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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.

This study aims to assess and analyse the efficiency of the tourism centres in the Southern Red Sea region, Egypt to apply coastal tourism development through the blue economy perspective. According to this aim, the study used two efficiency methods: Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH). A total of 29 tourism centres were selected to conduct the DEA and FDH methods. These efficiency methods (DEA-FDH) used inputs and outputs variables to estimate the efficiency of the tourism centres. The selected inputs were the length of the shoreline (km), area (ha), tourism investments (million EGP), quality of coral reefs, numbers of hotels, and tourism accommodation capacity. While the outputs were employees’ number and tourists’ number. The results indicate that, generally, the tourism centres in the Southern Red Sea region of Egypt showed high-efficiency scores, which reflects their good preparedness to implement the various coastal tourism development strategies from the blue economy perspective. The tourism centres in the Safaga-Quseir tourism sector were the most efficient ones, regardless of the efficiency models used. While the tourist centres representing the Ras Banas tourism sector were the least efficient centres in the whole sample (29 tourism centres).

A goal of land change modelers should be to communicate scenarios of future change that show the variety of possible future landscapes based on the consequences of management decisions. This study employs the Markov-FLUS model to simulate land-use changes in Hubei Province in multiple scenarios that consider social, economic, and ecological policies using 18 driving factors, including point-of-interest data. First, the Markov-FLUS model was developed and validated with historical data from 2000 to 2020. The model was then used to simulate land-use changes from 2020 to 2035 in four scenarios: natural development, economic priority, ecological protection, and cultivated land protection. The results show that the Markov-FLUS model effectively simulates the land-use change pattern in Hubei Province, with an overall accuracy of 0.93 for land use simulation in 2020. The Kappa coefficient and FOM index also achieved 0.86 and 0.139, respectively. In all four scenarios, cultivated land remained the primary land use type in Hubei Province from 2020 to 2035, while construction land showed an increasing trend. However, there were large differences in the simulated land use patterns in different scenarios. Construction land expanded most rapidly in the economic priority scenario, while it expanded more slowly in the cultivated land protection scenario. We designed the protection scenario to restrict the rapid expansion of construction land. In the natural development and economic priority scenarios, construction land expanded and encroached on cultivated land and forests. In contrast, in the ecological protection scenario, forests and water areas were well-preserved, and the decrease in cultivated land and the increase in construction land were effectively suppressed, resulting in a large improvement in land use sustainability. Finally, in the cultivated land protection scenario, the cultivated land showed an increasing trend. The spread and expansion of construction land were effectively curbed. In conclusion, the Markov-FLUS model applied in this study to simulate land use in multiple scenarios has substantial implications for the effective utilization of land resources and the protection of the ecological environment in Hubei Province.