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Article

Evolutionary Relationship between Tourism and Real Estate: Evidence and Research Trends

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Faculty of Urban and Regional Planning, Cairo University, Giza 12613, Egypt
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Doctoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences (MATE), 2100 Godollo, Hungary
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Faculty of Management, Bournemouth University, Poole BH12 5BB, UK
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Institute of Economics, Faculty of Social Sciences, Eötvös Loránd University, 9700 Szombathely, Hungary
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Department of Tourism and Hospitality Management, Faculty of Economics and Business, University of Debrecen, 4032 Debrecen, Hungary
*
Authors to whom correspondence should be addressed.
Sustainability 2022, 14(16), 10177; https://doi.org/10.3390/su141610177
Submission received: 21 July 2022 / Revised: 10 August 2022 / Accepted: 11 August 2022 / Published: 16 August 2022

Abstract

:
With the growing number of academic studies being published each year, scientific knowledge is expanding at an unparalleled rate. Therefore, analyzing the scientific production in a particular research area to identify future research directions and streams has become inevitable. This study adopted a two-step methodological approach—bibliometric (294 articles) and content-based analyses (63 articles)—to dissect tourism and real estate literature. Using different analytical modules and software to answer the six proposed research questions, the study findings reveal that the tourism and real estate literature still does not follow a specific research direction but is rather intertwined with many other research areas. Additionally, the results highlight some distinctive points in the tourism and real estate literature, including how it is predominantly composed of practical studies based on primary data and applied in various spatial units as case studies (e.g., coastal areas, cities and national and international units). Finally, this study explains how the findings will be beneficial for identifying the future research agenda in the tourism real estate scientific field by providing a clear roadmap for the research streams of this field.

1. Introduction

The real estate sector is one of the most lucrative sectors in the global economy, and it is one of the metrics for measuring the economic growth of any nation [1,2]. The real estate sector affects, and is affected by, other economic sectors, including tourism. In other words, it can be considered a cross-cutting economic sector. There is no clear or precise definition of the “real estate” term; the definition varies according to the issuer, whether it be an entity, institution, government, ministry, firm or individual. However, it can be said that most definitions of the term have two dimensions: first, real estate as a physical context, which refers to different types of properties and lands with a right of utilization and specific uses, and second, real estate as a business, which refers to the selling, purchase or renting of different real estate units [3].
The link between real estate and tourism is shaped by the way the former contributes to the latter. Tourism as a system consists of various intertwined components to make a strong bond. These components can be summarized in what is known as the “5 A’s of tourism”: attractions, activities, accessibility, accommodation and amenities [4,5]. The aforementioned two dimensions of real estate highlight how this sector is involved in the five different components of tourism.
The first tourism component is attraction, which is considered the most powerful influencer of all other components [6,7,8,9]. As the attraction is the first thing that tourists pay attention to, it is the start of any tourism activity, and is ranked at the top of the tourism supply chain [6]. Tourism attractions can be divided into two main types: natural (e.g., beaches, mountains, protected areas, wildlife, water resources, landscape, fauna, flora and safari) and manmade attractions (e.g., cultural sites, casinos, theme parks, monuments, discos/clubs, gambling centers, museums, stadiums, zoos and entertainment centers) [6,9]. Based on this classification of tourism attractions, as well as the definition of real estate, the real estate sector is involved in tourism through manmade attractions: these include a range of different land uses and buildings subject to many real estate features, such as purchase, profit, leasing and structure.
The second tourism component is activities, which represent the main factor that can make any ordinary tourism trip extraordinary. Tourism activities can be physical (such as trekking, hiking, diving, festivals/partying, swimming and boating) or nonphysical (such as sunbathing and relaxing). All these different kinds of tourism activities are associated with tourism attractions in specific geographical locations, and most of these locations are designed, and may be operated, by real estate companies [10]. Consequently, the real estate sector is linked to the tourism activities component.
The third tourism component is accessibility, which includes the different kinds of infrastructure and transportation means that tourists use to reach tourism destinations quickly, securely and appropriately [11]. Accessibility and mobility for different properties are divided into three main groups: surface (such as roadways and railways), air (i.e., flights) and water transportation (such as cruise ships) [11,12]. In the tourism industry, accessibility plays an important role in determining the market price of different real estate physical elements, especially tourism elements (such as hotels), because real estate is a heterogeneous product that is directly affected not only by its constituent features, but also by the various characteristics of the surrounding environment [13]. Additionally, in some cases, transportation means could be a tourism attraction; for example, tourism trains are often managed by real estate firms.
The relationship between real estate and the fourth component of tourism, accommodation, is clear. Tourism accommodation refers to places or accommodations where travelers/tourists stay [14]. There are two main types of tourism accommodations: (a) serviced accommodations, which represent accommodation units that present prepaid services (such as star-category hotels, guest houses, homestays, lodges and motels), and (b) self-catering accommodations, which refer to nonservice provider accommodations (such as youth hostels and tourist villages) [14,15]. Therefore, these accommodation units are literally express real estate, as they are considered physical properties that have a specific use and clear and predefined facilities, and they can be sold or rented.
Amenities, the fifth tourism component, represent the variety of facilities and services required by tourists/travelers at various levels of accommodation and tourist destinations [16]. Amenities include, but are not limited to, food, recreation, entertainment, multipurpose zones, picnic areas, signage, emergency services and other sports facilities (e.g., gyms and fitness courts) [17]. All these tourism amenities are constantly improved, which, in turn, affects the value of different uses of properties in the tourist area. Accordingly, it can be said that these different tourism amenities not only affect the tourism sector, but also extend their impact to the surrounding real estate, whether residential or service areas.
It is worthwhile mentioning that all the highlighted relationships between real estate and the fifth tourism industry component are bidirectional or reciprocal relationships. In other words, tourism and real estate mutually influence one another directly or indirectly. For example, the presence of many tourist amenities in an area directly increases the prices of different properties in the area, affecting the social level of residents of this geographical area in the future. Alternately, the existence of properties with different uses may play an important role in enhancing the tourism activities in this area, since these properties could act as service supporters for tourist areas by providing self-catering accommodations, which, in turn, may help to boom tourism in the area.
In addition to the strong relationships between real estate and the five components of the tourism industry, many relationships have emerged between these two fields, which has led to the emergence of some terms, such as “tourism real estate”. Tourism real estate emerged in the 1990s, and has been addressed in different scientific directions and areas [14,18]. For example, in the US, Canada and some European Union countries, with the start of the boom of various tourist properties and the emergence of large economic returns that attracted the attention of many investors, many research areas linking tourism with real estate have appeared, such as timeshare [18]. Timeshare was the focus of academic researchers at the time, especially after the conflicting views on the positive and negative impacts of this phenomenon [19]. This reinforced the study of this timeshare phenomenon by many researchers (such as [20,21,22,23]), thereby, deepening the relationship between tourism and real estate, especially from the economic perspective. Another example of the appearance of the tourism real estate term comes from China, where the term first appeared in 1996: [18] discussed three main models for the development of regional tourism real estate: the free, planning and hybrid models. Moreover, the integration between tourism and real estate has been supported by many economic driving forces. The four forces are: high market demand, competition between enterprises, technological innovation and different national policies [18].
Additionally, one of the important forms of the relationship between tourism and real estate is their connection to sustainability. On the one hand, real estate affects the achievement of sustainability in various tourism areas and destinations. For example, in coastal tourist areas, carbon emissions from different real estate products affect the tourism resources in the area, which in turn causes damage to these resources, and this constitutes an obstacle to achieving the principles of sustainability in the tourism sector. For this reason, many tourism buildings are seeking to obtain an LEED certificate (Leadership in Energy and Environmental Design) in order to be classified as green buildings; this is one of the pillars of the green tourism destinations concept [24,25]. On the other hand, the various tourism development policies and strategies, in turn, affect the concept of sustainability in real estate. For example, the failure of establishing a legal framework for the transformations in land uses and real estate uses that accompany the different tourism development policies may affect the sustainability of real estate in terms of unplanned changes in its prices and material value, as well as the waste of many different investments; this is inconsistent with the principles of achieving sustainability for real estate products [24].
In summary, this interesting relationship between tourism and real estate is considered the catalyst of this study and its main justification. This research aims to present a detailed and comprehensive understanding of the relationship between the tourism and real estate sectors from the literature perspective by answering the following six research questions (RQs):
  • RQ1: How has the relationship between tourism and real estate evolved, what are the main research streams, and which ones require further attention?
  • RQ2: How has the tourism industry dealt with real estate: as an investment or as a development?
  • RQ3: What are the spatial units (cities, coastal areas, tourism destinations, etc.) in which tourism studies have discussed the real estate sector?
  • RQ4: What are the used data collection methods in tourism and real estate studies (survey, questionnaire, official data, etc.)?
  • RQ5: What are the most significant real estate areas of interest in which tourism studies are concerned?
  • RQ6: What are the key methodological frameworks of tourism studies in the real estate field: theoretical or practical frameworks (case study)?

2. Materials and Methods

This study used a two-step methodological approach—bibliometric and content-based analyses—to answer the specified RQs. First, the bibliometric analysis approach was used to analyse the relationship between tourism and real estate, thus answering RQ1. Then, content-based analysis was used to highlight the trends in the selected literature, thus answering RQ2–RQ6. In general, the conceptual kernel of the content analysis was to discover the hot and blind spots in the dataset. The combination of bibliometric and content analyses increased the precision and reliability of the findings, and reduced the subjective bias that might exist in some other literature review approaches. Before conducting these two analytical approaches, the data collection process was reviewed.

2.1. Data Acquisition

This research depended on the WOS and Scopus databases to extract the required literature. Using the snowball technique, we conducted a brainstorming session with 14 researchers in the tourism and real estate field, and found two main groups of keywords linked together through the Boolean operator “AND”—“tourism” AND “real estate”. After that, research queries were identified as shown in Table 1.
This research query resulted in about 294 documents, which represent the main dataset of this research. Regarding the criteria for selecting the eligible documents, all documents published in 2022 have been excluded because the year has not yet ended. Furthermore, all duplicate documents in the two databases (WOS and Scopus) were excluded. Regarding the language criterion, although there is a debate about language bias in the tourism literature review articles, many studies support the idea that place-specific research should be enhanced by studies conducted in the native language of the area, so that they can be generalized and applied [26]. Therefore, place-specific research can be trustworthy and provide reliable findings. On that basis, in our study, all the languages of the articles were taken into consideration without any kind of exclusion. The study considered the article title as the main search field to reduce irrelevant records. Finally, all the information of the selected publications was exported, such as citation information (i.e., authors, publication year, sources and citation count), bibliographical information (i.e., affiliations, language and publisher), abstracts and keywords.

2.2. Analysis Levels

To present a comprehensive description of the evolutionary relationship between tourism and real estate, this research was developed based on two main levels of analysis: bibliometric and content-based analysis.
Bibliometric analysis was first proposed at the end of the 1980s by Campbell, and has since been used as an approach for analyzing scientific production in various scientific fields, from medicine to social sciences [27]. Even though the approach is old, it is still considered one of the most important techniques for analyzing different literature. Bibliometric analysis consists of several analytical modules using direct statistical techniques to analyse literature, such as the analysis of authors, keywords, countries, universities and so on [28,29]. Given the multiplicity of different analytical modules for bibliometric analysis, this research relied on seven different modules: scientific production, documents, journals, authors, institutions, countries and keywords. For each analytical module, different bibliometric techniques were used for both statistical analysis and visualization.
Several software packages can be used to conduct bibliometric analysis, including (but not limited to) BibExcel, Sci2 Tool [30], CitNetExplorer [31], SciMAT [32], VOSviewer [33] and R [34]. Each software has a different analytical capacity and focuses on conducting specific functions. In other words, each software has its strengths and weaknesses. For example, some of these software packages do not have any free access versions, so can only be accessed if paid for. Additionally, the interests of these programs differ from one to another, as some are used for statistical analysis, while others are used for visualization, and vice versa. For these reasons, this research relied on three main software programs: R, VOSviewer and CiteSpace. Regarding the R programing language, the bibliometrix package was used to present a statistical description of the collected dataset. The bibliometrix package was developed by Aria and Cuccurullo in 2017, and provides a collection of quantitative tools that can be used to perform scientometric and bibliometric analyses [35]. The main reasons to use R (in general) and the bibliometrix package (in particular) compared to the other software for scientific computation are probably the availability of robust and efficient statistical algorithms, availability of top-notch numerical routines and integrated data visualization views [34,35,36]. VOSviewer and CiteSpace were used in this research to visualize the different bibliometric networks. VOSviewer is a freely available Java application presented to the bibliometric research community by van Eck and Waltman in 2010 [33]. It uses the VOS mapping technique to visualize the similarities and present high-quality bibliometric network maps. CiteSpace is also a free Java application that produces interactive visuals aimed at identifying the research trends of a certain scientific field [37].
The main goal of using content-based analysis in this research was to link the bibliometric analysis results to their context to answer specific proposed RQs. The content-based analysis is defined as “a research method that provides a systematic and objective means to make valid inferences from verbal, visual or written data in order to describe and quantify specific phenomena” [38]. The content-based analysis in this research was conducted through three major steps. First, the extracted dataset was divided into four quarters based on two main criteria: total number of citations (NC) and publishing journal ranking. Consequently, 74 out of 294 documents were approved for conducting the content analysis. The approved documents went through a screening phase based on the availability criterion, resulting in 63 documents for the content analysis. Second, a literature matrix was created that included the main elements carefully selected to help answer the proposed RQs. Finally, the content-based analysis was conducted by precisely examining and text mining each section of the whole article (title, abstract, keywords and research body). This text mining process was performed through four workshops facilitated by the researchers, and took two months. The main aim of these workshops was to find answers to the proposed research questions. Subsequently, to avoid bias, the content-based analysis findings were presented to a group of experts for review, and to answer the question: to what extent did the answers to the research questions match the information in the examined records (63 articles)?

3. Results and Discussion: Identification of the Tourism and Real Estate Streams

Figure 1 shows the key information of the dataset derived from the bibliometric and content-based analyses. In general, the dataset contains 294 articles published in the period 1980–2021, with a citation rate of 8.8 per article. A total of 716 authors participated in writing these articles, which were published in 199 different sources. These articles contain around 897 keywords associated with tourism and real estate.

3.1. Bibliometric Analysis

3.1.1. Annual Scientific Production

Figure 2 shows a slight increase in the scientific production of research studies discussing tourism and real estate from 1980 to 2021, with a growth rate of up to 4.8%. This scientific production peaked in 2020 with 41 published articles. This noticeably increased relationship between tourism and real estate in the second millennium illustrates the extent to which this relationship is considered an emerging trend in the economic scientific society. This fact can be described with numbers: the proportion of articles published in this academic area, starting with the second millennium, represents about 94% of the total articles published since 1980. Comparing the number of published articles with the total citation number (see Figure 2), the scientific content linking tourism and real estate has high citation rates, up to 8.5 citations per article. In 2009, the total citations record reached a peak of 286 citations. According to many scholars, this increase in the interest in the real estate and tourism field was due to the global economic crisis of 2008–2009, which greatly affected the tourism sector, directing the academic trend towards the importance of land use and real estate in different tourism areas and destinations [39,40,41]. These studies are considered part of a significant research trend in this period focused on identifying new tourism patterns (e.g., rural and mountainous tourism) to help the tourism and real estate sectors recover from the severe damage caused by the crisis.

3.1.2. Document Analysis

Regarding the most relevant publications on tourism and real estate, Table 2 outlines the 20 most relevant documents ranked based on the average global citation per year (TGC/Y). The most significant article in this list is [42], with 20 total global citations per year. Most of the articles included in this list discuss the change in land use and its policies in the different tourism areas, as well as short-term rentals.
By analyzing the published articles in a co-citation network (see Figure 3), the scientific production in tourism and real estate can be divided into 10 co-citation clusters. The first cluster (red color), entitled “short-term rental”, is the largest cluster, containing 108 members. The peak in the articles published in this cluster was in the period 2011–2020, specifically in 2019 (see Figure 4). The main theme of this cluster was short-term rental in the tourism real estate, especially with the boom of many organizations supporting the sharing economy concept, such as Airbnb, Vrbo and Zillow. This cluster included several articles focusing on this theme, such as [42,60,61,62]. Additionally, it is worthy of note that most of the articles in this first cluster adopted different case studies in different geographical regions, such as New Orleans, Dublin, Barcelona, Madrid, Lisbon and Salzburg.
The second cluster (orange color), which has 72 members under the heading “sustainable tourism”, addressed the concept of sustainability in real estate tourism. Figure 4 shows that the peak of this cluster was between 2005 and 2020. In this period, the term sustainability generally flourished, and the United Nations set the 2030 Agenda, which encompassed the Sustainable Development Goals in 2015. This cluster includes research articles interested in applying sustainability to tourism real estate, such as [25,52,63,64].
The third cluster, entitled “real estate tourism development”, includes 52 members that all discuss different ideas related to real estate tourism development, such as ecological tourism, tourism in mountain areas, environmental real estate, eco-fishery tourism, tourism in biodiversity hotspots and wilderness tourism. The fourth cluster (yellow color), entitled “wine tourism development”, contains articles discussing the relationship between wine tourism and land use policies in various countries and geographical regions, such as [65,66].
The fifth cluster, named “land use change”, refers to articles that discuss land use as one of the main aspects of real estate tourism. This cluster contains many articles published from 1999 to 2018 (see Figure 4), such as [67,68,69]. The sixth and seventh clusters, entitled “tourism industry” and “changing determinant”, respectively, contain articles that explored changing the price of tourism properties, and presented this as a determinant and key element in the real estate tourism industry. Examples of such articles are [70,71,72,73].
Regarding the eighth cluster, entitled “adaptation”, the articles in this cluster focused on addressing the question of to what extent is the real estate adapted to various tourism development concepts, especially those related to sustainability and the conservation of natural tourism resources [74]. The ninth cluster, entitled “heritage property tourism”, included articles discussing real estate tourism in the historical heritage areas, and identified to what extent these areas were affected by various tourism activities [75,76]. The 10th cluster, named “tourism demand”, includes articles explaining the relationship between tourism demand and real estate in different tourism areas. While the 11th and final cluster was entitled “assessing tourists preferences”, and includes articles that discuss tourists’ preferences and their impact on changing the real estate tourism demand from one tourism destination to another, especially in coastal areas [77].
Through a general observation of the co-citation network in Figure 3, it is apparent that some articles are disconnected from others and do not belong to any cluster. These articles explored scientific topics that are emerging and represent future research in tourism and real estate, such as the changing preferences of tourists due to the COVID-19 pandemic, postcrisis development and knowledge base. Examples of such articles include [57,78,79].

3.1.3. Most Relevant Journals, Authors, Institutions and Countries

Table 3 presents the 20 most relevant journals that published the selected articles. The list was ranked based on the number of publications (NP). Of the 199 journals published on tourism and real estate, only four journals published more than six papers: Land Use Policy (eight articles), Current Issues in Tourism (eight articles), Tourism Management (seven articles) and Sustainability (six articles). Regarding the impact of the journal output and performance through the h-index, Land Use Policy was at the top of the list (8 h-index score), followed by Current Issues in Tourism and Tourism Management.
The research adopted author analysis, as another bibliometric analysis module, to identify the scientific community structure in the tourism and real estate field. The author analysis aimed to determine a clear answer to the main question: who are the most prolific authors and experts in the tourism and real estate field? Table 4 outlines the most relevant authors based on NP (to identify the most prolific authors), as well as the total citations record (to identify the experts). According to the NP criterion, the most prolific authors are Wang Y, Yrigoy I and Zhang H, with four published articles each, while the experts, based on the total NC, were Olcina-Cantos J, Rico-Amoros AM and Sauri D (a citation record of 149 each), followed by Hof A (119 citations). Comparing the most prolific authors list with the experts list, except for Hof A and Yrigoy I, the authors in these two lists are completely different, referring to the diversity of the authors that have published in the tourism and real estate field, as well as the specialization of some other authors.
Figure 5 presents the scientific production of the most prolific authors over the years. Although the publication period of the collected data was 1980–2021, the most prolific authors appeared only after 2005. Additionally, all the most prolific authors’ scientific work was conducted between 2011 and 2021—except for Guilding C, who dominated the five-year period from 2006 to 2011. This reflects the importance of the relationship between tourism and real estate from the academic perspective, especially in recent years.
Moving to the most relevant institutions, Table 5 presents the list of the top 20 ranked institutions that have published articles about tourism and real estate, based on the NP. The Prince of Songkla University and the University of Alicante topped this list, contributing 11 and 10 articles, respectively. Most of the universities participating in publishing articles about tourism and real estate are in Asian countries. In this study, China was the most predominant (seven institutions), followed by other Asian countries (such as Thailand, Bangladesh, India, Indonesia, Japan and Malaysia, with one institution each). Although the Asian countries dominated this list, Spain ranked second as the country with the highest number of institutions that have published articles about tourism and real estate, with three institutions: the University of Alicante, the University of Cordoba and the University of Extremadura.
Regarding countries’ collaboration networks, 55 countries participated in the publication of tourism and real estate literature. Figure 6 depicts the relationships between countries with the most contribution, where the size of the circle represents the NP and the linked lines represent the strength of the collaboration. Asian countries have high internal and external collaboration ties (e.g., China and Indonesia), while European countries are considered frequent collaboration partners (e.g., Italy, Finland and Portugal). However, Spain has strong ties with both Asian and other European countries. Considering the top 10 productive countries for tourism- and real-estate-related studies, China ranked first (148 publications), followed by Spain (143). Far behind, the US ranked third, with only about 36 articles published. Indonesia, Japan, Australia, UK, Italy, Finland and Portugal ranked 4th to 10th, with total number of articles of 31, 28, 27, 25, 22, 19 and 1, respectively.

3.1.4. Keywords and Burst Analysis

Co-word analysis is considered one of the most important bibliometric analysis modules, and it involves using keywords in any document to create relationships and determine the conceptual kernel of the investigated scientific field [80]. Figure 7 depicts the co-word analysis network of tourism and real estate literature, where the top five frequent keywords are tourism (n = 86), tourism development (n = 51), land use (n = 41), land use change (n = 31) and tourist destination (n = 29). Although it was expected that this network would present terms/keywords related to real estate as major nodes of this network, the terms/keywords that appear strongly in this network are related to land use and its change. It is also worthwhile mentioning the appearance of nodes related to specific geographical areas or regions, such as Spain, China, Canada, Australia, the Canary Islands and the Balearic Islands. This co-word network also shows a prominent absence of keywords related to COVID-19, reflecting the fact that many articles did not pay attention to the pandemic’s impact on the tourism real estate sector, despite the considerable impact of this crisis on the different economic sectors in the last two years.
Regarding the burst period of the keywords, Figure 8 presents the strongest citation bursts in tourism and real estate literature. The term “burst” refers to the prevalence of each keyword over time. By tracking the trends of keyword bursts, it is possible to identify the evolution trends in any scientific research area in a specific period. As shown in Figure 4, prior to 2006, there was no specific interest research area in tourism and real estate literature, as this period does not appear in the burst diagram. The year 2006 represents the start of emerging research trends or interests in tourism and real estate literature. In the initial period (2006–2009), the concentration of tourism and real estate research on conducting studies in different geographical areas was high, with the appearance of burst keywords such as Eurasia, Europe, Africa, Asia and GCC countries (Gulf Cooperation Council countries). In the following nine years (from 2009 to 2018), the research interests fluctuated between different themes of tourism and real estate, such as ecotourism, land use change, developing world and tourist destinations. In recent times, specifically from 2018 to 2021, the tourism and real estate literature has been interested in the sharing economy concept, leading to the appearance of keywords in the burst such as Airbnb, sharing economy, housing market and tourism market.

3.2. Content-Based Analysis

Figure 9 represents the analytical graphs resulting from the content-based analysis that helped to answer the RQs. According to RQ2 results, about 73% of the tourism literature addressed real estate from a developmental perspective, compared to only 24% of the literature that addressed it from an investment perspective. Many researchers are confused about the difference between the two terms “tourism real estate investment” and “tourism real estate development”. Consequently, this vagueness was addressed as one of the main RQs in this research. Generally, the tourism real estate investment concept refers to the different tourism real estate projects that usually have large constructions and seek to achieve maximum profit, such as tourism resorts, hotels and restaurants. Additionally, dealing with tourism real estate as an investment opportunity not only reflects its impact on the tourism sector, but also has many other impacts, especially on the investor’s side. For example, many countries (e.g., Turkey, Malta and Cyprus) consider that owning a property and renting it for tourism purposes gives the owner the right to acquire citizenship, which attracts many foreign investments. Moreover, the parameters of the real estate investment decision are associated with the conceptual kernel of the tourism sector [81]. The real estate investment decision is made through the investment triangle parameters (return, risk and liquidity), and the tourism sector is a fragile, volatile, resilient and sometimes seasonal sector that makes it a unique sector suitable for the investment-minded [81]. Meanwhile, tourism real estate development represents the different tourism real estate constructions and their impact on the surrounding urban environment [82]. Additionally, from the development perspective, tourism real estate is considered a driving force for both tourism and economic development [83]. For example, in underdeveloped tourist areas/regions, tourism real estate development enhances the positive agglomeration effects, and participates in the generation of economic growth in the other developed locations. Basically, tourism development cannot be realized without real estate development. Therefore, these two terms should be taken into consideration in the tourism development process, but with a clear vision of the difference between them.
Despite the variety of the spatial units used as case studies in the tourism and real estate literature, coastal areas dominated the case studies (about 49%); this reflects the continuous changes and resilience of the tourism coastal destinations, resulting in many studies being interested in them. Applying the tourism and real estate studies at the regional level (such as towns) ranked second, comprising 22% of the literature. Moreover, it is worth mentioning that the percentage of the studies that discussed tourism and real estate in individual destinations, such as real estate projects or tourist destinations, was approximately only 5%. These results reflect the spatial scales addressed as case studies in the articles.
RQ4 results indicate that the data used in the tourism and real estate studies were more primary (67%) than secondary (33%). Moving towards the areas of interest of the tourism and real estate studies, RQ5 results rank development and economic as the first and second areas of interest in the literature (62% and 17%, respectively). Finally, RQ6 findings confirm that most of the tourism and real estate studies used more practical methodological frameworks than theoretical frameworks. With 81% of studies applying their methodological frameworks in specific case studies, the importance of the uniqueness of each geographical area or region from another was manifested.

4. Recommendations for Future Research Agenda

Based on the results of both bibliometric and content-based analyses of the tourism and real estate literature, we present future research perspectives in five key points. First, the scientific society needs more studies discussing the relationship between tourism and real estate. Despite the growth rate of publications in this area, especially in the second millennium, the importance of the relationship between tourism and real estate and their impact on each other is increasingly growing. Therefore, a more solid synergy in the academic community is required to have sufficient knowledge of the relationship between these two areas, and to closely monitor the different variables affecting them.
Second, future research in the field of tourism and real estate should pay great attention to implementing and studying various geographical areas and regions. The heterogeneity of the characteristics of different tourist destinations and areas enhances the need to address tourism and real estate studies in more geographical areas to achieve more accurate and comprehensive results. In other words, the presence of diversity in case studies enriches the scientific content of tourism and real estate, and provides the appropriate knowledge for many decision makers to make the best decision based on real situation facts.
Third, an in-depth exploration of the difference between tourism real estate investment and tourism real estate development would be valuable. Through our analysis of the tourism and real estate literature, we had difficulty identifying whether the selected articles discussed the relationship between tourism and real estate from an investment or a development perspective. Accordingly, research perspectives could explore, theoretically, the differences between real estate investment and tourism real estate development, which might improve comprehension beyond the studies’ objectives and outcomes.
Fourth, future research can involve producing more publications on some areas of interest in the tourism and real estate literature (for instance, legal and financial). From the legal perspective, tourism real estate remains a legal limbo in many tourist areas and destinations [84]. This has caused a great loss in many investments in the tourism sector, as well as the “freezing” and incompletion of many tourism real estate projects (especially in developing countries), creating frustration among many investors and traders. Consequently, future research could pay more attention to analyzing the legal framework of tourism real estate. Similarly, further research could be beneficial for finding new metrics to analyse and evaluate tourism real estate projects from a financial perspective, especially considering that tourism real estate projects are commonly uncertain and complicated, involve various phases and span long periods [85].
The fifth and final point relates more to the structure of scientific research for the tourism real estate sector than to future research trends. The analytical results of this research necessitate the recommendation of creating a source/journal specializing in the scientific production of tourism real estate. Since tourism real estate discusses different aspects/dimensions that overlap with various economic sectors, such as the institutional, financial, development, individual and behavioral, investment, legal, governance and socioeconomic dimensions. Additionally, having specialized search platforms comprising tourism real estate studies should, in turn, facilitate the separation of tourism real estate issues from overlapping topics such as land use/cover changing, thus ensuring more focus in the future on the tourism real estate research area, and presenting more robust and credible research outcomes.

5. Conclusions

This study presented a statistical analysis of the tourism and real estate literature. A sample of 294 articles from the period 1980–2021 were investigated using different bibliometric analysis modules and techniques (e.g., scientific production, documents, journals, authors, institutions, countries and keywords). Content-based analysis was conducted to review the 63 most relevant articles based on total NC and publishing journal ranking.
The research findings answered the six proposed RQs. The bibliometric analysis results focused on answering RQ1, which enquired about identifying the main research streams in the tourism and real estate literature. Tourism and real estate scientific production was categorized into 11 main clusters: short-term rental, sustainable tourism, real estate tourism development, wine tourism development, land use change, tourism industry, changing determinant, adaptation, heritage property tourism, tourism demand and assessing tourists’ preferences. Land Use Policy (eight articles) and Current Issues in Tourism (eight articles) were the two most productive journals on tourism and real estate literature. The most prolific authors in the tourism and real estate literature were Wang Y, Yrigoy I and Zhang H (four articles each), while the experts in this field based on NC were Olcina-Cantos J, Rico-Amoros AM, and Sauri D (citation record of 149 each). Regarding the most productive institutions, Prince of Songkla University (Thailand) and the University of Alicante (Spain) ranked first and second with (11 and 10 published articles, respectively). Asian institutions dominated the list of the most productive institutions in the tourism and real estate literature; this list comprised 16 Asian institutions (65% of the total list). The keyword analysis presented an overall view of the tourism and real estate research directions. Despite the beginning of the tourism and real estate literature at the end of the 1980s, its real prosperity was from the beginning of the second millennium. At the beginning of this prosperity period, tourism and real estate literature focused on geographical dimensions, and the published articles were applied in a variety of case studies, resulting in the presence of keywords related to various geographical regions (such as Europe, Asia and the GCC countries). In the mid-2000s, tourism literature addressed many important tourism themes and their impact on real estate, such as ecotourism, land use change, sustainable tourism and the rental sector. The keywords of these concepts occupied the attention of researchers in this period. Turning to the recent period, keywords discussing the sharing economy concept have appeared in tourism and real estate literature, such as Airbnb, sharing economy, housing market and tourism market.
The content-based analysis findings answered the remaining five RQs (RQ2–RQ6). These findings present some facts about the tourism and real estate literature that could structure the future research agenda in this scientific area. Nearly 73% of tourism and real estate literature discussed real estate from a development rather than investment perspective. Despite the variety of the spatial units used as case studies in tourism and real estate publications, coastal tourism areas were the testing ground for most studies (49%), followed by regional-level units (22%), such as tourism cities. Most of the tourism and real estate studies relied on primary (67%) rather than secondary data, as well as on practical methodological frameworks (81%) compared to theoretical frameworks. The diversity of areas of interest for tourism and real estate literature, such as development, economic, behavioral, governance and legal areas, reflects its significance and its overlap with many research areas, which has importance for the further progression of tourism and real estate.
Generally, although the evolutionary relationship between tourism and real estate is important, it is still undefined in some research areas. This research attempted to explore tourism and real estate to determine the critical research gaps and present a clear road map for future research. Like any scientific study, this research was not free of limitations. Considering NC as the controlling element in many bibliometric analysis modules was the first limitation of this research. Additionally, opting for WOS and Scopus as the two main databases for extracting the tourism and real estate literature represented the second limitation of this research. To curb the effect of these limitations on the study findings, we conducted a content-based analysis of the most relevant publications in the tourism and real estate literature. Moreover, the disregard for certain datasets, such as Google Scholar, was due to the implicit quality inconstancy of the publications indexed in its records.

Author Contributions

Conceptualization, M.K. and L.D.D.; methodology, M.K. and L.D.D.; software, M.K.; validation, M.K., M.A., H.M.H., F.A. and M.K.; formal analysis, F.A. and M.K.; investigation, M.A., H.M.H., F.A. and M.K.; resources, M.K. and F.A.; writing—original draft preparation, M.K., M.A., H.M.H. and F.A.; writing—review and editing, M.K. and M.A.; visualization, M.K.; supervision, K.C., I.V. and L.D.D.; project administration, K.C., I.V. and L.D.D.; funding acquisition, M.A. and H.M.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Crowe, C.; Dell’Ariccia, G.; Igan, D.; Rabanal, P. How to deal with real estate booms: Lessons from country experiences. J. Financ. Stab. 2013, 9, 300–319. [Google Scholar] [CrossRef]
  2. Krause, A.L.; Bitter, C. Spatial econometrics, land values and sustainability: Trends in real estate valuation research. Cities 2012, 29, S19–S25. [Google Scholar] [CrossRef]
  3. Pagourtzi, E.; Assimakopoulos, V.; Hatzichristos, T.; French, N. Real estate appraisal: A review of valuation methods. J. Prop. Invest. Financ. 2003, 21, 383–401. [Google Scholar] [CrossRef]
  4. Dickman, S. Tourism: An Introductory Text, 3rd ed.; Hodder: Sydney, Australia, 1997; ISBN 0-7336-0677-6. [Google Scholar]
  5. Lee, C.-F. An investigation of factors determining industrial tourism attractiveness. Tour. Hosp. Res. 2016, 16, 184–197. [Google Scholar] [CrossRef]
  6. Lew, A.A. A framework of tourist attraction research. Ann. Tour. Res. 1987, 14, 553–575. [Google Scholar] [CrossRef]
  7. Wörndl, W.; Koo, C.; Stienmetz, J.L. (Eds.) Information and Communication Technologies in Tourism 2021: Proceedings of the ENTER 2021 eTourism Conference, 19–22 January 2021; Springer International Publishing: Cham, Switzerland, 2021; ISBN 978-3-030-65784-0. [Google Scholar]
  8. Yang, Y. Understanding tourist attraction cooperation: An application of network analysis to the case of Shanghai, China. J. Destin. Mark. Manag. 2018, 8, 396–411. [Google Scholar] [CrossRef]
  9. World Tourism Organization. What is a tourist attraction?/What is a tourist destination? (AUSTRALIA). In Tourism Satellite Account (TSA): Adapting the Tourism Satellite Account Conceptual Framework from a Regional Perspective (Contains Paper in English and French); World Tourism Organization: Madrid, Spain, 2000; pp. 1–4. ISBN 978-92-844-0710-1. [Google Scholar]
  10. Bardhan, A.; Begley, J.; Kroll, C.A.; George, N. Global Tourism and Real Estate. SSRN J. 2008. [Google Scholar] [CrossRef]
  11. Eichhorn, V.; Buhalis, D. Chapter 3. Accessibility: A Key Objective for the Tourism Industry. In Accessible Tourism: Concepts and Issues; Buhalis, D., Darcy, S., Eds.; Channel View Publications: Bristol, UK, 2010; pp. 46–61. [Google Scholar]
  12. Tóth, G.; Dávid, L. Tourism and accessibility: An integrated approach. Appl. Geogr. 2010, 30, 666–677. [Google Scholar] [CrossRef]
  13. Cordera, R.; Coppola, P.; dell’Olio, L.; Ibeas, Á. The impact of accessibility by public transport on real estate values: A comparison between the cities of Rome and Santander. Transp. Res. Part A Policy Pract. 2019, 125, 308–319. [Google Scholar] [CrossRef]
  14. Cooper, C.; Fletcher, J.; Gilbert, D.; Fyall, A.; Wanhill, S. Tourism: Principles and Practice; Pearson Education: London, UK, 2005. [Google Scholar]
  15. Sharpley, R. The influence of the accommodation sector on tourism development: Lessons from Cyprus. Int. J. Hosp. Manag. 2000, 19, 275–293. [Google Scholar] [CrossRef]
  16. Ismail, T.; Rohman, F. The Role of Attraction, Accessibility, Amenities, and Ancillary on Visitor Satisfaction and Visitor Attitudinal Loyalty of Gili Ketapang Beach. J. Manaj. Teor. Dan Terap. 2019, 12, 149. [Google Scholar] [CrossRef]
  17. Bernini, C.; Cerqua, A.; Pellegrini, G. Endogenous amenities, tourists’ happiness and competitiveness. Reg. Stud. 2020, 54, 1214–1225. [Google Scholar] [CrossRef]
  18. Sun, Y.; Fu, Y. Research on the Integration of Tourism Industry and Real Estate Industry in China. Mod. Econ. 2018, 9, 1654–1664. [Google Scholar] [CrossRef]
  19. Stavrinoudis, T. The impact of Timeshare on the tourism development of specific destinations. In Proceedings of the Tourism on Islands and Specific Destinations, University of the Aegean, Chios, Greece, 14–16 December 2000; p. 16. [Google Scholar]
  20. Hawkins, D.E. Tourist holiday options: Timeshare versus competition. Tour. Manag. 1985, 6, 252–271. [Google Scholar] [CrossRef]
  21. Hicks, G.J.; Walker, M.D. Training in the Timeshare Industry. Tour. Hosp. Res. 2006, 6, 296–300. [Google Scholar] [CrossRef]
  22. Huang, C.; Pennington-Gray, L.; Ko, Y.J.; Thapa, B. Engaging timeshare owners in tourism destination management: Tourism planning and tourism marketing implications. J. Travel Tour. Mark. 2010, 27, 14–30. [Google Scholar] [CrossRef]
  23. Woods, R.H. ImportanItssuefsora Grotig TimesharIendustry. Cornell Hotel Restaur. Adm. Q. 2001, 42, 71–81. [Google Scholar] [CrossRef]
  24. Fernández Gallardo, J.A.; Caridad y Ocerín, J.M.; Genoveva Millán Vázquez de la Torre, M. Evaluation of the Reception Capacity of a Certain Area Regarding Tourist Housing, Addressing Sustainable-Tourism Criteria. Sustainability 2019, 11, 6422. [Google Scholar] [CrossRef]
  25. Hao, H.; Kline, C.; Long, P.; Rassel, G. Property owners’ attitudes toward sustainable tourism. Tour. Hosp. Res. 2018, 18, 429–441. [Google Scholar] [CrossRef]
  26. Seraphin, H.; Kennell, J.; Mandic, A.; Smith, S.; Kozak, M. Language Diversity and Literature Reviews in Tourism Research. Tour. Cult. Commun. 2022, 17, 342–356. [Google Scholar] [CrossRef]
  27. ARMSTRONG, H.E. The Theory of National and International Bibliography (With Special Reference to the Introduction of System in the Record of Modern Literature). Nature 1896, 54, 617–618. [Google Scholar] [CrossRef]
  28. Broadus, R.N. Toward a definition of “bibliometrics”. Scientometrics 1987, 12, 373–379. [Google Scholar] [CrossRef]
  29. Osareh, F. Bibliometrics, Citation Analysis and Co-Citation Analysis: A Review of Literature I. Libri 1996, 46, 217–225. [Google Scholar] [CrossRef]
  30. Sci2 Team Science of Science (Sci2) Tool. Available online: https://sci2.cns.iu.edu (accessed on 20 July 2022).
  31. van Eck, N.J.; Waltman, L. CitNetExplorer: A new software tool for analyzing and visualizing citation networks. J. Informetr. 2014, 8, 802–823. [Google Scholar] [CrossRef]
  32. Cobo, M.J.; López-Herrera, A.G.; Herrera-Viedma, E.; Herrera, F. SciMAT: A new science mapping analysis software tool. J. Am. Soc. Inf. Sci. Technol. 2012, 63, 1609–1630. [Google Scholar] [CrossRef]
  33. van Eck, N.J.; Waltman, L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010, 84, 523–538. [Google Scholar] [CrossRef]
  34. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2016. [Google Scholar]
  35. Aria, M.; Cuccurullo, C. bibliometrix: An R-tool for comprehensive science mapping analysis. J. Informetr. 2017, 11, 959–975. [Google Scholar] [CrossRef]
  36. Aria, M.; Cuccurullo, C. bibliometrix R-Package. Available online: https://bibliometrix.org/ (accessed on 20 December 2020).
  37. Chen, C. CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. J. Am. Soc. Inf. Sci. Technol. 2006, 57, 359–377. [Google Scholar] [CrossRef]
  38. Downe-Wamboldt, B. Content analysis: Method, applications, and issues. Health Care Women Int. 1992, 13, 313–321. [Google Scholar] [CrossRef]
  39. Pedreira, B.C.C.G.; dos Santos, R.F.; da Rocha, J.V. Planejamento agroturístico de propriedade rural sob a perspectiva da conservação ambiental. Rev. Bras. Eng. Agríc. E Ambient. 2009, 13, 741–749. [Google Scholar] [CrossRef]
  40. Petrov, L.O.; Lavalle, C.; Kasanko, M. Urban land use scenarios for a tourist region in Europe: Applying the MOLAND model to Algarve, Portugal. Landsc. Urban Plan. 2009, 92, 10–23. [Google Scholar] [CrossRef]
  41. Rico-Amoros, A.M.; Olcina-Cantos, J.; Sauri, D. Tourist land use patterns and water demand: Evidence from the Western Mediterranean. Land Use Policy 2009, 26, 493–501. [Google Scholar] [CrossRef]
  42. Yrigoy, I. Rent gap reloaded: Airbnb and the shift from residential to touristic rental housing in the Palma Old Quarter in Mallorca, Spain. Urban Stud. 2019, 56, 2709–2726. [Google Scholar] [CrossRef]
  43. Magano, J.; Vidal, D.G.; Sousa, H.F.P.E.; Dinis, M.A.P.; Leite, Â. Validation and Psychometric Properties of the Portuguese Version of the Coronavirus Anxiety Scale (CAS) and Fear of COVID-19 Scale (FCV-19S) and Associations with Travel, Tourism and Hospitality. Int. J. Environ. Res. Public Health 2021, 18, 427. [Google Scholar] [CrossRef]
  44. Ayhan, Ç.K.; Taşlı, T.C.; Özkök, F.; Tatlı, H. Land use suitability analysis of rural tourism activities: Yenice, Turkey. Tour. Manag. 2020, 76, 103949. [Google Scholar] [CrossRef]
  45. Blanco-Romero, A.; Blázquez-Salom, M.; Cànoves, G. Barcelona, Housing Rent Bubble in a Tourist City. Social Responses and Local Policies. Sustainability 2018, 10, 2043. [Google Scholar] [CrossRef]
  46. Li, J.; Bai, Y.; Alatalo, J.M. Impacts of rural tourism-driven land use change on ecosystems services provision in Erhai Lake Basin, China. Ecosyst. Serv. 2020, 42, 101081. [Google Scholar] [CrossRef]
  47. Boori, M.S.; Voženílek, V.; Choudhary, K. Land use/cover disturbance due to tourism in Jeseníky Mountain, Czech Republic: A remote sensing and GIS based approach. Egypt. J. Remote Sens. Space Sci. 2015, 18, 17–26. [Google Scholar] [CrossRef]
  48. Hjalager, A.-M. Land-use conflicts in coastal tourism and the quest for governance innovations. Land Use Policy 2020, 94, 104566. [Google Scholar] [CrossRef]
  49. Hof, A.; Schmitt, T. Urban and tourist land use patterns and water consumption: Evidence from Mallorca, Balearic Islands. Land Use Policy 2011, 28, 792–804. [Google Scholar] [CrossRef]
  50. Cucari, N.; Wankowicz, E.; Falco, S.E.D. Rural tourism and Albergo Diffuso: A case study for sustainable land-use planning. Land Use Policy 2019, 82, 105–119. [Google Scholar] [CrossRef]
  51. Martín Martín, J.M.; Rodriguez Martín, J.A.; Zermeño Mejía, K.A.; Salinas Fernández, J.A. Effects of Vacation Rental Websites on the Concentration of Tourists—Potential Environmental Impacts. An Application to the Balearic Islands in Spain. Int. J. Environ. Res. Public Health 2018, 15, 347. [Google Scholar] [CrossRef]
  52. Martín Martín, J.M.; Guaita Martínez, J.M.; Molina Moreno, V.; Sartal Rodríguez, A. An Analysis of the Tourist Mobility in the Island of Lanzarote: Car Rental Versus More Sustainable Transportation Alternatives. Sustainability 2019, 11, 739. [Google Scholar] [CrossRef]
  53. Robertson, D.; Oliver, C.; Nost, E. Short-term rentals as digitally-mediated tourism gentrification: Impacts on housing in New Orleans. Tour. Geogr. 2020, 1–24. [Google Scholar] [CrossRef]
  54. Tyrväinen, L.; Uusitalo, M.; Silvennoinen, H.; Hasu, E. Towards sustainable growth in nature-based tourism destinations: Clients’ views of land use options in Finnish Lapland. Landsc. Urban Plan. 2014, 122, 1–15. [Google Scholar] [CrossRef]
  55. Boavida-Portugal, I.; Rocha, J.; Ferreira, C.C. Exploring the impacts of future tourism development on land use/cover changes. Appl. Geogr. 2016, 77, 82–91. [Google Scholar] [CrossRef]
  56. Shabrina, Z.; Buyuklieva, B.; Ng, M.K.M. Short-Term Rental Platform in the Urban Tourism Context: A Geographically Weighted Regression (GWR) and a Multiscale GWR (MGWR) Approaches. Geogr. Anal. 2021, 53, 686–707. [Google Scholar] [CrossRef]
  57. Katsinas, P. Professionalisation of short-term rentals and emergent tourism gentrification in post-crisis Thessaloniki. Environ. Plan. A Econ. Space 2021, 53, 1652–1670. [Google Scholar] [CrossRef]
  58. Chai, Y.; Qiao, W.; Hu, Y.; He, T.; Jia, K.; Feng, T.; Wang, Y. Land-Use Transition of Tourist Villages in the Metropolitan Suburbs and Its Driving Forces: A Case Study of She Village in Nanjing City, China. Land 2021, 10, 168. [Google Scholar] [CrossRef]
  59. Yrigoy, I. 580. Airbnb en Menorca: ¿Una nueva forma de gentrificación turística? Localización de la vivienda turística, agentes e impactos sobre el alquiler residencial. Scr. Nova 2017, 21. [Google Scholar] [CrossRef]
  60. Marques Pereira, S. Regulation of short-term rentals in Lisbon: Strike a balance between tourism dependence and urban life. Urban Res. Pract. 2020, 1–28. [Google Scholar] [CrossRef]
  61. Nannelli, M.; Buhalis, D.; Franch, M.; Lucia, M.D. Disruption of the market structure in the tourism and hospitality accommodation service. The impact of the new short-term rental players. e-Rev. Tour. Res. 2019, 17. Available online: https://ertr-ojs-tamu.tdl.org/ertr/index.php/ertr/article/view/529 (accessed on 20 July 2022).
  62. Zhao, J.; Peng, Z. Shared Short-Term Rentals for Sustainable Tourism in the Social-Network Age: The Impact of Online Reviews on Users’ Purchase Decisions. Sustainability 2019, 11, 4046. [Google Scholar] [CrossRef]
  63. Tang, Z. Sustainable Tourism and Property Rights: A Case Study on the World Heritage Site of Wulingyuan in China from the Perspective of Property Rights Economics. Hist. Environ. Policy Pract. 2014, 5, 275–287. [Google Scholar] [CrossRef]
  64. Warnken, J.; Guilding, C. Serviced apartment complexes in Australia: A critical analysis of their potential and challenges for sustainable tourism. In Proceedings of the Sustainable Tourism II; WIT Press: Bologna, Italy, 2006; Volume 1, pp. 47–57. [Google Scholar]
  65. Mitchell, R. International business, intellectual property and the misappropriation of place: Food, wine and tourism. In International Business and Tourism Global Issues, Contemporary Interactions; Taylor & Francis Group: London, UK, 2008; p. 19. ISBN 978-0-429-24056-0. [Google Scholar]
  66. Williams, P.W.; Graham, K.; Mathias, L. Land use policy and wine tourism development in North America’s Pacific Northwest. In Global Wine Tourism: Research, Management and Marketing; CABI Publishing: Wallingford, UK, 2006; pp. 27–47. ISBN 1-84593-170-X. [Google Scholar]
  67. Furgała-Selezniow, G.; Jankun-Woźnicka, M.; Kruk, M.; Omelan, A.A. Land Use and Land Cover Pattern as a Measure of Tourism Impact on a Lakeshore Zone. Land 2021, 10, 787. [Google Scholar] [CrossRef]
  68. Saha, J.; Paul, S. An insight on land use and land cover change due to tourism growth in coastal area and its environmental consequences from West Bengal, India. Spat. Inf. Res. 2021, 29, 577–592. [Google Scholar] [CrossRef]
  69. Yepes, V.; Medina, J.R. Land Use Tourism Models in Spanish Coastal Areas. A Case Study of the Valencia Region. J. Coast. Res. 2005, 49, 83–88. [Google Scholar]
  70. Li, S.; Gan, S.; Zhao, J. Application Research of Remote Sensing Images in the Land Use Special Planning of Tourism Industry in Yunnan Province. In Proceedings of the 2011 International Symposium on Image and Data Fusion, Tengchong, China, 9–11 August 2011; IEEE: Piscataway, NJ, USA, 2011; pp. 1–4. [Google Scholar]
  71. Liu, Y.; Yang, L.; Chau, K.W. Impacts of Tourism Demand on Retail Property Prices in a Shopping Destination. Sustainability 2020, 12, 1361. [Google Scholar] [CrossRef]
  72. Mansfeld, Y.; Winckler, O. The Role of the Tourism Industry in Transforming a Rentier to a Long-Term Viable Economy: The Case of Bahrain. Curr. Issues Tour. 2008, 11, 237–267. [Google Scholar] [CrossRef]
  73. Yang, L.; Chau, K.W.; Lu, Y.; Cui, X.; Meng, F.; Wang, X. Locale-Varying Relationships Between Tourism Development and Retail Property Prices In A Shopping Destination. Int. J. Strateg. Prop. Manag. 2020, 24, 323–334. [Google Scholar] [CrossRef]
  74. Vail, D.; Hultkrantz, L. Property rights and sustainable nature tourism: Adaptation and mal-adaptation in Dalarna (Sweden) and Maine (USA). Ecol. Econ. 2000, 35, 223–242. [Google Scholar] [CrossRef]
  75. Cerreta, M.; Mura, F.D.; Poli, G. Assessing the Interstitial Rent: The Effects of Touristification on the Historic Center of Naples (Italy). In Computational Science and Its Applications–ICCSA 2020, Proceedings of the 20th International Conference, Cagliari, Italy, 1–4 July 2020, Proceedings, Part III; Lecture Notes in Computer Science; Springer International Publishing: Cham, Switzerland, 2020; Volume 12251, pp. 952–967. ISBN 978-3-030-58807-6. [Google Scholar]
  76. Goodall, B.; Pottinger, G.; Dixon, T.; Russell, H. Heritage property, tourism and the UK Disability Discrimination Act. Prop. Manag. 2004, 22, 345–357. [Google Scholar] [CrossRef]
  77. Dachary-Bernard, J.; Rivaud, A. Assessing tourists’ preferences for coastal land use management: Oyster farming and heritage. Ocean Coast. Manag. 2013, 84, 86–96. [Google Scholar] [CrossRef]
  78. Braje, I.N.; Pechurina, A.; Bıçakcıoğlu-Peynirci, N.; Miguel, C.; del Mar Alonso-Almeida, M.; Giglio, C. The changing determinants of tourists’ repurchase intention: The case of short-term rentals during the COVID-19 pandemic. Int. J. Contemp. Hosp. Manag. 2022, 34, 159–183. [Google Scholar] [CrossRef]
  79. She, K.-S.; Haw, S.-C.; Chew, L.-J. Tourism Recommender System Utilising Property Graph Ontology as Knowledge Base. In Proceedings of the 12th International Conference on Computer Modeling and Simulation, Brisbane, QLD, Australia, 22–24 June 2020; Association for Computing Machinery: New York, NY, USA, 2020; pp. 14–18. [Google Scholar]
  80. Zupic, I.; Čater, T. Bibliometric Methods in Management and Organization. Organ. Res. Methods 2015, 18, 429–472. [Google Scholar] [CrossRef]
  81. Krulický, T.; Horák, J. Real estate as an investment asset. SHS Web Conf. 2019, 61, 01011. [Google Scholar] [CrossRef]
  82. Xu, H.; Wu, Y.; Wall, G. Tourism Real Estate Development as a Policy Tool for Urban Tourism: A Case Study of Dali and Lijiang, China. J. China Tour. Res. 2012, 8, 174–193. [Google Scholar] [CrossRef]
  83. Keller, P. Real estate and the development of tourism: Conclusions of the 45th AIEST congress. Tour. Rev. 1995, 50, 3–5. [Google Scholar] [CrossRef]
  84. Nguyen, H.D.; Dang, C.N.; Le-Hoai, L.; Luu, Q.T. Exploratory analysis of legal risk causes in tourism real estate projects in emerging economies: Empirical study from Vietnam. Int. J. Constr. Manag. 2021, 1–13. [Google Scholar] [CrossRef]
  85. Ying, D. Optimization of Tourism Real Estate Development Project Based on Option Premium Model. Discret. Dyn. Nat. Soc. 2021, 2021, 2954795. [Google Scholar] [CrossRef]
Figure 1. Key information of the collected dataset.
Figure 1. Key information of the collected dataset.
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Figure 2. Annual scientific production in tourism and real estate studies. TGC: total global citations.
Figure 2. Annual scientific production in tourism and real estate studies. TGC: total global citations.
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Figure 3. Clustered co-citation document network of tourism and real estate literature.
Figure 3. Clustered co-citation document network of tourism and real estate literature.
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Figure 4. A timeline view of clustered co-cited documents in tourism and real estate literature.
Figure 4. A timeline view of clustered co-cited documents in tourism and real estate literature.
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Figure 5. A timeline view of the top 10 prolific authors in the tourism and real estate literature. NP, number of publications; TC/Y, total citations per year.
Figure 5. A timeline view of the top 10 prolific authors in the tourism and real estate literature. NP, number of publications; TC/Y, total citations per year.
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Figure 6. Country collaboration network.
Figure 6. Country collaboration network.
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Figure 7. Co-word analysis network.
Figure 7. Co-word analysis network.
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Figure 8. Top 25 keywords with the strongest citation bursts in tourism and real estate literature.
Figure 8. Top 25 keywords with the strongest citation bursts in tourism and real estate literature.
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Figure 9. RQ2–RQ6 results according to the content-based analysis of tourism and real estate literature.
Figure 9. RQ2–RQ6 results according to the content-based analysis of tourism and real estate literature.
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Table 1. Research protocol for the data collection.
Table 1. Research protocol for the data collection.
Search QueryTITLE ((“touris*”) AND (“real estate” OR “land use” OR “landed propert*” OR “land propert*” OR “real propert*” OR “propert*” OR “landed interest*” OR “land interest*” OR “Realtor” OR “estate surveyor*” OR “estate valuer*” OR “estate agent*” OR “rent*” OR “Landowner*” OR “Land owner*” OR “apartment*”))
DatabaseWOS and Scopus
Database Period1980–2021
Table 2. Most relevant articles on tourism and real estate filed in the present study (sorted by total global citations per year).
Table 2. Most relevant articles on tourism and real estate filed in the present study (sorted by total global citations per year).
RankAuthor (Year)TLC/YTLCTGC/YTGC
1Yrigoy (2019) [42]1.33420.0060
2Magano et al. (2021) [43]0.00018.0018
3Ayhan et al. (2020) [44]0.50116.0032
4Blanco-Romero et al. (2018) [45]0.75313.5054
5J. Li et al. (2020) [46]0.50113.5027
6Rico-Amoros et al. (2009) [41]0.38511.46149
7Boori et al. (2015) [47]0.1418.7161
8Hjalager (2020) [48]0.0008.5017
9Hof and Schmitt (2011) [49]0.0008.0088
10Cucari et al. (2019) [50]0.3318.0024
11Martín Martín, Rodriguez Martín, et al. (2018) [51]0.2517.7531
12Martín Martín, Guaita Martínez, et al. (2019) [52]0.0007.6723
13Robertson et al. (2020) [53]0.0007.5015
14Tyrväinen et al. (2014) [54]0.0007.1357
15Boavida-Portugal et al. (2016) [55]1.3387.0042
16Shabrina et al. (2021) [56]0.0007.007
17Petrov et al. (2009) [40]0.3146.3182
18Katsinas (2021a) [57]0.0006.006
19Chai et al. (2021) [58]0.0006.006
20Yrigoy (2017) [59]0.0005.8029
TLC, total local citations; TLC/Y, average TLC per year; TGC, total global citations; TGC/Y, average TGC per year.
Table 3. The 20 most productive journals in tourism and real estate literature (sorted by number of publications).
Table 3. The 20 most productive journals in tourism and real estate literature (sorted by number of publications).
RankSource/JournalNPh_indexTC
1Land Use Policy88400
2Current Issues in Tourism86109
3Tourism Management76167
4Sustainability (Switzerland)6499
5Boletin De La Asociacion De Geografos Espanoles5316
6Land4341
7Tourism Geographies4362
8Annals of Tourism Research33100
9Revue De Geographie Alpine3318
10Asia Pacific Journal of Tourism Research3231
11Journal of Policy Research in Tourism, Leisure and Events3212
12WIT Transactions on Ecology and The Environment3111
13Ecosystem Services2237
14Environment and Planning2214
15Environmental Earth Sciences2223
16International Journal of Environmental Research and Public Health2249
17International Journal of Housing Markets and Analysis2229
18International Journal of Strategic Property Management2216
19Journal of China Tourism Research2215
20Journal of Coastal Research2274
NP, number of publications; TC, total citations.
Table 4. Top 10 most prolific authors and experts in the tourism and real estate literature.
Table 4. Top 10 most prolific authors and experts in the tourism and real estate literature.
Most Prolific Authors (a)Experts (b)
RankAuthorsNPRankAuthorsTC
1Wang Y41Olcina-cantos J149
2Yrigoy I42Rico-amoros AM149
3Zhang H43Sauri D149
4Chapagain SK34Hof A119
5Fukushi K35Yrigoy I94
6Guilding C36Baker A88
7Hof A37Genty D88
8Li Y38Schmitt T88
9Liu Y39Blázquez-salom M85
10Liu Z310Kasanko M82
NP, number of publications; TC, total citations. (a) The list of the most prolific authors based on NP. (b) The list of experts based on TC.
Table 5. Top 10 most productive institutions in the tourism and real estate literature.
Table 5. Top 10 most productive institutions in the tourism and real estate literature.
RankAffiliationNPCountry
1Prince of Songkla University11 Sustainability 14 10177 i001 Thailand
2University of Alicante10 Sustainability 14 10177 i002 Spain
3Sichuan University9 Sustainability 14 10177 i003 China
4Simon Fraser University9 Sustainability 14 10177 i004 Canada
5North South University8 Sustainability 14 10177 i005 Bangladesh
6Yunnan Normal University8 Sustainability 14 10177 i006 China
7Griffith University7 Sustainability 14 10177 i007 Australia
8Nanjing Normal University7 Sustainability 14 10177 i008 China
9CSIR7 Sustainability 14 10177 i009 India
10Udayana University7 Sustainability 14 10177 i010 Indonesia
11Sun Yat-sen University6 Sustainability 14 10177 i011 China
12Universidad De Córdoba6 Sustainability 14 10177 i012 Spain
13Anhui Normal University5 Sustainability 14 10177 i013 China
14Fujian Normal University5 Sustainability 14 10177 i014 China
15Huaqiao University5 Sustainability 14 10177 i015 China
16Natural Resources Institute Finland5 Sustainability 14 10177 i016 Finland
17UNU-IAS5 Sustainability 14 10177 i017 Japan
18Universidad De Extremadura5 Sustainability 14 10177 i018 Spain
19Universiti Sains Malaysia5 Sustainability 14 10177 i019 Malaysia
20University of Exeter5 Sustainability 14 10177 i020 England
NP, number of publications.
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MDPI and ACS Style

Kabil, M.; Abouelseoud, M.; Alsubaie, F.; Hassan, H.M.; Varga, I.; Csobán, K.; Dávid, L.D. Evolutionary Relationship between Tourism and Real Estate: Evidence and Research Trends. Sustainability 2022, 14, 10177. https://doi.org/10.3390/su141610177

AMA Style

Kabil M, Abouelseoud M, Alsubaie F, Hassan HM, Varga I, Csobán K, Dávid LD. Evolutionary Relationship between Tourism and Real Estate: Evidence and Research Trends. Sustainability. 2022; 14(16):10177. https://doi.org/10.3390/su141610177

Chicago/Turabian Style

Kabil, Moaaz, Mohamed Abouelseoud, Faisal Alsubaie, Heba Mostafa Hassan, Imre Varga, Katalin Csobán, and Lóránt Dénes Dávid. 2022. "Evolutionary Relationship between Tourism and Real Estate: Evidence and Research Trends" Sustainability 14, no. 16: 10177. https://doi.org/10.3390/su141610177

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