economic impact of tourism in china

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China’s Travel & Tourism Sector to Create More Than 30 Million Jobs Over the Next Decade

London, UK: The World Travel & Tourism Council (WTTC) has revealed the Travel & Tourism sector in China is expected to create more than 30 million jobs over the next decade, representing a quarter of all new jobs globally.

The forecast from WTTC’s latest Economic Impact Report (EIR) shows the sector will reach more than 107 million employed within the sector by 2032. According to the global Tourism body’s latest data, Travel & Tourism’s GDP is expected to grow at an average of 9.7% over the next 10 years, more than twice the 4.4% growth rate of the national overall economy, making it one of the fastest growing countries.

This growth will boost the sector to reach more than ¥25.2 trillion (13.7% of the total economy) by 2032.

The report shows the Travel & Tourism sector’s contribution to China’s economy could also surpass pre-pandemic levels next year, when it is projected to rise almost 10% above 2019 levels.

By the end of 2023, the sector’s contribution to the national economy could reach more than ¥ 13 trillion, with a year-on-year growth of more than 32%. Employment within the sector could also exceed pre-pandemic levels, creating more than 766,000 additional jobs, to reach more than 83 million by the end of 2023.

WTTC warns that this will only be achieved if China continues to facilitate both international and domestic travel.

Julia Simpson, WTTC President & CEO, said: “Over the next decade, the outlook is incredibly positive.

“But in the short term, while much of the rest of the world and indeed the region is now open to travellers, travel to China remains off limits for many international travellers.

“Domestic travel has provided and will continue to provide some relief to China’s economy, but at the moment, international travel spending is very low and is critical for the Chinese overall economy.

“Although cutting the quarantine time for international travellers is a step in the right direction, it’s not enough to have any real positive impact.”

In 2019, when Travel & Tourism was at its peak, international visitor spending in China reached nearly ¥951 billion (14% of total internal spending). However last year, as China kept its borders closed, the total spend was less than ¥91 billion (3%), missing out on nearly ¥862 billion every year.

Before the pandemic, China’s Travel & Tourism total contribution to GDP was 11.6% (more than ¥11.9 trillion) in 2019, falling just to 4.3% (nearly ¥4.5 trillion) in 2020, representing a staggering 62.5% loss.

The sector also supported more than 82 million jobs, before a complete halt to international travel which resulted in a loss of more than 12 million (15.2%), to reach just over 69 million in 2020.

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The impact of economic and environmental factors and tourism policies on the sustainability of tourism growth in China: evidence using novel NARDL model

• Research Article
• Published: 14 October 2022
• Volume 30 , pages 19326–19341, ( 2023 )

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• Qin Chen 1  

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Recently, sustainability of tourism growth has become an international issue due to environmental and economic uncertainty that needs recent researchers’ focus and also requires the policymakers’ attention. Therefore, the present research has examined the role of economic and environmental factors and tourism policy related to tourist arrival on the sustainability of tourism growth in China. The economic factor includes the gross domestic product (GDP), national income, and foreign direct investment (FDI), while environmental factors include carbon dioxide (CO 2 ) emission, greenhouse gas (GHG) emission, and nitrous oxide emission. The study has extracted the data from World Development Indicators (WDI) from 1990 to 2020. The present research has employed nonlinear autoregressive distributed lagged (NARDL) to check the linkage among variables. The current study also examines the unit root using Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests. The results revealed that GDP, national income, tourism policy related to tourist arrival, and FDI have a positive linkage with the sustainability of tourism growth. The results also exposed that environmental factors such as CO 2 emission, GHG emission, and nitrous oxide emission have a negative linkage with the sustainability of tourism growth. This study provides the guidelines to the relevant authorities and regulators in developing and implementing the regulators regarding the sustainability of tourism growth by promoting economic and environmental conditions and effective tourism policies in the country.

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Introduction

The sustainability of tourism growth is a significant factor in a country’s development as it assures sustainability in social and economic well-being. The tourism industry, with all related activities like transportation, lodging, feeding, and entertainment venues, can be taken as the source of economic development. It in itself provides a complete mechanism to create employment opportunities, increase production levels, and generate income in both the formal and informal economic industries. Sustainability of tourism growth creates sustainability in the foreign exchange earnings that are generated from international trade in goods and sometimes from the act of financing the purchases of capital goods from foreign countries, availability of the goods that are necessary for the manufacturing or service sectors in the economy (Ainou et al. 2022 ; Streimikiene et al. 2021 ). The sustainability of tourism growth is also a source of sustainable social growth in the country, which ends with a sustainable rise in economic growth. The sustainability in growth in the tourism industry of the country keeps on attracting many foreign travelers, often businesses travelers, to the country and giving them a chance to get familiar with the businesses operating within countries, their characteristics like their risks and opportunities, and develops social relations among them (Bianchi 2018 ; Chien et al. 2021 ). These social relations come to an end with the commercial dealings or contracts among the travelers and the particular firms’ representatives. Moreover, when the travelers meet with the local people, they exchange their ideas and culture, which brings improvement to their lives. Hence, tourism growth enhances the human capital within the country and provides efficient human resources to the business firms within the country (Chien et al. 2022a ; León-Gómez et al. 2021 ).

Economic growth, environmental quality, and tourism policies are crucial factors in developing sustainability in tourism growth. The sustainability of tourism growth depends on the development of transportation, accommodation, food production and processing, innovative shopping centers, recreational parks, or other sort of entertainment. For all these tourism practices, financial resources are required in a sufficient amount; it also requires increased and sustainable productivity in other related economic sectors as well and needs improved human capital that not only develops tourism but also sustains this development (Chien et al. 2022b ; Kyrylov et al. 2020 ). Economic growth like the increase in GDP, NNI, and FDI enhances financial resources, increases productivity in all economic sectors, and improves human capital. So, the increase in GDP, NNI, and FDI, along with favorable and effective tourism policies related to tourist arrival, enhances tourism growth and helps to sustain it (Hall 2019 ). The natural environment provides a setting for tourist destinations; it determines the quality of natural resources, food, and water facilities for the tourists and the work efficiency of human resources performing their services for the tourism industry. If the country is confronted with environmental pollution like CO 2 emissions, GHG emissions, and nitrous oxide (N 2 O) emissions, it becomes difficult to develop tourism destinations and other tourism practices there as the quality of natural resources, food, and water facilities for the tourists, and health and work efficiency of human resources, etc. (Huang et al. 2021 ; Kapera 2018 ). In addition, Covid-19 is also a significant factor that affects the tourism growth around the globe. The travelling restrictions due to the Covid-19 had dramatic effects on tourism, but the current study has taken the data from 1990 to 2020; thus, only the year 2020 suffered from this disaster so Covid-19 did not affect the study results.

The tourism policy is the collection of decisions, discourses, and practices driven by governments alone or governments in collaboration with some social or private actors with the motive to achieve objectives regarding tourism. The content of the tourism policy is subject to copyright. The tourism policy provides a collection of rules, regulations, directives, guidelines, development goals, and strategies that offer a framework within which the group, as well as individual, decisions directly influence daily activities within a destination and sustainable tourism development. For instance, if the tourism policy designed by the government declares that the tourism firms must undertake environmentally friendly activities, the quality of the atmosphere, land resources, food products, transportation, and all other things are kept clean and not damage the tourist, employees, or general public health. This ensures a clean tourism environment, healthy labor, social support, and the preference of potential customers. So, the firm can enjoy sustainable tourism development (Adu-Ampong 2019 ; Kamarudin et al. 2021 ; Lan et al. 2022 ).

This study examines the influences of economic factors; GDP, GNI, and FDI; and environmental factors, CO 2 emissions, GHG emissions, and N 2 O emissions, on tourism growth in China. The tourist industry in China is one of the fastest-growing sectors of the economy and one of the industries with a particular worldwide competitive advantage. In terms of worldwide tourist competitiveness, China's tourism industry rose from 71st in 2007 to 13th in 2019 (Li et al. 2021a , b ; Scheyvens and Biddulph 2018 ). China has established itself as a major player in the global tourism industry. Following the formation of the world’s largest domestic tourism market, China has become the state that generates tourists in the largest number in the country for outbound tourism. Moreover, inbound tourism maintains its position as a global leader (Liu et al. 2020 , 2022a ). The domestic tourist industry keeps on growing at a rapid pace. In 2019, there were 6.01 billion domestic tourists, up 8.4% from the previous year; of these, 4.4710 billion were urban people, up 8.5%, and 1535 million were rural people, up to 8.1%. Domestic tourism revenue increased by 11.7% to 5.73 trillion yuan (the US$1.36 trillion). Urban people made have made expenditures of 4.75 trillion yuan (the US$ 1.13 trillion), an 11.6% increase, while rural people made expenditures of 0.97 trillion yuan (the US$ 0.23 trillion), a 12.1% increase (Liu et al. 2022b ; Wang and Yotsumoto 2019 ).

Domestic tourism consumption per capita climbed from 511 yuan (US$ 160.59) in 2008 to 945 yuan (US$ 225.11) in 2019, and it is still growing. The disparity in per capita spending between urban and rural populations is diminishing. In 2019, urban people spent 1062.6 yuan (US$ 253.12) per capita, while rural residents spent 634.7 yuan (US$ 155 33) per capita on domestic tourism. From 574.1 yuan (the US$ 180.42) to 427.9 yuan (the US$ 101.93), the difference between urban and rural populations has decreased (Li et al. 2021a , b ; Moslehpour et al. 2022a ). China’s outbound tourism industry increased gradually in 2019 as a result of tourism consumption increase and income growth. The number of Chinese people who traveled abroad in 2019 was 155 million, up 3.3% from the previous year. In general, China’s inbound tourist market is gradually growing. As per the 2018 statistics, 47.95 million foreign tourists visited the country. The number of international visitor arrivals in China was steady from 2008 to 2018 (Moslehpour et al. 2021 ; J. Zhang and Cheng 2019 ). International tourism receipts totaled the US$127.102 billion, a 3.0% increase from the last year. China rose three times in terms of international tourism earnings, and its share of global tourism continues to rise. It can be seen that international tourists’ consumption levels have increased in China, indicating that the country’s tourism market is maturing. Inbound tourism in China has a lot of potentials (Moslehpour et al. 2022b ; Yu et al. 2020 ). The State Council unveiled a development strategy for the tourism industry during the 14th Five-Year Plan period on January 20 (2021–2025). According to this plan, by 2025, China will have a more robust contemporary tourism system that integrates cultural development and boasts enhanced services and a barrier-free environment. The nation wants to be a global tourism powerhouse by 2035, with a greater range of tourist hotspots, such as national cultural parks, top-notch resorts, and tourist attractions and state-level cities and blocks that cater to tourism and leisure. Many policies for technological advancements, cultural development, infrastructure, and special tourism zones have been made (Haibo et al. 2020 ; Sadiq et al. 2022a ). Some statistics related to the tourism growth in China is given in Fig.  1 .

Tourism Growth in China

The majority of China’s tourist-generating countries are located in its immediate vicinity. South Korea has been the leading source of tourists to China these years. Despite the fact that Japan is the second most popular tourist destination after China, the visitors’ strength has decreased, which may be because of the China-Japan tension (Gao et al. 2021a , b ; Sadiq et al. 2022b ). Since China presents a mysterious, unique culture, tourists from America, Russia, Malaysia, Mongolia, Singapore, and other neighboring countries feel interested in China (Sadiq et al. 2022c ; Zhang et al. 2021 ). Though the tourism industry in China has been growing at a significant rate, it is still required that information on the threats which are feared to become a hurdle to getting high tourism growth is acquired, and these threats must be removed. This is the main concern of the present study so that the Chinese tourism industry can be led to sustainable growth. The objective of the study is to explore the influences of three economic factors, GDP, GNI, and FDI; tourism policy; and three environmental factors, CO 2 emissions, GHG emissions, and N 2 O emissions, on tourism growth.

This study is a great contribution to the literature on tourism. First, in the past literature, the authors have written about the role of economic conditions and environmental elements in tourism growth. But it is rare in the existing literature that the role of economic and environmental conditions in the sustainability of tourism growth has not been checked through single research. The study of Cave and Dredge ( 2020 ) has examined only economic condition impacts on sustainable tourism development and shows the need for environmental factor impacts on sustainable economic development. Moreover, little attention is paid to tourism policies’ impacts on sustainable tourism growth. The present article, which amalgamates the role of economic conditions, environmental conditions, and tourism policies on sustainable tourism growth, makes a contribution to literature. Second, CO 2 emissions and N 2 O emissions are hazardous gases that cause GHG effect and degrade the environment. These gases and their impacts on sustainable tourism growth have been examined as GHG emissions like D. Liu et al. ( 2021 ). The study, which individually checks CO 2 and N 2 O emission impacts on tourism growth with ample detail, adds to the literature. Third, the economy of China significantly relies on tourism practices and earnings from this sector. China is one of the largest countries causing environmental pollution, which is a hurdle to sustainable tourism growth. But little study has been done on sustainable tourism growth for economic conditions, environmental conditions, and tourism policies. The present article adds much to the literature by analyzing the impacts of economic conditions, environmental conditions, and tourism policies on sustainable tourism growth in the context of China.

The present paper has several parts: The 2nd one analyzes the relationship between the GDP, GNI, FDI, tourism policy related to tourist arrival, CO 2 emissions, GHG emissions, and N 2 O emissions and tourism growth with a review of past literature. The 3rd part is about the process adopted for the collection of data and the analysis of the information in hand for the nexus among the factors under consideration. The analysis provides the study findings of the nature of the relationship among the study constructs. The results after analysis are compared with the relevant findings of previous studies. Thereafter, the conclusion of the study, its implications, and limitations are given.

Literature review

In any country, the tourism industry has great significance to economic development and social prosperity. It creates revenues for the country in the form of national currency or foreign exchange from the tourists, generates taxes from tourism, and stimulates the productivity of other related commercial enterprises (Xu and Gu 2018 ). It can achieve many progressive opportunities from economic growth. For example, with economic growth like the increase in GDP, GNI, FDI, and favorable tourism policies, there is a better financial position, technological development, increased productivity, production quality improvement, and new ways to attract tourists. On the other hand, tourism has some environmental threats, such as CO 2 emissions, GHG emissions, and N 2 O emissions. As the environment and its elements provide resources for different economic activities, pollutants like CO 2 emissions, GHG emissions, and N 2 O emissions by destroying environmental quality retard tourism growth (Shen et al. 2019 ; Tan et al. 2021 ). The relationship between economic factors like GDP, GNI, FDI, and tourism policy and three environmental factors like CO 2 emissions, GHG emissions, and N 2 O emissions and tourism growth has frequently been discussed in the existing literature. The present study examines the relation of economic growth like GDP, GNI, and FDI, and tourism policy related to tourist arrival and environmental pollutants like CO 2 emissions, GHG emissions, and N 2 O emissions with tourism growth in the light of previously conducted studies.

In a research article, Ben Jebli and Hadhri ( 2018 ) wrote about the impacts of real GDP, energy use, and CO 2 emissions from transport on international tourism. A survey was conducted on ten international tourism destinations over the the period from 1995 to 2013, with the help of the Granger causality and error correction model, the relationship between the real GDP, energy use, CO 2 emissions from transport, and international tourism. The study implies that real GDP has a positive relation to international tourism growth. With the increase in the GDP, the capacity of the country to arrange for the resources to be used in tourism practices increases as it raises the productivity of the goods and services that are essential in tourism and also assists in improving the quality of tourism resources and services. A study was conducted by Ghosh et al. ( 2020 ) to investigate the nexus between a country’s per capita GDP and the growth of marine tourism in the Oceania region, the area of the South Pacific Ocean containing many different collections of islands. A panel of data was acquired from a sample of 11 nations of Oceania spanning the period from 1995 to 2018. The study implies that when it is prosperous with high GDP, marine development is likely to grow within the country as it can invest in the implementation of tourism activities like accommodation, recreation, restaurant, and food services to coasts along with other coastal and marine tourism infrastructure including retail system, transport hubs, activity suppliers, and marinas. Tian et al. ( 2021 ) also find a positive link between a country’s GDP and tourism growth as it is the source of investment and essential resources available for tourism. Through an in-depth investigation, León-Gómez et al. ( 2021 ) examine the relationship of economic growth measured by GDP with sustainable tourism growth. The authors collected the required information for GDP and sustainable tourism growth from 668 articles on the topic of economic growth and sustainable tourism development published in the Web of Science database. The research states that when a country is making high economic growth, the tourism firms are able to utilize sustainable technologies in tourism practices. This leads the tourism industry towards sustainable growth. Hence, GDP has a positive link with sustainable tourism growth.

Many foreigners with an intention to expand their source of earnings make an investment in domestic business projects, construction, or developmental projects. FDI may be directly in the tourism firms, tourism destination development projects, or tourism construction works. It may also be in the firms engaging in natural development, tourism resource production, and providers of tourism-related facilities like tourism infrastructure, transportation, communication, and information system. So, when the FDI increases, the tourism firms have the chance to add value to the existing tourism destination and services and expand the tourism scope (Paramati et al. 2018 ; Zhao et al. 2021 ). The study by Fauzel ( 2020 ) analyzes the influences of FDI on tourism growth. By employing a panel vector error correction model (PVECM), the authors analyzed the FDI impacts on tourism development in the selected collection of 17 small island economies for the time from 1995 to 2018. The authors found a positive and direct relation between FDI and tourist arrivals or tourism growth. This study implies that FDI plays a vital role in tourism development. When the countries can successfully attract FDI and growth economically, the tourism sector can grow soon in the future as it depends much on economic growth. The research by El Menyari ( 2021 ) examines the impacts of FDI on international tourism growth. The authors collected data from the economy of Morocco for the period from 1983 to 2018. Using the autoregressive distributed lag (ARDL) approach and causality tests, the authors found a positive relationship between FDI and international tourism growth. The increase in the amount of investment from foreign sources clears the way for the tourism industry to place its feet beyond the state boundaries. The study conducted by Amin et al. ( 2020 ) investigates the influences of FDI on sustainable tourism development. The annual time series data for FDI and sustainable tourism development were acquired from Bangladesh for the period 1972–2017. Standard econometric techniques, like ADF, PP, and Zivot-Andrews unit root tests; Granger causality test; Johansen cointegration test; VECM, DOLS, and ARDL estimation methods; and cumulative sum (CUSUM) stability test have been applied to check the relationship among factors. The study results reveal that with the increase in FDI, the technological and managerial capital gets improved in the tourism industry. With the improved technologies and managerial capital, tourism growth can be sustainable. Thus, there is a positive relation between FDI and sustainable tourism development.

The tourism industry is a wide economic sector, and it is based on many other economic practices carried on within the country as it requires a large number of products and services that others produce. It is also dependent on the financial position of the country and its inhabitants. The country’s GNI increase refers to the increase in the production of goods and services within the country and also determines the financial strength of the country and the financial prosperity of the individuals. So, the country’s GNI has a positive link to tourism growth within the country (Razzaq et al. 2021 ). Empirical research by Zhang and Cheng ( 2019 ) analyzes the relation of national income with the sustainability of tourism growth. It highlights that when a country’s national income is high, the economy is stable, and business firms are engaged in their production activities. Because of their stronger financial position, they are able to focus not only on the marketing of existing items but also on the enhancement of product and service quality. In the tourism industry, enterprises’ own concentration on providing high-quality services to visitors, as well as the procurement of high-quality resources and products from other businesses, enables them to match the tourists’ quality expectations. Gao et al. ( 2021a , b ) identify the relationship between economic growth measured by national income, environmental protection, and sustainable tourism development with the evidence through a panel from 18 Mediterranean countries for the period from 1995 to 2010. The study implies that with the rise in the national income, a stronger financial position allows the ecological friendly initiatives on the part of government and individual firms. The improved atmosphere and better quality of natural resources help the growing tourism industry and getting sustainability of tourism firms. The literary article of Umurzakov et al. ( 2022 ) throws light on the economic development measured by national income and sustainable tourism growth. The information for national income and sustainable tourism development was acquired from 57 BRI countries for the time from 2000 to 2018, and the GMM estimator was applied to extract results that indicated a positive link between national income and sustainable tourism growth.

Empirical research was conducted by Kapera ( 2018 ) to examine the role of tourism policies in developing the sustainability of tourism growth. The standardized questionnaire was applied in this research, and it was distributed to 2500 municipal offices in Poland either through the empirical survey or through electronic ways in order to collect data regarding the tourism policy for providing clean tourism destinations and other tourism facilities and the sustainability in tourism growth. The data were collected from 600 end respondents. The study posits that when the policies regarding the tourism destination and practices are favorable and effectively implemented, it brings improvement in tourism facilities. For instance, if the tourism policy related to tourist arrival improvements is effectively implemented, it maintains the quality of accommodation and recreational destinations established by tourism firms maintain the clean environment for the tourists, and also assists the production of other economic products. So, favorable tourism policies enhance the sustainability of tourism growth. A study presented by Guo et al. ( 2019 ) identifies the relationship between tourism policy and the sustainability of tourism growth. The study is based on a previous research review. A total of 515 observations were taken from this literary research survey. The research survey proves that different tourism growth policies were formulated by government authorities and tourism firms for enhancing the social and environmental development of the tourism industry within the country and to develop sustainability in tourism growth. So, tourism policy and sustainable tourism growth are positively linked. The study presented by A. Khan et al. ( 2020 ) focuses on tourism policy influences on sustainable tourism growth. It examines the tourism policies regarding capital, investment, energy consumption, and environmental management in developing countries with greater attention to Pakistan. Various econometric techniques and procedures were employed to check the proposed hypotheses. The results convey that positive tourism policies encourage sustainable tourism growth. Likewise, the article by Hall ( 2019 ) also affirms that the tourism policy that is a set of specific rules, regulations, practices, strategies, and decisions automatically leads the tourism industry towards sustainable growth.

CO 2 emissions are one of the hazardous gases that could adversely affect the environment’s capacity to produce natural resources, the quality of natural resources, and the heath of living creatures, including human beings (Koçak et al. 2020 ). Tourism is the economic sector that is directly or indirectly linked to the natural environment and its elements. When in a country, because of households or operations of many commercial entities, there are a large amount of CO 2 emissions into the air, the practices of tourism become paralyzed, the tourism services may lose quality, and tourists’ attraction becomes a difficulty. So, there is downward tourism growth as a result of CO 2 emissions, and sustainability of tourism growth becomes difficult (Fethi and Senyucel 2021 ). Liu et al. ( 2019 ) intended to explore the relationship between energy consumption, CO 2 emission, and sustainability of tourism growth with respect to international tourism. The data for the nexus between these factors and tourism growth was taken from the economy of Pakistan over the years from 1980 to 2016 by using the autoregressive distributed lagged (ARDL) model. Furthermore, Granger causality and the DOLS model were applied for robust analysis. The findings show that economic growth and energy consumption are major causes of CO 2 emissions in a country. In this situation, there are adverse changes in the climate balance, weather pattern, soil condition, and ocean level. Consequently, the natural scenery and natural resources that are used as recreation sources or food for tourists are adversely affected and weaken tourism growth. Hence, sustainability in tourism growth is disturbed because of the increase in CO 2 emissions. Dogru et al. ( 2020 ) proclaim that the increasing amount of CO 2 emissions into the air pollutes the atmosphere, disturbs the water level, and traps the heat in over quantity. The environmental deterioration can endanger the health of human resources and tourists; thus, it reduces the tourism growth rate and becomes a threat to the sustainability of tourism growth. In a literary workout, Zha et al. ( 2020 ) examine the relation between CO 2 emissions and sustainable tourism growth. The nexus among the understudy factors was analyzed in developing economies like China for the period of 2005 to 2016. The results showed a negative relation between CO 2 emissions and sustainable tourism growth. In a literary article, Ozturk et al. ( 2021 ) investigates the relationship among economic growth, energy consumption, CO 2 emissions, and sustainable tourism growth. The data was acquired from Saudi Arabia for the period from 1968 to 2017. The DOLS and FMOLS methods were applied to analyze the proposed hypotheses. The study finds that when the huge amount of non-renewable energy is being utilized, the CO 2 gas is emitted in large amount, and it damages the natural parks, islands, and natural beauty serving as tourism destinations. So, the tourism growth is jeopardized as well as the relationship between CO 2 emissions and sustainable tourism growth.

GHG emissions refer to the emissions of toxic gases like H 2 O, CO 2 , N 2 O, methane, ozone, HFCs, HCFCs, and perfluorocarbons, which, whenever they exceed the balanced quantity, destroy the layer protecting the earth from sun heat, and the excessive heat into earth disturbing the weather pattern, soil and water quality, and production capacity directly affects the health of the living creatures. These environmental factors and environmental productivity provide resources for the tourism industry and affect its growth. The lack of environmental quality, adverse quality natural resources produced by the environment, and the weak and inactive labor all create problems in the performance of tourism activities and its future growth. So, sustainability in tourism growth is restricted (Usman et al. 2021 ). Lasisi et al. ( 2020 ) examine the impacts of GHG emissions on the sustainability of tourism growth. It posits that natural resources such as greens, grass, crops, trees, flowers, various plants, marine creatures, animals, and birds all fulfill the tourism industry’s demands for housing, recreation, and feeding. However, as a result of GHG emissions, the quality of these natural resources is projected to deteriorate, putting tourism expansion in jeopardy. Therefore, the increase in GHG emissions creates hurdles to sustainability development in tourism growth. The study of Ahmad et al. ( 2019 ) is an investigation of the relation of GHG emissions with the sustainability of tourism growth. According to the authors’ views, the GHG emissions and tourism growth are bound in a reciprocal relationship where when the country is making rapid growth and expansion, there are a large amount of GHG emissions, but on the other side, the increasing GHG emissions by destroying the environments resists the sustainability in tourism growth. A study of Banga et al. ( 2022 ) investigates the influences of energy consumption patterns and GHG emissions on sustainable tourism development. The research survey was conducted in 38 OECD countries from 2008 to 2019, and the nexus among the factors was analyzed with the help of a dynamic GMM model. The study finds that GHG emissions because of the excessive use of fossil fuels destroy the natural beauty and put sustainable tourism development in danger.

N 2 O is the most significant GHG after CO 2 and methane. It is the biggest human-sourced threat to the ozone layer, gathering heat from the sun into the earth. It destroys the atmospheric quality of the environment, the environment’s capacity to produce natural resources, the quality of natural resources, and the heath of living creatures, including human beings (Zhang et al. 2019 ). The tourism industry of a country has sound relations to the natural environment and its features. When there is a huge amount of GHG emissions into the air in a country due to households or operations of many commercial entities, tourism practices become stopped thoroughly, tourism services may lose quality, and the number of tourists decreases. As a result of GHG emissions, tourism growth is declining. In this case, the sustainability of the tourism facilities and their marketing are disturbed (Chien et al. 2022c ; Haseeb and Azam 2021 ). Villanthenkodath et al. ( 2021 ) proclaim that the work environment for tourism staff is ruined, and the labor quality is affected as a result in the region where substantial volumes of N2O are released by fuel combustion, agriculture, industrial activities, and wastewater management. The poor performance of human resources, which are critical to total tourist performance, constitutes a roadblock to tourism expansion. Hence, there is a negative relation between N 2 O emissions and sustainable tourism growth. The literary article of Pan et al. ( 2018 ) throws light on the N 2 O emissions and sustainable tourism development. The study suggests that N 2 O is a great environmental pollutant that could restrict the undertaking of tourism activities in the future as it is destructive to the natural beauty of destinations and increasing health risks. Hence, there is a negative relation between N 2 O emissions. Khan et al. ( 2019 ) check the nexus among GHG emissions, energy use, financial development, renewable energy, and tourism growth. The authors collected evidence on the relationship among GHG emissions like CO 2 , N 2 O, methane, and others; energy use; financial development; renewable energy; and tourism, from 34 high-income developing countries from the continents of Asia, Europe, and America from 1995 to 2017. The results showed that the increase in N 2 O emission into the air does not allow the tourism industry to grow with sustainability because it deteriorates the natural environment and the natural assets of the industry.

Research gaps

Sustainable tourism growth is not a new topic of research or discussion. It has been discussed and debated by many authors in the previously conducted research articles. Despite this, the current research article secures a distinctive position in the literature by removing several literary gaps. First, in the past literary articles, different authors have presented their views in different directions while analyzing the relationship between economic factors like GDP, FDI, and GNI, environmental factors like CO 2 emissions, GHG emissions, and N 2 O emissions as well as tourism policies with sustainable tourism growth. The present study shows the positive relation of economic factors like GDP, FDI, and GNI and tourism policies with sustainable tourism development while the negative relation of environmental factors CO 2 emissions, GHG emissions, and N 2 O emissions with sustainable tourism growth. Second, the majority of the previous literature has either analyzed the influences of economic factors like GDP, FDI, and GNI or environmental factors like CO 2 emissions, GHG emissions, and N 2 O emissions on sustainable tourism growth. However, the current literary article is about the impacts of economic factors and environmental factors along with tourism policies for sustainable tourism growth. Thus, it adds to the literature. Third, the previous research studies have analyzed the role of GDP, FDI, GNI, CO 2 emissions, GHG emissions, and N 2 O emissions and tourism policies in sustainable tourism growth in different world economies such as Mediterranean countries, the South Ocean Pacific region, Morocco, Poland, small Island economies, Pakistan, Bangladesh, and Bri economies. The current article removes this literary gap and examines these factors’ impacts on sustainable tourism growth in China. In past literature, different statistical and econometric approaches are applied to check the nexus between GDP, FDI, GNI, CO 2 emissions, GHG emissions, and N 2 O emissions and tourism policies in sustainable tourism growth. The present article adds to the literature as it finds data from the WDI and applies the ADF and PP model for analyzing these factors and their relationship.

Research methodology

The research has examined the role of economic and environmental factors and tourism policy related to tourist arrival on the sustainability of tourism growth in China. The economic factor includes the GDP, national income, and FDI, while environmental factors include CO 2 emission, GHG emission, and nitrous oxide emission, so there is no need to add further factor of environment. The study has extracted the data from WDI from 1990 to 2020. The present research has employed NARDL to check the linkage among variables. The current study also examines the unit root using ADF and PP tests. The equation is given below:

tourism growth

time period

gross domestic product

foreign direct investment

net national income

tourism policy

carbon dioxide emission

greenhouse gas emission

nitrous oxide emission

The present article has taken sustainability of tourism growth as the main construct of the study and measured the international tourism expenditures (% of total imports). In addition, the current article has taken three economic and three environmental factors and tourism policy related to tourist arrival as predictors. The economic factor includes the GDP measured as GDP growth (annual percentage), NNI measured as NNI (annual % growth), and FDI measured as a net inflow (% of GDP). Moreover, the environmental factors include CO 2 emission measured as CO 2 damage (% of GNI), GHG emission measured as GHG emission (% change from 1990), and nitrous oxide emission measured as NO emission (% change from 1990). Finally, tourism policy related to the tourist arrival is measured as the international tourist, the number of arrivals. The variables with measurement and sources are given in Table 1 .

The present research has examined the descriptive statistics that show the standard deviation, total observation used, minimum values, mean values, and maximum values of the constructs. Moreover, the study has also run the year-wise descriptive statistics that show the details of variables with respect to years. In addition, the current article also runs the correlation matrix that exposes the directional linkage among variables. Moreover, the unit root among the variables has also been examined using ADF and PP tests. The equation is given below:

The ADF and PP tests exposed guidelines for the suitable model for the study. The current study has adopted the NARDL co-integration technique because it is preferable when dealing with variables that are integrated of a different order, I(0), I(1), or a combination of both and robust when there is a single long-run relationship between the underlying variables in a small sample size. In addition, it permits us to examine asymmetries nonlinearly and thus violates linearity assumption. Moreover, the NARDL model examines for the possibility of asymmetric negative and positive impact of the independent variable(s) on the predictive variable in the long and short runs. Finally, the NARDL model also permits to capture co-integration for single equation framework compared with the linear ARDL model. The ARDL equation is mentioned below:

In addition, the current study has also examined the asymmetric role of GDP, national income, and FDI. For this purpose, the equation is given as

The current study has estimated the positive and negative role of GDP, national income, and FDI on the sustainability of tourism growth. The individual asymmetric equation is given as below:

Finally, the positive and negative role of GDP, national income, and FDI on the sustainability of tourism growth have been added to the ARDL model and converted into the NARDL. The equation is given below:

Findings of the study

The present research has examined the descriptive statistics that show the standard deviation, total observation used, minimum values, mean values, and maximum values of the constructs. The findings indicated that the mean value of TG was 8.978%, and the average value of GDP was 9.116%. In addition, the outcomes also revealed that the mean value of FDI was 3.302%, while the average value of NNI was 10.306%. In addition, the mean value of TP related to the tourist arrivals was 97,915,333 arrivals. Moreover, the output also exposed that the average value of CO2E was 5.240%, while the mean value of GHGE was 85.047, and the average value of NOE was 27.360. Finally, a total of 31 observations were used in the study. Table 2 shows these details.

Moreover, the study has also run the year-wise descriptive statistics that show the details of variables with respect to years. The results exposed that the maximum value of TG was in 2020 (16.652), while the minimum value of TG was in 1990 (2.766). Moreover, the outcomes also exposed that the highest value of GDP was 14.225% in 2014, while the lowest value of GDP was 2.348% in 1990. In addition, the results exposed that the maximum value of FDI was in 2010 (6.187) while the minimum value of FDI was in 2013 (0.966). Moreover, the outcomes also exposed that the highest value of NNI was 15.513% in 2016, while the lowest value of NNI was 4.631% in 2020. The lowest value of TP related to tourism arrivals was 14,332,500 arrivals in 1990, and the maximum value of TP was 162,538,000 arrivals in 2018. The results also exposed that the maximum value of CO 2 E was in 2012 (8.554), while the minimum value of CO 2 E was in 1992 (2.984). Moreover, the outcomes also exposed that the highest value of GHGE was 209.922 in 2020, while the lowest value of GHGE was 2.611 in 2013. Finally, the results exposed that the maximum value of NOE was in 2020 (67.052) while the minimum value of NOE was in 2013 (− 2.036). Table 3 shows the year-wise descriptive statistics figures.

In addition, the current article also runs the correlation matrix that exposes the directional linkage among variables. The results revealed that GDP, national income, and FDI have a positive linkage with the sustainability of tourism growth. The results also exposed that environmental factors such as CO 2 emission, GHG emission, and nitrous oxide emission have a negative linkage with the sustainability of tourism growth. Table 4 shows these outcomes.

Moreover, the unit root among the variables has also been examined using ADF and PP tests. The results exposed that GDP, NNI, TP, GHGE, and NOE have no unit root at the level, but TG, FDI, and CO 2 E have no unit root at the first difference. Table 5 shows the PP and ADF results.

In addition, the current article has also run the NARDL bound test that shows the cointegration, and the findings exposed that the 5.91 value of f-statistics calculated is larger than the critical value and exposed cointegration exists. Table 6 exposes these outcomes.

The NARDL results revealed that GDP, national income, and FDI have a positive linkage with the sustainability of tourism growth. The results also exposed that environmental factors such as CO 2 emission, GHG emission, and nitrous oxide emission have a negative linkage with the sustainability of tourism growth. Finally, the tourism policies related to tourist arrivals have a positive impact on the sustainability of tourism growth. Table 7 shows the NARDL results.

Discussions

The results stated that GDP is in a positive relation to the sustainability of tourism growth. These results are supported by Lee et al. ( 2021 ), which show that tourism is a combination of multiple activities, including many resources that can be acquired from different other firms, such as the firms which give infrastructure facilities, transportation facilities, and food processing, all things which are available at shopping centers serving the tourists. In the countries having high GDP, the production level in almost all the business enterprises rises. Thus, the availability of different resources to be used in tourism practices accelerates tourism growth and develops sustainability in it. These results are also in line with Scarlett ( 2021 ), which examines the GDP’s role in developing sustainability in tourism growth. This study posits that when there is high GDP growth, the firms have economic prosperity and enough resources that they can develop variety in the tourism practices like improvement in the accommodation facilities on an innovation basis, variety of food items provided at the restaurants, and availability of innovative, quality products at malls and increase in the number of recreational activities. Thus, the increase in GDP successfully adds to sustainability in tourism growth.

The results revealed that FDI has a positive relation to the sustainability of tourism growth. These results agree with Sou and Vinnicombe ( 2021 ), which highlight that the investment from persons or firms from abroad in the tourism industry increases the financial resources, economic and physical resources, and regulations and provides efficient management. Thus, the encouragement of FDI for tourism firms enables them to broaden the scope of their business, improve the quality of their services as well, and keep on growing well over time. So, these results match with the past study of Zhuang et al. ( 2021 ), which states that when domestic firms accept investment from both domestic and foreign sources, their financial position is strong, and they have considerable funds to utilize in order to keep the tourism services innovative. The use of heavy innovative technologies, technologies, and resources with high quality and novel design attracts more tourists both at the national and international levels. Thus, the tourism industry within the country can grow at a sustainable rate as a result of employing FDI. These results match with Sheng Yin and Hussain ( 2021 ), where the authors wrote about the role of FDI in tourism growth. This study shows that the firms which have high investments from foreigners are accountable to them and must disclose their operations and financial position. This motivates them to form and enforce social and environmental regulations, which ultimately improve their overall performance and enable them to grow with high sustainability.

The results indicated that GNI has a positive relation to the sustainability of tourism growth. These results are supported by Eyuboglu and Eyuboglu ( 2020 ), which reveals that in case the country has a high national income, there is peace in the economy, and business firms are active in their production practices. Because of their better financial position, they not only focus on the marketing of the existing goods but quality improvement in the products and services. In the tourism industry, the firms’ own focus on the quality services to tourists and the acquisition of quality resources and products from other firms allow them to meet the quality requirements of the tourists. Thus, tourism growth can be sustainable in the country. These results match with Aslan et al. ( 2021 ); when the GNI of a country is increasing at a consistent rate, the employment rate is high. When the large population has employment and has high salaries as determined by high production and marketing on the part of employers, their living standard is high, and they can afford big tours. This sustainable demand and marketing for tourism services give rise to sustainability in tourism growth.

The results also showed that tourism policy has a positive relation to the sustainability of tourism growth. These results are supported by Higgins-Desbiolles ( 2018 ), which highlights that the positive favorable tourism policies regarding the environmentally friendly quality of tourism, if it is effectively implemented, help improve the quality of the environment to tourists, improve attraction in recreational destinations, and provide healthy diet during the survey. When tourists have a clean and pleasant environment and good quality food and beverages in the tourism destinations, they retain the same industry and also become a mouth of share for the tourism destinations and their services. Thus, tourism firms, with consistency in the marketing of tourism services, can make sustainable environmental and economic growth. These results are in line with Sharpley ( 2020 ), which checks the tourism policies for the accommodation and hospitality to tourists and sustainability in tourism growth. If these policies include the terms that accommodation facilities and hospitality must be based on innovation and these policies are effectively implemented, the tourism firms continue to improve its accommodation and hospitality services to tourists and succeed in attracting more tourists from national and international sides. The effective implementation of tourism policies develops sustainability in tourism growth.

These results demonstrated that CO emissions have a negative relation to the sustainability of tourism growth. These results are supported by Teng et al. ( 2021 ), which show that the environment of a country is a crucial factor in tourism development within that country. But when the economic activities are smooth and social practices are at their peak and cause CO 2 emissions into the air in large amounts, global warming is high, and environmental condition degrades. Environmental degradation as a result of CO 2 emissions adversely affects the health of the tourists. In the countries where the CO 2 emissions are larger than others, tourists hesitate to visit the destination. The decrease in the marketing of tourism services reduces the rate of the tourism firms’ growth. These results agree with Sghaier et al. ( 2019 ), which examine the influences of CO 2 emissions on tourism development. The authors argue that the increasing amount of CO 2 emissions into the air pollutes the atmosphere, disturbs the water level, and traps the heat in over quantity. Thereby, it destroys the quality of natural resources as well as the living creatures which are found on the land, underwater, and in the sky. All these resources are used in different tourism services like food or water supplies, accommodation, and recreation. Consequently, it becomes difficult for the tourism industry to grow at sustainable rate.

The results indicated that GHG emissions have a negative impact on the sustainability of tourism growth. These results agree with Liu et al. ( 2021 ), which ponder the influences of GHG emissions on tourism growth. The study shows that the emissions of GHG like water vapor, CO 2 , N 2 O, CFCs, HCFCs, and perfluorocarbons are very harmful to the environment. Because of the excessive heat and suffocation in the environment affect the breathing power and physical health of the people who are the human resources of tourism firms, different service providers, and tourists. So, the lack of healthy and efficient labor in the tourism industry reduces the quality (agility, responsiveness, and level of amusement) of the tourism services, which does not allow the concerned firms to perform effectively and grow hastily as time passes. Similarly, the lack of tourists reduces the marketing level in the tourism industry. Hence, GHG emissions do not allow the tourism firm to grow. These results are also supported by Dube and Nhamo ( 2021 ), which highlight that in the tourism industry, natural resources like greenery, grass, trees, flowers, different plants, sea creatures, animals, and birds and the crops and trees used for food all serve the industry for accommodation, recreational, and feeding needs. But as in the existence of GHG emissions, the quality of these natural resources is likely to reduce, and thus, eventually, tourism growth is in danger, and sustainability in tourism growth is not possible.

The results indicated that N 2 O emissions have a negative impact on the sustainability of tourism growth. These results are supported by Larsson et al. ( 2018 ), which state that the N 2 O is a harmful gas that destroys the ozone layers, contributes to global warming, and brings climate change. It is more damaging to the ecosystem than other GHGs and has fast, destructive influences on the environmental elements, which are part of the resources in the tourism firms. Environmental degradation as a result of N 2 O reduces tourism growth. These results are in line with Lu et al. ( 2018 ), which state that in countries where fuel combustion, agriculture, industrial processes, and wastewater management release N 2 O in large amounts, the work environment for the tourism employees is destroyed and affects the labor quality. The weak performance of the human resources, who are the key to the overall tourism performance, becomes a hurdle in the way to sustainable tourism growth.

Implications

The present study has both theoretical and empirical implications. With the literary contribution, this study gives avenues to authors how they must conduct studies on sustainability in tourism growth. The present study has much theoretical significance because of the contributions it makes to the theory of tourism. This study addresses the global concept of the tourism growth in great detail. It analyzes the influences of three economic factors, GDP, GNI, FDI, and tourism policy, and three environmental factors, CO 2 emissions, GHG emissions, and N 2 O emissions, on tourism growth. In the previous studies, the impacts of both economic and environmental factors on a country’s tourism growth have been explored. But, a study is scarcely found which have thrown light on both economic and environmental factors for determining tourism growth. The present study, which examines the impacts of both economic and environmental factors on tourism growth, is an extension of the literature. Moreover, the present study seeks the facts and figures regarding the impacts of GDP, GNI, FDI, tourism policy, CO 2 emissions, GHG emissions, and N 2 O emissions on tourism growth in the Chinese economy, which in itself is a great contribution to literature.

The present study carries empirical implications as well, as the tourism industry, which has a lot of social, cultural, and economic significance, is the main concern of this study. This study is not only significant for the Chinese economy but also for the emerging economies which are interested in tourism development through some measures and particular precautions. (1) This study provides the guidelines to the relevant authorities and regulators in developing and implementing the regulators regarding tourism growth by promoting economic and environmental conditions in the country. (2) This study reveals that the government, economists, and other entities involved in providing tourism practices must take benefit from economic factors like GDP, GNI, and FDI, through effective decisions-making and promote the country’s tourism industry. (3) It also guides the audience, which would be government, economists, and tourism firms, that must try to struggle for environmental regulations so that the CO 2 emissions, GHG emissions, and N 2 O emissions can be controlled to gain high tourism growth. (4) It guides the government and tourism firms that they must try to formulate favorable tourism policies to put the tourism industry on the track to sustainable growth. The policies must be formulated to promote sustainable technologies in tourism and relevant industries, force to employ renewable energy sources, to bring improvement in tourism infrastructure, or convert the specific regions into tax-free zones for tourism. The execution of such policies improves the environmental and social performance of tourism and thus develops sustainability in tourism growth.

Conclusions and limitations

China has long been involved in providing tourism practices and takes many social, cultural, and economic benefits from these practices. Though the tourism industry in the country has been making progress over the previous years, still, the progress rate is low, and there are many threats to the sustainable development of this industry. As the authors felt the issue and needed to resolve it, they aimed to explore the measures to grow the tourism industry and the reasons which create hurdles in the way to get high tourism growth. The study was to examine the role of economic factors like GDP, GNI, FDI, and tourism policy in increasing the tourism growth rate and checking the impacts of environmental factors like CO 2 emissions, GHG emissions, and N 2 O emissions on tourism growth. The Chinese tourism industry was sought out to collect information about the influences of GDP, GNI, FDI, tourism policy, CO 2 emissions, GHG emissions, and N 2 O emissions on tourism growth. The results showed a positive relationship between GDP, GNI, FDI, tourism policy, and tourism growth. The results indicated that when a country’s GDP growth rate is high, the tourism firms can acquire quality resources in abundance and an effective and efficient labor force, which brings improvement in the tourism practices and the large marketing for tourism services as well. Similarly, in a country making high GNI, value additions, newness, and creativity can be developed in tourism practices, and marketing also increases. The increase in FDI enhances the financial resources, information, regulations, and marketing which all ultimately improve tourism growth. The results indicated that the careful formation and effective implication of tourism policies regarding different aspects like green tourism, digital tourism, hospitality sector skills, tourism small, micro and medium firms, and destination administration helps to develop sustainability in tourism growth. The results indicated a negative relation among environmental factors like CO 2 emissions, GHG emissions, N 2 O emissions, and tourism growth. These results mean that the sustainable growth of the tourism industry depends on the quality of natural tourism destinations, the quality of the food, the comfort of tourists, and the health of the employees and when there is a rapid increase in CO 2 emissions, which destroys the environmental quality, natural resources, and the health of the stakeholders, and sustainability in tourism growth is impossible. Likewise, N 2 O emissions, a more destructive gas than CO 2 emissions, disturb sustainable tourism growth because they affect the natural environment and resources that are the soul of any tourism destination. The results revealed that GHG emissions are hazardous gases that deplete the ozone layers, trap heat into the earth, and raise the environment’s temperature. These gases change the weather pattern and deteriorate the quality of all forms of nature and the health of the living bodies on all which the tourism industry is based.

Some specific limitations are associated with this study. These limitations are required to be removed in future studies. The present study examines a limited number of economic and environmental factors for the analysis of tourism growth within the country. The future authors are recommended to increase the factors which help to enhance tourism growth and the factors which restrict the tourism growth within the country so that a study that could be a better guideline for tourism growth can be presented. Moreover, the present study finds the relations between the GDP, GNI, FDI, tourism policy, CO 2 emissions, GHG emissions, and N 2 O emissions and tourism growth through research on the Chinese economy. China has specific economic policies, economic conditions, environmental circumstances, and geographical areas separate in nature from those in other countries. So, the reliability of the study may not be equal in different countries, so a general study that is based on the data from multiple countries is required from future authors.

Data availability

The data that support the findings of this study are attached.

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The path toward eco-friendly travel in China

In the past decade, Chinese tourism’s total revenue saw double-digit annual growth. 1 “Silent Spring: Tourism’s way to fight the epidemic,” McKinsey, February 28, 2020; Yang Qian, “The National Economic and Social Development Statistical Bulletin issued by the National Bureau of Statistics shows that In 2019, there were 6.01 billion domestic tourists, and the domestic tourism revenue was 5,725.1 billion yuan,” The Ministry of Culture and Tourism of the People’s Republic of China, March 2, 2020. Just before COVID-19 shocked the industry, the country’s 6 billion domestic and 155 million outbound trips from mainland China generated around $1 trillion in travel spend. This propelled China to the top of global rankings for domestic tourism spend and outbound traveler numbers.

About the authors

This article is a collaborative effort by Monica Li, Spencer Liu, Steve Saxon , Jonathan Woetzel , and Jackey Yu, representing views from McKinsey’s Travel, Logistics & Infrastructure practice.

Now, confidence in post-pandemic tourism recovery is growing. Chinese travelers are still yearning to travel—and with domestic and international reopening policies in place, tourism’s recovery is on the horizon. 2 Steve Saxon, Chen Wei, and Yu Zijian, “Out of the haze, China's tourism market begins to recover,” McKinsey, December 30, 2022.

In a new report, The path toward eco-friendly travel in China , McKinsey, Accor, and Trip.com Group explore how the Chinese travel industry impacts the environment and spotlight actions that travelers, tourism providers, and industry stakeholders could take to achieve real sustainable travel. As China’s tourism bounces back, it is more urgent than ever to tackle the industry’s contribution to environmental damage. Given tourism’s diverse stakeholders and activities along its value chain, it is easy to overlook the environmental footprint of individual actors. Their combined impact, however, is substantial.

With its huge traveler numbers and market size, Chinese tourism can play a critical role in advancing the sustainability agenda.

Travel in China: Calculating its environmental footprint

To take stock of the combined environmental impact of individual stakeholders, the report examines the carbon emissions, water consumption, and waste generation that tourism was responsible for in 2019. 3 The calculations were based on data from multiple sources including the International Civil Aviation Organisation (ICAO) carbon emissions calculator; Cornell Hotel Sustainability Benchmarking Index 2021; Ecoinvent; China Products Carbon Footprint Factors Database; Water Footprint Network database; and industry standards for emissions calculations and other national standards. That year, mainland China’s domestic tourism generated approximately 800 megatons (Mt) CO 2 e. This accounts for about 6 to 8 percent of overall emissions in China, of which about 50 percent are direct emissions (Exhibit 1).

Domestic tourists in mainland China also consumed between 7 and 8 billion cubic meters (m 3 ) of water, with accommodation accounting for about 50 percent of this. Domestic tourists in mainland China generate between 12 and 14Mt of solid waste annually.

To put these numbers into context, consider the environmental footprint of one tourist trip—in this case a three-day round trip by air between Beijing and Shanghai. In this scenario, the traveler takes a private car to the airport and, after the flight, catches a taxi to their hotel. During the three-day hotel stay, the traveler uses and discards the single-use consumables provided by the hotel, including water bottles, soap wrappers, and combs. The traveler showers every morning and enjoys one bath on their last night. Towels are washed and replaced daily, and the bedsheets are changed once. For meals, the traveler eats breakfast at the hotel, and dines out for lunch and dinner, leaving behind a small amount of leftover food per meal. As the traveler sightsees and shops, they acquire disposable plastic packaging, discarding these immediately after use.

The total direct emissions from this trip add up to approximately 330kg CO 2 e. Direct water consumption is around 1,200 liters, and this traveler generates about 5kg of waste during their stay (Exhibit 2).

This three-day trip illustrates how finite actions can add up to intensify the environmental footprint of each traveler. Though there is a clear need to accelerate a transition to sustainable travel, travelers also need to be on board with the shift to see any real improvements in sustainability.

Learn more about our Travel, Logistics & Infrastructure Practice ?

Chinese travelers are calling for sustainable travel, but have a long way to go.

Chinese travelers could be instrumental in the shift toward sustainable travel. Understanding their sentiment is a crucial step in unlocking simple but meaningful behavior changes. McKinsey’s latest survey results show that Chinese travelers are aware of sustainability but are not yet willing to pay a premium for more sustainable products or services (Exhibit 3). 4 Based on McKinsey’s sustainable travel survey 2021, total 5457 respondents from Brazil, India, Spain, China, US, Saudi Arabia, Germany, Canada, UK, Poland, Australia, Japan, and Sweden; Sustainable Travel Consumer Report 2022, Trip.com Group, September 2022.

Chinese travelers, however, also believe that sustainable tourism is a shared responsibility and indicate that governments and tourism providers have a prominent role to play in supporting the transition (Exhibit 4).

As they start to look for sustainable travel options, these travelers expect online travel providers to assist them with their search (Exhibit 5).

Taken together, these factors suggest that the tourism industry could harness this intent and empower Chinese travelers to reduce their environmental footprint. Sustainable tourism is indeed a joint effort, but what can tourists do to champion climate-friendly travel?

Travelers have many “smarter” options available to significantly lower their environmental footprint

Domestic tourists can change their habits to effect immediate change in their environmental footprint. For instance, travelers can make the following choices as they plan and execute their itinerary.

• Choose and book sustainable travel options with certified service providers. Travelers can visit the websites of certification bodies to identify travel services and hotels that meet specific sustainability criteria.
• Choose more sustainable transport modes. For short-haul journeys, tourists can opt to travel by rail rather than air. Travelers could also select cars that run on renewable energy sources for rentals, and book flights with lower carbon emissions.
• Reduce food and packaging waste. Order only as much as is needed. Many restaurants have recommended portions to help reduce waste, and others indicate dishes’ carbon emissions on their menus to nudge travelers toward more sustainable choices. Travelers could also come prepared with reusable items such as water bottles, cutlery, and straws.
• Try local cuisine and meals made with locally sourced food. This can cut down carbon emissions from logistics, and enrich the experience of the trip.
• Shop with a sustainability mindset. Travelers can reduce packaging waste by bringing their own carrier bags and buying durable souvenirs instead of those that may be discarded soon after purchase.

To see this in action, let’s revisit the three-day trip from Beijing to Shanghai. If that traveler had adopted sustainable behaviors and habits, on that trip they could have reduced carbon emissions by 45 percent, decrease water use by 25 percent, and cut waste by 65 percent. Though individual actions could significantly reduce overall environmental impact, relying on traveler behavior alone is only the first step; individual tourism providers can support travelers in choosing sustainable options.

Accelerating the transition to net-zero travel

Tourism providers have business opportunities to reduce their environmental footprint.

When individual tourism providers make sustainable changes to their operations, they can reduce their overall footprint. As a result, travelers will have more sustainable options to choose from—if these options are made visible.

As the first stop for planning a trip, travel agencies are well positioned to educate consumers on sustainable travel. Travel agencies could use their existing rewards programs, platforms, and new technologies to help travelers plan their trips more sustainably. Providers could also use clear labeling and provide tools like personal carbon credit accounts, helping travelers to understand the effect of their choices on the environment.

Air travel is often the largest source of emissions for any trip. As travelers embark on their journeys, airlines could employ data analytics to tackle emission reduction. Sustainable technologies could combine flight, environmental, and other external data to predict the optimum amount of fuel needed for a flight. Sustainable aviation fuel (SAF) has also been identified as a promising next step in reducing fuel-based emissions. Airlines may also consider collaborating with suppliers on issues such as transparent carbon reporting , monitoring, and decarbonization—helping to reduce emissions across the supply chain.

At the destination, hotel operations contribute disproportionately to the industry’s overall energy use, water consumption, and waste generation footprint. Hotels could revisit their operations management and find opportunities to leverage new smart technologies to monitor, plan, and reduce their consumption and waste. Switching to renewable energy sources could also further diminish carbon emissions, while upgrading infrastructure and keeping up with maintenance may prevent excess energy loss and waste.

Many more travel providers, including asset owners, car rental services, and tour operators could play a part in shaping the future of sustainable travel, but long-term change requires joint action from the entire travel industry.

All stakeholders can collaborate to shape the future of sustainable travel

Travelers and tourism providers could help the travel industry realize the “quick-wins” of sustainable impact. Lasting sustainability improvements, though, will take concerted industry-wide effort.

While the premium that a traveler is willing to pay for sustainable travel is markedly lower than the cost of providing it, the industry will likely need to consider covering the costs of sustainable transition. The travel industry could add weight to its sustainability intentions by collectively agreeing to minimum sustainability targets. Further credibility could be added to sustainability claims if a unified, industry-wide sustainability rating system were established. A centralized rating system could focus on defining and measuring environmental impact, allowing travelers to make informed choices.

Aligning the motivations of stakeholders within the tourism industry’s complex structure could also amplify the transition toward sustainable travel. This could be done by including sustainability in regulations and wider industry standards that affect the interests of all parties. Including more mandatory sustainability criteria in the star rating system of hotels, for example, could bring the motivations of both hotel owners and operators into alignment.

Though certain sustainability technologies and solutions such as SAF are available, this is not enough to support industry-wide adoption, and supply is limited. Leading industry actors could help solve demand-supply deadlock and boost supply scale-up by forming a first-mover coalition and committing to adopting sustainable solutions. Adoption could become more affordable through funding programs, especially where smaller actors may be less likely to afford the upfront investment.

Where industry actors do not have enough information to successfully adopt sustainable measures, the industry could aim to bridge actors’ knowledge gaps by hosting platforms that distribute information and match providers’ needs to key sustainable technologies and funding opportunities.

When diverse voices are aligned, combined action across the travel value chain could bring the travel industry significantly closer to the future of sustainable travel.

The future of sustainable travel

In a possible future, each stage of a traveler’s journey could include numerous elements that reinforce climate-friendly travel and encourage sustainable behaviors (Exhibit 6). From the beginning of the journey when the traveler becomes inspired, researches, and books a trip, sustainable offerings are visible and accessible. Throughout the journey, all activities and facilities are geared toward reducing emissions. Emissions from transport, especially aviation, could be minimized by transport providers switching to clean fuel or adopting hydrogen powered shuttles, electric autonomous vehicles, and electric vertical take-off and landing (eVTOL) flights—these technologies having matured from today’s small-scale innovators through industry-wide co-development efforts. In addition to purchasing green electricity, accommodation providers could collectively commit to installing renewable energy on site.

The largest proportion of waste generation and water use occurs in hotels and restaurants. In this future scenario, a circular model would ensure that materials are recycled, and water is not wasted. Waste sorting facilities could be onsite in locations with high food and material consumption, such as hotels, restaurants, shopping malls, and airports. Urban farms could compost food waste for fertilizing vegetables and crops, and hotels could have collection and purification systems for gray and rainwater. Adoption of these solutions could be funded by financial mechanisms designed to support sustainability projects. Furthermore, all buildings would be designed to be non-intrusive and take environmental consequences into account.

The Chinese tourism industry is large enough to take the lead in advancing the sustainability agenda. As travelers resume their adventures post-COVID-19, each step of their journey presents opportunities to make small choices—actions that could immediately reduce their environmental footprint. But the onus is not on the traveler alone. Long-term change calls for collaboration between actors across the entire travel industry, from hotels and travel agencies, to green investors and technology suppliers.

Monica Li is a consultant in McKinsey’s Beijing Office, Spencer Liu is an associate partner in the Hong Kong Office, where Jackey Yu is a partner; Steve Saxon is a partner in the Shenzhen Office, and Lola Woetzel is a senior partner in the Shanghai office; Brune Poirson is the chief sustainability officer at Accor, where Gary Rosen is the chief executive officer Greater China; Ray Chen is the senior vice president of Trip.com Group and CEO of Accommodation Business.

The authors wish to thank Carrie Chen, Zi Chen, Margaux Constantin, Giuseppe Genovese, Yanran Guo, Lili Li, Esteban Ramirez, Shashank Singh, Mingming Sun and Cherie Zhang for their contributions to this report. They also wish to thank Christophe Lauras, Violet Jiang, Ken Wong, and Vivian Yeh from Accor and Richard Beh and Quanwu Xiao from Trip.com Group for their contributions to this report.

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Research Article

The contribution of tourism mobility to tourism economic growth in China

Roles Conceptualization, Funding acquisition, Methodology, Resources

Affiliation School of Tourism, Hubei University, Wuhan, Hubei, China

Roles Software, Writing – original draft

Affiliation School of Urban and Regional Science, East China Normal University, Shanghai, China

Roles Data curation, Formal analysis, Writing – review & editing

* E-mail: [email protected]

Affiliation School of Business, Hubei University, Wuhan, Hubei, China

Roles Conceptualization, Investigation, Methodology

Affiliation School of Tourism, Hainan University, Haikou, Hainan, China

• Jun Liu, 
• Mengting Yue, 
• Fan Yu, 

• Published: October 27, 2022
• https://doi.org/10.1371/journal.pone.0275605
• Peer Review
• Reader Comments

Mobility is the key factor in promoting tourism economic growth (TEG), and the transportation infrastructure has essential functions for maintaining an orderly flow of tourists. Based on the theory of fluid mechanics, we put forward the indicator of tourism mobility (TM). This study is the first to measure the level of TM in China and analyze the spatiotemporal evolution characteristics of TM. Applying the Exploratory Spatial Data Analysis method, we analyze the global and local spatial correlation characteristics of TM. Moreover, we further estimate the contribution of TM to TEG by econometric models and the LMDI method. The results show that (1) the TM in China has maintained rapid growth for a long time. However, there are differences in the rate of growth in different regions. The TM in each region only showed a significant positive spatial correlation in 2016–2018. The space-time pattern is constantly changing over time. The local spatial autocorrelation results of TM are stable, and various agglomeration states are stably distributed in some provinces. (2) The regression results of the traditional panel data model and spatial panel data model both show that TM has a significant positive effect on TEG. Moreover, TM has a negative spatial spillover effect on neighboring regions. (3) The result from the decomposition of LMDI shows that the overall contribution of TM to TEG is 15.76%. This shows that improving TM is a crucial way to promote the economic growth of tourism.

Citation: Liu J, Yue M, Yu F, Tong Y (2022) The contribution of tourism mobility to tourism economic growth in China. PLoS ONE 17(10): e0275605. https://doi.org/10.1371/journal.pone.0275605

Editor: Hironori Kato, The University of Tokyo, JAPAN

Received: March 3, 2022; Accepted: September 20, 2022; Published: October 27, 2022

Copyright: © 2022 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data on RAILWAY, HIGHWAY, ROAD1, ROAD2, ROAD, GDP, TERTIARY INDUSTRY, and POPULATION are from the Chinese Nation Bureau of Statistics ( https://data.stats.gov.cn/easyquery.htm?cn=C01 ). The data on TOURISM REVENUE and VISITORS are from the CEIC database ( https://insights.ceicdata.com ). The data on TRAFFIC, TOURISM MOBILITY, RECPTION, INDUSTRY, and STRUCTURE were calculated by the authors. Please see the paper for details.

Funding: This work was supported by grants from National Social Science Foundation of China [grant number 17CJY051].

Competing interests: The authors have declared that no competing interests exist.

Introduction

In recent years, the tourism industry has maintained rapid development. By 2019, the total number of global tourist trips exceeded 12.3 billion, an increase of 4.6% over the previous year. The total global tourism revenue was US$5.8 trillion, equivalent to 6.7% of global GDP (World Tourism Economy Trends Report [ 1 ]). Tourism has made important contributions to economic growth by increasing employment, improving infrastructure, and accumulating foreign exchange earnings for destinations [ 2 ]. Due to the impact of COVID-19, People’s travel is restricted. The total number of international tourists in 2021 decreased by 72% compared with 2019, and international tourism consumption dropped by nearly half compared with 2019 [ 3 ].

The above facts remind us that mobility has become an essential feature of tourism activities [ 4 , 5 ]. Tourists from origins to destinations result in a series of mobility of information, material, and capital. These mobilities have a great influence on tourist destinations [ 6 – 9 ]. If tourism mobility (TM) stagnates, tourist attractions, reception facilities and transportation facilities built for tourists will be idle. Tourism workers will lose their jobs and tourism economic growth (TEG) will also stagnate. Therefore, studying the impact of TM is necessary and important.

As one of the important tourist destinations in the world, China’s domestic tourism and inbound tourism are developing rapidly. In 2019, the total contribution of China’s tourism industry to GDP reached 10.94 trillion yuan, accounting for 11.05% of the total GDP, exceeding the proportion of international tourism in the global GDP. A total of 28.25 million people were directly employed in tourism, and 51.62 million people were indirectly employed in tourism. The total employment in tourism accounts for 10.31% of the total employed population in the country [ 10 ]. However, due to the impact of COVID-19, the development level of China’s tourism industry has not recovered to the level of 2019. In 2021, the total number of domestic tourists in China was 3.246 billion, which is only 54% of that in 2019, and directly leads to a total tourism revenue of 2.92 trillion yuan, which is only 51% of that in 2019. This shows that TM is more important to China’s tourism industry. Therefore, we decide to focus on the TM in this study and take China as the research sample.

The top priority of this study is to obtain the right measurement of TM. Transportation infrastructure is an important carrier for the exchange of factors in tourism. Existing studies have confirmed that transportation is a key factor in promoting TEG [ 11 – 13 ]. The establishment of the transportation system has an obvious effect on improving the accessibility of tourist destinations and promoting the inflow of the tourist population [ 14 ]. However, most existing studies only take tourist arrivals to characterize TM [ 15 – 21 ]. They ignore that the transportation infrastructure is also an important factor affecting the TEG. Therefore, this study redefines TM, which considers both transport infrastructure and tourist arrivals.

Another important purpose of this study is to explore the effect of TM on TEG. Existing literature analyzes the links between TM and international trade [ 22 , 23 ] or focuses on the relationship between economic growth [ 24 , 25 ]. However, less literature has focused on the relationship between TM and TEG. There are two possible reasons for the lack of attention. First, the positive and significant impact of the tourist arrivals and TEG no longer needs to be verified. It is common sense that the more tourists the destination receive, the higher the tourism income. Second, tourist arrivals, as a single indicator to measure TM, are able to affect the TEG. Our measurement of the TM concludes both transport infrastructure and tourist arrivals in this study. Therefore, we decide to explore the contribution of TM to the TEG based on the new measurement for TM.

We first use econometric methods to test whether there is a significant impact of TM on TEG. Considering the positive impact of transport infrastructure on China’s TEG [ 26 ], we hypothesize that TM has a positive impact on TEG. Previous studies have also shown that the spatial spillover effect of tourism may significantly affect the TEG [ 27 – 29 ]. Therefore, we further apply the spatial Durbin model to test the impact of TM on TEG.

Moreover, we also use the LMDI (Logarithmic Mean Divisia Index) method to further analyze the contribution of TM to TEG in more detail. The LMDI method is often used to study environmental issues such as energy consumption and carbon emissions [ 30 , 31 ]. In the field of tourism research, the LMDI method is mostly used to decompose tourism carbon emissions or energy consumption [ 32 , 33 ]. Few studies are using the LMDI to analyze TEG. Therefore, we further use the LMDI method to decompose TEG into five influencing factors including the tourism mobility effects ( TM ), the cumulative traffic effects ( Traffic ), the effects of the tertiary industry ( Industry ), the structural effects of the tourism industry ( Structure ) and the reception effects ( Reception ), and examine the contribution of TM to TEG.

Different from previous studies, this study makes two contributions to the literature. First, we introduce the related concepts of fluid mechanics to construct the indicator TM. We also consider the superposition effect of tourist arrivals and transportation infrastructure. This deepens the understanding of TM and promotes the integration of interdisciplinary knowledge. Second, we are the first to examine the impact of TM on TEG using econometric models and the LMDI method. This deepens the understanding of the mechanisms that influence TEG. The results of this study also provide a reference for tourism-related policy makers. Regions wishing to develop tourism can achieve TEG by expanding the size of the source market and promoting the construction of transportation infrastructure.

The rest of this study is organized as follows. Section 1 summarizes the relevant literature. Section 2 presents the theoretical framework, methods, and data. Section 3 introduces the spatiotemporal pattern and evolutionary trend of TM. Section 4 analyzes the contribution of TM to TEG from two different perspectives. Section 5 discusses and analyzes the research results. The last section concludes this study.

Literature review

As the core of tourism activities, TM refers to the mobility of tourists from the origin to the destination, and the stay of tourists in the region [ 34 ]. It is often associated with tourism demand and is measured by tourist arrivals [ 35 ]. Since the 1970s, many studies have paid attention to the influencing factors and the spatial structure of TM [ 15 , 16 ]. The existence of regional heterogeneity makes TM affected by many factors, such as infrastructure, income, GDP, and cultural distance [ 17 , 18 , 20 ]. Moreover, it also makes the spatial structure of TM different. Therefore, TM prediction has become one of the research hotspots [ 36 ]. A large body of research has focused on TM forecasting [ 21 ], including using a combination and integration of forecasts, using nonlinear methods for forecasting, and extending existing methods to better model the changing nature of tourism data [ 37 ]. The gravity model is an earlier method used to analyze international TM [ 38 ]. Due to its effectiveness in explaining TM [ 22 ], gravity models are often used to analyze international tourism service trade. Although the use of gravity models to predict bilateral TM still lacks a corresponding theoretical explanation mechanism, empirical evidence supports the applicability and robustness of gravity models for TM [ 23 ]. Existing research focuses on examining the movement patterns and spatial structure of international TM in destinations [ 39 ], such as the transfer of inbound TM within regions and the influencing factors of inbound TM within destinations [ 40 ]. There are still few studies on the overall spatial characteristics of TM within destination countries, and the only literature is mainly based on digital footprints or questionnaire data to analyze the spatial structure of TM [ 41 , 42 ].

Unlike the tourist arrivals indicator, which focuses more on the mobility of people, TM examines a wider range of content, including the mobility of people, the mobility of materials, the mobility of ideas (more intangible thoughts and fantasies), and the mobility of technology [ 8 ]. The early tourist movement focused more on tourist travel decisions and the resulting movement patterns. Lue et al. [ 43 ] summarized five travel patterns of tourists between destinations. Li et al. [ 44 ] revealed the spatial patterns of TM and tourism propensity in the Asia-Pacific region over the past 10 years. McKercher and Lau [ 45 ] took Hong Kong as an example and identified 78 movement patterns and 11 movement styles of TM within the destination. In recent years, with the help of technologies such as GPS, GIS, and RFID, the movement of tourists within scenic spots has attracted attention [ 46 ]. Research on visitor movement in national parks, theme parks, protected areas, etc. continues to increase [ 47 – 49 ], and explore the influencing factors of visitor movement [ 50 ], broadening the microscale visitor mobility research content. TM also has economic, social, and cultural impacts on destinations through the movement of tourists. Numerous empirical studies have shown that tourist arrivals have a positive impact on economic growth [ 51 ]. Tourism is an important driver of economic growth [ 52 ]. However, some studies have shown that tourist arrivals do not directly lead to economic growth, but promote TEG through regional economic development [ 53 – 55 ]. The mobility of tourism will also bring about changes in destination transportation facilities. Transportation is not only an important carrier of TM but also an important part of tourists’ travel experience [ 8 ]. It also has a positive impact on destination company value together with TM [ 26 ].

There are many theoretical discussions and empirical studies on the factors influencing TEG. From the perspective of suppliers, resource endowment [ 56 – 58 ] and environmental quality [ 59 – 62 ] are the fundamental factors determining tourism development. Simultaneously, as a typical service industry, human capital and physical capital in the tourism industry [ 63 , 64 ] and service level [ 65 ] will impact tourism economic efficiency. From the perspective of demanders, the rise of per capita income and consumption upgrading continue to drive the transformation in the tourism industry [ 66 ], which in turn leads to an increasing scale of market demand [ 67 ], which provides the possibility of increasing the foreign exchange earnings, local capital accumulation, and consumption spillovers. From the perspective of supporters, scholars have verified the significant effects of factors on TEG, including the transportation facilities and accessibility [ 68 – 71 ], the basis of the economy and marketization [ 72 ], industrial structure [ 73 ], public policy [ 74 – 76 ], and technological progress [ 77 ].

In summary, the research on TM has paid attention to its impact on the regional economy, but they both ignored the role of TM on TEG. Studies of TEG based on static factors have primarily relied on econometric models [ 78 ]. Although the spatial spillover effects of influencing factors have gradually gained attention, its depth is limited and fails to explore the impact of TM and other related factors on the TEG. TM is becoming central to tourism activities and understanding the capital mobility of tourism will have implications for tourism development under the new mobility paradigm [ 79 ]. This study proposes the concept of TM based on the theory of fluid mechanics, explores its impact on TEG, and analyzes the contribution of each influencing factor to TEG.

Theoretical framework, research methods, and data sources

Theoretical framework.

Traditionally, tourism research considers the tourism system as tourist sources, tourist destinations, and tourist corridors (transportation systems) [ 80 , 81 ]. Under the new mobility paradigm, this study regards the spatial transfer of tourists from the source to the destination as a mobility process. Tourist mobility is the fundamental reason for the existence of tourism. If tourists stop flowing, tourism will cease to exist.

It is known that the fluid will be affected by a variety of factors, such as viscosity, density, resistance coefficient, and altitude. As shown in Fig 1 , the total mobility of tourists from a tourist origin to a tourist destination is the number of tourists (Q). The spatial transfer of tourists, on the other hand, requires the use of transportation infrastructure as well as means of delivery. As an essential vehicle to support tourism development, transportation infrastructure directly reflects regional accessibility and relevance and is a crucial factor influencing TM [ 82 – 84 ], and its construction level has different effects on TEG in different regions [ 11 , 85 – 87 ]. According to the equations in fluid mechanics, the average velocity is equal to the flow rate ratio to the cross-sectional area. It can be deduced that TM = Q/TL. TM is determined by the number of tourists (Q) and the length of transportation infrastructure (TL). According to the definition, this indicator considers both tourist arrivals and flow rate, and its significance lies in its ability to characterize the mobility of tourism factors relying on tourists and physical transportation. This paper also connects the factor decomposition method to determine the importance of TM to TEG and presents theoretical implications for identifying essential factors to enhance tourism efficiency and stimulate tourism industry development.

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https://doi.org/10.1371/journal.pone.0275605.g001

Research methods

Measurement of tourism mobility..

Exploratory spatial data analysis.

It is generally believed that tourism has a spatial spillover effect and spatial correlation [ 28 ]. Therefore, we use Exploratory Spatial Data Analysis (ESDA) to detect spatial correlation among the variables. ESDA is used to analyze spatial characteristics through global and local spatial autocorrelation measurements [ 42 , 89 ].

The global Moran’s I is an indicator of whether factors are spatially correlated and its value ranges from -1 to 1. When 0<I≤1, it indicates a positive spatial correlation; when -1≤I <0, it indicates a negative spatial correlation; when I = 0, there is no spatial relationship. The equation is as in ( 2 ).

With a Z statistical test as in Formula ( 4 ), the cluster and outlier analyses can identify H_H (High_High) clusters, L_L (Low_Low) clusters, L_H (low value surrounded by high values) clusters, and H_L (high value surrounded by low values) clusters at a 95% confidence level.

Econometric model.

The econometric model, including tourism economic growth (TEG), tourism mobility (TM), physical capital in the tourism industry (TP), and human capital in the tourism industry (TH), is constructed according to economic growth theory without considering spatial spillover effects. Besides, since the measurement of TM only considers land transportation infrastructure data, the passenger traffic by the airport (TA) is introduced in the model to characterize the air capacity. Eq ( 5 ) represents the econometric model (TEG it ) in province i and year t, where α is the constant term, β is the parameter to be estimated, μ i denotes the spatial effect, and ε it denotes the random error term.

However, the spatial correlation of TEG will lead to biased parameter estimates of traditional econometric models. If the test results of global Moran’s I indicate that TEG is significantly spatially correlated, a spatial econometric model should be introduced to solve the bias-variance problem. The spatial Durbin model ( Eq 6 ) is developed according to Eq 5 . The spatial weight matrix used in the spatial Durbin model is an adjacency matrix. y it represents the TEG in province i and year t; x it represents the TM, TP, TH, and TA in province i and year t; and W ij y jt and W ij x jt are the TEG and lagged terms of each influencing factor, respectively. ρ and φ are spatial lagging coefficients, and v t denotes the time effect.

LMDI decomposition.

The LMDI decomposition method is widely used because it can effectively solve the residual problem in the decomposition and zero and negative values in the data. LMDI In this study, TEG is decomposed according to Eq ( 7 ). The influencing factors of TEG are decomposed into tourism mobility effects ( TE ), cumulative traffic effects ( Traffic ), effects of the tertiary industry ( Industry ), structural effects of the tourism industry ( Structure ), and reception effects ( Reception ). The equations are shown in ( 8 ) to ( 11 ). Traffic indicates the weighted road length; GDP (service) intimates the value added of the tertiary industry; Population represents the population in each province, and Visitors is the number of tourists. Introducing the log-average function L(x,y) defined in Eq ( 12 ). Eq ( 7 ) is decomposed into Eq ( 13 ) by LMDI, where ΔTEG denotes the amount of change in TEG from initial time 0 to period t, and ΔTM、ΔT、ΔI、ΔS、ΔW represent the contribution of each influencing factor to TEG. The equations are shown in ( 14 ) to ( 18 ).

Data sources

The study area is 31 provinces of China (excluding Hong Kong, Macao, and Taiwan), which is divided into seven regions according to the geographical divisions of China. The provinces included in each region are listed in supporting information. Since data availability varies widely across regions, the research period of TM and LMDI decomposition is from 2000 to 2018. As the National Bureau of Statistics of China (NBS) started to collect the employment data of private enterprises and individuals by sector in 2004 and the data for 2018 has not been updated yet, the research period of the spatial econometric model only covers the period from 2004 to 2017.

The data sources involved in the paper are as follows: the transportation infrastructure data come from the China Statistical Yearbook; the number of tourists is obtained from the Statistical Bulletin on National Economic and Social Development. Air passenger traffic data is collected from Civil Aviation Airport Production Statistics Bulletin. We employ the social fixed asset investment in transportation, storage, and postal services, wholesale and retail trade, accommodation and catering, and culture, sports, and entertainment as proxies for physical capital in the tourism industry (TP). This is because various aspects influence tourism development. Considering that only direct tourism investment does not reflect the total investment in tourism by society, we choose the four industries closely related to tourism development as physical capital in the tourism industry.

In this paper, private and individual employees in the transport, storage, and postal industry, wholesale and retail trade, and accommodation and catering industries are used to represent the human capital in the tourism industry (TH). The main reason for this is that, on the one hand, most studies only consider the number of employees in travel agencies, scenic spots, and star hotels, which differs significantly from the actual number of direct and indirect employees in tourism. On the other hand, since private enterprises and individual employment solve more than 80% of the urban employment problem, the number of private enterprises and individual employment in the three industries related to the tourism industry is chosen to represent the human capital. All the above data are collected from the NBS ( http://data.stats.gov.cn ). In the LMDI decomposition, the value added of the tertiary industry and the population in each province come from the China Statistical Yearbook.

Analysis of tourism mobility measurement results

Spatiotemporal evolution characteristics of tourism mobility.

Limited by space, Table 1 only shows the results of TM over five years. During the study period, TM increased from 56~12745 p visitors /km to 382~18865 p visitors /km, with an average annual growth rate between 2.20% and 13.46%. According to the average value of TM ( Fig 2 ), the study areas are divided into the following three types.

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https://doi.org/10.1371/journal.pone.0275605.t001

• “Leading Area”, including East China and North China, ranked first and second in all regions. Their TM increased from 2679.39 and 1884.34 p visitors/km in 2000 to 5859.93 and 5209.94 p visitors/km in 2018. However, their annual average growth rates were 5.07% and 6.43%, respectively, ranking first and second from the bottom in all regions. East China is located on the coast, relying on superior natural conditions and an economic foundation, and its regional transportation system is relatively complete. Therefore, it has formed many advantageous tourist resource gathering areas and has become the main tourist destination of inbound tourists in China, and its mobility has long ranked first in the country. As a political and economic center, Beijing has become a tourist attraction for domestic and inbound tourism with a large number of historical and cultural tourism resources. It also drives the joint development of the tourism industry in North China with the Beijing-Tianjin-Hebei urban agglomeration as the core, making North China the second largest core area of TM after East China.
• “Stable Area”, including South China, Southwest China, Central China, and Northeast China, ranked third to sixth in all regions. Their TM increased from 903.57p visitors/km, 695.15p visitors/km, 632.06p visitors/km, 493.33 p visitors/km in 2000 to 2626.11p visitors/km, 2754.97p visitors/km, 2857.88p visitors/km, 2244.68 p visitors/km in 2018. The average annual growth rates were 6.58%, 8.81%, 9.06%, and 9.38%, respectively. TM in South China grew rapidly during 2005~2015, while it has gradually slowed down in recent years. This is mainly due to the construction of the early transportation system in South China, which increased tourist mobility. After the basic construction of facilities, the incremental tourist inflows decreased, and the overall growth remained stable. Central China has become one of the core transportation hubs under its location and has driven regional tourism development, becoming a central province in the second echelon of TM. Due to geographical restrictions, Northeast and Southwest China are less connected to the transportation network than coastal areas, resulting in relatively low levels of TM. Northeast China focuses on the development of heavy industry but pays little attention to the tertiary industry, and tourism infrastructure construction and resource development are relatively weak, which leads to low TM. There are many mountains in Southwest China, and its early traffic development level lags. With the opening of the Chengdu-Chongqing high-speed railway and Chengdu-Guizhou high-speed railway, and the development of the air transportation industry, the land and air transportation layout in Southwest China is becoming increasingly mature. Southwest China actively developed its resources, and the tourist inflow increased from 145 million (2000) to 2.994 billion (2018), with an average value of TM catching up with that of southern China during 2016~2018.
• “Potential Area”, including Northwest China, ranks last in terms of average tourist mobility. Its TM increased from 282.01 p visitors/km in 2000 to 1427.58 p visitors/km in 2018, but its average annual growth rate was 10.01%, ranking first among all regions. As less developed region, Northwest China has a poor foundation in economic development and openness to the outside world, and TM has long been at the bottom of the list. Although TM in Northwest China has long been at the bottom of the list, its mobility growth rate leads other regions as tourism infrastructure construction and resource development levels have improved under the active promotion of Western Development policies, the Five-Year Plan, and the Territorial Tourism Strategy.

To more intuitively observe the temporal and spatial change characteristics of TM during the study period, we apply the method of natural breaks to classify the 31 provinces. Natural breaks classes are based on natural groupings inherent in the data. Class breaks are identified that best group similar values and maximize the differences between classes. The features are divided into classes whose boundaries are set where there are relatively big differences in the data values. The natural breaks classification method is a data classification method designed to determine the best arrangement of values into different classes. This is done by seeking to minimize each class’s average deviation from the class mean while maximizing each class’s deviation from the means of the other groups [ 92 ]. We divided the 31 provinces into five categories, highest-value area, higher-value area, medium-value area, lower-value area, and lowest-value area, according to the TM in 2000, 2005, 2010, 2015, and 2018. As shown in Fig 3 , (1) Shanghai and Beijing have long been in the highest-value area and higher-value area of TM. Tibet, Qinghai, Ningxia, Xinjiang, Inner Mongolia, Gansu, Jilin, Heilongjiang, Hubei, and Hainan have long been in the lowest-value and lower-value areas. (2) Over time, the number of provinces in the highest-value area and the higher-value area increased significantly, from 2 provinces in 2000 to 12 provinces in 2018. The number of provinces in the lowest-value area and lower-value area significantly decreased, from 26 provinces in 2000 to 12 provinces in 2018; the number of provinces in the medium-value area fluctuated randomly, with the fewest 3 in 2000 and the most 13 in 2015. (3) Except for Shanxi, Northwest China has been in the lowest-value area and the lower-value area for a long time; The TM values in Southwest China have changed greatly. Chongqing and Guizhou have jumped from the lower-value area to the higher-value area, and Yunnan has jumped from the low-value area to the medium-value area. Tibet is relatively stable and has been in the lowest-value area for a long time; South China is relatively stable, but the average value TM in Guangxi has changed greatly, jumping from the lower-value area to the higher-value area; The average TM in Central China has been in the low-value area for a long time. Central China is also relatively stable, and its average TM has long been located in the lower-value area and the medium-value area. Except for Shanghai, which has always been in the highest-value area, the initial value of TM in other provinces in East China has jumped upward. In the Northeast, Liaoning’s TM has always been in a leading position, and it has gradually transitioned from a lower-value area to a higher-value area. However, Jilin and Heilongjiang have always been in the lowest-value area and the lower-value area, respectively. Changes in TM in North China are diverse. Beijing has long been located in the highest-value area and higher value area. Inner Mongolia has been in the lowest-value area for a long time. Hebei is in the lower-value area most of the time. Tianjin and Shanxi changed greatly and finally jumped to the highest-value area and the higher-value area, respectively.

a. 2000, b. 2005, c. 2010, d. 2015, e. 2018.

https://doi.org/10.1371/journal.pone.0275605.g003

We use the standard deviation ellipse to identify the direction of TM in each province. As shown in Fig 3 , the lengths of the minor semiaxis and major semiaxis of the ellipse increased significantly. The growth of the short semiaxis reveals that the degree of dispersion of TM in China’s provinces is gradually increasing. This result is consistent with the previous analysis conclusions that TM in some provinces shows a more obvious transition trend, which makes the overall dispersion of TM increase.

Spatial correlation characteristics of tourism mobility

Global spatial autocorrelation of tourism mobility..

We use ArcGIS 10.8 to calculate the global Moran’s I of TM for 2000–2018, and the results are shown in the table below ( Table 2 ). The global Moran’s I values from 2000 to 2018 were all positive, and the results from 2000 to 2015 were not significant, and the results from 2016 to 2018 were all significant at the 90% level. TM presents a significant positive spatial correlation. This shows that provinces with high TM in China have relatively high TM in their surrounding areas. From the overall trend, the spatial correlation degree of China’s TM has gradually increased, but its value has not exceeded 0.1, indicating that the spatial agglomeration effect of China’s TM is still weak.

https://doi.org/10.1371/journal.pone.0275605.t002

Local spatial autocorrelation cluster of tourism mobility.

The global Moran’s I cannot reflect the spatial correlation exhibited by local regions or individual provinces. We further use ArcGIS 10.8 to draw the LISA cluster diagram for 2000, 2005, 2010, 2015, and 2018 ( Fig 4 ). The research samples are divided into four types of agglomeration: provinces with high TM are surrounded by provinces with high TM (H-H agglomeration), provinces with high TM are surrounded by provinces with low TM (H-L agglomeration), provinces with low TM are surrounded by provinces with high TM (L-H agglomeration), and provinces with low TM are surrounded by provinces with low TM (L-L agglomeration).

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The results show that (1) provinces with H-H aggregation of TM in different periods are relatively stable; L-L and L-H aggregation types are stable but mixed with changes; The H-L aggregation type does not appear, which indicates that there is no "darkness under the light" area for China’s provincial TM. Provinces with high TM can improve the TM of weekly provinces to a certain extent. (2) The H-H agglomeration is mainly concentrated in Jiangsu and Zhejiang. These regions are economically developed and have high per capita discretionary income. Moreover, the tourism infrastructure in these regions is more complete than that in other regions, and the tourist reception scale is also higher, so their TM shows a high local concentration. (3) The L-L agglomeration types are mainly distributed in geographically remote areas such as Qinghai, Tibet, Gansu, and Xinjiang in inland China. Moreover, Xinjiang and Gansu temporarily withdraw from the L-L agglomeration area. The main reason for this pattern is that the transportation infrastructure in the areas above mentioned is relatively underdeveloped. The "space-time compression effect" brought about by the rapid development of China’s transportation is not significant. Furthermore, due to the distance from the main tourist source markets, although the TM shows a high growth rate, it is still in the lowest-value area and the lower-value area for a long time. (4) L-H agglomeration is mainly transferred in Anhui, Shandong and Hebei, and these provinces are located in the “Leading Area”. The average value of TM in the surrounding provinces is generally high, forming a "collapse area" for TM.

The impact of tourism mobility on tourism economic growth

Spatial autocorrelation of tourism economic growth.

In this study, a Monte Carlo simulation was selected to analyze the spatial autocorrelation of TEG ( Table 3 ). Moran’s I was positive from 2000 to 2018. They passed the significance test of different degrees except in 2006, indicating that TEG has a significant positive spatial correlation. Therefore, a spatial econometric model should be selected to analyze the influencing factors of TEG.

https://doi.org/10.1371/journal.pone.0275605.t003

Traditional panel data model

The unit root test using LLC and Fisher showed no unit root for TEG, TM, TH, TP, and TA ( Table 4 ). The Kao test, Pedroni test, and Westerlund test were used to determine the cointegration relationship between the variables. The test results showed a cointegration relationship, indicating that the data can be used for modeling.

https://doi.org/10.1371/journal.pone.0275605.t004

In terms of the regression model, the BP Lagrangian test results show the rejection of the mixed model. Wooldridge and Wald’s test indicates the presence of heteroskedasticity and autocorrelation in the data. The presence of heteroskedasticity would lead to an increase in the variance of the model parameters and invalidate the Hausman test results. If the regression is still performed using the method without heteroskedasticity, it will undermine the validity of the t-test and F-test, while autocorrelation will exaggerate the significance of the parameters. Therefore, the panel model is selected by the over-identification test (Hausman test result is significant), and the result shows that the Sargan-Hansen statistic is 14.32 and significant, so fixed effect modeling should be selected.

To further address heteroskedasticity and autocorrelation, this study uses Driscoll-Kraay standard errors for regression. The results in Table 5 show a significant positive effect of each variable on TEG, where each 1% increase in TM will promote 0.62% growth in the tourism economy.

https://doi.org/10.1371/journal.pone.0275605.t005

Spatial panel data model

In this paper, the specific form of the spatial panel data model was determined by LM-LAG and LM-ERROR tests. If the result of LM-lag is significant and LM-error is not significant, then SLM should be used, and vice versa, SEM should be used. If LM-lag and LM-error statistics are significant, it indicates that the spatial correlation of the lag term and the spatial correlation of the residuals should be considered. In this case, the SDM can be used to set the model. Subsequently, this study determined whether the SDM model would degenerate into SLM or SEM by Wald and LR tests, and the results showed that all passed the significance test. Meanwhile, the test results of LM-lag, LM-error, LM-lag (robust), and LM-error (robust) were significant ( Table 6 ), indicating that the model set using SDM has a certain rationality.

https://doi.org/10.1371/journal.pone.0275605.t006

We selected the regression model through the Hausman test, and the result showed that the value was 19.31, and the corresponding probability value was 0.007, which indicated that the null hypothesis of random effect was rejected. Therefore, the fixed-effect model was selected for regression analysis. Table 7 shows the estimation results, where ρ rejects the original hypothesis only in the Spatio-temporal fixed-effects model. Therefore, this paper provides a specific analysis of the Spatio-temporal fixed-effects model. The regression results indicate that TM shows a significant positive effect on regional TEG.

https://doi.org/10.1371/journal.pone.0275605.t007

According to the results and spatial effect decomposition ( Table 8 ), ρ is -0.559, indicating that the growth of the tourism economy in neighboring provinces will have a negative impact on the local area. The direct effect of TM is significant, indicating that TM will promote TEG. However, the indirect effect results show that the increase in TM in neighboring provinces will have a negative impact on the local TEG.

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Decomposition of the influencing factors by LMDI.

We decompose the influencing factors and analyze their contribution trend. Table 9 shows the specific contribution of each influencing factor to the TEG in the seven regions.

https://doi.org/10.1371/journal.pone.0275605.t009

ΔT increases from 15.41% in 2000~2005 to 22.55% (2005~2010), and then decreases to 9.35% in 2010~2015 and 7.01% in 2015~2018. Overall, the ΔT showed a downward trend, but it is still an important factor in promoting TEG. The average contribution rate of the ΔT from 2000 to 2018 reached 14.82%.

ΔI maintained an overall downward trend during 2000 ~2018. It gradually decreased from 31.42% (2000~2005) to 22.94% (2015~2018). In contrast, the added-value of tertiary industry per capita increases from 3653 yuan to 34,969 yuan in the same period, indicating that the contribution of tertiary industry to TEG continues to decline, and tourism is gradually decoupled from the development of the tertiary industry.

ΔS maintained an overall upward trend during 2000~2018, from 7.09% (2000~2005) to 14.67% (2015~2018). The overall contribution rate was 11.50%, indicating that increasing the proportion of the tertiary industry in tourism can promote TEG.

ΔR shows a negative effect on TEG, and the degree of adverse effect increases slowly from 26.22% to 27.67%. The overall contribution rate was 28.67%. Reception is defined as the ratio of the resident population to the number of tourists. This shows that on the premise that the permanent resident population remains basically unchanged, the contribution to TEG can be effectively increased by expanding the scale of tourists.

Regression results of tourism mobility on tourism economic growth

This study briefly analyzes the regression results of the traditional and spatial panel data model. However, the spatial autocorrelation test results of TEG show an overall trend of fluctuating and increasing spatial correlation, especially with 2009 as the abrupt change point and a significant increase in the degree of agglomeration. Therefore, the article discusses the results of the spatial panel data model in detail, and the primary purpose of analyzing the traditional panel data model is to compare it with the spatial econometric results.

The regression results of the spatial econometric model show that both TM and TA have a significant positive impact on TEG, which verifies the hypothesis we proposed above. This result is also consistent with Wu et al. [ 93 ] and Perboli et al. [ 94 ]. In contrast, TP and TH have no significant impact on TEG. However, previous studies have also shown that the spatial spillover effect of tourism can significantly affect the TEG [ 27 – 29 ]. Therefore, the impact of TP and TH on TEG remains to be further confirmed.

According to the decomposition results, TM will promote the growth of the local tourism economy but will have a negative impact on neighboring provinces, which indicates a more obvious competition in tourism development among provinces. The increase in mobility in a particular place under a given number of tourists will lead to a diversion of tourists, which will have a negative impact on neighboring regions. Therefore, the tourism industry should also pay attention to the competitive situation in the surrounding areas. The development of tourism focus not only on improving local tourism mobility but also on neighboring areas. Both TP and TH manifest substantial spatial spillover effects. The increase in TP and TH in neighboring areas will produce positive effects, making local areas attach importance to the development of tourism resources and enhancing tourism attraction. TA has a significant positive contribution to TEG, which is consistent with the conclusion of Yang and Wong [ 27 ]. However, the spatial spillover effects of TA on TEG are not significant, which may be related to the fact that air traffic does not depend on adjacent spaces.

Analysis of influencing factors’ contribution rate to tourism economic growth

Tm and δtm..

The ΔTM in North, Central, Southwest, and South China all show a trend of "falling and rising." It should be noted that the ΔTM in North China was negative from 2005 to 2010, mainly due to the significant decline in TM in Tianjin and Hebei. The improvement in the transportation infrastructure has a significant impact on TM in Central and Southwest China. The opening of high-speed railroads is a fundamental reason for the fluctuation in ΔTM. For South China, due to the implementation of the overnight visitor count statistics in the tourism statistics system of Guangdong in 2015~2018, the number of tourists decreased significantly compared to 2010~2015, which in turn led to a significant weakening of the ΔTM. In contrast to the regions mentioned above, the ΔTM in Northeast China shows a trend of "rising and falling" changes. From 2010 to 2015, the contribution of TM to TEG in Northeast China declined and was negative. The main reason is the overall decline of the regional economy in the Northeast region at this stage. In 2014 and 2015, the GDP growth rates of Northeast China were 4.23% and -0.84%, respectively, ranking second and last among the seven regions in China during the same period. At the same time, the Northeast region began to carry out statistical "squeeze water" at this stage, which caused obvious fluctuations in the scale of tourists. Therefore, the downturn in the regional economic environment and stricter tourism statistics have negatively affected the contribution of tourism mobility to tourism economic growth. However, since 2016, China has put forward the " all-for-one tourism" policy. Provinces began to pay more attention to the role of tourism in regional economic growth. All-for-one tourism policies and new management systems have led to the continuous improvement of TM in Northeast China from 2015 to 2018, and the contribution to TEG has increased significantly compared with 2010–2015. The ΔTM in East China gradually increased from 6.35% to 25.66%, which is related to the opening of the high-speed railroad network in 2010, leading to a significant increase in TM. Northwest China has made the tourism industry a key point for economic growth, and its tourist reception and transportation construction levels have been rapidly improved under the impetus of the all-for-one tourism strategy.

Traffic and ΔT.

The contribution of ΔT to TEG generally shows a downward trend. However, during the same period, Traffic showed a gradual upward trend. In 2018, it increased by 258.72% compared with 2000. Among them, it increased by 35.61% from 2000 to 2005, increased by 91.36% from 2005 to 2010, increased by 24.83% from 2010 to 2015, and increased by 10.73% from 2015 to 2018. From this, it can be judged that there may be a "threshold" in the transportation infrastructure. When the stock of transportation infrastructure in China reaches a certain level, the accumulation of transportation infrastructure cannot improve the contribution to the TEG. The role of transportation infrastructure in influencing tourists’ decisions and determining TM cannot be ignored. However, its contribution rate gradually decreases as transportation facilities are gradually improved and regional accessibility differences narrow. The ΔT is 14.82% during the examination period, in which the contribution rate of Traffic to TEG in East China (16.15%), Central China (17.44%), Southwest China (15.75%), and Northwest China (15.40%) is higher than that in North, Northeast and South China. This is mainly because Central China and East China are the regions with the largest passenger turnover in China. From 2000 to 2018, the average passenger turnover in Central China and East China was 118.988 billion person-kilometers and 84.595 billion person-kilometers, respectively. The Southwest China and Northwest China are among the regions with the fastest growth in passenger turnover in China, increasing by 3.13 times and 1.77 times respectively, ranking first and second in all regions.

Industry and ΔI.

The tertiary industry consists of transportation, warehousing and postal industry, information transmission, real estate industry, financial industry, wholesale and retail industry, accommodation and catering industry, etc. Tourism is only a part of it. The per capita added value of the tertiary industry reflects the degree of development of the service industry in various regions, and this indicator has achieved a relatively large increase in terms of changing trends. It increased from 3,653 yuan in 2000 to 34,969 yuan, an increase of 8.57 times. The contribution of ΔI to TEG has gradually declined, mainly due to the slowdown in the growth rate of the per capita added value of the tertiary industry. The growth rate dropped from 91.30% in 2000–2005 to 34.35% in 2015–2018. The contribution of ΔI to TEG in North China, South China, Northwest China, and Southwest China is consistent with the national trend. Northeast China, East China, and Central China show different trends. Especially in the Northeast region, the contribution of ΔI to TEG has dropped significantly. The overall contribution rate of Industry reached 28.18%, indicating that the quality of tertiary industry development has a vital role in promoting TEG. ΔI is generally stable in East and Central China and declines significantly in Northeast China, which may be related to the deceleration of tertiary industry development, as the data show that the added-value of tertiary industry per capita in Liaoning, Heilongjiang, and Jilin increased by 93.04%, 75.15% and 90.43% from 2010 to 2015, while it only grew by 0.63%, 39.88% and 23.18% from 2015 to 2018. Central China was inconsistent with the overall national trend from 2005 to 2010. This is mainly due to the slow increase in the per capita added value of the tertiary industry during this period, ranking last in all regions. During this period, the industrial structure of Central China was still dominated by industry. In 2010, the average industrial added value accounted for 56.37% of GDP, the highest in all regions of the country. East China was inconsistent with the overall national trend in 2015–2018. The main reason is that the proportion of the tertiary industry in Fujian and Jiangxi in the region has not exceeded 50%, and there is a large room for optimization and improvement of the industrial structure. Therefore, the growth rate of the added value of the tertiary industry per capita exceeds the previous stage, and the contribution of ΔI to TEG is still rising.

Structure and ΔS.

The share of tertiary industry in tourism in Beijing and Tianjin increased significantly from 2010 to 2018 compared to 2000, leading to the rapid growth of ΔS in North China. The ΔS in Northeast China was -3.96% from 2005 to 2010, mainly since the growth rate of tertiary industry in Heilongjiang and Liaoning lagged behind that of the tourism industry. The ΔS in East, Central, and Southwest China is relatively stable, indicating that tourism and tertiary industry maintain a coordinated development. The ΔS in South China has achieved a shift from negative to positive growth. As the economic volume of Guangdong accounts for a large proportion in South China and the growth rate of tourism significantly lags behind the development rate of the tertiary industry, it leads to a low ΔS in South China from 2000 to 2010. The opening of high-speed rail provides new opportunities for tourism development, and the ΔS in South China gradually increased to 14.38% and 10.73% in 2010~2018. The ΔS in Northwest China has been increasing, which suggests that the tourism economy is the primary driver of tertiary industry growth. The continuous growth of the ΔS contribution to TEG is partially consistent with the findings of Chang et al. [ 95 ], De Vita and Kyaw [ 96 ], and Zuo and Huang [ 97 ]. The higher Structure is, the greater the contribution of ΔS to TEG. However, the literature above mentioned also pointed out that ΔS has a turning point. For example, Zuo and Huang [ 97 ] found that this value in China is 8.25%.

Reception and ΔR.

The ΔR has a negative impact on TEG. Zuo and Huang [ 97 ] used the ratio of tourist arrivals to the permanent resident population to characterize tourism specialization in a study evaluating China’s tourism-oriented economic growth. Before reaching the inflection point of 30.34 (that is, the tourism reception effect value is 0.03), this indicator has a significant positive impact on TEG. From 2000 to 2018, the tourism reception effect value dropped from 1.47 to 0.11, still less than 0.03. Therefore, the results of our study also partially confirm the research of Zuo and Huang [ 97 ]. While expanding the scale of tourists, various regions should also pay attention to the "inflection point" of the Reception value. When the inflection point is reached, the larger the scale of tourists is, the smaller the contribution to the TEG. However, the ratio of regional population to tourist decreases from 1.47 to 0.11 during the period from 2000 to 2018, indicating that not only the number of tourists should be taken into account, but also the quality of the tourism and the per capita tourism consumption should be attached importance to the TEG. ΔR is relatively stable, among which the southwest and northwest China have the most significant negative contribution to the TEG, indicating that the growth rate of the number of tourists received in the above regions is higher than that of other regions.

Conclusions

This paper proposes the concept of TM based on the hydrodynamic equation, constructs an econometric model of TEG with TM as the core explanatory variable, explores the direct and indirect effects of TM on TEG, measures the specific contribution of each influencing factor using the LMDI decomposition, and draws the following conclusions.

• The TM in China has maintained rapid growth for a long time. However, there are differences in the rate of growth in different regions. East China and North China are Leading Area, with the highest average tourism mobility, but the smallest average annual growth rate; Central China, South China, Northeast China, and Southwest China are Stable Area, with the middle average TM and average annual growth rate; Northwest China is Potential Area, which has the smallest average TM, but the largest average annual increase. The TM in each region only showed a significant positive spatial correlation in 2016–2018. The space-time pattern is constantly changing over time. The high-value areas and high-value areas of TM increased significantly, while the low-value areas and low-value areas decreased significantly. The local spatial autocorrelation results of TM are stable, and various agglomeration states are stably distributed in some provinces.
• The regression results of the traditional panel data model and the spatial panel data model both show that TM has a significant positive effect on TEG. Under the premise of considering the spatial effect, the improvement of TEG in a province by TM will have a negative impact on the adjacent province.
• Applying the LMDI decomposition method, the TEG is decomposed into TM , Traffic , Industry , Structure , and Reception. The results show that the contribution of TM and Structure to TEG showed an upward trend, with average annual contribution rates of 15.76% and 11.50%, respectively. It indicates that improving TM is a crucial way to promote tourism development. The contribution of the Traffic and Industry to TEG generally showed a downward trend, with average annual contribution rates of 14.82% and 28.18%, respectively. The Reception has a negative impact on the TEG, but it is still a positive contribution, with an average annual contribution rate of 28.67%. The five types of effects of TEG decomposition were different due to regional differences.

The main contributions of this study are as follows: (1) Based on fluid mechanics, we constructed an indicator of TM. We comprehensively consider the impact of tourist arrivals and transportation infrastructure on TEG, which is rarely proposed by scholars in the literature. Our research enriches the research on the influencing factors of TEG. (2) We analyze the influence of TM on TEG based on the econometric model, which highlights the importance of TM. Moreover, we found that TM has negative spatial overflow.(3) Based on the LMDI method, we decompose TEG into five major effects, rather than just considering traditional variables such as human input, capital input, and tourism resource input. Our study further enriches the research on the influencing factors of TEG.

Based on our findings above, we draw the following policy implications. To improve TEG, late-developing regions should improve TM by building large-scale tourism transportation infrastructure, promoting destination marketing to attract tourists, and paying attention to the possible negative effects of increased TM in neighboring regions. At the same time, the improvement of TM should be emphasized at different stages. The threshold effect of tourism transportation infrastructure should also be fully considered. After the transportation infrastructure reaches a certain stock, its contribution to TEG will decrease. At this time, expanding the scale of tourists should become the main tourism development policy.

There are still some limitations in this study. It is difficult to directly collect data on the inflow and outflow of tourist between certain provinces. Therefore, we only select inflow of tourists as the primary data and do not consider the influence of the tourists’ outflow on TM. In fact, increased transport accessibility will not only expand the inflow of tourists but also affect the outflow of tourists. Therefore, the superposition effect of traffic and tourist inflow/outflow should be considered comprehensively to improve the scientific rationality of TM measurement. This study lacks comparative studies across multiple countries. The research in our study may show differentiated findings for developed or less developed countries. When constructing the econometric model, we mainly consider TM as the core explanatory variable, and only select human input and capital input, and air traffic related to traffic as control variables from the perspective of the economic growth model. In the future, the theory and practice of TM will be further explored with multivariate data to form a more rigorous and systematic cognitive framework.

Supporting information

S1 fig. map of the seven regions..

https://doi.org/10.1371/journal.pone.0275605.s001

S1 File. Research data.

https://doi.org/10.1371/journal.pone.0275605.s002

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Tourism in China: 2022 Trends and Investment Opportunities

The COVID-19 pandemic continues to impact Chinese tourism, more so because of the country’s zero-Covid policy. New trends have emerged – which has seen a surge in domestic tourism and changing travel preferences among various demographic categories. In this article, we explore how China’s indigenous tourism market is diversifying, successfully catering to the lifestyles of Gen Z and young families, and touch on the prospects for the return of China outbound tourism. We also offer insights for foreign businesses interested in China’s tourism sector and its allied service industries like retail and sustainability.

As more countries open their borders to international tourism, the absence of Chinese visitors is causing more than a little economic pain. From Phuket to Paris, major tourist destinations have relied on an average of 150 million Chinese travelers spending up to US$255 billion yearly on sightseeing. Now three years into the COVID-19 pandemic, many of these destinations are starting to realize th at it will be a while till the Chinese t ourists return. Some analysts believe that this could impose serious economic consequences on affected countries.  

Despite the rest of the world moving toward an endemic approach to the virus, China continues to implement a zero-Covid policy. As of August 2022, China has a  quarantine system   in place for inbound travelers as well as rigorous  measures that get promptly activated in case of outbreaks. Yet, it is precisely such measures that allow Chinese tourists to feel safer when traveling across provinces and have fueled the growth of the country’s domestic tourism industry.  

Nevertheless, tourism market data from China in the first quarter of 2022 showed a significant dip when compared to the same period in the previous year . Data from the Ministry of Culture and Tourism, for example, revealed that, during the New Year’s Day and Spring Festival, 52 million and 251 million people traveled across the country between the two holidays , showing a year-on-year decrease of 5.3 percent and 2.0 percent, respectively. This of course can be put down to the resurgence of Covid-19 with multiple regional and global outbreaks due to more infectious variants.   However, with the beginning of the summer holiday season, the slowdown appears to have once again reversed as ticket sales are noticeably on the rise. This presents us with a unique opportunity to zoom in on China’s tourism market and explore how it has transformed since the pandemic . We discuss who is the new Chinese traveler, look at destination trends, as well as the types of services required by the tourism market.    

The Chinese tourist profile at a glance

Family traveling at its peak   .

The pandemic has caused the decline in popularity of destinations previously famous for group travel, a revenue mainstay for the tourism industry. Chinese travelers are instead opting for different plans based on needs and preferences, giving rise to more family vacations, healthcare tours, and research trips. In particular, “parent-child tourism” has gained momentum throughout 2021 and 2022, along with the steady revival of the national tourism industry.    

The 2022 Summer Travel Market Trend Report released by Ctrip (one of China’s leading travel companies) showed that family travel packages have reached a peak in the 2022 summer booking spree. In July 2022, the number of family air tickets sold increased by 804 percent, compared to the previous month. Similarly, bookings of family-friendly hotels grew 80 percent, compared to the same period in 2021, and were up by 20 percent from 2019 – most of these bookings being concentrated in four- and five-star hotels.  

Moreover, in July, the number of families traveling from Shanghai and Beijing, as well as from other big cities in China, increased significantly compared to previous holiday periods, such as the Labor Day Holiday or the Dragon Boat Festival. The backlog of travel demand from these places was primarily due to the impact of the epidemic response in the first half of the year, which gradually eased at the beginning of summer.  

Looking at the preferred travel destinations, families with children in primary or junior high schools prefer island tours to Sanya, Haikou, Qingdao, and Xiamen , among others, largely because of their family-friendly services. These two groups of travelers have also turned their attention to the tours to the northwestern provinces of Qinghai, Gansu, and Xinjiang.  

The Ctrip air ticket data also showed that younger travelers were accompanied by more family members. For example, primary and junior high school students travel with 3.5 and 3.2 people in summer vacations, respectively. On the other hand, college students are more independent in their travel habits.  

Gen Z: T he online buyers  

As Gen Z’s purchasing power increases, travel has become a significant avenue for them to seek leisure and enjoyment. Survey data showed that over half (52.7 percent) of the Gen Z travelers surveyed looked for travel information on social media and short video platforms, including Xiaohongshu, Kuaishou, Weibo, and Bilibili. About 49 percent of those surveyed chose online travel agencies (OTAs) like Trip.com, Qunar, and Meituan. According to the research, just 16.7 percent of the tourists used offline services to obtain information.    

As of 2022, prices and budget remained the main deciding factors for Gen Z when planning their tours, followed by other elements such as transit convenience and safety. 62.5 percent of Gen Z use OTAs to book their travel, with official supplier websites coming in second, followed by social media and e-commerce sites like Xiaohongshu, Douyin, and Taobao.  

  Data also revealed that natural landscapes were the main draw for Gen Z tourists in 2022. Despite higher spending power, these Chinese travelers had little interest in visiting popular retail malls or luxury sites.  

Corporate travel  

According to data from the Global Business Travel Association (GBTA) , China took the top spot globally for business travel expenditure in 2021. Indeed, following a 38 percent drop in that same category over the previous year, China’s corporate travel expenditure increased by 31.7 percent in 2021 as the local market rebounded – more than doubling the worldwide growth rate.  

According to the study, 16.3 percent more Chinese businesses used travel management agencies in 2021 than they did in 2020. In China’s top cities , including Beijing, Shanghai, and Guangzhou, this number increased by 24.6 percent.   

By 2024, the business travel industry in China is predicted to recover and reach pre-pandemic levels, with total spending on business travel topping US$400 billion. The strong recovery momentum in China’s business travel industry is reflected in the Trip.com Group’s 2021 performance, with hotel reservations on Trip.Biz (the business-dedicated section of CTrip) increasing by almost triple digits.   

China’s latest tourism trends by destination

Peripheral or ‘short-distance’ tourism on the rise  .

With the continuous development of leisure tourism in recent years, the short-distance tourism model has gained enough market recognition and respect.   

Affected by the pandemic, many people in China still have concerns about the health risks of long-distance traveling. Several primary and secondary schools still restrict the travel of students during long holiday periods, resulting in families preferring to travel short distances and explore nearby landmarks. Local tours, “rediscovering the beauty of the surroundings”, have become popular. new trend as residents gets the opportunity to experience the place where they were born and raised.  

The improvement of both tourist facilities and services in the hospitality sector has made it possible for this type of tourism to attract a larger pool of customers.    

Rural tourism  

Holiday destinations have undergone an evolution from country to the city and back again. Against the background of rural revitalization , the government has appointed a series of “village +” destinations to promote tourism, such as the Yellow River Suji Village and the Jijiadun Ideal Village. Ctrip data shows that the order volume of rural hotels more than doubled in 2021 compared to the previous year, attracting visitors mainly born between the 1980s and the 1970s.    

In the past, rural vacations meant spending time between mountains, rivers, and the serene scenery offered by the countryside. Today’s offers are much more diversified, as enterprises combine their business models with sustainable development goals and attract tourists with higher spending capacity.  

Cultural products   

With the growing enthusiasm of young people for Chinese culture, cultural tourist offers have become more popular.    

Various museums, for example, have recently become a hot topic on the search list for nationwide destinations. At the beginning of 2022, the unearthing of cultural relics at the Sanxingdui Ruins site set off a boom in museum tourism. Similarly, the China Grand Canal Museum in Yangzhou (Jiangsu province) has become a popular tourist check-in place, so much so that it attracted a monthly audience of more than 250,000 visitors during its trial operation period alone.   

At the same time, the organic integration of traditional folk culture has become more popular, and activities such as temple blessings and intangible cultural heritage experiences, are very popular among tourists. The rural market in northern Anhui, for example, staged wonderful performances , such as Huainan Shouxian drum, Suzhou Sixian Sizhou opera, and Taihe lion lantern , among others, attracting many tourists. Various places in Fujian have carried out splendid, themed activities around the “Fu” culture .  

A sense of cultural self-confidence among young Chinese people can be attributed as the main reason for the growth of such cultural destinations and scenic spots – not to be confused with the popular “Red Tourism” .    

Closer to nature   

The data collected by Ctrip at the beginning of 2022, revealed that natural protected areas and national forest parks appeared in the top five popular scenic spots announced by over 22 cities on the mainland.  

Indeed, Chinese travelers are paying increasing attention to nature-immersive destinations. According to the report of Qiaoyou.com, more than half of the app’s users have been to at least one of the first batch of national parks officially announced in October 2021, and 83.6 percent of the surveyed people plan to travel there in the future.  

It is worth mentioning that Chinese tourists nowadays engage more with natural destinations through a variety of activities, such as photography, acquiring natural knowledge, exercising, etc. Increasing this skill set has become an important factor in attracting travelers to explore outdoor scenic spots; hiking and camping have become popular new ways to get closer to nature.  

Prospects for outbound tourism

According to recent forecasts , a ‘strong wave’ of outbound travel from China will start up again in 2023, returning to its pre-pandemic levels by 2024. Such predictions are backed by plans announced by the country’s aviation regulator, which has issued a five-year development plan , with a strong focus on expanding domestic flights and restoring international air travel by 2025.   

Chinese tourists’ interest in overseas destinations has remained attractive though recovery is still a long way off. The Asia-Pacific region remains the most popular with Chinese tourists. Most desired overseas destinations are Southeast Asia, Europe, Russia, and Japan.   

The lifting of international border restrictions in China and the incidence of COVID-19 cases in the destination country are key factors shaping Chinese decision-making about outbound travel. Travel patterns to destinations such as Hong Kong and Macao demonstrate how COVID-19 cases and quarantine requirements have an immediate effect on travelers’ decision-making.  

Innovation is key to the development of China’s tourism products

Fintech for flexibility  .

New payment patterns have been quietly emerging behind the scenes as the travel sector has steadily recovered from the pandemic slowdown. One of the most prominent developments in travel technology in recent years is the growing confluence of finance and travel. Whether it is new payment options offered by travel suppliers, improvements in the flow of funds among tourism market players, or travel agencies launching full-fledged fintech solutions, the way the travel sector does business is rapidly changing.   

Aligned with these trends, airlines, hotels, and travel agencies may seek to modify their customer loyalty programs to encourage clients to utilize their specialized services thereby entrenching their position in this high-margin market .     

Smart scenic spots  

Nearly half of Chinese tourists cited COVID-19 prevention and control measures as the most important factor when planning a trip, according to a survey. Self-guided tours, small group tours, and customized tours with less contact with strangers are preferred. This may accelerate the pace of construction of smart scenic spots.    

Through online platforms and the travel app of the scenic spot, tourists can learn about their destination, find information to support travel route planning, book tickets for scenic spots and hotel accommodation, besides online shopping for souvenirs in advance. Such services and digital products allow tourists to be informed before, during , and after their tour is completed, while also enhancing the attraction of scenic spots.    

Technology empowers hospitality  

With the deepening integration of “Internet +” tourism, information communication technology has become the driving force for tourism development.  

With newer applications of the Internet, big data, and artificial intelligence, which will get accelerated in the 5G era, digital technology is being fully integrated into the tourism industry. This has brought changes to tourism supply and consumption, promoting new business models, and higher quality development of the tourism industry overall.  

Alibaba, China’s e-commerce and technology behemoth debuted its first robotic hotel, the FlyZoo Hotel, in December 2018. This “hotel of the future” was set up in the company’s hometown, Hangzhou , by Alibaba’s online travel agency (Fliggy) together with other company divisions, including Alibaba A.I. Labs and Alibaba Cloud.   

This high-tech hotel’s major goal is to show how artificial intelligence is already changing China’s hospitality sector and how it will motivate other countries’ travel and hospitality sectors to embrace innovation.   

  FlyZoo Hotel CEO Wang Qun has frequently said in several interviews that the company would keep developing “smart brains” for automated hotels in China as well as more specialized experiences for visitors.   

Key takeaways for foreign investors

Retail shopping while traveling  .

Retail shopping while traveling is emerging as a popular consumption trend in China. The pop-up store may not be a brand-new concept, but it is making a comeback in the Chinese travel landscape. For instance, in collaboration with China Duty-Free Group, several companies, including SK-II and Clé de Peau Beauté, have opened pop-up shops in Hainan to cater to the demands of customers who have been unable to go abroad due to the epidemic.  

Clé de Peau Beauté’s pop-up shop , for instance, has hosted several live-streamed events, and offered exclusive experiences in Sanya (a top-tourist city on the Chinese island of Hainan), including a simulator room, QR codes, and AR mirrors. These features have notably improved the Clé de Peau Beauté pop-up experience, with the live stream attracting a record of 6.4 million impressions and over 700,000 views on Yizhibo.  

Meanwhile, an AI skin analyzer, animated shorts, a WeChat mini-program, as well as an AR video game were among the features included at SK-“Social II’s Retail” pop-up store (also located in the Sanya International Duty-Free Shopping Complex).   

Travel companies need to adapt  

There is a clear desire to travel, and a huge pent-up demand for outbound travel. At the same time, despite intermittent COVID-19 outbreaks, interest in domestic travel has continued to increase – particularly whenever the epidemic situation stabilizes. In this fluid market scenario, travel agencies can plan for demand spikes while also considering changing travel tastes. To better serve tourists, travel agencies may need to become more flexible with their strategies. Given frequent changes in legislation, travel agencies can be more accommodating when clients adjust their plans. Additionally, they may concentrate on nearby communities that are accessible by car, diversify their product offerings to adapt to demand changes, and foster loyalty by paying closer attention to customer happiness and the distinctiveness of the tourism experience. Travel agencies may also utilize digital channels to communicate with consumers and can customize content and presentation.  

Analyzing trends in the tourism industry suggests that China’s domestic market has much-untapped potential. Various opportunities exist for the travel industry to diversify its product offerings, such as through curated and immersive experiences or by responding to changing customer needs. In turn, tourism marketing strategies can incorporate insights from the dynamic experiences of the domestic market during the pandemic — enabling the domestic operating model to achieve long-term inclusive and sustainable growth.    

Gen Z is the new decision-makers  

Consumers no longer primarily travel for shopping. Gen Z in China, which dominates the upcoming generation of tourists, seeks different experiences when traveling. Hiking, low-altitude flying, and water sports are just a few of the trending activities researched by this new group of travelers, according to recent data .   

This shows that tourists now seek more than a pleasant travel experience. They are typically more specific about their travel goals and eager to meet individuals who share their interests. This opens space for companies to engage in the digital market and invest in social media apps that feature tools to connect with travel and tourism. Additionally, most young travelers looking for a variety of unique experiences. Since social media content is how many choose their specific destinations or travel activities, Gen Z tourists in China are eager to replicate some of the experiences they encounter on these apps. Therefore, the way to win these consumers’ hearts, particularly in this demographic group, is to offer experiences (rather than products) – which may have more personal value.  

China Briefing is written and produced by Dezan Shira & Associates . The practice assists foreign investors into China and has done so since 1992 through offices in Beijing, Tianjin, Dalian, Qingdao, Shanghai, Hangzhou, Ningbo, Suzhou, Guangzhou, Dongguan, Zhongshan, Shenzhen, and Hong Kong. Please contact the firm for assistance in China at [email protected] . Dezan Shira & Associates has offices in Vietnam , Indonesia , Singapore , United States , Germany , Italy , India , and Russia , in addition to our trade research facilities along the Belt & Road Initiative . We also have partner firms assisting foreign investors in The Philippines , Malaysia , Thailand , Bangladesh .

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These are the top 10 countries for travel and tourism

The US retains its prime position in the World Economic Forum's latest Travel & Tourism Development Index. Image:  Unsplash/EveLazco

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• Pent-up demand after the pandemic is expected to drive passenger numbers back up to pre-pandemic levels in 2024.
• The recovery of the travel and tourism sector since the pandemic has been uneven, however, and some nations are better placed than others to respond to the challenges and opportunities of the future.
• The top three best-placed countries for travel and tourism are the US, Spain and Japan, according to the World Economic Forum’s Travel & Tourism Development Index.

If you were desperate to get away after the restrictions and enforced staying at home of the pandemic years, you were far from alone.

Global international tourist arrivals are expected to meet pre-pandemic levels in 2024 driven by this pent-up demand. But, the recovery of the travel and tourism sector since the pandemic has not been without challenges. Add to that macroeconomic, geopolitical and environmental factors, which have added pressures on the industry.

These pressures will amplify and evolve over the coming years and, along with the growth of digital technologies and AI, may well force the travel industry to adapt.

Some economies are better placed than others to make these changes, respond to future risks and ensure that travel and tourism is a driver of economic growth and prosperity.

With this in mind, the World Economic Forum’s Travel & Tourism Development Index (TTDI) aims to serve as a benchmark for stakeholders to gauge progress, inform decisions and policies, and encourage sustainable and resilient growth.

A mixed recovery in challenging conditions

Europe dominates the top 10 economies for T&T, as ranked by the 2023 index, although the top spot is clinched by the US.

But the index also shows that while 71 of the 119 economies it ranks improved their scores between 2019 and 2023, the average improvement is just 0.7% above pre-pandemic levels.

On the one hand, the rebound in travel and tourism has coincided with rising global air route capacity and connectivity, improved international openness, and increased investment in natural and cultural resources driving tourism. On the other hand, non-leisure demand is still lagging, there are ongoing labour shortages, and air route capacity and connectivity, capital investment and productivity have struggled to keep pace with demand.

This has created a supply and demand imbalance which, along with inflationary pressures, has led to reduced price competitiveness and service disruptions.

Europe and Asia-Pacific have the most favourable conditions

Of the top 30 TTDI scorers in 2023, 26 are high-income countries. Nineteen of them are based in Europe, and seven in Asia Pacific.

These countries benefit from favourable business environments and labour markets, open travel policies, advanced technology adoption, excellent transport and tourism infrastructure, and rich natural, cultural and non-leisure attractions.

As a result, this group of 30 accounted for more than three-quarters of T&T industry GDP in 2022, and 70% of GDP growth between 2020 and 2022.

But although this group is leading the way, many of the above-average improvements in scores come from low- to upper-middle-income countries, including sub-Saharan and North Africa, Eurasia, South America, South Asia, and the Balkans and Eastern Europe.

While many have shown improvements, these less affluent countries still make up the vast majority of below-average scorers in the index. More investment is needed to help increase their share of the market and improve their readiness for future risks and opportunities.

Progress needed on resilience and equality

The ability of the travel and tourism sector to grow is limited by challenges like tight labour markets, growing fiscal constraints and concerns around health and security conditions. Labour market resilience will be an increasingly important factor for the sector, but issues like equality of job opportunities, workers’ rights and social protection are holding many economies – particularly low- and middle-income ones – back in this area.

As other sectors proceed to decarbonize, the aviation sector could account for a much higher share of global greenhouse gas emissions by mid-century than its 2%-3% share today.

Sustainable aviation fuels (SAF) can reduce the life-cycle carbon footprint of aviation fuel by up to 80%, but they currently make up less than 0.1% of total aviation fuel consumption. Enabling a shift from fossil fuels to SAFs will require a significant increase in production, which is a costly investment.

The Forum’s Clean Skies for Tomorrow (CST) Coalition is a global initiative driving the transition to sustainable aviation fuels as part of the aviation industry’s ambitious efforts to achieve carbon-neutral flying.

The coalition brings together government leaders, climate experts and CEOs from aviation, energy, finance and other sectors who agree on the urgent need to help the aviation industry reach net-zero carbon emissions by 2050.

The coalition aims to advance the commercial scale of viable production of sustainable low-carbon aviation fuels (bio and synthetic) for broad adoption in the industry by 2030. Initiatives include a mechanism for aggregating demand for carbon-neutral flying, a co-investment vehicle and geographically specific value-chain industry blueprints.

Learn more about the Clean Skies for Tomorrow Coalition's impact and contact us to find out how you can get involved.

Another major hurdle for the sector is balancing growth with sustainability. Although there has been broad progress in areas like energy sustainability, some progress – like the fall in emissions seen during the pandemic – is likely to only be temporary.

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Travel, Tourism & Hospitality

Contribution of China's travel and tourism industry to GDP 2014-2023

Travel and tourism industry's share of gdp in china from 2014 to 2022 with a forecast for 2023, by direct and total contribution.

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2014 to 2022

*Forecast. Direct contributions cover visitor exports, domestic expenditure, internal tourism consumption, government individual spending, and purchases made by tourism providers (including imported goods). The figure was not disclosed from 2018 onwards.

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• Special Coverage

Chinese and Amercian students perform at the opening ceremony of the 14th China-U.S. Tourism Leadership Summit in Xi'an, northwest China's Shaanxi Province, May 22, 2024. (Xinhua/Shao Rui)

XI'AN, May 22 (Xinhua) -- High expectations ignited calls at a China-U.S high-level tourism summit on Wednesday for concrete actions to remove tourism barriers between the two countries.

The 14th China-U.S. Tourism Leadership Summit drew nearly 400 representatives of the governments, institutions, and tourism-related enterprises of the world's top two economies to the ancient Chinese city of Xi'an.

Chinese State Councilor Shen Yiqin read a message from Chinese President Xi Jinping at the opening ceremony. She said President Xi's message fully demonstrates the great importance attached to the China-U.S. relations and ardent expectations for deepening China-U.S. tourism cooperation.

STRONG PENT-UP DEMAND

History has proven that China-U.S. cooperation potential in the tourism industry is huge.

Annual bilateral tourist flow reached a milestone in 2016 -- surpassing 5 million for the first time. Notably, the number of Chinese tourists visiting the United States exceeded 3 million for the first time that year, and their total travel expenditure surpassed 30 billion U.S. dollars for the first time, Dai Bin, president of the China Tourism Academy, said at the summit.

Escalating geopolitical tension and the sudden impact of the COVID-19 pandemic, however, have combined to reduce bilateral exchanges in recent years.

China responded to the ebbing of the pandemic by stepping up efforts to boost its tourism sector. From resuming a steadily increasing number of international flights and implementing a visa-free policy for more countries and cruise travelers, to simplifying visa-application procedures and optimizing payment services, Chinese authorities pressed the "acceleration button" to facilitate the recovery of its tourism industry.

Julie Durazo, with Pathways Travel based in Los Angeles, said the visa application process to enter China is now "a lot easier," compared to what was required during the pre-pandemic era.

Durazo, who is in Xi'an to research tour options, is planning to bring dozens of U.S. high school students to China this fall.

"I remember before it was at least a six-month waiting process. So we had to have our students sign up close to a year in advance," she said, adding that both paperwork and procedures have since been significantly reduced.

Durazo's husband, Paul Orr, joined her on the research trip and it took just four days for him to get his visa after submitting all necessary documents.

Latest figures released by China's National Immigration Administration showed that the number of foreigners visiting China had increased by more than threefold in the first quarter of 2024, when compared with the same period last year.

Meanwhile, approximately 1.1 million visitors from China had traveled to the U.S. in 2023, representing a 192.9-percent surge compared with the previous year, according to data from the U.S. National Travel and Tourism Office. The trend, however, is still more sluggish than what insiders had anticipated.

Attendees at the summit in Xi'an attributed these disappointing travel levels to a lack of flights, visa challenges, crime concerns, and general geopolitical tensions.

Currently, there are 100 direct flights every week between the two countries, which is less than one-third of the pre-pandemic level.

"Before the pandemic, we could fly direct from Los Angeles to Beijing or Shanghai, but now we have to make a stopover in San Francisco, and the ticket fare is much more expensive," said Durazo.

There is also a visa challenge that needs to be dealt with. Despite being one of the most desired overseas destinations among Chinese tourists, the U.S. visa application process has deterred many Chinese from planning a trip to that country.

"The average waiting time for a U.S. visa appointment is currently three months. In addition, the United States only offers individual visas, which require in-person interviews, and applicants from Xi'an have to go to either Beijing or Guangzhou for such an interview," said Peng Shuping, chairman of Xi'an Spring International Travel Service Co., Ltd. "We really hope that the visa application process can be simplified," Peng added.

Another obstacle is that Washington has issued a level-3 advisory concerning travel to China, calling on Americans to "reconsider" such travels, which has deterred many Americans who otherwise may have been more likely to visit China.

"We strongly hope that the relevant policies will be adjusted as soon as possible," said Zhou Xiaoguang, president of China Odyssey Tours.

COMMON EXPECTATIONS

The U.S. Commerce Department and Tourism Policy Council in June 2022 released a national strategy, setting an ambitious five-year goal of attracting 90 million international visitors to the United States each year, which would generate 279 billion U.S. dollars to support American travel workers and businesses.

"An important factor in achieving this goal is the ability of the U.S. travel and touring industries to attract more Chinese travelers to visit the United States for leisure, business and education purposes," Grant Harris, assistant secretary of commerce for industry and analysis at the U.S. Commerce Department, said at the opening ceremony in Xi'an. Harris also read a message from U.S. President Joe Biden at the summit.

China, which welcomed over 82 million inbound tourists while its domestic residents made nearly 101 million outbound trips in 2023, has also put tourism in a prominent position in its drive to encourage economic growth.

A national meeting on the development of the tourism sector was held last week in Beijing, highlighting that it is "imperative to promote high-quality development of the tourism sector," and the need to "speed up building China into a country strong in tourism."

Seeing the event in Xi'an as an opportunity to further revive the tourism market, industry insiders who attended it voiced strong anticipation for more pro-tourism measures to boost the global tourism industry.

"We regard Sino-U.S. travel as a barometer, so the tourism sector has great expectations for the recovery of Sino-U.S. travel," said Feng Gaoxuan, general manager assistant of Xi'an Overseas Tourist Co., Ltd.

Travel and tourism between the U.S. and China is of great importance not just to the world's two largest economies, but also to the entire global community, said Chris Clark, who is chairman of Visa Asia Pacific, at the summit.

"The importance of cultural exchange cannot be understated," Clark added. "It helps us understand and appreciate different cultures, values, and traditions that are different from our own, fostering mutual respect and understanding, and can improve communication and build better relationships between people and nations."

（Editor:Fu Bo）

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