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Abstract

Using bibliometric analysis, quantitative content analysis, qualitative thematic analysis, and spatial analysis, this paper analyzes the intellectual landscape of research on tourism resilience over the past two decades. The results show that tourism resilience research has not yet established a close collaborative network at the international level, although the themes of tourism resilience research have been diversified. Due to the outbreak of the COVID-19 pandemic, research on tourism resilience can be divided into two stages. Climate change and the pandemic are the two major factors affecting tourism resilience at destination, organizational, and individual levels. Additionally, we identified five major themes of tourism resilience research. Finally, we provide three suggestions for rebuilding a new paradigm of tourism development in the post-pandemic era. It is hoped that the study contributes to promoting tourism resilience studies and provokes critical thought about whether tourism development need a “pandemic turn.”

Keywords

tourism resilience bibliometric analysis thematic analysis content analysis COVID-19

Introduction

Prior to the outbreak of COVID-19, various actors, including governments, communities and enterprises, usually adopted the sustainability paradigm to formulate development policies and practices (Anderies et al., 2013). In the context of globalization and climate change, however, this development paradigm seems to be incapable of fully addressing environmental and social issues (Anderies et al., 2013). From a sustainability perspective, the nature of our world is in a stable state (Lew et al., 2016), and thus sustainability indicators, as traditional assessment methods adopted by researchers, usually focus on current conditions, which leads to the misidentification and misinterpretation of social and ecological impacts (Salazar, 2022).

Since the mid-2000s, research adopting the perspective of resilience “as an alternative development model” (Lew et al., 2016, p. 19) or a complementary concept for sustainability (Espiner et al., 2017) has significantly increased. Originating in physics and developed in ecology and disaster management, the concept of resilience currently has wide acceptance in both the natural and social sciences (Davidson, 2010). According to Zolli and Healy (2013), resilience is “the capacity of a system, enterprise, or a person to maintain its core purpose and integrity in the face of dramatically changed circumstances (p.7).” This capacity becomes increasingly important because of the growing complexity caused by globalization and climate change, which leads to multiscale and multilevel interactions and dynamics (Anderies et al., 2013). Individuals, groups, and societies obtain substantial benefits from global mobility in a fast-changing world while also facing increasing risk incurred by the new socioeconomic paradigm (Biggs et al., 2011).

The outbreak and worldwide spread of the COVID-19 pandemic is convincing proof that we are living in a “risk society” (Beck, 1992; Constantinou, 2021; Giritli Nygren & Olofsson, 2020; Mansouri & Sefidgarbaei, 2021) and that uncertainty is all around us (Callaghan, 2021; Kay & King, 2020; King et al., 2021). Adapting to risk (Bradshaw et al., 2012; Dilling et al., 2015; Eakin et al., 2016; Rauter et al., 2020; Wamsler, 2014) and uncertainty (Barnett, 2001; Perrin & Tyrrell, 2020; Tashman & Rivera, 2016; Wierenga & Moore, 2020) and preventing, responding to, and recovering quickly from crises (Inam, 2013; Marana et al., 2018; McCartney et al., 2021) have become an urgent issue that individuals, organizations, and societies must tackle.

The tourism industry has been regarded as a highly sensitive and vulnerable industry (Aramberri & Butler, 2005; Bai & Ran, 2022; Biggs, 2011; Chen, 2010; Dube et al., 2021; Duro et al., 2021; Hu et al., 2021; Kennedy et al., 2022; Liu, 2003; McKercher, 1993; Smith & Eadington, 1992; Sönmez et al., 1999; Zheng et al., 2022) because both natural and social factors, such as economic crises (Papatheodorou et al., 2010), crime (Michalko, 2004) and terrorism (Sönmez et al., 1999), infectious diseases (Butler, 2020; Duro et al., 2021; Hall et al., 2021), tsunamis(Calgaro & Lloyd, 2008), earthquakes (Mazzocchi & Montini, 2001), floods and debris flows (Tsai & Chen, 2011), and climate change (Amelung et al., 2007; Nyaupane & Chhetri, 2009; Santos-Lacueva et al., 2017; Scott et al., 2019), can have tremendous negative impacts on the sustainable development of the industry. These impacts can further increase the vulnerability of tourist destinations, especially those that highly depend on the tourism sector (Calgaro & Lloyd, 2008; Farrell et al., 2020; Sheller, 2021), and of individuals such as the local residents of tourist destinations (Seraphin et al., 2020), tourists (Zheng et al., 2021), and tourism practitioners (Lombardi et al., 2021; Luu, 2021).

Before the outbreak of the COVID−19 pandemic, “tourism resilience” has become an important theme in tourism research (Arrowsmith & Inbakaran, 2002; Calgaro & Lloyd, 2008; Calgaro et al., 2014; Cheer & Lew, 2017; Espiner & Becken, 2014; Hall et al., 2017; Larsen et al., 2011; Lew, 2014; Lew et al., 2016; Slocum & Kline, 2017; Strickland-Munro et al., 2010). Considering the complexity of the tourism system, Hall et al. (2017) proposed an analytical framework for tourism resilience research, suggesting that tourism resilience can be examined from three perspectives: individual, organizational, and destination. Similar to their opinion, Prayag (2020) divided tourism resilience into three levels: the resilience of the tourism system, the tourist destination, and the tourism community, that is tourism resilience at the macrolevel; at the meso-level, tourism resilience is the resilience of different types of tourism organizations, tourism networks, and value chains (or the supply chain); and, at the microlevel, tourism resilience is the resilience of tourism practitioners, tourists, local residents, and other individuals related to tourism. Over the past decade, a large body of literature has formed from these three perspectives.

Over the past 2 years or so, the heavy blow to the global tourism industry caused by the COVID-19 pandemic (Cheung et al., 2021; Gössling et al., 2020; Rivera et al., 2021; Škare et al., 2021; Wieczorek-Kosmala, 2022) has once again proven the vulnerability of the tourism industry (Arbulú et al., 2021; Berbekova et al., 2021; Cave & Dredge, 2020). Facing their greatest challenge ever, tourism destinations, enterprises, and practitioners need to develop rigorous crisis management policies and procedures and to formulate adaptation strategies (Do et al., 2022). In addition, the global tourism shutdown has reduced population mobility on a global scale (Ioannides & Gyimóthy, 2020). This development has undoubtedly had an impact on the natural environment (Cooper & Alderman, 2020; Venter et al., 2020) and on tourism consumption and tourist behavior (Hall et al., 2021; Wen et al., 2021). These two factors, in turn, are closely related to the adaptation and recovery of the tourism sector. Therefore, the relationship between the COVID-19 pandemic and tourism provides a realistic perspective for exploring the resilience of tourism (Utkarsh et al., 2021; Yang, Zhang et al., 2021), encouraging tourism scholars and practitioners to think about the way in which the industry can recover quickly (Yeh, 2021) and about the directions of tourism development in the post-pandemic era (Yang, Zhang et al., 2021): going back to the old way of growth-oriented overtourism (Cheer et al., 2019) or taking an alternative route in the future (Cave & Dredge, 2020; Hall et al., 2021; Ioannides & Gyimóthy, 2020; Sharma et al., 2021).

Tourism researchers across the world have created a large body of literature. A review of the research on a specific area can, not only help us understand the progress of the research, but also inform us about the research gaps and the future research direction. In addition to narrative reviews, systematic reviews (Barasa et al., 2018; Brown et al., 2017; Gibbes et al., 2020), bibliographic reviews (Su et al., 2019; Utkarsh et al., 2021), and text-mining techniques (Loureiro et al., 2020) have emerged as new methods for tourism researchers when conducting literature reviews. All review approaches have their strengths and limitations. Thus, some researchers have used mixed methods to review tourism research themes (Cheng et al., 2018; Yang, Zhang et al., 2021), providing a “realist review” approach (Spector et al., 2019) for tourism studies. In this paper, the development of tourism resilience research is examined by combining bibliographic analysis, quantitative content analysis, qualitative thematic analysis, and spatial analysis.

Three questions are considered in this review article: (1) In the process of producing knowledge related to tourism resilience, what kind of knowledge landscape has been created by actors, including scholars, institutions, and academic journals? (2) Has there been the progress in the theoretical understanding of tourism resilience and in the development of research on tourism resilience at different scales? (3) How far has the COVID-19 pandemic impacted tourism resilience research? Based on our answers to these questions, the article concludes with suggestions for improving tourism resilience in the future. The research contributes to expanding the focus of tourism resilience studies, promoting tourism scholars to discuss the choice of tourism development routes in the post-pandemic era.

Methods

Data Collection

Our bibliographic data were obtained from the Web of Science (WoS), because it is one of the leading citation indices and research intelligence platforms in the world. The terms that we used to identify the relevant literature were “resilience,” “resiliency,” “tourism,” “tourist,” and “hospitality.” We selected data from the WoS core collection, including SCI-EXPANDED (1900–2022), SSCI (1900–2022), A&HCI (1975–2022), and ESCI (2017–2022). The search query was set as follows: TS = (touris* OR hospitality) AND (resilienc*). The time span was set as “All Years,” the literature type was set as “Article” and “Review,” and the language was set as “ENGLISH.” After applying the above searching criteria, we obtained a total of 1,295 records on April 22, 2022. The data set was then saved in the form of “Full Record and Cite References” and exported in plaintext format, and in the form of “Full Record” and exported in Excel format for subsequent inspection.

Further refinement included selecting those papers that focus on tourism resilience. In addition to discussing the concept of tourism resilience, researchers have also empirically explored tourism resilience from three perspectives (Hall et al., 2017; Prayag, 2020). Thus, a manual inspection of all papers in the sample was completed, checking whether these papers discuss the four topics of tourism resilience: theoretical analysis of tourism resilience, destination (community) resilience, organizational resilience, and individual resilience. Two investigators independently performed manual inspections by sequentially reading through the title, keywords, abstract, and full text of each paper. A few articles that did not analyze tourism resilience (e.g., an article discussing the resilience of ideological notions of “proletarian” tourism in the Soviet Union), and some papers that only briefly deal with tourism resilience, were removed from the sample. As a result of this screening process, the final sample consisted of 445 papers. The earliest article identified in the sample was published in 1994, and papers on tourism resilience have increased rapidly since 2018 (Figure 1). Finally, four datasets were obtained for follow-up analysis: the bibliographic data of 445 articles (in plaintext), the sample consisted of 445 papers, the keywords of 431 articles (some papers do not have keywords) with publication years (in Excel sheet), and the keywords of 85 papers discussing COVID-19 and tourism resilience (in Excel sheet).

Figure 1.

Annual distribution of the papers on tourism resilience.

Research Tools

We conducted bibliometric analysis with CiteSpace. To visualize the relationship between scientific studies, experts in bibliometrics have developed a number of software packages, and CiteSpace is an excellent tool for bibliometric analysis (Niazi, 2016) for three reasons. First, this package continues to deploy advanced techniques and algorithms for the effective visualization of scientific literature, enabling researchers to use this package to review the literature in the field (Niazi, 2016). Second, Chen provides strong support for users, and detailed information about how to use this application can be found in his book (Chen, 2016), articles (Chen, 2006), and website (Chen, 2014). Third, scholars from various areas have used this software package to identify the development of their fields (Chen, 2006; Luo et al., 2017; Su et al., 2019; Wei et al., 2015; Zhang, Wang, Sun, et al., 2020), showing its effectiveness in mapping the intellectual landscape of a domain.

We applied KH Coder for text mining and qualitative content analysis. KH Coder is a free application developed by Japanese scholar Koichi Higuchi that can perform content analysis and build semantic networks for a variety of texts in English, Chinese, Japanese and other languages (Higuchi, 2016). Thus, it is well received by some researchers and used in various disciplines (Blasco-Gil et al., 2020; Tang et al., 2018; Ylijoki & Porras, 2016). Keywords are important components of an article. We used KH Coder to identify the co-occurrence network of keywords.

We used hotspot analysis in ArcGIS to detect the hot zones of global tourism resilience research. The diversity of the locations of authors is an important sign of a mature and rich research field. GIS software facilitates the visualization of spatial information (Liu & Zhu, 2008; Mennis et al., 2013) and an improved understanding of the location, distribution, and relationship of spatial phenomena (Miller et al., 2003; Yuan, 2001). ArcGIS is one of the most commonly used commercial GIS software programs worldwide due to its powerful capabilities in spatial visualization and spatial analysis. Hotspot analysis is a spatial statistical method that can help us identify the clustering of spatial phenomena, and ArcGIS provide hot spot analysis in its toolbox.

Research Procedure

Data processed by CiteSpace

Chen (2014) provides a clear idea for visualizing and analyzing scientific literature. In tourism studies, some researchers have used CiteSpace to carry out bibliometric analysis. According to the research process developed by tourism researchers (Jiang, Ritchie, & Benckendorff, 2019; Su et al., 2019) and considering the particular research purpose of our study, we conducted our analysis by CiteSpace (6.1.R15.7.R5W) published in 2021 in the following way:

(1) Set basic parameters. The overall time span was from 1994 through 2022. The time slice was set as 1 (year), the threshold value for selecting cited items from each slice was fixed as TOP 50, and the value of “Threshold Interpolation” was set by default.

(2) Examine the data with repeated operations. We identified four main problems of the bibliometric data. First, we found that if a bibliographic record contains both the date of early publication and that of official publication, the software package could not recognize the bibliographic record. Therefore, if the record had two dates, we removed the date of early publication.

Second, we found that if the full name of an author and the same author’s last name plus initials simultaneously existed in CiteSpace, the package treated this author as two researchers. Thus, we removed the full names of all authors in the file.

Third, in addition to the keywords (in the field DE) provided by the author, some bibliographic records include “KeyWords Plus” terms (in the field ID). We found that if CiteSpace used these two types of keywords at the same time, the result was not desirable. Thus, we replaced the label “ID” with “AB” for the “KeyWords Plus” terms. Additionally, we merged the synonyms such “COVID-19,” “the COVID-19 pandemic,” and “the coronavirus pandemic” into one word (“COVID-19”), using an alias file saved in the project folder.

Finally, we found that in the WoS database, the address information of researchers in the United Kingdom (the UK) were recorded at the country/regional level (England, Scotland, Wales, and Northern Ireland) rather than at the national level of the UK. We tried to replace these country/regional names in the address field with the UK, but found that the package could not recognize this spatial information. Therefore, we separately counted these four places in CiteSpace. After exporting the number of authors in different countries/regions produced by CiteSpace, however, we aggregated the data for the above four countries/regions into the data for the UK.

(3) Examine the cooperation networks, the co-cited networks, and the most active areas of tourism resilience research. We selected “Author,”“Country,” and “Institution” as the node type to create the maps of cooperation networks, respectively. Next, we selected the node type as “Reference,” “Cited Author,” and “Cited Journal” to produce the co-citation maps, respectively. Finally, we selected “Keywords” as the node type to identify the clusters of tourism resilience research, and used “Burst Detection” to identify the most active area (Gómez et al., 1999) of studies on tourism resilience.

Finally, we explain several terms that are used in this article. The betweenness centrality score of a node in a network is a key indicator measuring the extent to which the node connects two or more large groups of nodes with itself in-between (Chen, 2014, p. 28). The betweenness centrality score of a node provided by CiteSpace is between 0 and 1 (Chen, 2014, p. 28). Additionally, the package uses the silhouette value to measure the quality of a clustering configuration. If CiteSpace creates 7 to 10 clusters with 10 or more members, and each of the clusters has a silhouette value greater than 0.70, we can consider this is a desired result, which indicates a good range of the number of clusters (Chen, 2014, p. 50). The modularity Q is also an important indicator for measuring the overall qualities of the network, telling us “the extent to which a network can be decomposed to multiple components(Chen, 2014, p. 82).” Chen (2014) suggests that 0.7141(>0.7) is a relatively high value for the modularity Q.

Data processed by KH coder

To obtain a desirable result, we refined the keywords in the Excel sheet. First, we checked the synonyms. For example, “COVID-19,” “the COVID-19 pandemic,” and “the coronavirus pandemic” were merged into “COVID-19.” Second, we converted all keywords to lowercase, avoiding the upper- and lower-case versions of the same term being treated as different keywords. Third, the keywords consisting of more than one word were extracted from the Excel sheet and imported into a “forced pick up” text file (a stop words file). Using the “Select Words to Analyze” tool, we imported the file into the package, and the package regarded the multiple word terms in the file as one word concept. After conducting the “Pre-Processing” operation, “_” was used by the application to connect words in a phrase, and these words were labeled “TAG.” Using the tools for analyzing words, we obtained the frequency list of the keywords. Finally, we set the minimum term frequency as 5, set the words included in building the network as top 60, and obtained the co-occurrence networks of the keywords.

We used the same steps as above to analyze the data set that contained the term “COVID-19” in the keywords field. We obtained the frequency list and the co-occurrence networks of the keywords.

Finally, after removing the words “tourism” and “resilience,” we saved the 31 most frequent keywords in a text file, which was adopted as the coding rule file. Using the “Crosstab” command in the application and then selecting “H5” for “Coding Unit” and “Year” for “Crosstab,” we obtained the percentage of keywords to which the code applies with respect to year of publication. The tabulation results were transformed into a bubble plot, which shows annual changes in the frequency and popularity of the keywords.

Qualitative thematical analysis

In a recent paper, Yang, Zhang et al. (2021) used quantitative content analysis and qualitative thematic analysis to review early COVID-19 research in tourism. Spector et al. (2019) provided a systematic review of the resilience of rural New Zealand using thematic analysis and bibliometric analysis. This study synthesizes the methods of these researchers, and the results produced by bibliographic analysis and quantitative content analysis were used to inform the reading of articles and categorization of themes. In the process of reading the articles, we constantly rechecked the results of bibliographic analysis and quantitative content analysis. As a result, the data was refined and optimized for the visualization of the results. The results were explained based on the review of the relevant literature. Through this interactive process, we obtained the major themes of tourism resilience research.

Data processed by ArcGIS

In this study, we used the frequencies of countries/regions of origin of authors as the attribute data. After carrying out the “country (region) cooperation networks” operation in CiteSpace, we obtained a data set of the frequencies of countries (regions) of origin of authors who published papers on tourism resilience, and this data set was in HTML format. Next, we imported the data into Microsoft Excel, and the data of the country/region names and the data of the frequencies of authors were extracted and save in another Excel sheet. The label “Fre” was placed in the first cell of the sheet, which indicates the number of authors saved in the first column, and the label “COUNTRY_NAME” was placed in the second cell of the sheet, which indicates the country/regional names saved in the second column. This sheet was imported into ArcGIS. Using the “Join” function in ArcGIS, we connected the Excel sheet with the attribute table of the world map in ArcGIS, with the country/regional name as the field to be joined. Next, we used “Symbology” to visualize the frequencies and conducted hotspot analysis to find countries (regions) that were statistically significant hot spots.

Results

The Intellectual Landscape of Research on Tourism Resilience

Weak cooperation networks

Tourism resilience research at different scales shows that cooperation and mutual assistance (social capital) (Brown et al., 2017; Choi et al., 2021; Chowdhury et al., 2019; Cirer-Costa, 2021; Espiner & Becken, 2014; Holladay & Powell, 2013; Kimbu et al., 2019; Luthe et al., 2012; Musavengane & Kloppers, 2020; Williams et al., 2020) are core elements for improving local, organizational, and individual resilience. Unfortunately, this research shows that scholars, institutions, and countries/regions engaging in tourism resilience research have not developed a close and extensive cooperative network.

First, scholars on tourism resilience have not built close partnerships. The author collaboration network contributing to tourism resilience research consisted of 1,072 nodes (authors) and 1,744 collaboration links, with a density of 0.003 (Figure 2A). The top 10 authors who have published 5 or more papers are presented in Figure 2A. Hall has published 13 papers, and he has been a leading scholar in tourism resilience studies. There were different degrees of cooperation among highly productive authors, resulting in some small cooperative groups such as the group centered around Hall, and that centered around Biggs (Figure 2B). Our results demonstrate that the betweenness centrality scores of all nodes were zero, indicating that no scholar played an important role in connecting different research teams.

Figure 2.

Co-occurrence analysis of authors: (A) top 10 authors in terms of co-occurrence counts and (B) collaboration network of some top authors.

Second, institutions interested in tourism resilience research have not established close networks. A total of 599 nodes (institutions) and 775 links between these nodes were identified, with a density of 0.0043 (Figure 3A). Figure 3A shows the top 10 institutions that published more than 7 or more papers on tourism resilience. Among them, the University of Canterbury (21), the University of Queensland (14), the University of Otago (13) were the top three institutions. Centered on these universities, relatively close cooperative relationships were established (Figure 3B). The University of Canterbury took a bridging role between different research networks, with the betweenness centrality score of 0.10 (indicated by the purple circle in the Figure 3A). This result indicates that universities in Australia and New Zealand played a key role in tourism resilience research.

Figure 3.

Co-occurrence analysis of institutions: (A) top 10 institutions in terms of co-occurrence counts and (B) collaboration network of some top institutions.

Third, the spatially uneven development of research into tourism resilience was identified. The spatial distribution of the papers on tourism resilience demonstrates the main countries/regions where researchers have paid attention to theories on and practice of tourism resilience (Figure 4). Scholars from 80 countries/regions published articles on tourism resilience, demonstrating that tourism resilience has received attention from scholars in various regions of the world (Figure 4). The map clearly shows that scholars in North America, Australia and New Zealand, Western and Northern Europe, and East Asia produced the majority of articles on tourism resilience. The spatial analysis shows that North America including the United States (the USA, 79) and Canada (13), and Australia (69) were the hotspots of tourism resilience research (Figure 5).

Figure 4.

Research papers published by countries/regions (1994–2022).

Figure 5.

Hot spots of tourism resilience research (1994–2022).

Finally, relatively strong collaborative networks had been built between developed countries/regions involved in tourism resilience research. Figure 6A demonstrates the top 10 countries that published papers on tourism resilience. A total of 83 nodes (countries/regions) and 233 links between these nodes were detected, with a density of 0.0685 (Figure 6A). Some cooperative networks formed centering around the USA, around the UK (using the data of England) (Figure 6B), and around Australia. England, the USA, and New Zealand had the betweenness centrality scores of 0.68, 0.25, and 0.21, respectively. This result demonstrates that developed countries/regions played a key role in producing the knowledge of tourism resilience. However, researchers in developing countries with high tourism vulnerability, such as in the Maldives, did not participate in the global network.

Figure 6.

Co-occurrence analysis of countries/regions: (A) top 10 countries/regions in terms of co-occurrence counts and (B) collaboration network of some top countries.

Diversified development of tourism resilience research

Empirical studies on tourism resilience demonstrate that diversification contributes to building resilience (Amoamo, 2021; Baral, 2014; Broegaard, 2022; Choi et al., 2021; Holladay & Powell, 2013; Jamaliah & Powell, 2018; Lim & Won, 2020; Luthe et al., 2012; Ruiz-Ballesteros, 2011). Fortunately, the contents and perspectives of tourism resilience knowledge and the platforms for producing and disseminating this kind of knowledge have been diversified.

First, the theoretical explanations of tourism resilience research are diverse. Figure 7 shows the top 10 cited authors in the field of tourism resilience research, with co-citation counts of 86 and above. Among the 10 highly cited authors, three-fifths were involved in tourism studies, including Hall (152), Becken (108), Ritchie (103), Gossling (105), Biggs (95), and Lew (95), while the other two-fifths focused on broader resilience research, including Holling (113), Adger (98), Walker (95), and Folke (88). The research of these four scholars has provided a theoretical basis for tourism resilience research. Holling (1973), for the first time, introduced the concept of “resilience” into the field of ecology. After developing this theory, Holling attracted many researchers’ attention to the concept of “resilience” (Espiner & Becken, 2014; Larsen et al., 2011). Walker et al. (2004) proposed four key elements that construct resilience, namely, latitude, resistance, precariousness, and panarchy; meanwhile, they used the basin of attraction to describe the connotation of resilience, making the concept clearer and more precise. Adger (2000) defined the concept of social resilience and analyzed the relationship between social resilience and ecological resilience. His research has contributed to exploring the socio-ecological resilience of tourism destinations/communities. Folke et al. (2002) proposed a framework for responding to rapid, complex change by maintaining and building adaptive capability, arguing that structured scenarios and active adaptive management are two important tools to build resilience in social-ecological systems. These concepts and tools have been accepted and applied by scholars in tourism studies (Gabriel-Campos et al., 2021; Hartman, 2016; Islam et al., 2018; Nguyen et al., 2021; Phan et al., 2021).

Figure 7.

Co-citation analysis of authors with the top 10 cited authors.

In recent years, researchers in the field of tourism have also continued to make tourism resilience research a product of the dialog between resilience science and tourism studies. Hall and Gossling (another collaborator was Scott) have worked together on tourism resilience research. Early on, they focused on global climate change and tourism resilience (Scott, Hall, & Gössling, 2016; Scott, Hall, & Gossling, 2016; Scott et al., 2019). Since the outbreak of COVID-19, they have turned their attention to the relationship between the outbreak and tourism resilience (Gössling et al., 2020; Hall et al., 2021). They suggested that the pandemic may promote a redirection of tourism development in some cases, and may lead to nationalist policies in some countries (Hall et al., 2021). Furthermore, they also pessimistically noted that while enhancing the resilience of global tourism requires worldwide cooperation and efforts, achieving such a positive shift will be difficult (Hall et al., 2021).

Becken’s research has also focused on global climate change and tourism resilience (Becken, 2013; Hughey & Becken, 2014; Loehr et al., 2022; Nalau et al., 2017), providing a framework for evaluating the resilience of tourism subsystems to climate change (Becken, 2013). The recent research conducted by Ritchie and collaborators focused on tourism crises and disaster management (Jiang, Ritchie, & Benckendorff, 2019; Mair et al., 2016; Ritchie & Jiang, 2019; Wang & Ritchie, 2013), a concept that is very closely linked to tourism resilience. Richie and collaborators also used the concept of organizational resilience to discuss how to deal with crises and risks in tourism organizations (Jiang, Ritchie, & Verreynne, 2019). Biggs discussed the resilience of protected areas and marine tourism (Biggs, 2011; Biggs et al., 2015, 2016; Biggs, Ban et al., 2012; Cumming et al., 2015), and Hall was his key collaborator. One of his articles concerned the resilience of informal tourism enterprises in Phuket, Thailand, which was an earlier study on the resilience of tourism enterprises (Biggs, Hall et al., 2012). Lew (2014), Lew et al. (2016) focused on tourism community resilience. Considering the rate of change and the scale of tourism interest, he proposed a model for understanding and managing tourism community resilience (Lew, 2014).

Both scholars from resilience science and those from tourism resilience research have become the highly cited authors of tourism resilience research. This illustrates that tourism resilience researchers need to obtain theoretical insights from general resilience studies, to continuously develop and construct new resilience frameworks for tourism in terms of the characteristics of tourism systems, to analyze and measure tourism resilience at different levels, and to find ways to enhance tourism resilience.

Second, the perspectives of tourism resilience research have been diversified. The top 10 highly cited studies (the co-citation counts were 28 and above) were all related to tourism resilience (Figure 8); however, these studies explored different aspects of tourism resilience. The book published by Hall et al. (2017) was the only non-journal article study, which proposes three levels of tourism resilience. Other papers explore organizational resilience in the tourism sector (Orchiston et al., 2016), disaster resilience in the hotel industry (Brown et al., 2017), the relationship between tourism resilience and sustainability (Espiner et al., 2017), the tourism crisis, risk, and resilience (Mair et al., 2016; Prayag, 2018; Ritchie & Jiang, 2019), community resilience (Bec et al., 2016), and the relationship between the COVID-19 pandemic and tourism resilience (Hall et al., 2021; Sigala, 2020).

Figure 8.

Co-citation analysis of references with the top 10 cited literature.

This result suggests that tourism researchers have been citing more literature on tourism resilience, especially those dealing with tourism resilience at a certain scale, than that of resilience studies. This indicates that tourism researchers have developed a specific research paradigm for the study of resilience, and tourism resilience research has become a relatively independent branch in the field of resilience science. Additionally, two papers related to COVID-19 were highly cited papers, signaling that the profound impact of the global pandemic on tourism has stimulated a new wave of investigation in tourism resilience.

Third, the academic outlets for producing and sharing the knowledge related to tourism resilience were diverse. We identified 1,076 publications, and the top 10 journals with co-citation frequencies over 115 are shown in Figure 9. These journals can be divided into two categories: tourism journals and other publications focusing on the environment (Global Environmental Change, cited 157 times, ranked sixth) and ecology (Ecology and Society, cited 129 times, ranked ninth). Two publications from other research areas illustrate that tourism resilience research was concerned the link between tourism resilience research and broader resilience research. In terms of tourism journals, Tourism Management (331), Annals of Tourism Research (294), and the Journal of Sustainable Tourism (278) ranked first through third. Numerous other tourism and hospitality journals such as Current Issues in Tourism, Tourism Geography, Tourism Management Perspectives, the Journal of Travel Research, and the Journal of Hospitality and Tourism Management, were also important sources for producing tourism resilience research results. The results here reaffirm the above conclusion that the tourism research community, as a well-established academic community with a large number of high-impact academic journals, has provided a variety of open forums for sharing tourism resilience research and advancing research in this area.

Figure 9.

Co-citation analysis of publications with the top 10 cited publications.

Climate change and COVID-19: two major factors influencing tourism resilience

The COVID-19 pandemic has so far significantly changed the knowledge landscape of tourism resilience research. Figure 10A shows the 10 most frequently used keywords. In addition, we obtained 18 clusters, and the lowest silhouette value was 0.786 (>0.7). Fifteen of these clusters had more than 10 members. Additionally, the modularity Q was 0.674, a value close to 0.7. Figure 10 demonstrates the 10 largest clusters. Using the default parameter settings (the minimum duration was 2), CiteSpace did not show any burst keywords. After setting the minimum duration as 1, we obtained five burst terms (Figure 10B). According to Figure 10, we argue that the outbreak of the COVID-19 pandemic has divided the research process of tourism resilience into two distinct phases: the first phase of tourism resilience research focusing on exploring how tourism can adapt to different types of changes (risks); and the second phase related to the outbreak of the pandemic, which has become a global “stress test” for reassessing and rethinking tourism resilience. Before the pandemic, responding to climate change and reducing carbon dioxide emissions had become a global consensus. A large body of literature focuses on the resilience of tourism, especially that of those tourism destinations/communities that are vulnerable to climate impacts (Alexander, 2016; Chin et al., 2019; Cocolas et al., 2016; Dingle & Stewart, 2018; Dogru et al., 2016, 2019; Fang et al., 2018; Jamaliah & Powell, 2018; Jiang et al., 2015; Klint et al., 2012; Luthe & Wyss, 2016; Luthe et al., 2012; Njoroge, 2014; Santos-Lacueva et al., 2017; Scott, Hall, & Gössling, 2016; Sovacool, 2012; Wyss et al., 2015). In the early stage of the pandemic, the severity of the chaotic situation interrupted research on climate change and tourism resilience, causing many researchers to turn their attention to the relationship between the pandemic and tourism resilience. Recently, some researchers have published articles on improving tourism’s capacities to adapt to climate change and on reducing the vulnerability of tourism systems (Cavallaro et al., 2021; Gössling & Higham, 2021; Jarratt & Davies, 2020), indicating that research on tourism resilience is getting back on track.

Figure 10.

Top 10 keywords, the keyword clusters, and the keywords with strongest.

The content analysis of the keywords produced by KH Coder confirmed the conclusion in the previous paragraph that the pandemic has divided the research process of tourism resilience into two phases (Figure 11). Before the outbreak of the COVID-19 pandemic, climate change was a hot theme in tourism resilience research, and the main objective of the research during this stage was to identify ways to enhance the adaptive capacity of the tourism industry and tourist destinations, especially in the context of global climate change. The outbreak of the pandemic has significantly reduced research efforts on this topic (Figure 11), and we have explained the possible reasons in the previous paragraph. In addition, since 2010, community resilience has emerged as a key term. Since 2018, organizational resilience has become popular; and recently, employee resilience has attracted attention (Figure 12). This research situation indicates that the way in which tourism organizations and practitioners can improve their ability to adapt to risks and crises became a major concern for many scholars (Brown et al., 2017, 2018, 2019; Ivkov et al., 2019). Since the outbreak of the COVID-19 pandemic, tourism resilience researchers have quickly turned their attention to the relationship between the pandemic and tourism resilience, and exploring the hospitality industry from the perspective of organizational and individual resilience in the context of crisis has become the focus of research (Brown et al., 2021; Burnett & Johnston, 2020; Knight et al., 2020; Melián-Alzola et al., 2020; Núñez-Ríos et al., 2022; Schwaiger et al., 2022; Sobaih et al., 2021; Teng et al., 2020).

Figure 11.

Annual change in high-frequency keywords.

Figure 12.

Co-occurrence network of the keywords.

Themes of Research on Tourism Resilience

Co-occurrence of the keywords

The co-occurrence network of the keywords produced by KH Coder gave more fine-grained clustering (Figure 12), and a total of seven clusters were detected. These research themes include tourism resilience and climate change, psychological capital and organizational resilience, community resilience, COVID-19 and tourism resilience, tourism destinations and socio-ecological systems, community tourism and socio-ecological resilience, and destination resilience. The above research themes illustrate that tourism resilience research has adopted individual, organizational, and destination dimensions (Hall et al., 2017) to better understand tourism resilience and thus to increase the adaptive and absorptive capacity of tourism. Tourism resilience at destination and community levels have gained more attention. With the outbreak of COVID-19 as a watershed moment, the great negative impact of COVID-19 on the tourism industry shows the urgency and need for tourism resilience research.

Co-occurrence of the keywords related to COVID-19

The co-occurrence networks of the keywords related to COVID-19 show six clusters (Figure 13). The topical areas include the recovery of the tourism and hospitality industry from the COVID-19 pandemic, the resilience of small and medium tourism enterprises, tourism employees and organizational resilience, risk and disaster management and tourism resilience, destination resilience, and climate change and community resilience. Over the past 2 years, the COVID-19 pandemic has demonstrated the importance of tourism resilience research, and it has also provided researchers and practitioners with a real stress test for how to improve tourism resilience and to respond to terrible crises. The way in which the tourism industry, especially the hospitality industry, has survived the pandemic and recovered quickly has become a major concern of researchers and practitioners alike. Additionally, researchers have again focused on climate change and tourism resilience.

Figure 13.

Co-occurrence network of the keywords related to COVID-19.

Five themes of tourism resilience research

According to the clustering of the keywords produced by CiteSpace and the clustering of the keywords created by KH Coder, and based on the reading of the full texts of the selected articles, we summarize the research progress on tourism resilience, with the following five themes.

Definition and conceptualization of tourism resilience

Tourism systems have different scales and a large number of actors, resulting in various developmental forms. Therefore, scholars have used different perspectives to examine tourism resilience. Kuščer et al. (2022) emphasize that resilience involves systems evolving, responding, and adapting to and from transformation processes, including learning from exceptional scenarios. Jamaliah and Powell (2018) argue that tourism resilience has four dimensions: social, governance, environmental, and economic. Hall et al. (2017) reviewed the literature on resilience and tourism and suggested that tourism resilience can be understood from the individual, organizational and destination perspectives.

Centered around the concept of tourism resilience are a series of kindred terms, including sustainability, vulnerability, risk, and crisis. Many scholars have explored the relationship between these concepts and resilience. In terms of sustainability and resilience, Espiner et al. (2017) suggest that the two terms are complementary. However, Strickland-Munro et al. (2010) regard sustainability as a traditional concept that focuses on current circumstances, whereas resilience is an emergent term that highlights that situations may change in the future. Additionally, Schianetz and Kavanagh (2008) argue that resilience is a key element of sustainability, and they developed a systemic indicator system that integrates resilience thinking, adaptive management, and system dynamics modeling to examine the sustainability of tourist destinations. Considering the viewpoints of different researchers, Calgaro et al. (2014) provided a comprehensive explanation of the similarities and differences between the concepts of sustainability and resilience. Regarding the similarities of the two terms, both concepts pay attention to how to best guarantee the existence of the system and how to reach a state of balance. The most significant difference between the two terms is with regard to their presupposition about the essence of the world: sustainability highlights a situation of steadiness and balance, while resilience focuses on a state of change and disorder.

Regarding vulnerability and resilience, Becken (2013) argues that resilience research is complementary to research on vulnerability: resilience thinking is based on complex systems theories and develops scientific ways to cope with coupled issues emerging in the society, while vulnerability research is actor-directed and highlights decreasing the vulnerabilities of particular groups. However, Calgaro et al. (2014) argue that these two terms are two sides of a coin, with both having coexisting qualities of a tourist destination system. Therefore, for specific tourism research issues, researchers simultaneously measure these two states. For example, in the context of climate change, Dogru et al. (2019) used six variables (food, water, health, ecosystem, human habitat, and infrastructure) and 10 factors (doing business, political stability and non-violence, control of corruption, rule of law, regulatory quality, social readiness, social inequality, ICT infrastructure, education, and innovation) to assess the vulnerability and resilience of the tourism industry and that of the overall economy.

Crises and risks are key scenarios to measure tourism resilience, and crisis management has been regarded as a means to increase resilience in tourism (Filimonau & De Coteau, 2020; Lew, 2014; Paraskevas et al., 2013; Prayag, 2018). Risk and crisis assessment, response to crises, and recovery from crises are important parts of tourism resilience management. Paraskevas and Quek (2019) proposed a five-stage resilience management framework for tourism organizations, which includes sensing the risk landscape, risk assignment, risk treatment, crisis response, and crisis recovery. Considering tourism resilience management in the context of the pandemic, Kuščer et al. (2022) divided the process into three stages: the response phase, the recovery phase, and the restart phase.

Tourism resilience at the macroscale

As far as tourism resilience is concerned at the macroscale, researchers mainly have discussed the influencing factors of destination resilience. Factors that help increase destination (community) resilience include learning and knowledge (Broegaard, 2022; Choi et al., 2021; Espiner & Becken, 2014; Ruiz-Ballesteros, 2011), diversity (Amoamo, 2021; Baral, 2014; Broegaard, 2022; Choi et al., 2021; Holladay & Powell, 2013; Jamaliah & Powell, 2018; Lim & Won, 2020; Luthe et al., 2012; Ruiz-Ballesteros, 2011), local participation and self-organization (Baral, 2014; Bethune et al., 2022; Broegaard, 2022; Choi et al., 2021; Espiner & Becken, 2014; Ruiz-Ballesteros, 2011; Sheller, 2021), connectivity, cooperation, and social capital (Choi et al., 2021; Cirer-Costa, 2021; Espiner & Becken, 2014; Holladay & Powell, 2013; Luthe et al., 2012; Musavengane & Kloppers, 2020; Williams et al., 2020), good governance (Choi et al., 2021; Holladay & Powell, 2013; Luthe & Wyss, 2016; Powell et al., 2009), citizenship (Weaver et al., 2022), local resources (Matarrita-Cascante & Trejos, 2013), innovation (Bethune et al., 2022), leadership (Bethune et al., 2022), technology (Bethune et al., 2022), and communication (Cartier & Taylor, 2020; Maureira & Stenbacka, 2015).

Understanding the real state of destination/community resilience is also a priority for scholars, and some researchers have developed frameworks for assessing destination (community) resilience, especially places that are vulnerable to disasters. For example, using surrogates for assessing latitude, resistance, and precariousness, Becken (2013) proposed a tourism-specific framework for evaluating the resilience of tourist destinations, and applied it to Queenstown-Wanaka in New Zealand. (Tsai et al., 2016) used four dimensions to assess community resilience, which include environmental fragility, community attachment, disaster prevention awareness, and adaptive responses; they adopted this framework to examine three communities in Taiwan that are regularly exposed to the threats of typhoons and flooding. Tsao and Ni (2016) used a community in Taiwan that experienced a typhoon as a case study, and they argue that communities respond to disasters through three dimensions, including sensitivity-stability, maladaptive capacity-recovery, and transformation.

Tourism resilience at the mesoscale

Researchers on tourism organization resilience have focused on factors that can enhance resilience. Organizational resilience in the tourism sector is central to sustainable tourism management (Biggs, Hall et al., 2012). Empirical studies show that factors influencing the resilience of tourism organizations include organizational traits (Nyaupane et al., 2021), preparedness (Nyaupane et al., 2021; Orchiston, 2013; R.-Toubes et al., 2020), material resources (R.-Toubes et al., 2020) such as human capital (Barasa et al., 2018; Biggs, 2011; Biggs et al., 2015) and intangible resources such as organizational culture (Barasa et al., 2018; Brown et al., 2017), decision-making (Nyaupane et al., 2021; R. Toubes et al., 2020), innovation (R. Toubes et al., 2020), information management (Barasa et al., 2018), collateral pathways and redundancy (Barasa et al., 2018), governance processes (Barasa et al., 2018), leadership practices (Barasa et al., 2018; R. Toubes et al., 2020), long-term planning (Brown et al., 2017; Nyaupane et al., 2021; Orchiston, 2013; R. Toubes et al., 2020), social capital (Brown et al., 2017; Chowdhury et al., 2019; Ngoasong & Kimbu, 2016; Wyss et al., 2015), lifestyle factors (Biggs et al., 2015; Biggs, Hall et al., 2012), corporate social responsibility (CSR) (Torres et al., 2001), diversification (Weaver et al., 2021), and entrepreneurship (Tervo-Kankare, 2019) .

Scholars have developed tools to differentiate types of organizational resilience and to assess the resilience of tourism organizations. Organizational resilience consists of three main elements: absorption, coping, and adaptation (Neise et al., 2021). Additionally, tourism organizational resilience can be divided into two forms: planned resilience and adaptive resilience (Prayag et al., 2020). Planned resilience is “a function of planning for and preparing for future crises,” while adaptive resilience is a function of “adapting to change and disruptions” (Barasa et al., 2018, p. 500). Using six variables including business size, business situation, impact on turnover, cessation of trading estimation, eligibility for government assistance, financial resources, and renting premises, Ntounis et al. (2022) developed a Business Resilience Composite Score (BRCS) to measure business resilience. Jiang et al. (2021) argue that organizational resilience is constantly changing due to internal and external factors, and thus, they proposed a dynamic resilience framework based on three dynamic capability steps (sensing, seizing, and transforming), explaining the way in which tourism organizations develop resilience elements at each disaster management stage.

Tourism resilience at the microscale

Tourism researchers have mainly focused on the resilience of tourism practitioners, especially employees. Psychological capital is a key term in organizational studies and human resources research, and resilience is one of the four dimensions that construct psychological capital. Empirical studies show that in the tourism industry, the psychological capital of owners/managers of small hotels can give hope and optimism to their employees, helping them to tolerate the current situation and arrange for future change (Pathak & Joshi, 2021); in addition, CSR has a positive impact on employee resilience (Mao et al., 2021). The positive psychological capital of employees in hotels has a positive impact on their job satisfaction and organizational citizenship behaviors (Jung & Yoon, 2015). High psychological capital of employees contributes to enhancing their work engagement, with resilience appearing to be the second most important indicator of psychological capital (Karatepe & Karadas, 2015). Additionally, optimism and resilience are two moderator variables between affective organizational commitment and turnover intention (Obeng, Zhu et al., 2021), while psychological capital helps to reduce work-family conflict, family-work conflict, and turnover and absence intentions (Karatepe & Karadas, 2014).

Some researchers have used the term employee resilience, composed of hardiness, resourcefulness, and optimism, to identify its influencing factors and resulting effects. Empirical results demonstrate that experienced general managers have increased resilience from broadening their experience and from wisely regulating their emotion (Haver et al., 2014), and the resilience of entrepreneurs helps to predict their business success (Ayala & Manzano, 2014). The resilience of women working in various sectors, including the hospitality industry, not only displayed a negative relationship with burnout but also showed a moderated relationship with organizational and family support (Gupta & Srivastava, 2021). Examining employees in tourism organizations in Egypt, a study demonstrated a direct relationship between employees’ resilience and business continuity, and distributive justice and trust partially mediate the relationship between the two factors (Saad & Elshaer, 2020). The resilience of travel agency employees reduces their intention to leave the job and enhance their work engagement. Employee resilience contributes to both the life satisfaction of tourism business operators and organizational resilience (Prayag et al., 2020). In addition, abusive supervision is a moderator of the relationship between resilience and turnover intention (Dai et al., 2019).

A small number of studies have paid attention to the resilience of residents and that of tourists (consumers). In an overtourism context, Seraphin et al. (2020) identified resilient locals are a type of four patterns of local residents. In the context of COVID-19, studies demonstrate that the psychological resilience of consumers using hotel services has a negative effect on their perceived health risk and emotional risk, and tourists plan to return to enjoy hotel services (Peco-Torres et al., 2021). In addition, “travel fear” caused by the pandemic leads to different coping methods. This situation enhances people’s psychological resilience, and they tend to exhibit prudent travel behaviors (Zheng et al., 2021). Veréb et al. (2020) argue that personal value orientation is key to formatting the resilience of a traveler, and they identified travelers with strong cosmopolitan conviction as a resilient tourist segment.

COVID-19 and the future way of tourism development

Two development routes have clearly emerged as to how tourism destinations, organizations, and individuals can respond to the crisis and recover from the negative impacts of the pandemic (Yang, Zhang et al., 2021). Some tourism scholars have questioned the model of tourism growth (overtourism) prior to the outbreak (Cheer et al., 2019; Cheung & Li, 2019; Milano et al., 2019). The unprecedented crisis and impact of the pandemic on global tourism is a testament to the foresight of these scholars. However, after the pandemic, the tourism development model that existed before the pandemic is likely to be taken back up in countries/regions around the world to quickly revive the economy (Hall et al., 2021; Ioannides & Gyimóthy, 2020; Jin et al., 2022). At the same time, the suppressed demand for tourism and mobility is bound to explode (Jin et al., 2022). The May Day holiday travel policy implemented by the Chinese government in 2021 is also likely to be a strategy to stimulate consumption adopted by other countries in the post-pandemic era. Thus, the first path is to return the development of tourism to its pre-pandemic trajectory, that is, to promote economic development by stimulating tourism consumption (Hall et al., 2021; Ioannides & Gyimóthy, 2020; Jin et al., 2022). For most countries, especially those that depend heavily on tourism, recovering from the pandemic may be their top priority in the post-pandemic period.

Other researchers have questioned the logic of capitalist development prior to the outbreak (Benjamin et al., 2020; Cave & Dredge, 2020) and the international organizations related to tourism that speak for this implicit logic (Gössling et al., 2020; Ioannides & Gyimóthy, 2020). Some scholars are calling for the need to use the pandemic as an opportunity to radically change the previous model of tourism growth (overtourism) and substitute it with the diverse economies model (Cave & Dredge, 2020; Ioannides & Gyimóthy, 2020). Assessing the prospect of tourism development, some scholars are optimistic about its future transformation, believing that the tourism industry may change into a new global development mode featured by sustainability, society’s well-being, collective action on climate change, and local participation (Sharma et al., 2021), while others seem to be slightly pessimistic about achieving this alternative vision (Hall et al., 2021).

Conclusions and Suggestions

Using mixed methods, we comprehensively review the research on tourism resilience over the past two decades. Although the contents and perspectives of tourism resilience research have been diversified, actors in tourism resilience research have not established a close collaborative network at the international level. The five themes of tourism resilience research that were identified are conceptualization, destination (community) resilience, organizational (industry) resilience, individual resilience, and the direction of tourism development in the post-pandemic age.

Climate change and the COVID-19 pandemic are the two major factors influencing tourism resilience. The impact of climate change on tourism is long-term. As the research schedules of tourism scholars gradually return to normal, examining factors affecting tourism resilience, especially climate change, will again be the focus of research. Though the pandemic will eventually be over, it has had major impacts on the tourism industry, which must be remembered by tourism scholars and practitioners. We agree with some researchers (Cave & Dredge, 2020; Hall et al., 2021; Ioannides & Gyimóthy, 2020) that tourism resilience research and practice need a “pandemic turn” to build a new paradigm of enhancing tourism adaptability in the future, which can facilitate a fundamental shift in the mode of tourism development.

Various actors participate in tourism systems. Systems are nested across various scales (Williams et al., 2021), and changes in one scale may affect the entire system (Walker et al., 2012, p. 26). Meanwhile, the complex adaptive system perspective suggests that the individual components of a system cause dynamic changes in the system as a whole rather than emphasizing that individual system components are in isolation from the larger system (Biggs, Ban et al., 2012; Williams et al., 2021). Thus, “optimizing and controlling components of a system in isolation of the broader system results in a decline in resilience” (Walker et al., 2012, p. 150).

The outbreak and spread of COVID-19 illustrate the interaction of different systems very well. In the context of the COVID-19 pandemic, individuals, communities, regions, and countries and the globe are nested and interact with each other. Working together to overcome the pandemic with a more inclusive and open mind rather than narrow nationalistic views is fundamental to helping the global tourism industry overcome this unprecedented crisis. Based on the above findings and thinking, we offer the following suggestions for the future development of tourism resilience research and practice.

Suggestion 1: Building greater international cooperation in tourism resilience research. As a tourism researcher, we should firstly build a close network between different individuals, institutions, countries. We suggest that key scholars on tourism resilience establish a society of tourism resilience research and education, which would include various branches or areas of focus, such as destination resilience research, organizational resilience research, individual resilience research, and research on tourism resilience education. It would be beneficial to start a new academic journal focusing on tourism resilience at different scales (e.g., the Journal of Tourism Resilience, which can be a sister journal to the Journal of Sustainable Tourism). Regular online and offline academic seminars should also be held, promoting the rapid development of a close and extensive cooperative network for tourism resilience research, and encouraging researchers from countries with high tourism vulnerability to express their views about tourism resilience. Furthermore, as the pandemic eases, we hope that more scholars will take a critical perspective to analyze tourism resilience and provide creative and insightful theories for research in this area.

Suggestion 2: Examining the relationship between tourism resilience at different scales. Tourism systems are complex and dynamic. Various actors at different scales interact with each other. The results show that organizations and communities are inextricably linked (McManus et al., 2008), and employee resilience helps to predict entrepreneurial success (Ayala & Manzano, 2014) and organizational resilience. A resilient organization (leader) helps employees cope successfully with uncertainty (Pathak & Joshi, 2021). Dividing tourism resilience into three scales helps us to recognize the structure of the concept. However, exploring how such different levels of resilience interact with each other not only contributes to improving the theoretical understanding of tourism resilience, but also helps build tourism resilience from a systematic thinking perspective.

Suggestions 3: Sharing the knowledge of tourism resilience with different stakeholders. Agreeing with Hall et al. (2017), we are not optimistic about the prospect that the route of global tourism development will fundamentally change in the near future. In the post-pandemic age, advocating for global collaboration will most likely lead to strong opposition from nationalists with a strong emphasis on national interests and from groups who have suffered greatly from unjust globalization promoted by capitalism (Cheer et al., 2019). However, consistent communication and trust are two key elements of effective collaboration, while competing demands and poor relationships are key barriers (Jiang & Ritchie, 2017). There is still time for tourism scholars, especially those concerned with tourism resilience, to make a difference.

First, educating future practitioners to understand the vulnerability of tourism (Ioannides & Gyimóthy, 2020). Tourism researchers usually take the role of educators. Therefore, it is beneficial to increase content for tourism resilience courses, improve the psychological resilience of future tourism practitioners through better curriculum design, and, in particular, rebuild the confidence of current hospitality and tourism management students for a more resilient tourism world.

Second, communicating our voices to the public and top policy makers. Studies show that public participation (Choi et al., 2021), citizenship (Weaver et al., 2022), and good governance (Choi et al., 2021; Holladay & Powell, 2013; Luthe & Wyss, 2016; Powell et al., 2009) help building resilience. We believe that in the era of social media, tourism scholars should continue to express their critical views on tourism resilience in academic journals; in addition, through the effective use of various social media, they can change the understanding of the tourism development model currently held by the public, governments, and international organizations. Therefore, providing MOOCs on tourism resilience, visualizing research findings and making the vulnerability of tourism more understandable to various stakeholders outside universities and research institutes should be part of the important work that tourism scholars undertake in the future.

In summary, researchers need to identify whether different stakeholders have developed a more positive awareness of the future during the pandemic and whether they are willing to make self-sacrifices for the common good (Lalot et al., 2021). Only then will it be possible to lead tourism on a resilient journey.

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study (both authors) was (were) supported by a grant from the National Social Science Fund of China (NSSFC) (18BJY117).

ORCID iD

Keshuai Xu

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Visualizing the Development of Research on Tourism Resilience With Mixed Methods

Abstract

Keywords

Introduction

Methods

Data Collection

Research Tools

Research Procedure

Data processed by CiteSpace

Data processed by KH coder

Qualitative thematical analysis

Data processed by ArcGIS

Results

The Intellectual Landscape of Research on Tourism Resilience

Weak cooperation networks

Diversified development of tourism resilience research

Climate change and COVID-19: two major factors influencing tourism resilience

Themes of Research on Tourism Resilience

Co-occurrence of the keywords

Co-occurrence of the keywords related to COVID-19

Five themes of tourism resilience research

Definition and conceptualization of tourism resilience

Tourism resilience at the macroscale

Tourism resilience at the mesoscale

Tourism resilience at the microscale

COVID-19 and the future way of tourism development

Conclusions and Suggestions

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iD

References