Web 2.0 and Destination Marketing: Current Trends and Future Directions

Abstract

Over the last decade, destination marketers and Destination Marketing Organizations (DMOs) have increasingly invested in Web 2.0 technologies as a cost-effective means of promoting destinations online, in the face of drastic marketing budgets cuts. Recent scholarly and industry research has emphasized that Web 2.0 plays an increasing role in destination marketing. However, no comprehensive appraisal of this research area has been conducted so far. To address this gap, this study conducts a quantitative literature review to examine the extent to which Web 2.0 features in destination marketing research that was published until December 2019, by identifying research topics, gaps and future directions, and designing a theory-driven agenda for future research. The study’s findings indicate an increase in scholarly literature revolving around the adoption and use of Web 2.0 for destination marketing purposes. However, the emerging research field is fragmented in scope and displays several gaps. Most of the studies are descriptive in nature and a strong overarching conceptual framework that might help identify critical destination marketing problems linked to Web 2.0 technologies is missing.

1. Introduction

Today, tourism destinations are facing escalating and unprecedented levels of uncertainty and complexity and therefore have to navigate a fast-paced and turbulent business environment, wherein achieving and sustaining a competitive advantage, even over short periods [1], is progressively more difficult and challenging. This situation is particularly critical in the travel and tourism industries, where hyper-competition [2] is becoming increasingly apparent and demanding in the face of an ever changing economic, social, technological, regulatory and ecological landscape [3,4]. To achieve and maintain their competitive advantage and enhance their economic, social and environmental performance over a longer sequence of short periods in such an unstable landscape, tourism destinations and more specifically Destination Marketing Organizations (DMOs) are increasingly investing in digital technologies [5,6]. Among digital technologies, Web 2.0 technologies under the guise of social networking sites (SNSs) and social media (SM) have been increasingly adopted over the last decade by destination marketers as a cost-effective means to market destinations. Not only do Web 2.0 technologies possess features that by definition encourage a two-way interaction between DMOs and destination stakeholders (i.e., tourists, residents, the public and private sector) and allow for fast, one-to-many, many-to-many, convenient and potentially anonymous communication [7], but they also allow to partially make up for the drastic reduction of funding and marketing budgets for many DMOs at the different levels (national, regional and local) across countries and regions [8,9].

Recent scholarly and industry research has emphasized that Web 2.0 plays an increasing role in destination marketing [3,8,9]. However, no comprehensive appraisal of this research area has been conducted so far. To address this gap, this study conducts a quantitative literature review to examine the extent to which Web 2.0 features in destination marketing research that was published until December 2019, by identifying research topics, gaps and future directions, and designing a theory-driven agenda for future research. The study’s findings indicate an increase in scholarly literature revolving around the adoption and use of Web 2.0 for destination marketing purposes. However, the emerging research field is fragmented in scope and displays several gaps. Most of the studies are descriptive in nature and a strong overarching conceptual framework that might help identify critical destination marketing problems linked to Web 2.0 technologies is missing.

2. Materials and Methods

To provide an objective synopsis of the research at the intersection between Web 2.0 and destination marketing, this study adopts a quantitative literature review approach rather than a more traditional narrative literature review method, as the former one is more reproducible and offers quantitative analytical insights [10,11].

First, we identified the two research fields pertinent to the analysis: “web 2.0”, and “destination marketing”. Second, for each of the aforementioned fields, the researchers elaborated a set of meaningful keywords: the keywords identified encompass “destination marketing”, “web 2.0”, “social media”, “social network site”, as well as a list of terms covering the most popular social networking sites (SNSs) such as “Facebook”, “YouTube”, “WhatsApp”, “Weixin”, “WeChat”, “Instagram”, “Douyin”, “Tik Tok”, “QQ”, “QZone”, “Sina Weibo”, “Reddit”, “Snapchat”, “Twitter”, “Pinterest” and “Kuaishou” [12], and travel specific social networks such as TripAdvisor. Third, we used the keywords identified in the previous stage to develop search queries/strings deploying the Boolean operators “OR” and “AND”. In line with [13], the search queries were performed using the database Scopus, currently indexing more than 70 million items including almost 22,800 active serial titles from over 11,000 publishers. The database was chosen as its coverage is nearly 60% larger than Web of Science’s (WoS) [14]. We also conducted a robustness analysis and performed the same search queries in WoS and detected that the number of the documents collected from Scopus was consistently higher than the number of those collected from WoS and that those gathered using WoS represented a subsample of those covered by Scopus. Without adding any further limitation criteria, the search query returned 95 results. Fourth, we further refined the query by including further selection criteria, ensuring that the document had to be (1) published up until the end of 2019; (2) written in English; and (3) classified as an article, an editorial or review. The refined query returned 78 document results. Figure 1 illustrates the data collection process.

Last, the authors read the documents to dig, in depth, about features including the following ones: nature of the study (empirical or conceptual); research design (quantitative, qualitative, mixed methods); methods adopted in the study (case study, ethnography, regressions, etc.); type and sources of the data (primary/secondary and source); broad topic (distinguishing drivers of adoption, and use of Web 2.0 technologies for destination marketing as well as impacts); for empirical studies and if quantitative: dependent, independent, moderating, and mediating variables; sample type, size and period; and findings.

3. Results

3.1. Overall Trends and Descriptive Statistics

The evolution and development of the scientific production revolving around Web 2.0 in destination marketing can be illustrated by plotting the trend of the documents collected (see Figure 2).

As is clear from the above figure, the first few articles dealing broadly with Web 2.0 technologies for destination marketing were published between 2008 and 2011, thus witnessing that the research object of this literature review is relatively novel. This seems to reflect, with a lag of 3–4 years, the timing of the adoption of Web 2.0 platforms by marketing managers after their introduction in the marketing practice: Facebook, for instance, was launched in 2004, but started becoming part of the toolset of digital marketers starting from 2005 and so Twitter was launched in 2006 as a pivot of the podcasting platform Odeo, but the first contributions dealing with it date back to 2012 [15]. After a relevant growth over the period 2011–2013, the next relevant increase takes place over the period 2017–2019. Certainly, the recent development of this research area mirrors (1) the relatively recent adoption of Web 2.0 technologies for destination marketing purposes; and (2) the increasing scholarly interest in the role, drivers and use of Web 2.0 for effective destination marketing over the last decade. The most prolific authors based on the database are identified and illustrated in Figure 3. Interestingly, scholars have originally approached the focal research stream from two perspectives based on their expertise: on the one hand, ICTs applications to the tourism sector (e.g., D. Buhalis, U. Gretzel, and M. Mariani), and on the other hand, tourism destination marketing and management (e.g., S. Moreno-Gil and A.M. Morrison). Furthermore, we can identify recurring collaborative research within the following teams: (a) A.M. Morrison and U. Stankov; (b) A. Almeida-Santana and S. Moreno-Gil; (3) A.M. Morrison and B. Wu; (4) M.M. Mariani, M. Di Felice and M. Mura; and (5) J. Ge and U Gretzel. It appears that most of these collaborations are (1) driven by a common interest of the research team in specific destination countries located in a specific geographical region where the scholars are based (e.g., A. Almeida-Santana and S. Moreno-Gil have mainly focused on European markets), and (2) tend to focus on a specific technology or SNS because the research team is particularly knowledgeable about that Web 2.0 platform (e.g., Ge and Gretzel).

Regarding the geographic distribution of documents by country, the contributing scholars display overwhelmingly an affiliation with US, Spanish or UK academic institutions (see Figure 4). This seems to mirror the historical development of destination marketing and management as a practical and research field. Indeed, as well noted by Pike and Page [16], the first DMOs and destination marketing teams were established in the UK and US between the end of the 19th century and the first half of the 20th century.

In general, most of the contributing Authors are affiliated with North American (Purdue University, University of Florida, University of North Texas, Virginia Polytechnic State University, University of Southern California) or Asian (Honk Kong Polytechnic University, Kyung Hee University, Beijing Forestry University, Peking University) academic institutions (see Figure 5). Of the European academic institutions, the most active are Spanish (e.g., Universidad de Las Palmas de Gran Canaria) and British ones (e.g., Bournemouth University). This seems to reflect not only the historical development of destination marketing and management as a practical and research field [16] in Europe and North America, but also the growth rates of (international and domestic) tourism flows into Asian destinations over time [17].

The most active funding sponsors are based in Spain and China. As far as the types of document are concerned, 94.9% are articles, while the remaining (marginal) part (5.1%) are classified as reviews by Scopus (see Figure 6). Regarding the subject area, more than half (50.4%) of the documents pertain to the business, management, and accounting areas; 32.6% can be ascribed to the wide social sciences area, and the rest can be prevalently classified into the computer science (7.8%) and environmental sciences (3.1%) areas (see Figure 7).

3.2. Themes and Topics

By examining, in depth, the text of the articles, we have been able to cluster them based on several analytical dimensions such as (1) the nature of the study; (2) the research design (for empirical articles only); (3) the methods adopted; (4) the type and sources of the data; and (5) the topic/s, among others. The results of this analysis led to

Table 1. Break down of documents by their dimensions.

Dimension	Paper Distribution	Notable Examples
Nature of the study	Empirical: 88.5%; Conceptual or theoretical: 11.5%.	Empirical: e.g., [8,9]. Conceptual: e.g., [18,19].
Research design (for empirical)	Quant: 55.1%; Qual: 36.2%; Mixed:8.7%.	Quantitative: e.g., [20,21,22]. Qualitative: e.g., [23,24]. Mixed: e.g., [9,25].
Research methods	Basic techniques: 63.8%; Ordinary techniques: 30.4%; Advanced techniques: 5.8%.	Basic techniques: e.g., [26,27]. Ordinary techniques: e.g., [28,29]. Advanced techniques: e.g., [20,30].
Type and sources of data	Primary data: 94.2%; Secondary data: 5.8%.	Primary data: e.g., [9,31]. Secondary data: e.g., [28,32].
Level of analysis	Individual (person): 34.8%; Individual (post/review): 18.8% Organization (DMO, NTO, Convention Bureau): 46.4%.	Individual (person): e.g., [33]. Individual (posts, reviews): e.g., [30]. Organization: e.g., [9].
Topic/s	Use and usage practices (and their drivers) of social networking sites (SNSs) by DMOs/NTOs/Convention Bureaus; measurement of engagement with and contribution to DMOs/NTOs’ SNSs; drivers of travelers’ engagement with and contribution to DMOs/NTOs’ SNSs; new methodologies to measure travelers’ attitudes towards destinations and attractions by means of SNSs’ content analysis; tourists’ destination experience with DMOs’ SNSs; impact of DMOs’ SNSs on online travelers attitudes, visit intentions, influence on other travelers, and bookings.	Use and usage practices (and their drivers) of social networking sites by DMOs/NTOs/Convention Bureaus [8,9,15,23,34,35,36,37,38,39,40,41]; measurement of engagement with DMOs/NTOs’ SNSs [9,21]; drivers of travelers’ engagement with and contribution to DMOs/NTOs’ SNSs [42,43]; new methodologies to measure travelers’ attitude towards destinations and attractions by means of SNSs’ content analysis [20,22,30,41,44]; tourists’ destination experience with DMOs’ SNSs [45,46,47,48,49]; impact of DMOs’ SNSs on online travelers attitudes, visit intentions, and bookings [29,31,33,50,51,52,53,54,55,56,57,58].

:

As is clear from Table 1, of the sample of 78 documents analyzed, the majority are empirical (88.5%) and out of the empirical articles, more than half (55.1%) adopt quantitative methods, with the majority embracing basic techniques (63.8%) such as descriptive statistics, as well as ordinary techniques (30.4%) such as regression analyses. Advanced techniques are a minority, for instance [20], deploy latent Dirichlet allocation (LDA) and naïve Bayes modelling to develop tools such as dimensional salience-valence analysis and lexical salience-valence analysis that can be deployed by destination marketers. Overall and surprisingly, only very few of the studies apply social network analysis techniques [59] and none of them rely on mixed methods approaches to network analysis [60]. In addition, experiments trying to bridge the stated vs. actual online behavior gap [61] are non-existent. Most of the empirical papers (94.2%) rely on primary data, while the level of analysis is mostly (46.4%) the organizational level. Topics researched encompass (1) the use and usage practices (and their drivers) of Web 2.0 and social networking sites (SNSs) by DMOs/NTOs/Convention Bureaus [8,9,15,23,34,35,36,37,38,39,40,41,62]; (2) the measurement of engagement with DMOs/NTOs’ SNSs [9,21]; (3) the analysis of the drivers of travelers’ engagement with and contribution to DMOs/NTOs’ SNSs [42,43]; (4) new methodologies to measure travelers’ attitudes towards destinations and attractions by means of SNSs’ content analysis [20,22,30,44]; (5) tourists’ destination experiences with DMOs’ SNSs [45,46,47,48,49]; and (6) the impact of DMOs’ SNSs on online travelers’ attitudes, visit and recommendation intentions, reactions to marketing and advertising messages, and bookings [29,31,33,50,51,52,53,54,55,56,57,58]. Overall, and regardless of the topic covered, there is a prevalence of studies on Facebook (31 studies), Twitter (21 studies), YouTube (15 studies) and TripAdvisor (10 studies). Some studies analyze two or more SNSs, e.g., [23,45,46,59,63].

To enrich our analysis, we also employed content analysis and visualization techniques and performed a word frequency analysis. The most frequently used terms in the titles and abstracts of the articles in our database were graphically summarized in the word cloud of Figure 8. A word cloud is a visual representation of word frequencies found in a text, based on an algorithm that enlarges the size of the word as the frequency of the word increases. It is useful to visualize the most recurrent terms (and related themes). Based on a frequency analysis, it is interesting to observe that the most recurrent words are not only confined to the keywords used to develop search queries (e.g., “destination marketing”, “social media”, “Facebook”, “Twitter”), but also further words that either relate to the geographical object of destination marketing (e.g., “destination” is the most recurrent word, almost two times more recurrent than the circumlocution “destination marketing”, ranking third by word frequency), the main institutional actors involved directly in the destination marketing activities (e.g., “DMOs”, “destination marketing organizations” and “destination marketers” ranking respectively 4th and 6th and 38th by word frequency), the aspects related to the content of destination marketing communications (e.g., “information”, “generated content” and “UGC” ranking respectively 9th, 11th and 35th in terms of frequency), and the features of the destination (e.g., “destination image” and “destination brand”, ranking respectively 10th and 34th). Interestingly, technological aspects are apparently less represented. For instance, the keyword “Web 2.0” and its variations, despite being used to develop the search queries, display a relatively low frequency (only 84th in the ranking) and ICT is ranked 49th. However, the intention to adopt technologies seems to be more extensively studied (for instance, “technology adoption” ranks 21st). Accordingly, it seems that technology related research has focused more on users’ behaviors (namely behavioral intentions) rather than the actual functioning of the technology itself. Taken together, these descriptive statistics seem to suggest that most of the scholarly debate so far has taken a functional approach, putting the marketing function of DMOs as well as destination marketers at the center of the stage, while technological aspects have been less thoroughly examined. Some of these insights will be partially used to develop the Discussion section of this work.

4. Discussion

This Discussion section is organized in three subsections. The first subsection illustrates a novel diagram that maps out the literature reviewed and might help scholars to make sense of extant literature and identify key research streams. In the second subsection, we discuss more holistically the findings and identify the current trends and research gaps. The third subsection delineates future research directions and offers insights on the theoretical perspectives that researchers might embrace and adopt to develop their own theory-driven research agenda.

4.1. Making Sense of Extant Literature

Based on the findings, we canvassed and developed a novel diagram which is helpful to map out the body of literature reviewed. The diagram, illustrated in Figure 9, might support researchers interested in the topic to make sense of extant literature and identify key research streams.

The above diagram is a parsimonious, yet a comprehensive representation of the body of research and knowledge created to date in the area at the intersection of Web 2.0 and destination marketing. It clearly identifies three major areas: (1) the drivers of adoption and acceptance of Web 2.0 technologies; (2) the usage patterns, practices and processes of Web 2.0 technologies; and (3) the outcomes of the use of Web 2.0. We use these three areas to map out the existing literature in the following subsections.

4.1.1. Drivers of Adoption and Acceptance of Web 2.0 Technologies

The drivers of adoption and acceptance of Web 2.0 technologies by DMOs and destination marketers have been examined in relation to several factors: the opportunities and costs of developing SNSs [19,56,64,65,66]; the budget, resources and time constraints [9,36,49,67,68]; the skills, knowledge, experience and competences needed to deploy Web 2.0 technologies professionally [23,69]; the social capital and trust requirements [35]; the need to develop and nurture a virtual community [70]; and the connectivity to other ICT websites [58].

The drivers of adoption and acceptance of Web 2.0 technologies by DMOs’ SNSs users and travelers have been analyzed in relation to several factors: demographic characteristics of the users/travelers [47,54]; motivation to visit the destination [29]; information sources needed [29]; past experience of destination visitation [33]; psychological, temporal and spatial distance to/from the destination [58]; identity and self-concepts [43,53]; emotions [25]; type of platform adopted [29]; level of interactivity [15,22,53,71]; media exposure [28]; and devices used [49].

4.1.2. Usage Patterns, Practices and Processes of Web 2.0 Technologies

The usage patterns, practices and processes of Web 2.0 technologies by DMOs and destination marketers have covered several aspects such as the quality and quantity of users [50]; the type of medium deployed [39,40,72]; the content type [50,66,73,74]; the destination marketers’ posting timing and frequency [9,21]; the use of Key Performance Indicators (KPIs) to measure the effectiveness of promotional and advertising campaigns [26,58]; and the comparison and benchmarking of SNSs’ usage practices across multiple DMOs [8,34,64,67,71,75,76,77].

Research on SNSs’ users’ and travelers’ practices is relatively scant and mostly relates to the co-creation of communication with digital natives [27] and influencers [51].

4.1.3. Outcomes of the Use of Web 2.0

The outcomes of the use of Web 2.0 on DMOs and destinations have been discussed in relation to several aspects: the marketing effectiveness of Web 2.0 initiatives [41,64,68]; the development of tools to improve the attractiveness of a destination and its attractions [20]; destination brand co-creation [37,46]; engagement with DMO’s SNSs [8,9,21]; destination knowledge and awareness [78]; destination image restoration after crises [38]; online reputation of a destination [63]; choice of optimal/suitable channels/media for segmentation and communication [45,79]; and the effect of DMOs’ SNSs on tourism flows and hotel occupancy [50].

The outcomes of the use of Web 2.0 on destinations’ potential, current, and past tourists and visitors have been examined in relation to several factors: tourists’ sentiment about a destination [20,30]; tourists’ attitudes towards a destination [31]; tourists’ destination image formation [22,29,57]; users’ intentions to visit and recommend a destination [28,33,55]; engagement with DMOs’ Web 2.0 platforms [9,21,27]; and intention to develop positive word of mouth and to share travel experiences online [18,55].

4.2. Current Trends and Research Gaps

A number of major current trends emerge from the analysis of the findings displayed in Section 3 and the diagram illustrated in Section 4.1. First, most of the research revolving around Web 2.0 and destination marketing is empirical in nature and contributions with a high degree of conceptualizations are rather scant, except for a few works with a varying degree of conceptual robustness [18,65,80,81]. Consequently, there is a cogent need to build an overarching and updated conceptual framework. More specifically, future research might draw on the diagram of Figure 9 as a departing point to develop a more articulated and comprehensive conceptual framework whose core elements might still be (1) the drivers of the adoption and acceptance of Web 2.0 technologies by DMOs and DMOs’ SNSs’ users and travelers; (2) the usage patterns, practices and processes of Web 2.0 technologies by DMOs, destination marketers, and SNSs’ users and travelers; and (3) the outcomes of the use of Web 2.0 usage on destination performance (measured in terms of tourism flows, occupancy, etc.) and on destinations’ potential, current, and past tourists and visitors. While building such a conceptual framework is beyond the purpose of this study, suitable extensions of the diagram developed in this work might help scholars to develop such a framework. Second, despite that most of the studies conducted are empirical in essence, the majority of them are descriptive and look at the “what” of the use of Web 2.0 technologies by Destination Marketing Organizations (DMOs) and destination marketers, often focusing on differences in the adoption of Web 2.0 across different destinations and DMOs [8,76]. This seems in line with the prevalence of a functional approach putting the marketing function of DMOs as well as destination marketers at the center of the stage, while technological aspects have been less thoroughly examined. Future research should certainly look at the “what” from multiple perspectives and adopt a multi- and inter-disciplinary approach, blending marketing, computer science and information systems approaches. This might allow to illustrate more comprehensively the role of different information and communication technologies, digital platforms and devices in connecting stakeholders within and outside the destinations [82,83,84]. Third, even those studies trying to address the “why” often examine in a compartmentalized manner either a few of the drivers of users’ engagement with DMOs’ social networking sites (SNSs) [42] or simply measure users’ engagement based on user generated content (UGC), descriptive statistics [75] or descriptive analytics [21]. More efforts should be made to understand if and to what extent cultural factors and language barriers can affect engagement with UGC consistently with other electronic Word-of-Mouth studies within the tourism management literature [85,86]. Furthermore, there are indeed very few studies trying to combine the analysis of user generated content (UGC) and interviews with destination marketers [9]. This prevents researchers trying to explain destination marketers’ and travelers’ behaviors from providing more depth to their findings and achieve a more comprehensive understanding of the phenomena analyzed.

Fourth, and despite the growing deployment of data science and big data analytics in management [87] and tourism management [88,89,90], only a handful of studies have developed innovative methodologies to measure travelers’ attitudes towards destinations and attractions by means of SNSs’ content [20,30,44]. Certainly, more emphasis should be given to mixed and multi-methods research [91] that looks to be severely underrepresented. For instance, the deployment of mixed methods adopting a social network approach would be more than welcome [60] to shed light on the use of Web 2.0 within destination marketing settings. Moreover, there is an urgent need to build on experimental research and try to overcome the stated behavior–actual behavior gap [61] when focusing on users’ online behaviors on DMOs’ SNSs, as recent research has found that content posted on generalist social media is a major driver of travel decision making and planning, beyond engagement [92].

Last, the impacts of DMOs’ SNSs on destination performance and firms operating within destinations have been very rarely examined empirically [31,50]. More research is needed in the area as the effectiveness of the use of web 2.0 technologies to improve the attractiveness and economic, social and environmental performance of a tourism destination is still largely underexplored and measures of return on investment on Web 2.0 activities are extremely rare and rudimentary [68]. Researchers interested in destination competitiveness and performance might find it useful to team up with scholars examining the role of digital technologies in the wide tourism, travel and hospitality settings and examine more closely the online destination marketing–destination performance nexus.

4.3. Future Research Directions and Indication of Theoretical Perspectives for a Theory-Driven Agenda

Based on the findings of this study and the previous Discussion subsections, we put forward some reflections on the research areas identified that need further development and offer insights on the theories that might inform such development. First, even if some of the studies have partially mentioned the need for DMOs and destination marketers to deal with budget constraints and upskilling needs [9,23,36,49,67,68,69], research addressing human and technological resource needs for DMOs (given their objectives) is somehow missing. Accordingly, future research might operationalize more explicitly resource and capabilities constraints by building on theoretical frameworks such as the resource-based view (RBV) [93,94] as well as the dynamic capabilities theoretical framework [95] and applying them to DMOs. Second, as far as the acceptance and adoption of Web 2.0 technologies in destination marketing are concerned, established models of the acceptance and adoption of technologies have been very rarely applied and, where applied, they have covered mostly end users’ online behaviors. For instance, there is only one case of application of a variation of the technology acceptance model (TAM) [96,97,98] to understand destination marketers’ acceptance and adoption of Web 2.0 technologies [35] and a very few cases [48] of application of the wider theory of planned behavior (TPB) [99,100] or the theory of reasoned action (TRA) [101]. Overall, more intellectual efforts might be made to understand the drivers that motivate destination marketers to adopt or choose a specific social media mix over others, as well as to explore and dissect drivers of usage of DMOs’ SNSs for web users. Third, while a handful of studies have dealt with users’ intentions to visit and recommend a destination after the use of DMOs’ SNSs [28,33,55], all of them are confined to analyze stated intentions and behaviors. Accordingly, future research should bridge the perception–actual behavior gap and delve into actual behaviors by means of realistic experiments drawing on a wide set of social psychology theories including social influence theory [102,103,104]. Last, in all the empirical work conducted on the users of DMOs’ Web 2.0 platforms, no clear distinction has been made between tourists and residents and most studies have not clearly identified how and to what extent different destination stakeholders interact on DMOs’ SNSs. In the very few cases where residents are mentioned explicitly, they are pooled together with tourists [29]. This constitutes an additional research gap and calls for more research to shed light on the similarities and differences in users’ behaviors across different groups of stakeholders. Indeed, different stakeholders might have different perceptions of a tourism destination [105,106] and this should be accommodated both conceptually and empirically. Accordingly, more studies building on the stakeholder theory [107,108,109] are welcome, as they might help scholars to shed light on Web 2.0 technologies adoption and usage behaviors across different stakeholders’ groups.

5. Conclusions and Future Research Directions

This literature review has generated several major key findings. Firstly, research revolving around Web 2.0 and destination marketing is quite fragmented in scope, encompassing a few disconnected research themes and streams. This study has developed a diagram that maps out the literature reviewed and might help scholars to make sense of the extant literature and identify key research streams. The diagram is a parsimonious yet comprehensive representation of the body of research and knowledge created to date in the area at the intersection of Web 2.0 and destination marketing. It clearly identifies three major areas: (1) the drivers of the adoption and acceptance of Web 2.0 technologies; (2) the usage patterns, practices and processes of Web 2.0 technologies; and (3) the outcomes of the use of Web 2.0. Future research might draw on the diagram and its three components as the building blocks to develop a more articulated and comprehensive conceptual framework.

Secondly, we have crafted some reflections on the research areas that need further development and have offered insights on four future research directions and theories that might inform such research directions and development. More specifically, more attention should be paid to human and technological resource needs for DMOs at different levels of government, whose study might benefit from theoretical perspectives such as the resource-based view (RBV) [93,94] and dynamic capabilities [95] theories; the drivers and antecedents of Web 2.0 adoption and acceptance, that might be closely inspected by using theories like the theory of reasoned action (TRA) [101], the theory of planned behavior (TPB) [99,100] and the resulting technology acceptance and adoption models [96,97,98]; actual online behaviors of online users of DMOs’ SNSs, whose examination might leverage social psychology theories like social influence theory [102,103,104]; and the similarities and differences in user behaviors and approaches across destination stakeholders that might be conducted by adopting stakeholder theory [107,108,109].

Thirdly, studies at the intersection between Web 2.0 technologies and destination marketing should move from answering “what” questions to answering “how” and “why” questions. This shift needs to be supported conceptually by blending different theories (including those mentioned above), encouraging multi-disciplinary research, and mixing different methods Accordingly, more studies adopting mixed methods [91] are needed as they might allow to address simultaneously both “how” and “why” research questions, with a combination of theory building and theory testing research techniques and approaches. Data science techniques [87,88,89] could be fruitfully deployed to support the aforementioned shift and to generate insights from UGC content produced on destinations’ SNSs: this might enable researchers and destination marketers to develop and exploit descriptive and predictive analytics. The latter ones might be useful to create destination business intelligence [98] useful for destination planning, development and marketing, ultimately potentially translating into increased tourism flows and enhanced economic, social and environmental destination performance.

This work is not without limitations. First, while our search queries appear comprehensive and capture most of the scholarly literature in English produced until 2019 in the focal field, this review might be extended in the future by juxtaposing additional literature that will be published after 2019 and in other languages. Second, while we focused on the most comprehensive database indexing scholarly research in the social sciences [11], future research might take into account also contributions indexed by search engines such as Google Scholar.