India Number of Hotels: Above Five Star data was reported at 153.000 Unit in 2017. This records an increase from the previous number of 146.000 Unit for 2016. India Number of Hotels: Above Five Star data is updated yearly, averaging 89.000 Unit from Dec 1997 (Median) to 2017, with 20 observations. The data reached an all-time high of 153.000 Unit in 2017 and a record low of 43.000 Unit in 1997. India Number of Hotels: Above Five Star data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under Global Database’s India – Table IN.QG004: Memo Items: Number of Hotels and Hotel Rooms.

The Research Team at VTC has contracted with STR, a leading lodging industry research company, to provide weekly and monthly lodging data for the Commonwealth of Virginia. The following reports include data for Virginia, STR’s pre-defined geographies across Virginia (markets and submarkets), and Virginia’s ten tourism regions. Statewide data is further broken down by hotel class scale such as Luxury, Upper Upscale, Upscale, Upper Midscale, Midscale, and Economy.

The hotel industry is essential for tourism. With the rapid expansion of the internet, consumers only search for their desired keywords on the website when they trying to find a hotel to stay, causing the relevant hotel information would appear. To quickly respond to the changing market and consumer habits, each hotel must focus on its website information and information quality. This study proposes a novel methodology that uses rough set theory (RST), principal component analysis, t-Distributed Stochastic Neighbor Embedding (t-SNE), and attribute performance visualization to explore the relationship between hotel star ratings and hotel website information quality. The collected data are based on the star-rated hotels of the Taiwanstay website, and the checklists of hotel website services are used to obtain the relevant attributes data. The results show that there are significant differences in information quality between hotels below two stars and those above four stars. The information quality provided by the higher star hotels was more detailed than that offered by low-star hotels. Based on the attribute performance matrix, the one-star and two-star hotels have advantage attributes in their landscape, reply time, restaurant information, social media, and compensation. Furthermore, the three-five star hotels have advantage attributes in their operational support, compensation, restaurant information, traffic information, and room information. These results could be provided to the stakeholders as a reference.

The global Hotel Market Intelligence Software market is experiencing robust growth, driven by the increasing need for hotels of all sizes to optimize revenue, enhance operational efficiency, and personalize guest experiences. The market, estimated at $2 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $6 billion by 2033. This expansion is fueled by several key factors. Firstly, the adoption of cloud-based solutions is accelerating, offering scalability, cost-effectiveness, and accessibility to real-time data for improved decision-making. Secondly, the rise of big data analytics and artificial intelligence (AI) within the software enables hotels to extract valuable insights from guest data, leading to more effective revenue management strategies, targeted marketing campaigns, and enhanced customer relationship management (CRM). The increasing competition within the hospitality sector further incentivizes hotels to leverage market intelligence software for a competitive edge. Segmentation within the market reveals strong demand across all hotel types, including luxury, mid-range, and budget options, reflecting the universal need for effective data-driven strategies regardless of hotel category. Geographical analysis shows a significant market presence in North America and Europe, with emerging markets in Asia-Pacific and the Middle East & Africa exhibiting rapid growth potential. However, challenges remain. The high initial investment cost of sophisticated software solutions, coupled with the need for ongoing technical support and training, can deter smaller hotels from adoption. Furthermore, data security and privacy concerns, along with the complexities of integrating various data sources, represent potential barriers to market penetration. Despite these restraints, the continuing trend toward technological advancement within the hospitality sector and the undeniable value proposition of data-driven decision-making are likely to drive sustained growth in the Hotel Market Intelligence Software market throughout the forecast period. The competitive landscape is dynamic, with a mix of established players and emerging innovators offering a wide array of solutions to cater to diverse hotel needs and preferences. The market's future trajectory appears strongly positive, with continued innovation and increasing adoption across all segments expected.

The hotel industry is essential for tourism. With the rapid expansion of the internet, consumers only search for their desired keywords on the website when they trying to find a hotel to stay, causing the relevant hotel information would appear. To quickly respond to the changing market and consumer habits, each hotel must focus on its website information and information quality. This study proposes a novel methodology that uses rough set theory (RST), principal component analysis, t-Distributed Stochastic Neighbor Embedding (t-SNE), and attribute performance visualization to explore the relationship between hotel star ratings and hotel website information quality. The collected data are based on the star-rated hotels of the Taiwanstay website, and the checklists of hotel website services are used to obtain the relevant attributes data. The results show that there are significant differences in information quality between hotels below two stars and those above four stars. The information quality provided by the higher star hotels was more detailed than that offered by low-star hotels. Based on the attribute performance matrix, the one-star and two-star hotels have advantage attributes in their landscape, reply time, restaurant information, social media, and compensation. Furthermore, the three-five star hotels have advantage attributes in their operational support, compensation, restaurant information, traffic information, and room information. These results could be provided to the stakeholders as a reference.

China Star-Rated Hotel: Number of Employee data was reported at 633.293 Person th in 2023. This records a decrease from the previous number of 636.889 Person th for 2022. China Star-Rated Hotel: Number of Employee data is updated yearly, averaging 1,350.581 Person th from Dec 2001 (Median) to 2023, with 23 observations. The data reached an all-time high of 1,672.602 Person th in 2009 and a record low of 633.293 Person th in 2023. China Star-Rated Hotel: Number of Employee data remains active status in CEIC and is reported by Ministry of Culture and Tourism. The data is categorized under China Premium Database’s Hotel Sector – Table CN.QHA: Star-Rated Hotel Operation.

A merged dataset of the Hotels, Motels, B&Bs, and Boarding Houses and the Short-Term Rentals datasets.

This table presents an overview of of the capacity (type of accommodation, rooms, beds) in the Netherlands in all hotels, motels, boarding houses, apartments with hotel services, youth accommodation and bed & breakfasts with at least 5 sleeping places. The figures can be broken down by star rating. Figures are available for The Netherlands as a whole, and for the city of Amsterdam.

The breakdown by star rating is based on the opinion of the accommodation itself. The star rating does not have to be officially registered. The breakdown contains all types of accommodation mentioned above, not just hotels. The '5 stars' category contains 5 star hotels, but also for instance 5 star bed&breakfasts.

Break in series: Figures on guests and overnight stays per star rating for the years until 2015, that were published before, were based on offical registrations of the number of stars by the 'Bedrijfschap Horeca en Catering'. This official registration does no longer exist. Therefore, Statistics Netherlands started asking accommodations about their number of stars in its annual survey. For this reason, the figures in this table are not directly comparable with figures published about the years until 2015.

Data available from: 2017

Status of the figures: The figures for 2024 are provisional and al other figures are final.

Changes as of 11 July 2025: The provisional figures for May 2025 have been added.

When will new figures be published? Figures of a new month become available within three months after the end of that month, these are provisional figures. The figures for the complete year are revised one month after publication of the December figures, these are revised provisional figures. Two months later definite figures will be published.

Spain Number of Hotels: Gold Star: 4 Stars data was reported at 2,480.000 Unit in Oct 2018. This records a decrease from the previous number of 2,628.000 Unit for Sep 2018. Spain Number of Hotels: Gold Star: 4 Stars data is updated monthly, averaging 1,616.500 Unit from Jan 1999 (Median) to Oct 2018, with 238 observations. The data reached an all-time high of 2,634.000 Unit in Aug 2018 and a record low of 669.000 Unit in Jan 1999. Spain Number of Hotels: Gold Star: 4 Stars data remains active status in CEIC and is reported by National Statistics Institute. The data is categorized under Global Database’s Spain – Table ES.Q020: Hotel Statistics.

China Star-Rated Hotel: Revenue data was reported at 39,001.000 RMB mn in Sep 2024. This records an increase from the previous number of 36,870.000 RMB mn for Jun 2024. China Star-Rated Hotel: Revenue data is updated quarterly, averaging 50,216.000 RMB mn from Sep 2010 (Median) to Sep 2024, with 55 observations. The data reached an all-time high of 65,759.000 RMB mn in Dec 2011 and a record low of 17,803.000 RMB mn in Mar 2020. China Star-Rated Hotel: Revenue data remains active status in CEIC and is reported by Ministry of Culture and Tourism. The data is categorized under China Premium Database’s Hotel Sector – Table CN.QHA: Star-Rated Hotel: Revenue.

Shanghai: Star-Rated Hotel: Number of Hotel data was reported at 144.000 Unit in 2023. This records a decrease from the previous number of 151.000 Unit for 2022. Shanghai: Star-Rated Hotel: Number of Hotel data is updated yearly, averaging 256.000 Unit from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 366.000 Unit in 2004 and a record low of 138.000 Unit in 1999. Shanghai: Star-Rated Hotel: Number of Hotel data remains active status in CEIC and is reported by Shanghai Municipal Tourism Administration. The data is categorized under Global Database’s China – Table CN.QHRA: Star-Rated Hotel: Shanghai.

Yunnan: Star-Rated Hotel: Revenue: Room data was reported at 1,666.000 RMB mn in 2023. This records an increase from the previous number of 1,160.160 RMB mn for 2022. Yunnan: Star-Rated Hotel: Revenue: Room data is updated yearly, averaging 2,150.976 RMB mn from Dec 2003 (Median) to 2023, with 21 observations. The data reached an all-time high of 3,945.761 RMB mn in 2013 and a record low of 664.476 RMB mn in 2003. Yunnan: Star-Rated Hotel: Revenue: Room data remains active status in CEIC and is reported by Yunnan Provincial Tourism Administration. The data is categorized under China Premium Database’s Hotel Sector – Table CN.QHRA: Star-Rated Hotel: Yunnan.

Beijing: Star-Rated Hotel: Room Occupancy Rate data was reported at 60.200 % in Dec 2024. This records a decrease from the previous number of 64.900 % for Nov 2024. Beijing: Star-Rated Hotel: Room Occupancy Rate data is updated monthly, averaging 60.150 % from Jan 2008 (Median) to Dec 2024, with 184 observations. The data reached an all-time high of 78.800 % in Aug 2019 and a record low of 16.500 % in Apr 2020. Beijing: Star-Rated Hotel: Room Occupancy Rate data remains active status in CEIC and is reported by Beijing Municipal Commission of Tourism Development. The data is categorized under China Premium Database’s Hotel Sector – Table CN.QHRA: Star-Rated Hotel: Beijing.

Jiangsu: Star-Rated Hotel: Room Occupancy Rate data was reported at 53.750 % in 2023. This records an increase from the previous number of 44.190 % for 2022. Jiangsu: Star-Rated Hotel: Room Occupancy Rate data is updated yearly, averaging 58.890 % from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 66.440 % in 2004 and a record low of 41.900 % in 2020. Jiangsu: Star-Rated Hotel: Room Occupancy Rate data remains active status in CEIC and is reported by Jiangsu Provincial Tourism Bureau. The data is categorized under Global Database’s China – Table CN.QHRA: Star-Rated Hotel: Jiangsu.

Indonesia Hotel Room Occupancy: Bali: 5 Star data was reported at 51.600 % in May 2019. This records a decrease from the previous number of 61.800 % for Apr 2019. Indonesia Hotel Room Occupancy: Bali: 5 Star data is updated monthly, averaging 62.600 % from Sep 1989 (Median) to May 2019, with 357 observations. The data reached an all-time high of 86.000 % in Sep 1989 and a record low of 17.900 % in Nov 2002. Indonesia Hotel Room Occupancy: Bali: 5 Star data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Indonesia – Table ID.QC001: Hotel Room Occupancy Rate.

Hainan: Star-Rated Hotel: Number of Hotel data was reported at 75.000 Unit in 2023. This records a decrease from the previous number of 85.000 Unit for 2022. Hainan: Star-Rated Hotel: Number of Hotel data is updated yearly, averaging 150.000 Unit from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 263.000 Unit in 2007 and a record low of 59.000 Unit in 1999. Hainan: Star-Rated Hotel: Number of Hotel data remains active status in CEIC and is reported by Hainan Tourism Administration. The data is categorized under Global Database’s China – Table CN.QHRA: Star-Rated Hotel: Hainan.

Number of Hotel Rooms: Gujarat: Three-Star data was reported at 2,949.000 Unit in 2020. This records a decrease from the previous number of 2,990.000 Unit for 2019. Number of Hotel Rooms: Gujarat: Three-Star data is updated yearly, averaging 1,697.000 Unit from Dec 2004 (Median) to 2020, with 14 observations. The data reached an all-time high of 2,990.000 Unit in 2019 and a record low of 1,188.000 Unit in 2014. Number of Hotel Rooms: Gujarat: Three-Star data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under India Premium Database’s Hotel Sector – Table IN.QHA004: Number of Hotel Rooms: by States.

Yunnan: Star-Rated Hotel: Number of Hotel data was reported at 298.000 Unit in 2023. This records a decrease from the previous number of 334.000 Unit for 2022. Yunnan: Star-Rated Hotel: Number of Hotel data is updated yearly, averaging 559.500 Unit from Dec 1991 (Median) to 2023, with 26 observations. The data reached an all-time high of 904.000 Unit in 2008 and a record low of 40.000 Unit in 1991. Yunnan: Star-Rated Hotel: Number of Hotel data remains active status in CEIC and is reported by Yunnan Provincial Tourism Administration. The data is categorized under Global Database’s China – Table CN.QHRA: Star-Rated Hotel: Yunnan.

Turkey Occupancy Rate: 5 Star Hotels data was reported at 31.884 % in Feb 2025. This records a decrease from the previous number of 33.928 % for Jan 2025. Turkey Occupancy Rate: 5 Star Hotels data is updated monthly, averaging 39.448 % from Jan 2017 (Median) to Feb 2025, with 98 observations. The data reached an all-time high of 93.787 % in Aug 2019 and a record low of 1.271 % in May 2020. Turkey Occupancy Rate: 5 Star Hotels data remains active status in CEIC and is reported by Republic of Turkey, Ministry of Culture and Tourism. The data is categorized under Global Database’s Turkey – Table TR.Q022: Accommodation Establishments: Occupancy Rate.

Turkey Accommodation Establishments: TI: 4 Star Hotels data was reported at 253.000 Unit in 2017. This records a decrease from the previous number of 296.000 Unit for 2016. Turkey Accommodation Establishments: TI: 4 Star Hotels data is updated yearly, averaging 163.500 Unit from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 311.000 Unit in 2013 and a record low of 90.000 Unit in 1996. Turkey Accommodation Establishments: TI: 4 Star Hotels data remains active status in CEIC and is reported by Republic of Turkey, Ministry of Culture and Tourism. The data is categorized under Global Database’s Turkey – Table TR.Q019: Accommodation Establishments: by Type and Class.