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Article

Spatial Distribution of Development Types of Forestry-Ecological-Culture Industries in Chinese Provinces

by
Luyu Huang
1,2,
Guochun Wu
1 and
Yukun Cao
1,*
1
School of Economics and Management, Northeast Forestry University, Harbin 150040, China
2
School of Marxism, Heilongjiang Bayi Agricultural University, Daqing 163319, China
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(18), 11566; https://doi.org/10.3390/su141811566
Submission received: 26 August 2022 / Revised: 10 September 2022 / Accepted: 14 September 2022 / Published: 15 September 2022
(This article belongs to the Section Sustainable Forestry)
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Abstract

:
It is vital to promote the sustainable economic and social development and ecological culture prosperity of forest areas in various regions to scientifically and objectively understand the development status of forestry-ecological-culture industries in all provinces (districts and cities) of China. It is also important to clarify the advantages of industrial development in various regions. Based on the comprehensive consideration of economic, social, and political factors, the evaluation index system of forestry-ecological-culture industry, which includes industrial productivity, industrial influence, industrial and driving force, is constructed in this study. Furthermore, the development of forestry-ecological-culture industry in 31 provinces and regions of China from 2014 to 2019 is analyzed by cluster analysis. The analysis categorized the industries into four development types: very high level developed, high level developed, medium level developed, and low level developed according to the principal component score, which sums up the characteristics of various types of industrial development. The results show that the forestry-ecological-culture industry in China presents the spatial distribution of “east high and west low”, which is related to the difference in regional economic development level. Furthermore, the advantage of resource endowment is not clear, the gap between provinces and regions is large, and the overall development level of industry is relatively low. The findings of this study provide theory-based guidance and policy suggestions for improving the efficiency of industrial development and optimizing spatial distribution of diversified industrial development.

1. Introduction

In addition to shouldering the substantial responsibility of national ecological security, forestry also plays an important role in economic and social development and ecological civilization construction. Key state-owned forest industry enterprises are in a key stage in which pillar industries have not yet formed and the present period represents an important period of reform promotion. Since the launch of the national natural forest protection project in 1998, and the comprehensive logging ban in state-owned forest areas in 2014, the development strategy and form of state-owned forest areas have changed comprehensively and fundamentally [1]. Thus, the development direction of the forestry industry has begun to transform and adapt. The development mode of forestry industry has changed from wood production to ecological restoration and construction, and economic construction and improvement of people’s livelihood have become the key tasks of forest area development. Over the years, the forestry industry has had the characteristics of composite industries with diversified product categories, long industrial chain, and a wide range of industrial categories, while having three relatively perfect industrial systems, forming a composite system of “economy-society-ecology”. Scientific and rational utilization of forestry resources, adjustment of the industrial structure of forest areas, accelerated development of alternative industries, efforts to transform ecological value into competitive and development advantages, and taking the road of high-quality and green development have become the main development trends of forestry industry. As a part of the cultural industry, the ecological cultural industry is becoming the most potential employment space and emerging industry that benefits people. Therefore, an evaluation system of forestry-ecological-culture industry should be constructed, and the spatial distribution of its diversified development types should be clustered and analyzed. Furthermore, the positioning, advantages and disadvantages, and future development trends of forestry-ecological-culture industries in each province should be further clarified is of great significance.
Ecological cultural industry is an emerging cultural industry model in China, and is also a sustainable development industry. Deng Xianchao et al. believed that from the perspective of cultural function, the ecological cultural industry is the ecological culture form presented by the ecosystem as the basic carrier, which reflects the material relationship between man and ecology [2]. Furthermore, they consider it as a business system or an industry that provides the production of ecological cultural products and ecological cultural services. Zhang Wenna et al. believed that from the perspective of consumer communication, the ecological cultural industry is the industrial power that injects the ecological culture into the economic and social development [3]. Jiang Zehui et al. considered ecological culture as the mainstream culture in the era of ecological civilization [4]. They believed that the ecological cultural industry involves market-oriented, industrialized business activities which are guided by national policy and market, with the theme of reflecting the relationship between man and nature, and ecological culture as its creative source, reflecting the concept of ecological culture. Thus, these activities provide the public with the physical form of ecological cultural creative products and the ecological cultural services can be participated in and selected. Based on this, the scope of forestry-ecological-culture industry mainly includes forest cultural industry, bamboo cultural industry, tea cultural industry, flower cultural industry, wetland cultural industry, and ecological tourism, among other related industries. There are some specific industrial development models that combine industries, such as “ecological culture + forest ecotourism”, “ecological culture + flower tourism”, “ecological culture + exhibition and entertainment services”, “ecological culture + sports and fitness”, “ecological culture + leisure and wellness”, “ecological culture + catering”, “ecological culture + creative furniture industry”, “ecological culture + wood and bamboo crafts processing”, “ecological culture + jade processing”, “ecological culture + green product production and packaging”, “ecological culture + film and television publishing”, and “ecological culture + museum (popular education)”, among other such models.
The existing research on the evaluation of forestry industry is limited and has focused mainly on two aspects. The first aspect has been on the overall competitiveness of the forestry industry, such as the research by Feng Qinliang et al. [5]., Tian Yun et al. [6], Li Wei [7], Huang Bei et al. [8], Zhang Guanglai [9], Zhao Huijie [10], which used principal component analysis to study the comprehensive competitiveness level of the forestry industry. The second aspect has been on the evaluation and analysis of specific forestry alternative industries. For example, Zhang Xiaomei et al. used the multi-index comprehensive index model to evaluate the food industrial structure level and the degree of industrial agglomeration in northeast state-owned forest region [11]. Li Deli et al. used entropy power gray correlation analysis to construct coupled coordination model to comprehensively evaluate typical replacement industries in Heilongjiang forest area [12]. Ritchie and crouch (1999) and Enright (2004) used the competitiveness model to evaluate competitiveness in the tourism industry [13,14]. Timo (2005) used DEA and the model was used to put forward ways of improving ecological production efficiency [15]. Mark (2009) analyzed important factors for industrial production efficiency from the perspective of the forestry industry [16]. Peltoniemi (2013) studied the theoretical mechanisms of capacity development in the forestry industry and identified the main mechanism for the evolution of capacity in the forestry industry [17].
Researchers pay more attention to the choice of replacement industries, but for wood pulp and paper industry, research on forest tourism, ecological tourism, and other industries have only focused on industry competitiveness evaluation, lack of systematic evaluation of specific industrial development level, and rarely on the prediction of industry trends. In the empirical research on forestry industry evaluation, most studies are still limited to the evaluation of industrial competitiveness or the competitiveness of forestry clusters in a single large forestry province, and there are few comprehensive and holistic studies of each province.
Evaluation studies on cultural industries are more abundant. An evaluation index system of talent, technology, and inclusion was constructed for the first time from a creative economy perspective by Florida and cultural industry was evaluated [18]. Gibson discussed the influence of regional cultural industry efficiency on economic development [19]. Throsby measured the efficiency of cultural industry from the economic value created by cultural creative artists [20]. The evaluation of the cultural industry competitiveness in the domestic research includes studies on the competitiveness evaluation of cultural industry in Yangtze River Delta based on VRIO correction model [21], the competitiveness performance evaluation of Yellow River Basin from the perspective of comparative analysis [22], and the competitiveness evaluation of provincial cultural industry foreign trade based on diamond model [23]. Evaluation research on integrated development of cultural industry used the entropy method to evaluate the integrated innovation ability of cultural industry in each province to analyze the characteristics of provincial differences [24]. Evaluation research on the integrated development also focused on the benefits of cultural industry and tourism industry [25,26]. In addition, it also involves the evaluation research of the high-quality development level of the cultural industry in various provinces [27,28].
On the basis of clarifying the concept of ecological culture industry and the basic development model of industry, this study aims to draw on industry evaluation methods from prior research in the field. In this study, an evaluation system is constructed to examine the development level of the forestry ecological culture industry. The development of the forestry ecological culture industry is also clustered and analyzed. The key influencing factors of the development of the forestry ecological culture industry are summarized according to the local conditions and the characteristics of the industrial environment and resources. The study further aims to provide theoretical guidance and policy suggestions for improving the efficiency of industrial development and optimizing the spatial distribution of diversified industrial development. The findings of this study provide a key reference for sustainable development of the forestry industry in China and other countries worldwide. The research undertaken in this study encompasses 31 Chinese provinces (autonomous regions and municipalities) from 2014–2019.

2. Methods

2.1. Construction of an Index System

This paper, based on the framework of the evaluation system of China’s provincial and municipal cultural industry development constructed in the “China Provincial and Municipal Cultural Industry Development Index Report” of Renmin University of China, integrates the evaluation framework of national cultural industries in the Asia-Pacific region proposed by UNESCO [29], the pyramid model of cultural industries, and the diamond evaluation system. It combines the characteristics of China’s forestry-ecological-culture industries and the available data to innovatively construct an evaluation system for the development level of China’s provincial forestry-ecological-culture industries. The evaluation system includes three primary indicators of industrial productivity, industrial influence, and industrial driving force, and nine secondary indicators of ecological cultural resources, ecological cultural capital, human resources, economic impact, ecological impact, social impact, market environment, public environment, innovation environment and nine other secondary indicators (see Table 1). 27 measurement variables were selected to conduct empirical research on forestry-ecological-culture industry in 31 provinces (autonomous regions and municipalities) across China. The construction of the evaluation index system more prominently reflects the development law and industrial characteristics of the forestry-ecological-culture industry, and more scientifically quantifies the tangible resources of the ecological culture. The economic, social, and ecological benefits of the industry are more conducive to a comprehensive understanding of the actual level of forestry modernization development in various provinces, and enable discovering the advantages and disadvantages of forestry industry development.

2.2. Variable Selection

2.2.1. Industrial Productivity

The “industrial productivity” index mainly measures the input level of talent, capital, and production factors such as ecological and cultural resource endowment. According to the characteristics of forestry-ecological-culture industry, the industrial productivity index can be decomposed into ecological cultural resources, ecological cultural capital, and human resources. This paper refers to the construction of an evaluation index of forest park tourism development level by Chen Lijun et al., which characterizes forest cultural resources by forest accumulation, flower cultural resources by ornamental seedling production, and forest ecotourism resources by total forest park area [30]. Furthermore, the index objectively and directly reflects the current development strength as well as future development potential of ecological cultural industry in a province and city through resource endowment. Ecological cultural capital mainly reflects the fixed asset investment related to ecological and cultural industries, which is a key production factor and the final explanatory variable in determining economic growth.

2.2.2. Industrial Influence

The “industrial influence” index mainly measures the output level of cultural industries in each region at three levels: economic impact, ecological impact, and social influence. The economic impact mainly includes “wood handicrafts and wood cultural and sports goods manufacturing industry”, “forestry tourism and leisure service industry” and the output value of other industries that are directly driven to represent the labor productivity of forestry-ecological-culture industry. The per capita cost reflects the attractiveness and participation of the ecotourism industry in each region [31]; Ecological influence mainly reflects the ecological benefits of forestry-ecological-culture industry, generally speaking, the richer the forestry resources are, the more significant its ecological benefits [32]. Social influence mainly refers to the impact on citizens or consumers through forestry-ecological-culture products and services, including the satisfaction of people’s ecological cultural spiritual needs and material needs, the promotion of ecological civilization awareness, cultural participation and experience, acceptance, and inclusion, among other factors.

2.2.3. Industrial Driving Force

The “industrial driving force” index mainly reflects the environment and attitude of provinces (regions and municipalities) in developing forestry-ecological-culture industry, and measures the external environment of the industry from three aspects of industrial demand, public environment, and innovation environment. Industrial demand is mainly represented by market demand to consider the uncontrollable factors in the social and economic environment of enterprises’ production and operation activities. Public environment mainly refers to the development environment provided by the public administrative departments and service departments for the industry. Within the forestry-ecological-culture industry, cultural industry is an intelligence-intensive industry; excellent human resources provide intellectual and creative support for the development of the cultural industry. The level of science and technology development, financing ability, and staff with senior titles are important indicators of the innovation environment. Therefore, the innovation environment for the development of forestry-ecological-culture industry, mainly considers factors such as information technology input and innovation ability.

2.3. System Cluster Analysis

2.3.1. Data Sources

In this paper, 31 provinces (excluding Hong Kong, Macao, and Taiwan) were selected for the study from 2014–2019. The data were from China Forestry Statistical Yearbook 2014–2017 [33], China Forestry and Grassland Statistical Yearbook 2018–2019 [34]; 2014–2019, China Statistical Yearbook [35], The Statistical Yearbook of Chinese Cultural Relics [36], China Statistical Yearbook on Culture and Related Industries [37], and statistical Yearbook of various provinces [38], supplemented by the statistical bulletin of national economic and social development of each province [39]. Individual missing data were adjusted by mean values, considering the completeness, availability, and continuity of the data.
The data sources of the specific variables are: “Tertiary index” of “Market demand”, root in China Statistical Yearbook, China Statistical Yearbook on Culture and Related Industries, statistical Yearbook of various provinces, supplemented by the statistical bulletin of national economic and social development of each province; “Provincial cultural expenses accounted for the proportion of fiscal expenditure” and “Annual per capita cultural undertaking expenses of provinces” of “Public environment”, root in The Statistical Yearbook of Chinese Cultural Relics, China Statistical Yearbook on Culture and Related Industries. In addition to, all root in China Forestry Statistical Yearbook, China Forestry and Grassland Statistical Yearbook.

2.3.2. Research Method

Based on the literature review and industry characteristics, this paper adopts the theory of industrial competitive advantage to provide a new theoretical analysis paradigm and a relatively complete research framework for the comprehensive evaluation of industrial development level from the perspective of industrial economics. At the same time, ecological cultural industry is highly related to cultural industry and ecological civilization. Therefore, the evaluation index system of cultural industry and the index system that is highly related to ecological cultural industry can provide some reference. Principal component analysis (PCA) method and systematic clustering method were also used for the empirical study. PCA method is often used in the comprehensive evaluation of multiple indicators, especially in the study of quantitative analysis of the competitiveness of forestry industry. Due to the large number of original variables in this study and the problem of multicollinearity, PCA can overcome the information overlap and calculation complexity of variables caused by the geometric growth of dimension, and reduce the interference of high correlation to the data analysis results.

2.4. Sample System Clustering

This paper, the commonly used systematic clustering analysis method was selected to conduct the hierarchical clustering study of Chinese forestry ecological culture industry, and the most similar samples were clustered into one category, and the data processing was completed using SPSS statistical software. According to the sample data, the inter-group distance is mainly the intergroup connection (class averaging method), and the sample distance is the square Euclidean distance, and the hierarchical diagram is shown in Figure 1. The hierarchical diagram is the process diagram of the cluster analysis. The number on the left side of the diagram is the region serial number, and each region becomes its own class, and the nearest region clusters in turn, and finally all the regions gather into one category, and gradually “truncated” from right to left, when the number of classifications is 4, the classification results are more reasonable, which is basically consistent with the actual situation of the forestry industry in each province, the final clustering results are obtained. Therefore, China 31 provinces (autonomous regions and municipalities) is divided into very high level developed, high level developed, medium level developed and low level developed four development types, to further analyze the diversification of development type of spatial distribution, explore the development law of forestry ecological culture industry, formulate regional economic development plan, the implementation of regional industrial development differentiation decision provides a scientific basis.

3. Results and Discussion

3.1. Extraction of the Main Indicators

According to the basic principles of principal component analysis (PCA), the idea of dimension reduction (linear transformation) was used under the premise of little information loss from multiple indicators into several unrelated indicators. Each principal component is a linear combination of the original variable, and each principal component is unrelated. However, it must retain more than 90% of the original variable information. The principal component has superior performance to the original variable to simplify the system structure, and grasp the essence of the problem. The PCA method was used to standardized process the raw data and obtain the total variance interpretation table (Table 2). The composite variables were ranked according to the magnitude of the original information contained, i.e., the ‘p’th variance contribution corresponds to the ‘p’th principal component. The contribution rate of each component reduced successively, and 12 principal components were extracted to explain 85.001% of the total variance of the original variables, which was sufficient to represent 27 original variables to evaluate the forestry-ecological-culture industry. The comprehensive evaluation index of forestry-ecological-culture industry was calculated.

3.2. Clustering Results

Based on the clustering analysis results, combined with the reality of forestry-ecological-culture industry development, this paper divides the 31 provinces (regions and municipalities) into very high level developed, high level developed, medium level developed and low level developed four development types. Furthermore, this information is combined with the main component comprehensive score, the characteristics of various types of industry development are summarized, and the spatial distribution of diversified development type is analyzed. The corresponding provinces (autonomous regions and municipalities) of each category are shown in Table 3. As a key subdivision of forestry-ecological-culture industry, although the evaluation indicators of development level are different, the overall evaluation results are basically similar to the development of national forest park tourism; the southern forest area and southwest forest area are the fastest followed by the northeast forest area and north China forest area, and the northwest forest area is relatively poor. The southern forest area includes the Qinling Mountains, the Huaihe River, and the east of the Yunnan-Guizhou Plateau. The southwest forest region includes the Hengduan Mountain region at the border of Sichuan, Yunnan and Tibet provinces and regions, as well as the southern slope of the Himalayas in southeastern Tibet. The northeast forest region includes the Greater Hinggan Mountains, Lesser Khinggan Mountains and Changbai Mountains. The forest area of North China includes the areas north of the Qinling Mountains and the Huaihe River and south of the Great Wall. The northwest forest areas include Shaanxi, Gansu, Ningxia, Qinghai, Xinjiang and western Inner Mongolia.
Very high level developed type (F > 1.02, In 2019). Hunan province has entered the first echelon for three consecutive years, with a relatively high level of industrial development. The regional characteristics of this type are its innate geographical advantages, solid economic foundation, excellent ecological resource conditions, superior infrastructure conditions, and continuous maintenance of good momentum of development. In contrast, the investment in forest park construction up to 19,699 million yuan, forestry information construction is the largest, about 23 million yuan (In 2019), and the proportion of forestry tourism and leisure industry reception is 69.15% in an absolute leading position (In 2019). This proves that the index system established in this paper is more scientific, and can realistically and objectively reflect the current development status of forestry-ecological-culture industry in the province.
High level developed type (0.30 < F < 0.618, In 2019). The provincial industrial development of this type is relatively stable, mainly concentrated in the provinces with good industrial development. As confirmed in other related studies, Beijing, Shanghai, Jiangsu, Zhejiang, and Guangdong are all in the “strong” development category in the national provincial and municipal cultural industry development Index cluster analysis of 2019 [40]. The ecological-economic development level of Zhejiang and Guangdong provinces is divided into the first development type, and classified as the second category in the cluster analysis of forestry sustainable development capability [41]. The regional characteristics of this type are the higher comprehensive score, the average comprehensive score for the provinces in this type was 0.452. The advantages of ecological resources are conspicuous, and the related output value of forestry-ecological-culture industry accounts for 0.4% proportion of the provincial forestry industry. In this development type, the investment in forestry informatization construction is emphasized.
Medium level developed type (−0.375 < F < 0.03, In 2019). Based on the clustering results for six consecutive years, it can be seen that the balance degree of forestry ecological and cultural industry has been significantly improved, and the number of provinces in the medium level developed type has increased. The regional characteristics of this type are that the investment in forestry tourism, leisure and health care, and ecological resource reserve are still in the upper-level area, with strong financing ability and certain industrial development potential. Some of the provinces are ranked low mainly because there is no location advantage, the traffic is not convenient, the natural environment is relatively harsh, and the industrial development environment is not ideal. Therefore, the social benefits and influence of the forestry ecological culture industry are not clear, and the overall development level is low.
Low level developed type (F < −0.375, In 2019). In recent years, the only province in this type is Hainan province (comprehensive score is −0.618). According to the data results, the main reasons for the low ranking of Hainan province are that several investment indicators are low, and the related output value of forestry-ecological-culture industry accounts only 0.07% proportion of the total output value of forestry industry. The main developing industries are Huanghua pear industry, oil tea industry, and special economic forestry industry, among few other industries.
The comprehensive score of forestry-ecological-culture industry development increased from the highest 0.76 in 2014, to the highest 1.02 in 2018. From 2014 to 2019, the transformation effect of the forestry industry was very obvious, showing a gradual upward trend on the whole.

4. Conclusions

By constructing the evaluation index system of forestry-ecological-culture industry, this paper clusters the development of forestry-ecological-culture industry in 31 provinces (cities and regions) in 2014–2019, analyzes the spatial distribution of diversified development types, and draws the following main research conclusions:
(1) The clustering results are divided into four development types: very high level developed, high level developed, medium level developed, and low level developed. Furthermore, the type of each province is determined, and the development characteristics of each type of industry are summarized, which reflects the development status of provincial forestry ecological culture industry accurately and objectively. The results show that the provincial forestry-ecological-culture industry development is basically consistent with the forestry industry development, which is associated with regional economic development level differences. The overall results point to “east high west low” spatial distribution and “east strong west weak, south high north low” unbalanced development pattern, and it is roughly consistent with the comprehensive level of cultural industry, which conclusively confirms the logical mechanism that economic development is the basis of cultural development.
(2) At present, the cultural industry is still in a state of agglomeration driven by cultural and natural resources and consumer market demand. The results of the cluster analysis for six consecutive years showed that there was a certain spatial aggregation. The development of forestry ecological culture industry among different provinces is unbalanced and the gap is large. In the field research, it was found that the provincial geographical advantages, local economic development level, human resources, transportation and other infrastructure played an important role in the development of forestry-ecological-culture industry. Therefore, it is particularly important to pay attention to the accumulation of the background conditions of ecological cultural industry, give full play to the advantages of ecological resource endowment, optimize the industrial development pattern, and realize the improvement of the overall level of industrial development.
(3) The driving force of industrial development is insufficient. For the provinces in which economic development lags behind the ecological situation, although the driving force of the cultural industry is continuously improving, it is far from enough to rely only on the investment in the region, and people’s growing ecological needs and personalized spiritual and cultural needs have not been well met. When formulating industrial development policies, it is necessary to consider the differences in development levels between regions and focus on characteristic industries to avoid disorderly development and homogeneous competition.

Author Contributions

Conceptualization, L.H. and Y.C.; methodology, L.H. and Y.C.; software, L.H.; formal analysis, G.W.; data curation, L.H.; writing—original draft preparation, L.H.; writing—review and editing, Y.C. and G.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Heilongjiang Province Philosophy and Social Science Research Planning Project of China (Grant No. 19GLE324).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Yukun, C. Development trend of state-owned forest area reform and natural forest protection project. Issues For. Econ. 2020, 40, 561–562. [Google Scholar]
  2. Xianchao, D.; Zhangwen, Y. Discuss the Development of Ecological Culture Industry in Jiangxi. Lit. Circ. CPC Hist. 2015, 22, 75–76. [Google Scholar]
  3. Wenna, Z.; Yajun, S. The SWOT Analysis of Eco-Cultural Industry in Beijing Mountain. Chin. Agric. Sci. Bull. 2011, 27, 151–154. [Google Scholar]
  4. Jiang, Z. Mainstream Culture of Ecological Civilization ERA—An Overview of China’s Eco-Culture System Study; People’s Publishing House: Beijing, China, 2013; ISBN 978-7-01-012852-8. [Google Scholar]
  5. Qinliang, F.; Fanding, T. Econometric analysis on forestry industry competitiveness in Guangxi by PCA. Guangdong Agri. Sci. 2012, 39, 163–167. [Google Scholar]
  6. Yun, T.; Junbiao, Z.; Bo, L. Analysis on the Spatial Differences of Comprehensive Competitiveness of Forestry Industry in China. J. Arid. Land Resour. Environ. 2012, 26, 8–13. [Google Scholar]
  7. Wei, L.; Zhifang, W.; Lijuan, Z. An Empirical Study on the Development Level of Chinese Forestry Industry. Com. Res. 2012, 6, 204–209. [Google Scholar]
  8. Bei, H.; Yu, W. Study on the Competitiveness of Industrial Cluster in Forestry Industry. Chin. Pop. Res. Env. 2011, 21, 554–557. [Google Scholar]
  9. Guanglai, Z.; Lu, L.; Wenmei, L. Principal component analysis of China’s forestry industry competitiveness. J. Zhejiang A&F Univ. 2016, 33, 1078–1084. [Google Scholar]
  10. Huijie, Z.; Jing, Z. Study on the Development Level of Yunnan Forestry Modernization by Clustering Analysis. For. Eco. 2018, 40, 92–97. [Google Scholar]
  11. Xiaomei, Z.; Si, C. Analysis of Forest Food Industry Structure Level and Spatial Agglomeration Characteristics in Northeast State-Owned Forest Regions. Issues For. Econ. 2019, 39, 512–519. [Google Scholar]
  12. Deli, L.; Ying, C. Evaluation on the Development of Substitute Industries in Heilongjiang Forest Industry Region. Issues For. Econ. 2019, 39, 231–237. [Google Scholar]
  13. Crouch, G.I.; Ritchie, J.R.B. Tourism, competitiveness, and societalprosperity. J. Bus. Res. 1999, 44, 137–152. [Google Scholar] [CrossRef]
  14. Enright, M.J.; Newton, J. Tourism destination competitiveness: Aquantitative approach. Tour. Manag. 2004, 25, 777–788. [Google Scholar] [CrossRef]
  15. Timo, K.; Kortelainen, M. Measuring Ecoefficiency of Production with Data Envelopment Analysis. J. Ind. Ecol. 2005, 9, 59–72. [Google Scholar]
  16. Mark, R.; Kant, S. The Influence of Context on Deliberation and Cooperation in Community-Based Forest Management in Ontario, Canada. Hum. Ecol. 2009, 37, 547–558. [Google Scholar]
  17. Peltoniemi, M. Mechanisms of Capability Evolution in the Finnish Forest Industry Cluster. J. For. Econ. 2013, 19, 190–205. [Google Scholar] [CrossRef]
  18. Florida, R. The Rise of the Creative Class: And How It’s Transforming Work, Leisure, Community and Everyday Life; Basic Books: New York, NY, USA, 2002. [Google Scholar]
  19. Gibson, C. Cultural Economy: Achievements, Divergences, Future Prospects. Geogr. Res. 2012, 50, 282–290. [Google Scholar] [CrossRef]
  20. Throsby, D. The Economics of Creativity: Economic and Cultural Value in the Working Lives of Creative Artists; Barjesteh van Waalwijk van Doorn: Eijsden, The Netherlands, 2001. [Google Scholar]
  21. Qiyang, Z.; Fuhua, N.; Haiping, Z. Evaluation of Cultural Industry Competitiveness in Yangtze River Delta Based on a Revised Model of VRIO. Aer. Deliv. Res. Dev. 2021, 40, 44–49. [Google Scholar]
  22. Hongjie, H. Performance Evaluation of Cultural Industry Competitiveness and Regional High Quality Development—Empirical Analysis Based on 8 Provinces in the Yellow River Basin. J. Henan Norm. Univ. (Philos. Soc. Sci.) 2020, 47, 38–44. [Google Scholar]
  23. Jianghui, Y.; Lijuan, Y. Evaluation of Foreign Trade Competitiveness of Provincial Cultural Industry Based on Diamond Model. Stat. Decis. 2019, 35, 58–61. [Google Scholar]
  24. Jinhua, G.; Shufen, G. Construction and Evaluation of the Evaluation Index System of Cultural Industry Integration and Innovation Ability. Stat. Decis. 2019, 35, 62–65. [Google Scholar]
  25. Huaguang, Y.; Jiujie, Q.; Yungui, Y.; Huanru, W. The Study of Developing Benefit Evaluation between Cultural Industry and Tourism Industry in the Wuling Mountain Area. J. Beijing Union Univ. (Humanit. Soc. Sci.) 2016, 14, 79–88. [Google Scholar]
  26. Bing, H.; Xiaoqian, Z. Assessment and Evaluation of Integration of the Culture Industry and Tourism Industry in Yangtze River Delta. Econ. Geogr. 2015, 35, 211–217. [Google Scholar]
  27. Yongjun, X.; Dengming, S. Evaluation and Countermeasures of Provincial Cultural Industry Competitiveness in China. Resour. Dev. Mark. 2015, 31, 301–304. [Google Scholar]
  28. Jiang, G.; Lili, G. Evaluation and Improvement of China’s InterProvincial Cultural Industry Competitiveness—An Empirical Analysis Based on Data in 31 Provinces and Municipalities. Fujian Trib. 2012, 8, 5–11. [Google Scholar]
  29. Peng, Y. Report on Development Index of Cultural Industries in Chinese Provinces, Autonomous Regions and Municipalities; China Renmin University Press: Beijing, China, 2018; ISBN 978-7-300-25580-4. [Google Scholar]
  30. Lijun, C.; Zhifang, W.; Jianghua, G. Study on the Evaluation of Tourism Development Level and Its Spatial-Temporal Evolution of Forest Parks in Chinese Provinces. For. Econ. 2020, 42, 70–82. [Google Scholar]
  31. Qi, L.; Guanghai, T. Analysis of Regional Tourism Industry Development Level and Its Core Competitiveness—Take Shaanxi Province as an Example. Stat. Decis. 2009, 15, 95–96. [Google Scholar]
  32. Qiangsheng, M.; Yan, L.; Xiufen, L. Study on the Sustainable Development of Forestry in Clustering Analysis. Sci. Technol. Manag. Res. 2015, 35, 109–113. [Google Scholar]
  33. The State Administration of Forestry. China Forestry Statistical Yearbook; China Forestry Publishing House: Beijing, China, 2014–2017. [Google Scholar]
  34. National Forestry and Grassland Administration. China Forestry and Grassland Statistical Yearbook; China Forestry Publishing House: Beijing, China, 2018–2019. [Google Scholar]
  35. Compiled by National Bureau or Statistics of China. China Statistical Yearbook; China Statistics Press: Beijing, China, 2014–2019. [Google Scholar]
  36. Ministry of Culture, RC. The Statistical Yearbook of Chinese Cultural Relics; National Library of China Publishing House: Beijing, China, 2014–2019. [Google Scholar]
  37. Compiled by Department of Social, Science and Technology, and Cultural Statistics National Bureau of Statistics of China Cultural Reform and Development office Publicity Department of CPC Central Committee. China Statistical Yearbook on Culture and Related Industries; China Statistics Press: Beijing, China, 2014–2019. [Google Scholar]
  38. Statistical Publications Published by the National Bureau of Statistics (2014–2019). Available online: http://www.stats.gov.cn/tjsj/tjcbw/ (accessed on 1 April 2021).
  39. The National Annual Statistical Bulletin Issued by the National Bureau of Statistics (2014–2019). Available online: http://www.stats.gov.cn/tjsj/tjgb/ndtjgb/ (accessed on 1 April 2021).
  40. Lang, Y. The Annual Development Report of Chinese Cultural Industries 2019; Peking University Press: Beijing, China, 2021. [Google Scholar]
  41. An, C.; Jingjing, W.; Yang, S.; Hongsong, T. Study on Construction and Application of Evaluation Index System for Sustainable Development of Urban Social Forestry. For. Econ. 2019, 41, 104–111. [Google Scholar]
Sustainability 14 11566 g001a 550Sustainability 14 11566 g001b 550
Figure 1. Cluster pedigree diagram from 2014–2019. Note: The horizontal axis is the interblock space; the vertical axis number represents the serial number of each province.
Figure 1. Cluster pedigree diagram from 2014–2019. Note: The horizontal axis is the interblock space; the vertical axis number represents the serial number of each province.
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Table
Table 1. Evaluation indexes measuring the development of eco–culture forestry.
Table 1. Evaluation indexes measuring the development of eco–culture forestry.
Primary IndexSecondary IndexTertiary Index
Industrial productivityEco–cultural resourcesForest Stock (ten thousand m3)
Yield of ornamental seedlings (ten thousand pieces)
Total area of Forest Park (ha)
Eco–cultural capitalForestry Tourism, Leisure and health care annual investment (ten thousand yuan)
Annual investment in Forestry Science and technology, education, rule of law and publicity (ten thousand yuan)
Annual National Investment in Forest Park (ten thousand yuan)
Human resourcesForest Park Social Tourism Practitioners (number of persons)
Total number of staff and workers employed in forest parks (number of persons)
Number of tour guides among Forest Park employees (number of persons)
Industry influenceEconomic impactRelative output value of eco–cultural forestry industry accounts for the proportion of the total output value of forestry industry (percentage)
Annual per capita expenditure of forestry tourism and leisure industry (yuan)
Annual per capita income of forest park tourists (ten thousand yuan)
Ecological impactIncrease in Forest Park area compared with the previous year (ha)
Number of forest parks increased from the previous year (number)
Forest Park area of the province (region, city) proportion of land area (percentage)
Social impactForestry tourism trips accounted for the total proportion of provincial (regional, municipal) tourism (percentage)
Forest Park tourism reception, total number of provincial (regional, municipal), total number of tourists proportion (percentage)
Proportion of overseas tourists received by Forest Park in the number of international tourists in the province (region, city) (percentage)
Industry driving forceMarket demandAnnual per capita cultural consumption expenditure of provincial (regional and municipal) residents (yuan)
Provincial (regional and municipal) per capita cultural consumption accounts for the proportion of per capita disposable income (percentage),
Per capita cultural consumption in provinces (autonomous regions and municipalities) accounts for per capita consumption expenditure (percentage)
Public environmentForest social infrastructure including road construction annual total (ten thousand yuan)
Provincial (regional and municipal) cultural expenses accounted for the proportion of fiscal expenditure (percentage)
Annual per capita cultural undertaking expenses of provinces (regions and cities) (yuan)
Innovation environmentAnnual investment in forestry informatization (ten thousand yuan)
Forest Park annual self-financing, investment (ten thousand yuan)
Number of senior professional and technical personnel in forestry workstations and administrative personnel in prefecture (county, city) (number of persons)
Table
Table 2. Interpretation of the total variance.
Table 2. Interpretation of the total variance.
ComponentInitial EigenvalueExtraction of the Sum of Load Squares
Total Contributing Rate of Variance %Contributing Rate of Cumulation %TotalContributing Rate of Variance %Contributing Rate of Cumulation %
14.9918.48118.4814.9918.48118.481
23.80314.08432.5653.80314.08432.565
32.80310.38242.9462.80310.38242.947
42.2618.37251.3192.2618.37251.319
51.7526.4957.8091.7526.4957.809
61.4885.5163.3191.4885.5163.319
71.3695.07268.3911.3695.07268.391
81.0944.0572.4411.0944.0572.441
91.0513.89276.3331.0513.89276.333
100.8943.31279.6450.8943.31279.645
110.7582.80882.4540.7582.80882.454
120.6882.54785.0010.6882.54785.001
130.6382.36387.364
140.5191.92489.287
150.5051.86991.156
160.3981.47292.628
170.3641.3593.978
180.3091.14595.123
190.291.07496.197
200.2721.00697.203
210.1940.7297.923
220.1650.6198.532
230.1540.57299.104
240.0960.35599.46
250.0770.28499.744
260.0560.20699.949
270.0140.051100
“Component”—the principal component serial number; “Contributing rate of variance %”: The covariance matrix was calculated to derive the principal component variance contributing rate; “Contributing rate of cumulation %”: Accumulated contributing rate of principal component one by one.
Table
Table 3. Clustering results of forestry-ecological-culture industries in 31 provinces (regions and municipalities), 2014–2019.
Table 3. Clustering results of forestry-ecological-culture industries in 31 provinces (regions and municipalities), 2014–2019.
Development TypesIn 2014In 2015In 2016In 2017In 2018In 2019
Very high level developed typeGuangdong, Beijing, JilinGuangdong, Beijing, JilinGuangdong, JilinJilin, Sichuan, Guangdong, Hunan, Beijing, Zhejiang, JiangsuHunan, Guangdong, Zhejiang, Sichuan, BeijingHunan
High level developed typeHunan, Jiangsu, Zhejiang, Shanghai, Sichuan, Heilongjiang, Guizhou, ShandongJiangsu, Zhejiang, Guizhou, Hunan, Shanghai, Sichuan, Nei Monggol, Shandong, HeilongjiangBeijing, Zhejiang, Jiangsu, Hunan, Sichuan, Guizhou, Shanghai Shanghai, Guizhou, Nei Monggol, Guangxi, Jiangxi, HeilongjiangShanghai, Jiangsu, Heilongjiang, Guangxi, Guizhou, Nei Monggol, Hubei, Shaanxi, Shandong, ChongqingGuangdong, Zhejiang, Beijing, Jiangsu, Sichuan, Shanghai
Medium level developed typeNei Monggol, Chongqing, Jiangxi, Henan, Shaanxi, Qinghai, Hebei, Fujian, Liaoning, Shanxi, Hubei, Ningxia, Xinjiang, Guangxi, Yunnan, Gansu, TianjinChongqing, Jiangxi, Shaanxi, Ningxia, Henan, Hebei, Liaoning, Hubei, Shanxi, Fujian, Xinjiang, Yunnan, Qinghai, China, Guangxi, Gansu, TianjinHeilongjiang, Nei Monggol, Shandong, Shaanxi, Hebei, Jiangxi, Ningxia, Chongqing, Liaoning, Hubei, Yunnan, Henan, Fujian, Xinjiang, Shanxi, Qinghai, Guangxi, Gansu, Anhui, TianjinHubei, Shandong, Shaanxi, Chongqing, Shanxi, Liaoning, Henan, Hebei, Yunnan, Qinghai, Gansu, Ningxia, Tianjin, Xinjiang, Fujian, AnhuiNingxia, Hebei, Liaoning, Fujian, Guangxi, Tianjin, Shanxi, Jilin, Gansu, Gansu, Henan, Xinjiang, Qinghai, Yunnan, Anhui, TibetHeilongjiang, Nei Monggol, Hubei, Jilin, Jiangxi, Chongqing, Shandong, Shaanxi, Fujian, Guangxi, Tibet, Shanxi, Qinghai, Ningxia, Yunnan, Yunnan, Guizhou, Tianjin, Liaoning, Henan, Hebei, Gansu, Anhui, Xinjiang
Low level developed typeTibet, Anhui, HainanAnhui, Tibet, HainanXizang, HainanXizang, HainanHainanHainan
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Huang, L.; Wu, G.; Cao, Y. Spatial Distribution of Development Types of Forestry-Ecological-Culture Industries in Chinese Provinces. Sustainability 2022, 14, 11566. https://doi.org/10.3390/su141811566

AMA Style

Huang L, Wu G, Cao Y. Spatial Distribution of Development Types of Forestry-Ecological-Culture Industries in Chinese Provinces. Sustainability. 2022; 14(18):11566. https://doi.org/10.3390/su141811566

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Huang, Luyu, Guochun Wu, and Yukun Cao. 2022. "Spatial Distribution of Development Types of Forestry-Ecological-Culture Industries in Chinese Provinces" Sustainability 14, no. 18: 11566. https://doi.org/10.3390/su141811566

APA Style

Huang, L., Wu, G., & Cao, Y. (2022). Spatial Distribution of Development Types of Forestry-Ecological-Culture Industries in Chinese Provinces. Sustainability, 14(18), 11566. https://doi.org/10.3390/su141811566

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