China's First! "China Tourist Attraction Happiness Index (THI)" Officially Released

On April 20, the “China Tourist Attractions Happiness Index (THI)”, jointly developed by the China Tourist Attractions Association and OCT Innovation Research Institute, was officially released. The index includes the “Top 100 China Tourist Attractions Happiness Index (THI)” and the top 20 in categories such as natural landscapes, cultural landscapes, museums, rural pastoral areas, and modern entertainment. Beijing’s Palace Museum, Shanghai Disneyland, and the Chengdu Research Base of Giant Panda Breeding took the top three spots in the 2019 China Tourist Attractions Happiness Index (THI) rankings.

▲ China Tourist Attractions Happiness Index (THI) Top 100 List

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▲Top 20 Happy Index Rankings of Natural Scenic Spots in Chinese Tourist Attractions

▲List of Top 20 Tourist Attractions in China by Human Landscape Joy Index

▲ Top 20 Happy Index of Chinese Tourist Attractions - Museum Category

▲Top 20 Chinese Tourist Attractions: Rural and Pastoral Joy Index

▲ Top 20 List of Modern Entertainment Joy Index for Chinese Tourist Attractions

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“The China Tourist Attractions Joy Index (THI)” is positioned as a fair and scientific tourism index system with social influence and industry guidance. Based on the application of big data in tourism, it quantifies and scientifically analyzes tourists’ comprehensive experience reviews under the principles of fairness and objectivity, reflecting the contemporary characteristics of China’s tourism industry development. This index product not only helps with scenic spot operations but also provides valuable references for tourists planning trips. The “Joy Index” and its rankings are pioneering in the national tourism industry, with its core algorithm having applied for a patent at the National Intellectual Property Administration.

01

The Online Tourism Era

Focusing on Tourist Experience

According to professional analysis, the number of users in China’s online tourism market reached 360 million in 2018, and it is estimated to hit 390 million in 2019. The internet drives tourism towards digitalization and smart services, offering tourists a more convenient experience. The transition from offline to online travel, as well as the trend of “online travel + offline travel,” has become evident. As things stand, the contradiction between the people’s growing needs for a better life and unbalanced and inadequate development also exists in the tourism industry. There is also a mismatch between the renewal and development of tourist attractions and the demands of tourists. As the industry scale rapidly expands, the quality of scenic spots—represented by aspects like “food, accommodation, transportation, sightseeing, shopping, and entertainment”—cannot be overlooked.

▲Shenzhen Happy Valley

With the rise of mobile internet and online travel, tourists have gradually gotten used to expressing their opinions online and choosing attractions based on online reviews. However, online reviews come with drawbacks like large data volume, fragmentation, and poor intuitiveness. At the same time, a tourist’s experience is influenced by multiple factors at a scenic spot, with different types of attractions offering different experiences. Travelers have clear goals before heading out, so how they quickly pick a destination that delivers a strong experience based on their own needs is a key concern for scenic area managers. Generally, tourist reviews can reflect the overall emotional experience visitors have with a scenic spot. Therefore, applying big data to the evaluation, assessment, selection, management, and industry guidance of tourist attractions holds deep significance.

02

In-Depth Application of Big Data Tools

Helping Scenic Areas Improve Service Quality

The “China Tourist Attractions Happiness Index (THI)” study uses big data mining and analysis techniques, introducing semantic analysis into the tourism evaluation field to enhance traditional evaluation methods from the ground up. The THI selects 1,181 scenic area samples nationwide and conducts a year-long tracking study of tourism big data. The classification of scenic areas in the study follows the group standard “Classification of Tourist Attractions” (T/CTAA0001-2019) released by the China Tourist Attractions Association. The Happiness Index can perform both broad analysis across the entire industry and detailed evaluation of individual entities’ value judgments and problem diagnosis.

Based on online review data from tourists after their visits, the Happiness Index uses semantic recognition of these reviews to convert abstract emotions, feelings, and experiences into quantifiable, intuitive, visible, and measurable data. This bottom-up evaluation of scenic areas by tourists, compared to traditional evaluation systems, more accurately and objectively reflects the visitor experience. It provides a tool to precisely and quickly gauge industry trends and track consumer preferences, while leveraging a big data platform to cover a wide range of tourist perspectives and experience-oriented monitoring around the clock.

▲ Happy Farmland at Huanglongxi, Chengdu

Compared to rankings based on visitor numbers, the Happy Index ranking of scenic spots can intuitively and quickly reflect market feedback at different times, dynamically showcasing the level of tourism services. Scenic spot operators can adjust their business strategies in a timely manner based on feedback during different periods and throughout the year. For tourists, purchasing decisions for tourism products increasingly rely on online word-of-mouth. The Happy Index ranking aligns with user needs, providing a more precise and convenient reference for tourists when choosing scenic spots.

03

Innovative Tourism Research

Insights into the Industry’s Future

The “China Scenic Spot Happy Index (THI)” has brought about a significant transformation in China’s tourism evaluation through innovation in ideas, methods, models, indicators, and formats, propelling tourism evaluation into the era of big data.

The China Scenic Spot Happy Index (THI) research closely connects with market and tourist demands. By using algorithmic models, it measures the popularity and satisfaction levels of scenic spots, gaining insights into new trends, directions, characteristics, and evolving tourist needs. This research leverages new technologies to integrate fragmented data, helping scenic spots enhance smart management and operations, effectively improving the service levels and operational efficiency of cultural tourism enterprises. It focuses on achieving three key innovations: First, it shifts away from traditional methods of evaluating scenic spot quality based solely on expert reviews and sample surveys, adopting big data research methods to objectively and systematically reflect the operations and quality of scenic spots; second, it changes the top-down evaluation system, objectively assessing scenic spots from the perspective of tourist experiences; third, it develops algorithmic models to transform abstract emotions, feelings, and experiences into intuitive, visible, and measurable data.

In the future, the China Scenic Spot Happy Index (THI) research will continue to deepen by expanding research samples, enriching research content, and producing more comprehensive happy index reports. At the same time, it will tap into the value of tourism big data, using this research as a foundation to broaden the scope of index studies and build a composite index system encompassing criteria for evaluating China’s scenic spots.

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Editor-in-Charge丨Liu Lingchen

This Issue Editor丨Yang Yawen, Wu Wanying

Content Source丨OCT Innovation Research Institute