agencies, and universities often have a claim on the value proposition of many larger destinations. As such, future research should continue to explore the dimensionality of MSMO within the context of larger DMOs.

A final limitation of this research lies in its treatment of DMO performance. As discussed above, the data acquired from STR were a reflection of the change in destination demand. Although there are several compelling reasons for using this particular metric, there are numerous performance metrics associated with destination marketing. DMAI’s handbook for standard DMO performance reporting (DMAI 2011) lists a number of functionally specific performance areas including convention sales, travel trade sales, marketing and communications, membership, and ROI, each of which has their own set of activity, performance, and productivity metrics. Thus, while the present research identified a positive relationship between MSMO and what could be considered an overall performance score, there are a number of different metrics that could be considered in future research. Considering the effects of MSMO on functionally specific measurements of performance would contribute to a more complete understanding of the objectives such an orientation seeks to achieve.

Conclusion

This article proposes and empirically develops a new theoretical construct, a multistakeholder market orientation, that more appropriately reflects the contemporary scope of marketing thought as well as the unique structure of the destination marketing environment. While a traditional customer/market-oriented perspective remains an important part of MSMO, the expanded conceptualization was supported in terms of both construct and nomological validity. Although the present research represents only an initial foray into the potential organizational impacts of MSMO, the results suggest that the implementation of an MSMO is an important component of destination marketing. While there is still much to know concerning the implementation of this approach, the preliminary evidence is encouraging.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Nathaniel D. Line is an assistant professor in the Dedman School of Hospitality at Florida State University. His 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.

Youcheng Wang is a Professor and Associate Dean at the Rosen College of Hospitality Management at the University of Central Florida. His research areas include destination marketing and management, collaborative strategies, stakeholder management, social media and technology management.

References

AMA (American Marketing Association). 2015. Marketing power. Dictionary. http://www.marketingpower.com/AboutAMA/Pages/DefinitionofMarketing.aspx.

Bhattacharya

C. B.

2010. “Introduction to the Special Section on Stakeholder Marketing.” Journal of Public Policy and Marketing 29 (1): 1–3.

Bhattacharya

C. B.

Korschun

2008. “Stakeholder Marketing: Beyond the Four Ps and the Customer.” Journal of Public Policy & Marketing 27 (1): 113–16.

Beritelli

Bieger

Laesser

2014. “The New Frontiers of Destination Management: Applying Variable Geometry as a Function Based Approach.” Journal of Travel Research 53 (4): 403–17.

Bieger

Beritelli

Laesser

2009. “Size Matters! Increasing DMO Effectiveness and Extending Tourism Destination Boundaries.” Tourism 57 (3): 309–27.

Bornhorst

Ritchie

J. R. B.

Sheehan

2010. “Determinants of Tourism Success for DMOs & Destinations: An Empirical Examination of Stakeholders’ Perspectives.” Tourism Management 31 (5): 572–89.

Buhalis

2000. “Marketing the Competitive Destination of the Future.” Tourism Management 21 (1): 97–116.

Cabiddu

Lui

T.-W.

Piccoli

2013. “Managing Value Co-creation in the Tourism Industry.” Annals of Tourism Research 42:86–107.

Cano

C. R.

Carrillat

F. A.

Jaramillo

2004. “A Meta-analysis of the Relationship between Market Orientation and Business Performance: Evidence from Five Continents.” International Journal of Research in Marketing 21 (2): 179–200.

10.

Churchill

G. A.

1979. “A Paradigm for Developing Better Measures of Marketing Constructs.” Journal of Marketing Research 16 (1): 64–73.

11.

Clarkson

1995. “A Stakeholder Framework for Analyzing and Evaluating Corporate Social Performance.” Academy of Management Review 20:92–117.

12.

Cooper

Scott

Baggio

2009. “Network Position and Perceptions of Destination Stakeholder Importance.” Anatolia: An International Journal of Tourism and Hospitality Research 20 (1): 33–45.

13.

Crouch

G. I.

2011. “Destination Competitiveness: An Analysis of Determinant Attributes.” Journal of Travel Research 50 (1): 27–45.

14.

d’Angella

F. M.

2009. “Tale of Two Cities’ Collaborative Tourism Marketing: Towards a Theory of Destination Stakeholder Assessment.” Tourism Management 30 (3): 429–40.

15.

Day

G. S.

1994. “The Capabilities of Market-Driven Organizations.” Journal of Marketing 58 (4): 37–52.

16.

Dess

Robinson

Jr.

1984. “Measuring Organizational Performance in the Absence of Objective Measures: The Case of the Privately-Held Firm and Conglomerate Business Unit.” Strategic Management Journal 5 (3): 265–73.

17.

DMAI (Destination Marketing Association International). 2011. Standard DMO Performance Reporting: A Handbook for Destination Marketing Organizations (DMOs).

18.

Dillman

D. A.

Smyth

J. D.

Christian

L. M.

2009. Internet, Mail, and Mixed-mode surveys: The Tailored Design Method, 3rd ed. Hoboken, NJ: Wiley.

19.

Donaldson

Preston

L. E.

1995. “The Stakeholder Theory of the Corporation: Concepts, Evidence and Implications.” Academy of Management Review 29 (1): 65–91.

20.

Drucker

P. F.

1954. The Practice of Management. New York: Harper and Row.

21.

Dwyer

Edwards

Mistilis

Roman

Scott

2009. “Destination and Enterprise Management for a Tourism Future.” Tourism Management 30 (1): 63–74.

22.

Dyer

J. H.

Singh

1998. “The Relational View: Cooperative Strategy and Sources of Interorganizational Comparative Advantage.” Academy of Management Journal 23 (4): 660–79.

23.

Ferrell

O. C.

Gonzalez-Padron

T. L.

Hult

T. M.

Maignan

2010. “From Marketing Orientation to Stakeholder Orientation.” Journal of Public Policy & Marketing 29 (1): 93–96.

24.

Foley

Fahy

2009. “Seeing Market Orientation through a Capabilities Lens.” European Journal of Marketing 43 (1): 13–20.

25.

Ford

R. C.

Peeper

W. C.

2007. “The Past as Prologue: Predicting the Future of the Convention and Visitor Bureau Industry on the Basis of Its History.” Tourism Management 28 (4): 1104–14.

26.

Ford

R. C.

Peeper

W. C.

2008. Managing Destination Marketing Organizations: The Tasks, Roles and Responsibilities of the Convention and Visitors Bureau. Orlando, FL: ForPer.

27.

Fornell

Larcker

D. F.

1981. “Evaluation Structural Equation Models with Unobservable Variables and Measurement Error.” Journal of Marketing Research 28:39–50.

28.

Freeman

R. E.

1984. Strategic Management: A Stakeholder Approach. Boston, MA: Pitman.

29.

Fyall

Garrod

2005. Tourism Marketing: A Collaborative Approach. Tonawanda, NY: Channel View.

30.

Glaser

1978. Theoretical Sensitivity. Mill Valley, CA: The Sociology Press.

31.

Greenley

G. E.

Foxall

G. R.

1997. “Multiple Stakeholder Orientation in UK Companies and the Implications for Company Performance.” Journal of Management Studies 34 (2): 260–84.

32.

Greenley

G. E.

Foxall

G. R.

1998. “External Moderation of Associations among Stakeholder Orientations and Company Performance.” International Journal of Research in Marketing 15:51–69.

33.

Greenley

G. E.

Hooley

G. J.

Rudd

J. M.

2005. “Market Orientation in a Multiple Stakeholder Orientation Context: Implications for Marketing Capabilities and Assets.” Journal of Business Research 58 (11): 1483–94.

34.

Gretzel

Fesenmaier

D. R.

Formica

O’Leary

J. T.

2006. “Searching for the Future: Challenges Faced by Destination Marketing Organizations.” Journal of Travel Research 45 (2): 116–26.

35.

Gummesson

2014. “Productivity, Quality and Relationship Marketing in Service Operations.” International Journal of Contemporary Hospitality Management 26 (5): 656–62.

36.

Gundlach

G. T.

Wilkie

W. L.

2010. “Stakeholder Marketing: Why ‘Stakeholder’ Was Omitted from the American Marketing Association’s Official 2007 Definition of Marketing and Why the Future Is Bright for Stakeholder Marketing.” Journal of Public Policy and Marketing 29 (1): 89–92.

37.

Hair

J. F.

Jr. Black

W. C.

Babin

B. J.

Anderson

R. E.

Tatham

R. L.

2006. Multivariate Data Analysis, 6th ed. Upper Saddle River, NJ: Pearson Prentice Hall.

38.

Jaworski

Kohli

A. K.

1993. “Market Orientation: Antecedents and Consequences.” Journal of Marketing 57 (3): 53–70.

39.

Jordan

E. J.

2015. “Planning as a Coping Response to Proposed Tourism Development.” Journal of Travel Research 54 (3): 316–28.

40.

Katz

M. L.

Shapiro

1985. “Network Externalities, Competition and Compatibility.” American Economic Review 75 (3): 424–41.

41.

King

2002. “Destination Marketing Organizations—Connecting the Experience Rather Than Promoting the Place.” Journal of Vacation Marketing 8 (2): 105–8.

42.

Kirca

A. H.

Jayachandran

Bearden

W. O.

2005. “Market Orientation: A Meta-analytic Review and Assessment of Its Antecedents and Impact on Performance.” Journal of Marketing 69 (2): 24–41.

43.

Kline

R. B.

2005. Principles and Practice of Structural Equation Modeling, 2nd ed. New York: Guilford.

44.

Kohli

A. K.

Jaworski

B. J.

1990. “Market Orientation: The Construct, Research Propositions, and Managerial Implications.” Journal of Marketing 54 (2): 1–18.

45.

Kotler

1972. “A Generic Concept of Marketing.” Journal of Marketing 36 (2): 46–54.

46.

Liao

S.-H.

Chang

W.-J.

C.-C.

Katrichis

J. M.

2011. “A Survey of Market Orientation Research (1995–2008).” Industrial Marketing Management 40 (2): 301–10.

47.

Lindell

M. K.

Whitney

D. J.

2001. “Accounting for Common Method Variance in Cross-Sectional Research Designs.” Journal of Applied Psychology 86 (1): 114–21.

48.

Line

N. D.

Runyan

R. C.

2014. “Destination Marketing and the Service-Dominant Logic: A Resource-Based Operationalization of Strategic Marketing Assets.” Tourism Management 43:91–102.

49.

Lusch

R. F.

2007. “Marketing’s Evolving Identity: Defining Our Future.” Journal of Public Policy & Marketing 26:261–68.

50.

Lusch

R. F.

Webster

F. E.

Jr.

2011. “A Stakeholder-Unifying, Co-creation Philosophy for Marketing.” Journal of Macromarketing 31 (2): 129–34.

51.

Matsuno

Mentzer

J. T.

2000. “The Effects of Strategy Type on the Market Orientation-Performance Relationship.” Journal of Marketing 64 (4): 1–16.

52.

McKercher

Guillet

D. B.

2011. “Are Tourists or Markets Destination Loyal?” Journal of Travel Research 50 (2): 121–32.

53.

Medlik

Middleton

V. T. C.

1973. “The Tourist Product and Its Marketing Implications.” International Tourism Quarterly 3:28–35.

54.

Mistilis

Buhalis

Gretzel

2014. “Future eDestination Marketing: Perspective of an Australian Tourism Stakeholder Network.” Journal of Travel Research 53 (6): 778–90.

55.

Modi

Mishra

2010. “Conceptualising Market Orientation in Nonprofit Organisations: Definition, Performance, and Preliminary Construction of a Scale.” Journal of Marketing Management 26 (5-6): 548–69.

56.

Morais

D. B.

Lin

C-H.

2010. “Why Do First Time and Repeat Visitors Patronize a Destination?” Journal of Travel & Tourism Marketing 27 (2): 193–210.

57.

Murdy

Pike

2012. “Perceptions of Visitor Relationship Marketing Opportunities by Destination Marketers: An Importance-Performance Analysis.” Tourism Management 33 (5): 1281–85.

58.

Narver

J. C.

Slater

S. F.

1990. “The Effect of a Market Orientation on Business Profitability.” Journal of Marketing 54 (4): 20–35.

59.

Oczkowski

Farrell

M. A.

1998. “Discriminating between Measurement Scales Using Non-nested Tests and Two-Stage Least Squares Estimators: The Case of Market Orientation.” International Journal of Research in Marketing 15 (4): 349–66.

60.

Palmer

Bejou

1995. “Tourism Destination Marketing Alliances.” Annals of Tourism Research 22 (3): 619–29.

61.

Park

O. J.

Lehto

X. Y.

Morrison

A. M.

2008. “Collaboration between CVB and Local Community in Destination Marketing: CVB Executives’ Perspective.” Journal of Hospitality & Leisure Marketing 17 (3-4): 395–417.

62.

Parmigiani

Rivera-Santos

2011. “Clearing a Path through the Forest: A Meta-review of Interorganizational Relationships.” Journal of Management 37 (4): 1108–36.

63.

Pike

2004. Destination Marketing Organizations. Oxford, UK: Elsevier.

64.

Pike

2007. “Consumer-Based Brand Equity for Destinations: Practical DMO Performance Measures.” Journal of Travel & Tourism Marketing 22 (1): 51–61.

65.

Pike

Murdy

Lings

2011. “Visitor Relationship Orientation of Destination Marketing Organizations.” Journal of Travel Research 50 (4): 443–53.

66.

Pike

Page

S. J.

2014. “Destination Marketing Organizations and Destination Marketing: A Narrative Analysis of the Literature.” Tourism Management 41:202–27.

67.

Podsakoff

P. M.

MacKenzie

S. B.

Lee

J.-Y.

Podsakoff

N. P.

2003. “Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies.” Journal of Applied Psychology 88 (5): 879–903.

68.

Porter

M. E.

1985. Competitive Advantage. New York: Free Press.

69.

Ritchie

J. R. B.

1996. “Beacons of Light in an Expanding Universe: An Assessment of the State-of-the-Art in Tourism Marketing/Marketing Research.” Journal of Travel & Tourism Marketing 5 (4): 49–84.

70.

Sheehan

Ritchie

J. R. B.

Hudson

2007. “The Destination Promotion Triad: Understanding Asymmetric Stakeholder Interdependencies among the City, Hotels, and DMO.” Journal of Travel Research 46 (1): 64–74.

71.

Sheehan

L. R.

Ritchie

J. R. B.

2005. “Destination Stakeholders: Exploring Identity and Salience.” Annals of Tourism Research 32 (3): 711–34.

72.

Shoham

Ruvio

Vigoda-Gadot

Schwabsky

2006. “Market Orientations in the Nonprofit and Voluntary Sector: A Meta-analysis of Their Relationships with Organizational Performance.” Nonprofit and Voluntary Sector Quarterly 35 (3): 453–76.

73.

Slater

S. F.

Narver

J. C.

1999. “Market-Oriented Is More Than Being Customer-Led.” Strategic Management Journal 20 (12): 1165–1168.

74.

Strauss

Corbin

1998. Basics of Qualitative Research, 2nd ed. Thousand Oaks, CA: Sage.

75.

Vargo

S. L.

Lusch

R. F.

2004. “Evolving to a New Dominant Logic for Marketing.” Journal of Marketing 68 (1): 1–17.

76.

Vargo

S. L.

Lusch

R. F.

2008. “Service Dominant Logic: Continuing the Evolution.” Journal of the Academy of Marketing Science 36:42–53.

77.

Velázquez

B. M.

Saura

I. G.

Molina

M. E. R.

2011. “Conceptualizing and Measuring Loyalty: Towards a Conceptual Model of Tourist Loyalty Antecedents.” Journal of Vacation Marketing 17 (1): 65–81.

78.

Venkatraman

Ramanujam

1986. “Measurement of Business Performance in Strategy Research: A Comparison of Approaches.” Academy of Management Review 11 (4): 801–14.

79.

Wang

2008. “Collaborative Destination Marketing: Roles and Strategies of Convention and Visitors Bureaus.” Journal of Vacation Marketing 14 (3): 191–209.

80.

Wang

Krakover

2008. “Destination Marketing: Competition, Cooperation or Competition?” International Journal of Contemporary Hospitality Management 20 (2): 126–41.

81.

Wang

Xiang

2007. “Toward a Theoretical Framework of Collaborative Destination Marketing.” Journal of Travel Research 46 (1): 75–85.

82.

Williams

P. W.

Stewart

Larsen

2011. “Toward an Agenda of High-Priority Tourism Research.” Journal of Travel Research 51 (1): 3–11.

83.

Yuan

K.-H.

Bentler

P. M.

Kano

1997. “On Averaging Variables in a Confirmatory Factor Analysis Model.” Behaviormetrika 24 (1): 71–83.