1. Introduction
With the rapid development of the cultural and entertainment industry, the consumption of culture and entertainment has become an important part of residents’ lives. The spatial distribution patterns of cultural and entertainment facilities have become important indicators to measure the quality of life of residents and the level of social and economic development [
1,
2]. Due to the increasing pressures of life and work, people urgently need cultural and entertainment activities to meet their spiritual and cultural enjoyment needs [
3]. Global cultural and entertainment consumption exceeds USD 1 trillion, and among them, Americans spend USD 280 billion on culture and entertainment each year. The growth of production and wealth further liberates people’s social needs and yearning for entertainment [
4,
5]. Cultural and entertainment consumption is not only restricted by the development of the social economy but also interacts with the social atmosphere [
6,
7]. Therefore, understanding the differentiation of the distribution of cultural and entertainment facilities is helpful to understand the regional characteristics of culture to a certain extent [
8]. As an important function of the city and an important part of the urban spatial structure, the spatial distribution of cultural and entertainment facilities is not only related to the spatial structure of the city, but it even affects the recovery of urban functions [
9]. At the same time, although the city’s economy and built environment are gradually improving, the service delivery enjoyed by urban residents is very unevenly distributed [
10,
11]; this includes cultural and entertainment facilities. In the context of rapid economic development and spatial changes, there are huge differences in the supply of cultural services between different regions and between urban and rural areas, and there are also diversified groups within a city with different demands for cultural and entertainment services [
12]. Therefore, understanding how to optimally arrange cultural and entertainment facilities is essential for enabling residents to enjoy a balanced cultural life [
13]. This has become an important issue that geographers, urban planning scholars and government departments are increasingly concerned about.
The culture and entertainment industry has become a hot research field in academia since the mid to late 1990s [
14]. The field of geography tends to focus on two major aspects: firstly, the spatial distribution characteristics of the cultural entertainment industry in cities and, secondly, its evolution and the influencing factors of spatial distribution (location distribution and site selection), with the ultimate aim of analyzing the cultural and entertainment industry at the local level [
15,
16,
17,
18,
19,
20,
21,
22]. The research scale is usually limited to a city or the main urban area of a city. The research conclusions provide reference values for the understanding of the spatial distribution characteristics of cultural and entertainment facilities in different areas of Beijing and the detailed planning of the urban cultural and entertainment industry.
Current research on urban cultural and entertainment facilities mainly focuses on the planning, design, adaptive transformation, spatial distribution and evolution characteristics and spatial influencing factors of urban cultural and entertainment facilities. First of all, in analyzing the spatial distribution and evolution characteristics of the cultural and entertainment industry, a variety of spatial analysis and visualization tools based on GIS (Geographic Information System) are widely used because it is a tool to visualize relevant conclusions. Huang et al. [
23] found that Shanghai’s (a city of China) cafes formed a spatial pattern of one main core and multiple secondary cores. The urban clustering effect is the most significant factor in the main urban area; different types of cafes have different spatial clustering characteristics. Jia et al. [
24] found that Urumqi’s (a city of China) cultural facilities are mostly distributed in science, education and cultural enrichment areas or multi-ethnic mixed living areas, which have become important hot spots for regional cultural exchanges. Yang et al. [
25] found that the agglomeration characteristics of movie theaters in Xi’an (a city of China) changed significantly from 2011 to 2016, gradually expanding from the old city to the new suburban city and finally forming a new hotspot clustering area in the new city. Yu et al. [
26] found that the Tongzhou District and Changping District of Beijing (a city of China) have formed multiple centers of cultural and entertainment facilities, which are areas with better cultural and entertainment development in the suburbs.
Secondly, in terms of analyzing the influencing factors of the spatial distribution of the cultural and entertainment industry, the urban social and cultural environment and residents’ demands for cultural enjoyment have received more attention. Zhao et al. [
27] found residents’ cultural consumption habits, education levels and the cultural life atmosphere has an important impact on the distribution of different types of cultural facilities. In addition, the urban social space and the spatial evolution of culturally integrated commercial complexes have an impact on the distribution pattern of movie theaters [
25]. Xue et al. [
21] discovered that traditional cultural tourism areas and places rich in historical and cultural resources often have denser cultural and entertainment facilities. Some scholars construct models to incorporate multiple factors such as socioeconomics, transportation locations, cultural atmospheres, etc., to analyze in detail the spatial distribution of certain types of cultural and entertainment facilities. For example, Huang et al. [
23] found that employed population density, road network density and the land price have a large influence on the number of the cafes, and chain cafes have higher requirements for traffic communication and consumer demand. The distance from the nearest colleges and universities has relatively larger influence on the number of independent cafes than other types of cafes. Therefore, the distribution of the independent cafes pays more attention to the innovation environment.
It is worth mentioning that Chinese scholars pay the most attention to the spatial distribution of cultural and entertainment facilities, while scholars from other countries pay more attention to urban green spaces, medical emergency facilities and other facilities that are closely related to people’s health and safety [
28,
29,
30,
31]. In conclusion, research on cultural and entertainment facilities is relatively scarce. Throughout the research on the distribution of facilities, it is obvious that few scholars have conducted research on the spatial distribution of various types of cultural and entertainment facilities, especially in areas with developed cultural and entertainment industries such as Beijing. Furthermore, existing research is limited to the analysis of a single type of cultural and entertainment facilities, and there is still a lack of multi-index quantitative analysis of the impact of the social economy, the built environment and other factors on the spatial distribution of the overall cultural and entertainment facilities. Therefore, this study analyzed the distribution of cultural and entertainment facilities of Beijing, which is a developed area of innovation and development, that will help to comprehensively and deeply understand the current distribution of Beijing’s cultural and entertainment industry and related issues and provide references for the planning and development of Beijing’s cultural industry. Therefore, this study will address the following questions: What is the diversity pattern of cultural and entertainment facilities in the city area and in six urban districts? What are the spatial distribution characteristics of cultural and entertainment facilities in the city area and in six urban districts? What are the clustering characteristics of cultural and entertainment facilities in six urban districts? What are the scale effects and hierarchical characteristics of the clustering characteristics of cultural and entertainment facilities in six urban districts? How do factors such as social economy and the built environment affect the spatial distribution of cultural and entertainment facilities in six urban districts?
This research first used the Simpson Index to detect the diversity of the spatial distribution of cultural and entertainment facilities. Then, it analyzed the spatial distribution characteristics of different types of cultural and entertainment facilities. The grid method and kernel density method were used to analyze the spatial distribution of cultural and entertainment facilities. The nearest neighbor index was used to analyze the overall clustering characteristics of cultural and entertainment facilities in the six urban districts. The K function was used to analyze the clustering characteristics of cultural and entertainment facilities at different scales in the six urban districts. The nearest neighbor hierarchical cluster analysis was used to analyze the clustering hotspots of different levels of cultural and entertainment facilities in the six urban districts. Finally, a spatial regression model was constructed to analyze the influence of the social, economic and built environment on the spatial distribution of cultural and entertainment facilities and to identify the factors that significantly affect the distribution of cultural and entertainment facilities.
4. Discussion
At first, based on the results obtained above, we further discuss the spatial distribution characteristics of cultural and entertainment facilities and their influencing factors.
When it comes to the diversity of cultural and entertainment facilities, the traffic accessibility and the urban historical and cultural heritage are conducive to enhancing cultural and entertainment diversity. In addition, the reasons for the diversity of cultural and entertainment facilities may be that the effect of the policy that the proposal of Beijing’s sub-center was released in 2016. The southern part’s economic and industrial strength is relatively weak, which inhibits the diverse distribution of the cultural and entertainment industry in this place.
For the spatial distribution of various cultural and entertainment facilities, the leisure and fitness venues and parks and amusement parks are relatively even, because they are public welfare venues and are mostly planned and arranged by the government to meet the daily leisure needs of surrounding residents, and more consideration is given to the principle of balance. However, cafes, tea houses, etc., are profit-making establishments and are mainly distributed according to market demand behaviors. Most of them are concentrated in areas with dense populations, convenient transportation, developed commerce and active social and economic activities. In the six urban districts, for the bars and cafes, they tend to gather in the middle of the eastern part. The reason for this may be that a large number of foreigners lived near the Sanlitun embassy area in the early days, so bars and cafes developed here first. Another reason may be that after the reform and opening up, the business and financial formats of CBD have grown rapidly and have become a gathering place for foreigners’ business exchanges. Cinemas and theaters have a significant clustering effect in the center. The reason is that most of the historical districts in Beijing are in the center. Traditional and historical performance projects (acrobatics, cross talk, etc.) promoted the early concentration and distribution of theaters in the city center. Cinemas are mostly distributed in prosperous areas, so they also present a concentrated distribution. The clustering characteristics of tea houses, clubs, internet cafes and parks and amusement parks are relatively weak. The reason for their even distribution is that the housing distribution in the six urban districts is relatively even, and such facilities usually serve the local citizens first.
The cultural and entertainment facilities have such a huge urban–rural difference and a center–peripheral structure. The reasons for this are as follows: first, Beijing’s western and northern mountainous areas have a large area, and the southeast plain has more villages. The cultural and entertainment facilities are mostly rendered to the living configuration of urban residents, therefore, the peripheral area is not conducive to the distribution and development of related facilities; second, Beijing has improved its “pancake” urban expansion model and is undergoing a connotative and intensive development route. Therefore, Beijing’s industrial development and the population density at this stage are still concentrated within the Fifth Ring Road. Due to the limited scale of industrial expansion in the suburbs, it is difficult to promote the development of new cities. Therefore, it is difficult for cultural and entertainment facilities to grow on a large scale in the peripheral areas of the city and only a small amount of distribution near the residence.
For the clustering characteristics of facilities in the six urban districts at different scales, compared with other facilities, bars tend to gather at the smallest spatial scale, indicating that bars tend to compete for a large number of human traffic within a small area. In addition, bars have the strongest clustering characteristics, and the reason for this may be that with the historical background of Beijing, Sanlitun and the CBD area were the places where foreigners concentrated in the early days. Thus, bars were the first to gather here and still maintained the most significant clustering until now. The degree of clustering of parks and amusement parks is the weakest. This is related to the green space service provided by the parks for the life of urban residents. It also shows that the construction of municipal parks and amusement parks is not clustered, thus facilitating residents’ life and improving infrastructure construction.
For the factors influencing the distribution of facilities, the greater density of the road network and higher housing rent are associated with a greater number of cultural and entertainment facilities. The facilities tend to follow the spatial layout of high-end residential areas. In places with a high density of financial insurance institutions, and many buildings and high-quality employment spaces have encouraged cultural and entertainment facilities, leading to a directional distribution of employment spaces. However, the distance to nearest scenic spot and the securities company density are two negatively correlated factors. The former shows that the distribution of cultural and entertainment facilities tends to be adjacent to the scenic spots; the latter indicates that cultural and entertainment facilities may only be deployed in association with security companies in some streets and towns. However, in most areas where the density of security companies is relatively high, cultural and entertainment facilities are more sparsely distributed, probably because security companies are not concentrated in business districts or industrial parks.
The second is to compare with other similar studies. Compared with Zhou, Zhang, Dai et al. [
46], our research pays more attention to the analysis of the basic pattern of POI, but lacks further analysis of the pattern, such as the analysis of spatial autocorrelation characteristics. Their research results show that historical and cultural sites have single-center distribution characteristics, but our cultural and entertainment facilities have multi-center distributions. Compared with Cui, Wang, Wu et al. [
47], we have more types of cultural and entertainment facilities, but the discussion on the distribution of the road network structure and facilities is not so detailed, and we did not conduct an in-depth investigation of the spatial structure of the road network. They found that karaoke bars are highly clustered at the distance range of 2.5–3.0 km, while any type of POIs are highly clustered at the distance range of 7 to 10 km. Compared with Yi, Yang, Liu et al. [
48], our research only focuses on cultural and entertainment facilities themselves and lacks extensive research on urban functions and cultural developments that reflect their spatial distribution patterns. Compared with Jing, Liu, Cai et al. [
49], our research found the circle distribution characteristics of cultural and entertainment facilities, that is, the number decreases from the city center to the outside, but for the facilities at different distance from the city center, the distribution characteristics are not discussed, and their research found that the law of gradient change in leisure facilities from the center to the periphery.
Thirdly, we will render some suggestions for the development of Beijing’s cultural and entertainment facilities. Comparing
Figure 2 and
Figure 5, we can find that the diversity and quantity distribution patterns are not completely consistent. For areas with high population densities such as Huilongguan-Tiantongyuan, although the facilities are more diverse, the number is relatively small. Therefore, in the layout and planning of the cultural and entertainment industry, the living needs of community residents should be considered. In areas with high residential population density, the number of cultural and entertainment facilities should be appropriately increased to meet the structure of the community’s cultural life circle. Then, we found that according to the regression results of the spatial lag model, in the six urban districts, housing rent and the distribution of cultural and entertainment facilities have a significant positive correlation. Therefore, for residents living in the places of lower housing rents, they may not be able to enjoy enough cultural and entertainment service. The government should introduce inclusive cultural and entertainment facilities to meet the development needs of regional cultural and entertainment industries for these residents and to promote the fairness of urban public facilities supply. In addition, Beijing’s mid- to long-term plan (2019–2035) for promoting the construction of a national cultural center puts forward, turn the South Fifth Ring Area into a functional area for national culture and international communication, and build a new gateway for international communication in the southern part of the city. According to our results, the South Fifth Ring District is a cold spot for cultural and entertainment facilities, whether it is on the scale of city area or the six urban districts. Therefore, one of the focuses of the layout and planning of cultural and entertainment facilities in Beijing should focus on the South Fifth Ring area in the future. According to the results of the regression, it is a feasible way to introduce mid-to-high-end industries to drive the growth of cultural and entertainment facilities and attract related investment, which will ultimately benefit the lives of regional residents and make this area become a new cultural landmark and a new gateway.
The data volume, coverage, accuracy, update frequency and other aspects of POI data from the domestic internet electronic map are considered to generally meet the needs of basic POI data for GIS applications in different industries. This paper uses the currently popular internet capture big data technology to collect Baidu map POI data and conducts a spatial analysis of urban cultural and entertainment facilities, thus adopting a different approach from the previous ways of collecting statistical data. However, the experimental data are from a single POI data source, and they are mostly studied from a spatial perspective, without the concept of time. Future research is expected to add the element of time to further study the temporal and spatial evolution processes and influencing factors of the formation, clustering and development of urban culture and entertainment facilities. What is worth mentioning is the classification of cultural and entertainment facilities. According to the Classification of Culture and Related Industries (2018) issued by the National Bureau of Statistics and the research of some scholars, we divided cultural and entertainment facilities into eight categories, but there are still some limitations: First, parks and amusement parks are grouped into one category. It is obvious that natural, cultural and amusement parks are not suitable for being classified into one category; in addition, unlike tea houses and cafes, bars and internet cafes may play a small role in the spread and exchange of culture, therefore, whether they should be classified as cultural and entertainment facilities is also a matter that is worth exploring. When setting factors that affect the distribution of cultural and entertainment facilities, our analysis for the road network is relatively superficial, and in-depth indicators such as accessibility and topological structure characteristics should be added in the future. In addition, big data have the characteristics of fine granularity, fine scale, large sample size and wide coverage. Meanwhile, traditional questionnaire data have shortcomings such as small sample size, challenging collection, poor timeliness and poor representativeness, amongst others. In the future, we can try to combine big data and small data and add human spatiotemporal behavior factors into the research on the factors affecting the distribution of cultural and entertainment facilities. This will further explore influences on the distribution of cultural and entertainment facilities, to a certain extent, to enrich and deepen the research on the spatial layout and influencing factors of cultural and entertainment facilities.
The contribution of this research is to analyze the spatial distribution characteristics of Beijing’s overall cultural and entertainment facilities and different types of cultural and entertainment facilities, as well as the clustering characteristics and influencing factors of cultural and entertainment facilities in the six urban districts. Another contribution is the findings of the unbalanced characteristics of the spatial distribution of cultural and entertainment facilities, the scale effect of the spatial agglomeration of different types of facilities, and the socio-economic and built environment factors that have a significant impact on the distribution of cultural and entertainment facilities. The results can provide a reference for more reasonable layout planning of cultural and entertainment facilities, stimulating regional cultural vitality, ensuring the efficient development and utilization of Beijing’s local cultural resources, optimizing the quality of urban cultural space and coordinating the spatial distribution of the cultural and entertainment industry with other industries.
5. Conclusions
To more objectively present the spatial distribution of urban cultural and entertainment facilities in Beijing, location-based interest data (POI) are undoubtedly an important choice. The Simpson Index was used to detect the diversity of the spatial distribution of cultural and entertainment facilities. The grid method and kernel density method were used to analyze the spatial distribution of cultural and entertainment facilities. The nearest neighbor index, the K function and the nearest neighbor hierarchical cluster analysis were used to analyze the clustering characteristics of the facilities in the urban six districts. Finally, a spatial regression model was constructed to analyze the influence of the social, economic and built environment factors on the spatial distribution of the facilities in six urban districts. The conclusions are as follows.
Regarding the spatial distribution of the diversity of cultural and entertainment facilities, the diversity within the Fourth Ring Road is relatively high.
The overall cultural and entertainment facilities have a significant center–peripheral structure. The hotspots of cultural and entertainment facilities are mainly distributed in the center of Beijing, while in the suburbs, the hotspots are only in the area where the district government is located.
The facilities in the six urban districts are generally clustered, but the clustering degree varies between different types of facilities. The most significant range of facility clustering characteristics is found within a radius of 10 km. Bars tend to gather in a very small spatial scale compared with other type facilities.
The cultural and entertainment facilities in the six urban districts can be divided into three levels of agglomeration hotspots. These agglomeration hotspots are closely related to environmental factors such as commerce, employment, traffic and universities.
The factors that characterize the social and economic vitality and the built environment have an important impact on the spatial distribution of cultural and entertainment facilities in Beijing. Financial insurance institution density, building density, security company density, housing rent and the distance to the nearest scenic spot are the main factors affecting the distribution of cultural and entertainment facilities in Beijing.