Spatial–Temporal Evolution Characteristics and Economic Effects of China’s Cultural and Tourism Industries’ Collaborative Agglomeration
Abstract
:1. Introduction
2. Indicators and Methods
2.1. Indicators
2.2. Methods
2.2.1. Coupling Coordination Model
2.2.2. Spatial Correlation Test
- (1)
- GMI: In this study, we explored the overall correlation between the culture and tourism industries through GMI. Its mathematical expression can be given as:
- (2)
- Local Moran’s I (LMI): We analyzed the local correlation between the culture and tourism industries through LMI. Its mathematical expression is:
2.2.3. Spatial Vector Autoregressive Model
2.2.4. Impulse Response Function
3. Empirical Analysis
3.1. Coupling and Coordination Degree of Culture and Tourism Industries
3.2. Spatial Correlation between Culture and Tourism Industries
3.3. Economic Effect Test of Collaborative Agglomeration of Culture and Tourism Industries
4. Conclusions and Recommendations
- (1)
- From 2010 to 2019, there was a coupling and coordination relationship between the China’s culture and tourism industries in 31 provinces, and the collaborative agglomeration between the two was in the primary stage. Temporally, the degree of coupling and coordination between Chinese culture and tourism industries showed a tendency to increase in fluctuation—namely, from 2010 to 2017 when the degree of coupling and coordination between the two industries was on the rise. From 2017 to 2018, this degree of coupling and coordination decreased slightly, and from 2018 to 2019, it rose again. Spatially, the collaborative agglomeration development of the culture and tourism industries was stronger in the coastal areas than in the inland areas, and the level of coupling and coordination gradually decreased from the coastal to inland areas.
- (2)
- From 2010 to 2019, the overall spatial positive correlation between the Chinese cultural and tourism industries in 31 provinces was significant, while the local spatial correlation was different. In terms of the overall spatial correlation, the overall spatial positive correlation of Chinese cultural and tourism industries increased significantly from 2010 to 2014. From 2014 to 2018, the overall spatial positive correlation of the two industries showed a downward trend. However, the overall spatial positive correlation of the cultural and tourism industries increased again from 2018 to 2019. In terms of local spatial correlation, the provincial culture and tourism industries in Eastern China had a high degree of local spatial correlation, and the interregional industrial linkage effect was significant. The local spatial correlation between provincial culture and tourism industries in the central region was relatively low, and the interregional industrial linkage effect was general. The local spatial correlation between provincial culture and tourism industries in Western China was relatively high, and the effect of interregional industrial linkage was not significant.
- (3)
- The impact of the collaborative agglomeration of Chinese culture and tourism industries on the economy was nonlinear, and the impact of different industrial collaborative agglomeration factors on the Chinese economy was different. Six factors had a strong correlation with economic effects: (1) per capita cultural expenses, (2) domestic tourism revenue, (3) proportion of tourism revenue in the GDP, (4) per capita daily tourism foreign exchange revenue, (5) proportion of cultural establishments in financial expenditure, and (6) proportion of the added value of culture and related industries in the GDP. Among the factors, the four factors of per capita cultural expenses, domestic tourism revenue, proportion of tourism revenue in the GDP, and per capita daily tourism foreign exchange revenue had a positive impact on the economic effect, with the first two factors’ effects being more significant. The impact of the proportion of cultural establishments in financial expenditure on the economic effects fluctuated greatly in the early stage, but not significantly in the later stage. The impact of the proportion of the added value of culture and related industries in GDP on the economic effect showed a positive and negative fluctuation trend in the early stage, and the impact on the economic effect in the later stage was not significant.
5. Limitations and Future Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
- (1)
- Per Capita Cultural Expenses: Per capita expenditure of funds for cultural industry in various regions in China.
- (2)
- Proportion of Cultural Establishments in Financial Expenditure: Proportion of funds used for cultural industry in all regions in China in total regional financial funds.
- (3)
- Proportion of Added Value of Culture and Related Industries in GDP: The proportion of the output value created by the cultural industry and the related industrial production activities of all permanent residents in a region in a certain period of time of the regional GDP.
- (4)
- Number of Cultural Property Collections: Representative cultural relics with important historical, artistic, and scientific value.
- (5)
- Public Library Collections Per Capita: The number of books published in that year that can be owned by each person in the region within one year.
- (6)
- Number of Public Libraries: The total number of public cultural facilities open to the public free of charge in the region for collecting, sorting, and preserving literature information and providing inquiry, borrowing, and related services.
- (7)
- Number of Cultural Centers: The total number of institutions that provide free places for cultural activities to the public in the region.
- (8)
- Number of Museums: The total number of nonprofit institutions in the region that provide the public with access to historical and artistic relics.
- (9)
- Number of Art Performance Teams: The total number of all kinds of professional art performance groups that are sponsored by the regional cultural department or managed by the industry and specialized in performing arts and other activities.
- (10)
- Number of Employees in Public Libraries: The total number of people who work in public libraries and receive remuneration.
- (11)
- Number of Employees in the Cultural Centers: The total number of people who work in cultural centers and receive remuneration.
- (12)
- Number of Employees in Museums: The total number of people who work in museums and receive remuneration.
- (13)
- Number of Employees of Art Performance Groups: The total number of people who work in art performance groups and receive remuneration.
- (14)
- Number of Visitors to the Public Libraries: The total number of people who borrow and search for information in a public library in a unit of time.
- (15)
- Number of Visitors to the Cultural Centers: The total number of people who conduct cultural activities in a cultural center in a unit of time.
- (16)
- Number of Visitors to the Museums: The total number of visitors to the museum per unit time.
- (17)
- Number of Audience of Art Performance Groups: The total number of people who watch art performances per unit time.
- (18)
- Number of Domestic Tourists: The number of Chinese mainland residents and foreigners, and overseas Chinese and compatriots from Hong Kong, Macao, and Taiwan who have resided in China for more than one year and stayed in tourist facilities in other places of China for at least one night and at most six months.
- (19)
- Number of Inbound Tourists: The number of foreigners, and overseas Chinese, Hong Kong, Macao, and Taiwan compatriots who come to China to visit, travel, visit relatives, friends, recuperate, investigate, attend meetings, and engage in economic, scientific, technological, cultural, educational, religious and other activities. It does not include the staff of foreign permanent offices in China, such as embassies and consulates, news agencies, enterprise offices, or foreign experts, foreign students, and people who stay on shore for no more than one night.
- (20)
- Domestic Tourism Revenue: All the expenses that tourists spend on transportation, sightseeing, accommodation, catering, shopping, entertainment, etc., during their travel and sightseeing in China.
- (21)
- Proportion of Tourism Revenue in GDP: The proportion of tourists’ total expenses in the process of travel and sightseeing in various regions in China in the GDP.
- (22)
- Per Capita Daily Tourism Foreign Exchange Revenue: The average daily tourism income from each tourist in a tourist destination area.
- (23)
- Number of Scenic Spots: The total number of places with clear geographical boundaries and available for people to visit, stay, and rest.
- (24)
- Number of Starred Hotels: The total number of places providing accommodation, catering, and other services for tourists that meet the evaluation criteria of the China Tourism Administration.
- (25)
- Number of Travel Agencies: The total number of profit-making units that provide tourists with travel, residence, and related tourism services.
- (26)
- Number of Tourism Colleges and Universities: The total number of schools offering tourism-related majors such as tourism management and hotel management.
- (27)
- Number of Employees in Scenic Spots: The total number of people who work in scenic spots and receive remuneration.
- (28)
- Number of Employees in Starred Hotels: The total number of people who work in starred hotels and receive remuneration.
- (29)
- Number of Employees in Travel Agencies: The total number of people who work in travel agencies and receive remuneration.
- (30)
- Number of Students in Tourism Colleges: The total number of students studying tourism management, hotel management, and other tourism-related majors.
- (31)
- Operating Revenue of Scenic Spots: The total income of scenic spots from providing services or selling goods to consumers in the course of business activities.
- (32)
- Operating Revenue of Starred Hotels: The total income obtained by starred hotels through providing labor services, renting rooms, and catering.
- (33)
- Operating Revenue of Travel Agencies: The total income of travel agencies when providing various tourism services to tourists.
- (34)
- Total Number of People Received in Scenic Spots: The total number of people who visit and stay in scenic spots.
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Industry Type | Primary Index | Secondary Index | Industry Type | Primary Index | Secondary Index |
---|---|---|---|---|---|
Culture Industry () | Basic Information | Per Capita Cultural Expenses () | Tourism Industry () | Basic Information | Number of Domestic Tourists () |
Proportion of Cultural Establishments in Financial Expenditure () | Number of Inbound Tourists () | ||||
Proportion of Added Value of Culture and Related Industries in GDP () | Domestic Tourism Revenue () | ||||
Number of Cultural Property Collections () | Proportion of Tourism Revenue in GDP () | ||||
Public Library Collections Per Capita () | Per Capita Daily Tourism Foreign Exchange Revenue () | ||||
Cultural Organizations (Libraries, Cultural Centers, Museums, etc.) | Number of Public Libraries () | Event Venues (Hotels, Travel Agencies, and Tourism Institutions) | Number of Scenic Spots () | ||
Number of Cultural Centers () | Number of Starred Hotels () | ||||
Number of Museums () | Number of Travel Agencies () | ||||
Number of Art Performance Teams () | Number of Tourism Colleges and Universities () | ||||
Employees | Number of Employees in Public Libraries () | Employees | Number of Employees in Scenic Spots () | ||
Number of Employees in the Cultural Centers () | Number of Employees in Starred Hotels () | ||||
Number of Employees in Museums () | Number of Employees in Travel Agencies () | ||||
Number of Employees of Art Performance Groups () | Number of Students in Tourism Colleges () | ||||
Profit & Loss Effects | Number of Visitors to the Public Libraries () | Profit & Loss Effects | Operating Revenue of Scenic Spots () | ||
Number of Visitors to the Cultural Centers () | Operating Revenue of Starred Hotels () | ||||
Number of Visitors to the Museums () | Operating Revenue of Travel Agencies () | ||||
Number of Audience of Art Performance Groups () | Total Number of People Received in Scenic Spots () |
Level | Coupling Coordination Degree | |
---|---|---|
1 | Extreme imbalance | (0.0,0.1) |
2 | Severe imbalance | [0.1,0.2) |
3 | Moderate imbalance | [0.2,0.3) |
4 | Mild imbalance | [0.3,0.4) |
5 | Verge of imbalance | [0.4,0.5) |
6 | Reluctant coordination | [0.5,0.6) |
7 | Primary coordination | [0.6,0.7) |
8 | Intermediate coordination | [0.7,0.8) |
9 | Well-coordinated | [0.8,0.9) |
10 | High-quality coordination | [0.9,1.0) |
Year | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
---|---|---|---|---|---|---|---|---|---|---|
Moran’s I | 0.144 | 0.190 | 0.187 | 0.207 | 0.214 | 0.184 | 0.177 | 0.173 | 0.127 | 0.141 |
Z | 2.356 | 2.480 | 2.284 | 2.520 | 2.586 | 2.450 | 2.515 | 2.530 | 2.455 | 2.353 |
P | 0.019 | 0.014 | 0.023 | 0.012 | 0.010 | 0.014 | 0.012 | 0.012 | 0.014 | 0.019 |
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Chi, Y.; Fang, Y.; Liu, J. Spatial–Temporal Evolution Characteristics and Economic Effects of China’s Cultural and Tourism Industries’ Collaborative Agglomeration. Sustainability 2022, 14, 15119. https://doi.org/10.3390/su142215119
Chi Y, Fang Y, Liu J. Spatial–Temporal Evolution Characteristics and Economic Effects of China’s Cultural and Tourism Industries’ Collaborative Agglomeration. Sustainability. 2022; 14(22):15119. https://doi.org/10.3390/su142215119
Chicago/Turabian StyleChi, Yihan, Yongheng Fang, and Jiamin Liu. 2022. "Spatial–Temporal Evolution Characteristics and Economic Effects of China’s Cultural and Tourism Industries’ Collaborative Agglomeration" Sustainability 14, no. 22: 15119. https://doi.org/10.3390/su142215119