The Network Evolution and Influencing Factors of the Global Cultural Printed Material Trade

Abstract

Understanding the global trade network in the printing industry is crucial for promoting sustainable development and cultural exchange and knowledge dissemination. However, the extant literature does not reveal the contours of the global cultural printed material trade network. This paper uses a social network analysis and QAP analysis to explore the global printing industry trade network pattern. The aim of this paper is to discern the core and emerging nodes and explore the evolutional characteristics on the network spatial linkage and country role. The results show the following: ① The printing industry’s global trade network is growing increasingly intricate, with trade links between nations (regions) becoming closer, the network’s connectivity steadily improving, and the hierarchical structure becoming more apparent. ② Germany, France, and Belgium are important intermediary bridges. The “circle of friends” in the trade of cultural products has a growing effect, and China can more easily establish close ties with Southeast Asia, Northern Europe, and Central and Eastern Europe. ③ The industrial chain and geographical proximity are the primary factors in the formation of the trade network. Economic proximity and political proximity significantly and positively contribute to the formation of the trade network, while institutional stability gradually plays a weaker role. As for cultural proximity, a common language and colonial relationship will positively contribute to the formation of a network, while immigrants have no obvious impact. Digital technology is becoming an “emerging force”. Additionally, this paper extends sustainable policies and recommendations for the global cultural trade.

1. Introduction

As a downstream product of the printing industry with the attributes of the processing industry and cultural industry, cultural printed material is the realization form of an important carrier of the cultural industry. Due to the technological innovation of the printing industry, the entire industry has been developed in the direction of high quality, precision, and sophistication, which has triggered the transformation and upgrading of the printing industry to the three-in-one attribute of technology–creativity–culture [1,2]. Cultural printed materials not only have a rich cultural value, but also are an important medium of the inheritance and communication of culture. Cultural printed materials are the basis of knowledge sharing and dissemination, and they are constantly integrated with digitalization, providing an important support for the rapid dissemination and global diffusion of knowledge and information [3]. With the development of society and the progress of information and communication technology, the printing industry continues to develop and grow, and has gradually formed an industrial economic system with intellectualization and informatization as the main content and can affect international competitiveness. Unlike conventional industrial product trade, the trade of cultural printed material contributes to spread the diversified values of mankind, weaken the bondage of cultural barriers, and encourage cultural mutual learning. Thus, cultural printed material has emerged as a key element of national soft power [4,5]; it is not only a labor-intensive industry, but also a cultural and creative industry. The raw materials required for its upstream production include ink, base paper, and printing equipment (printing machine), which are closely related to the manufacturing industry; products produced in the midstream, such as plastic packaging and paper bag, are typical of production and the living service industry; the application of terminal products is more complex, which is roughly divided into three categories: food packaging, book and periodical publishing, and clothing and daily chemical products (this classification of printing products comes from a research report by Zhiyanzixun, and the title is the analysis of China’s printing industry chain in 2022: https://www.chyxx.com/industry/1144931.html [last accessed 20 November 2024]). Therefore, the healthy and sustainable development of the printing industry is not only related to the needs of the economic level, but also related to the interaction of the spiritual level. The trade of cultural printed material not only contributes to the dissemination and identification of cultures between countries, but also brings benefits to the local economy, especially to promote the development of cultural and creative industry. At the same time, cultural printed material plays a crucial role in the field of education, and studying its trade network can contribute to the effective distribution and circulation of educational resources, especially to enhance the educational opportunities of Global South countries. In the long term, it will promote the sustainable development of the social economy.

In 2021, global printing sales surpassed $760 billion (these data are from the report of the market prospective and investment strategy planning in the China printing industry (2024–2029) by Forward Business Information Co., Ltd., Shenzhen, China). In East Asia, emerging countries such as China and South Korea are actively implementing the “going global” strategy of culture to promote the global dissemination of culture through cultural trade and strive to introduce various cultures to the international market [6]. This initiative seeks to establish a nation characterized by a flourishing cultural landscape through the advancement of cultural trade [7]. According to the data of the Chinese Commerce Ministry, in 2021, the total value of China’s foreign culture trade exceeded $200 billion, an increase of 38.7 percent year-on-year, of which the import and export value of cultural products exceeded $150 billion, an increase of 43.4 percent. The import and export of China’s printing industry involves 230 countries and regions on five continents. Through the trade with all continents around the world, China’s printing industry has achieved close ties and interactions with economies in different regions, promoting the profound reshaping of the global cultural printed material trade network. Nevertheless, the cultural printing industry is still closely related to the industrial base, industrial chain, and social and cultural openness of different countries. Therefore, what is the posture of the global trade network of the cultural printing industry? It is not only related to the development of a country’s economic trade, but also linked to geopolitics and international relations. However, the existing research on cultural trade is lacking in the exploration of the structural evolution of its network on a global scale, and the research on the sustainable development of the cultural industry trade that is increasingly exerting global influences is obviously insufficient.

The study of the international trade system from the perspective of the network began with Serrano’s study of the international trade network; it is found that the “small world” trait and a high concentration are the prominent characteristics of the international trade network [8]. Thereafter, some studies have investigated the topological structure and temporal evolution characteristics of the world trade network utilizing a weighted network analysis, and found that the countries with close trade relations are comparatively concentrated [9]. Some Chinese scholars pointed out that the global commodity trade has a strong correlation with the economic scale and influence of countries [10]. The existing international trade network research has trade network research on a certain type of resources or products of a country [11,12]; at the same time, it also studies the characteristics of the product trade structure in a certain region from the regional perspective [13,14]. In addition, it explores the relationship between the Belt and Road trade network and the global trade network from the local and global perspective, and reveals the hierarchical grouping law of the global trade network [15]. Therefore, the study of the global trade network is inseparable from the role of countries, regions, and even localities.

Specific to cultural printed materials, a large amount of literature focuses on digital technology applications, industrial clusters, and intelligent 3D and 4D printing technology [16,17,18]. Studies related to the trade of cultural products have revealed that a few large countries have exerted a general cultural influence on the rest of the world through the export of films, music, books, and periodicals [19], and have argued that the export of these cultural products can indirectly influence the politics of other countries (regions) [20]. Take China’s film industry as an example: Vlassis finds that the cultural industry trade plays a driving role in enhancing the soft power of emerging powers [21]. Thus, unlike energy [22], agricultural products, and manufactured goods [23,24], cultural printed material trade has multiple attributes, involving not only a trade in products, but also geopolitics, cultural ties, and technological diffusion [25,26]. Then, is the pattern of the cultural printed material trade network and its influencing factors directly related to these factors? Based on the above assumptions, this study attempts to explore the global trade network of cultural printed material through a complex network analysis, and clarify the hierarchical status and role of cultural printed material in different countries in the trade network. In the analysis of influencing factors, the analysis of politics, culture, technology, institution, and other factors is added. Following the validation of the assumptions, the policy recommendations on the development of global cultural printed material trade are put forward. This study can not only promote the improvement of the trade level within the cultural printed material industry, but also promote global cultural communications from the national politics and cultural environment affecting the external cultural printed material industry, which is the basis of social and cultural sustainable development and has reference significance for the cultural development strategies of different countries.

The sustainability of cultural exchanges implies that such activities can preserve their dynamism and impact throughout the long-term developmental process, thereby ensuring that cultural exchanges remain sustainable and robust, which encompasses the depth, breadth, and frequency of international cultural exchange activities. Among them, the cultural printed material trade network serves as a direct indicator of the sustainability of cultural exchanges. Printed material contributes to the dissemination of various types of culture, knowledge, and technology. The cultural printed material trade indicates the long-term viability of worldwide cultural exchanges, and the dynamics and evolution of the trade network can be used to describe the convenience of global cultural and educational development. Consequently, this research examines the evolution of its network and the factors influencing it to enhance the depth and breadth of the global cultural exchange, thereby ensuring the sustainability of cultural exchanges. The evolution of the network demonstrates the processes and outcomes of global cultural exchanges, and investigating the causes influencing these processes and outcomes is the foundation for maintaining the level of global cultural exchanges and achieving common cultural prosperity. The aim of this paper is to create a favorable socio-cultural environment for sustainable development from a global trade perspective.

The extant studies lack a global perspective on the trade in cultural printed material, focusing on trade competitiveness, trade development and countermeasures, trade efficiency, and trade potential. Moreover, most of the research on the printing industry stays on the analysis of the economic output value related to cultural printed materials, and has not yet noticed the importance of the cultural attributes of the downstream cultural printed products within the printing industry, and is less likely to explore the value of the trade in cultural products from the geographical perspective. The influencing factors on the trade of cultural products have neglected the role of the industrial chain and the attributes of cultural products. Certain research has indicated that a social network analysis can elucidate the specific configuration of global trade networks. The Quadratic Assignment Procedure (QAP), the Exponential Random Graph Model (ERGM), and various other methodologies can elucidate the influencing factors that affect both the formation and maintenance of trade network relationships. In this research, we conduct a comprehensive analysis of both the formation and evolution of the network, employing the QAP analysis method to elucidate the interrelationships within the networks. Given the preceding analysis, the industrial chain element is considered as a concrete manifestation of the sustainability of cultural exchanges. Therefore, by incorporating the industry chain as a factor, the relationship among different industrial links can be explored in depth, the interaction among producers, suppliers, and consumers can be analyzed, and the influence mechanism of the industry chain on the formation and evolution of the cultural products trade network can be revealed. In this paper, we integrate the factor of the industry chain into the analysis of network formation and influencing factors, and, on this basis, we construct the research hypotheses in the subsequent section.

2. Theoretical Framework and Hypothesis

The multidimensional proximity theory in economic geography holds that the interaction between actors depends on the interaction between acting subjects, such as geography, cognition, institutional proximity, etc. [27,28]. However, for cultural trade, it is not clear which indicators can be used to measure cognitive proximity. Like trade in all products, the printed material trade is affected by the economy, geography, and other factors. Beyond that, the printed material trade involves geopolitics, cultural ties, and technological diffusion, which have not been revealed in previous studies. Based on this, this study takes the factors of the economy, geography, geopolitics, cultural ties, and technology diffusion into account together to construct an analytical framework for analyzing the evolution of the global cultural printed material trade network focusing on the seven dimensions of economy, politics, geography, culture, institution, technology, and production chain, which are substantiated one by one, the size of cultural trade is defined as the aggregate of the imports and exports of cultural printed materials within a country (region) (Figure 1).

2.1. Multidimensional Proximity

Multidimensional proximity encompasses not only geographical proximity, but also economic and political dimensions [29]. Economic proximity pertains to the degree of similarity in economic level between two countries [30]. Studies have shown that affluent countries are more engaged in transnational economic activities than poor countries, and poor countries are more inclined to invest and trade with wealthier countries. The homogeneity of economic conditions reflected the convergence of income levels. When the economic distance is comparatively far, the outward direct investment will decrease [31]. Therefore, we conclude the following:

H1: 

Economic proximity is positively correlated with cultural trade.

Political proximity refers to the degree of similarity between two countries in trade-related policies, trade openness, and terms of trade [32]. Geographical concentration is more likely to form common trade policy preferences [33]. The differences in right-wing/left-wing political systems across countries have a robust negative impact on trade flows [32]. Therefore, we conclude the following:

H2: 

Political proximity is positively correlated with cultural trade.

Geographical proximity pertains to the physical distance separating two nations [34]; as this distance decreases, the geographical proximity between them increases. While globalization does facilitate bilateral trade, the restraining effect of geographical distance on trade remains strong [35]. Geographical proximity will increase conflict and cooperation in bilateral relations without trade [36]. Therefore, we conclude the following:

H3: 

Geographical proximity is positively correlated with cultural trade.

2.2. Socio-Cultural Relations

The use of a common language significantly impacts cultural trade by facilitating transnational cultural exchanges and fostering mutual understanding. It broadens the market for cultural products, lowers communication costs, and enhances cultural influence, thereby playing a vital role in advancing cultural trade and globalization [37,38].

A colonial relationship reflects the historical and cultural background. Colonial powers are able to control and monopolize the export of culture to their colonies, control the production, distribution, and communication channels of cultural products, and limit the independent development and international dissemination of colonial culture (products), which make the colonial powers and colonies have a similar cultural background and promote the occurrence of trade in a certain extent [39,40].

Bilateral immigration can stimulate bilateral trade through various channels; when the stock of immigrants is sufficient, the impact of transnational immigration on trade is significant, and, when the immigrants exceed the threshold, the trade will no longer increase [41]. Based on the state-level export data of 75 trading partners of the United States, it is shown that immigration plays a role in promoting exports and offsets part of the inhibitory effect of cultural distance on trade [42]. Therefore, we conclude the following:

H4: 

The cultural trade of countries with similar socio-cultural cultures is easier to carry out.

2.3. Institutional Stability

Institutional stability refers to the stability of the behavior, support, and operation norms agreed by regional subjects, such as political stability, power of discourse, government efficiency, and laws and regulations [43]. A good legal system contributes to a country’s economic development [44,45]. Therefore, we conclude the following:

H5: 

Institutional stability is positively correlated with cultural trade.

2.4. Digital Technology

The level of development of digital technology can be measured by the shared technical experience and knowledge base [46]. Digital technology has promoted the personalized and customized production of cultural products, has met the diverse needs of consumers in different countries and regions, and has promoted the diversified development of cultural trade [47]. Therefore, we conclude the following:

H6: 

Digital technology is positively correlated with cultural trade.

2.5. Industrial Chain

Through a systematic division of labor and collaboration, the industrial chain can optimize the allocation of resources, improve the productivity and innovation of production, and reduce costs and enhance market competitiveness, thus promoting the healthy development and sustainable growth of the entire industry [48]. Trade between locations of products linked by production chains is more likely to occur; innovation and technology transfer are also more likely to take place between regions with production chains [49]. Therefore, we conclude the following:

H7: 

Product trade of the upstream of the production chain is positively correlated with cultural trade.

3. Data and Method

3.1. Data Source

Cultural printed material trade data and variable data are selected from the International Trade Centre, World Bank, ITU, and French CEPII Database. Cultural printed materials include books, newspapers, magazines, periodicals, children’s paintings, music-related products, maps, hydrographs, architectural drawings, stamps, pad printings, calendars, and pictorial printings; the data from 2002 to 2021 are extracted and coded as HS49 classification. Seven first-level variables and sixteen second-level variables are identified based on the previous assumptions (

Table 1. Indicators of factors influencing the global cultural printed materials trade network.

Level-One Variable	Level-Two Variable	Clarification	Data Source
Economic proximity	Gross Domestic Product (GDP)	The economic foundation of the country	World Bank
	GDP Growth Rate (GDPgro)	The country’s economic growth potential	World Bank
Political proximity	Foreign Direct Investment (FDI)	The openness of the country	World Bank
	Trade Condition Index (TCI)	A comparative index obtained by comparing the export price index with the import price index	World Bank
Geographical proximity	Geographical Distance (Dist)	The farther the geographical distance is, the higher the cost of trade transportation will be	French CEPII Database
	Contiguity (Contig)	Geographical contiguity: if the two countries have a common border, trade is smoother	French CEPII Database
Socio-cultural relations	Colonial Relationship (Col45)	If there is a colonial relationship between the two countries, the acceptance of products is higher in the process of trade	French CEPII Database
	Common Language (Comlang)	Two countries using the same language can reduce the cost of external communication	French CEPII Database
	Total Population (TP)	The total population reflects the demand for cultural products	World Bank
	Net Migration (Netmig)	Degree of cultural integration	World Bank
Institutional stability	Political Stability and Non-violence Index (PV)	A higher index indicates the political situation is relatively stable, which is conducive to trade	World Bank
	Institutional Composite Ranking (ICR)	It can be gained by comprehensively measuring the five aspects of national discourse power, government efficiency, quality supervision, corruption supervision, and laws and regulations	French CEPII Database
Digital technology	Internet Coverage (Cov)	The families who have Internet	ITU Database
Industry chain	Printing Machine (Machine)	The upstream products of the printing industry chain	UNCOMTRADE
	Base Paper (Paper)		UNCOMTRADE
	Ink (Ink)		UNCOMTRADE

). Among them, the selection of second-level variables of economy, geography, and socio-cultural relationship refers to the indicators of existing studies. The degree of national development is used to measure the political proximity, and the combination of FDI and TCI can reflect the openness of its trade. Institutional stability is measured by PV and indirectly calculated institutional composite index. The indicator of Internet coverage, which is available at the national scale, is used in digital technology, and this indicator can cover the situation of telephony and e-commerce platform, as it is a fundamental indicator. The industry chain mainly considers upstream and downstream products to fully reflect the vertical sustainable development level of an industry.

3.2. Research Methods

3.2.1. Network Construction

A network constitutes entities that are interconnected in some manner. A “social network”, on the other hand, is a collection of social actors (multiple points) and their relationships (lines between nodes). Networks are often expressed using dots and lines, which is a formalized definition of a social network. In international trade, the information about the import and export of a country (region) can reflect its status in the global economic system, and a global trade network can be constructed by abstracting the countries (regions) into nodes and their import and export relationships into lines. Studying international trade from a network perspective can intuitively present the complex relations between countries and regions in the trade network of cultural products and help to identify the core nodes of trade, and also track the evolution of the trade network, analyze the changes in the structure of the network at different time nodes, and reveal the impact of globalization or policy changes on the trade of cultural products.

Since social network analysis can yield important network connections based on the analysis of large amounts of complex data, we, therefore, construct the oriented weighted trade network based on the cultural printed material of the country (region), and analyze the characteristics of the global cultural printed material trade network by using the complex network theory.

In this study, we examine global trade in cultural printed material between countries (in this study, country refers to a geographical unit of a country, region, or economy) (regions) using a network analysis approach that provides a powerful analytical tool to demonstrate complex trade relationships between countries (regions). Since China joined the World Trade Organization in 2001, it has entered the international trade market. In 2012, with the rapid development and update of information technology and Internet media products, it had a profound impact on the cultural print trade. Therefore, three time nodes in 2002, 2012, and 2021 are selected for network analysis. The flow of cultural printed materials has formed the trade relations of printing industry between countries, which includes one-way import or export trade, as well as two-way trade. A directed network is constructed by taking countries as nodes, taking the export relationship between countries and countries as the connection, and taking the value of exports from country i to country j as the weight.

3.2.2. Network Analysis

Network characteristics. Density can intuitively reflect the closeness of the connection between nodes and help us understand the overall structure and characteristics of the global print trade network. The average clustering coefficient is a measure of the degree of aggregation of nodes in the network, which can reflect the closeness of the connection between nodes in the network and the characteristics of the local structure. The average path length can measure the distance of information dissemination between nodes in the network, and a shorter average path length can reflect that information is disseminated more rapidly and efficiently in the global print trade network. Therefore, three indicators, namely, network density, average clustering coefficient, and average path length, are selected to characterize the network.

The calculation formula of network density is as follows:

$$D={\displaystyle \frac{m}{n(n-1)}}$$

m is the number of trade links; and n is the total number of nodes.

The calculation formula of average clustering coefficient is as follows:

$$ACC={\displaystyle \frac{1}{n}}\sum _i^n{\displaystyle \frac{2e_i}{D_i(D_i-1)}}$$

n is the total number of nodes; e_i is the number of connected edges between each adjacent node; and D_i is the degree of node i.

The calculation formula of average path length is as follows:

$$APL={\displaystyle \frac{1}{n(n-1)}}\sum _{i,j\ne 1}{h}_{ij}$$

n is the total number of nodes; and h_ij is the distance between country i and j.

Core–periphery structure analysis. Core–periphery structure analysis is to calculate the weighted centrality of a country, and then quantitatively divide the country into the core region and the periphery region according to the weighted centrality, to judge the position of each country in the network. The countries in the core region have a strong ability to gather and attract various elements of the countries in the periphery region, and the countries are closely connected and in a leading position.

Community detection—modularization. Community detection can identify the most closely connected groups in the printing trade network, reflect the number of associations in the trade network and the countries involved in each association, and present the basic state of the internal substructure of the network structure [50]. The calculation formula is as follows:

$$Q={\displaystyle \frac{1}{2m}}{\sum }_{ij}\left[w_{ij}-{\displaystyle \frac{k_i{k}_j}{2m}}\right]\delta \left(C_i,C_j\right)$$

Q represents modularity; m represents the weight of all sides in the network; w_ij represents the weight of the periphery between node i and j; k_i and k_j represent the degree of node i and j, respectively; and δ(C_i, C_j) represents whether i and j are in the same community, 1 if yes, and 0 otherwise.

Trade cooperation status index. Based on the analysis of the structural evolution of global cultural printing trade network, we further discuss the network role of each country in the network [51]. The cooperation status index S_i is introduced to measure the cooperation status of each country; it is comprehensively evaluated by degree centrality, intermediate centrality, and proximity centrality [52], and the specific formula is as follows:

$$S_i=\alpha {DC}_{\left(i\right)}+\beta {BC}_{\left(i\right)}+\gamma {CC}_{\left(i\right)}$$

DC_(i), BC_(i), and CC_(i) are degree centrality, intermediate centrality, and proximity centrality of countries, respectively; and α, β, and γ represent the weight of degree centrality, intermediate centrality, and proximity centrality, respectively. Based on the interpretive status of the three factors, in this study, the weights of all three are assigned as 1/3: α = β = γ = 1/3.

3.2.3. QAP Analysis

Quadratic Assignment Procedure (QAP) is a hypothesis testing method to study the relationship between two types of “relations” [53]. This method contributes to a reduction in the problem of multicollinearity, thus improving the accuracy and reliability of the model, and has advantages in large-scale data processing. The calculation process can be simplified by means of matrix replacement, while maintaining the accuracy of the analysis. QAP correlation analysis can not only study whether two “relation” matrices are related, but also study whether an attribute is related to a relation. QAP regression analysis can study the regression relationship between multiple matrices and one matrix, and evaluate the significance of the coefficient of determination—R². Therefore, the QAP method is used to analyze the influencing factors.

4. The Network Evolution Pattern

4.1. Network Characteristics

From 2002 to 2021, the amplitude in variation of the network density was relatively minor, with an overall gradual increasing trend. In 2002, 160 countries participated in the global trade of cultural printed materials, which expanded to 174 countries by 2021, indicating a broad geographical reach and strong network connectivity in cultural trade. From 2002 to 2011, the average clustering coefficient exhibited a fluctuating upward trend, while, from 2011 to 2021, it demonstrated a downward trend, with the average clustering coefficient in 2021 being lower than that of 2002. Compared to 2002, the average path length in 2021 was shorter, a reduced average path length typically signifies that nodes in the network are more closely connected (

Table 2. Overall indicators of the global cultural printed materials trade network.

Year	Node	Side	Network Density	Average Clustering Coefficient	Average Path Length
2002	160	1139	0.045	0.503	2.357
2003	169	1238	0.0444	0.510	2.283
2004	173	1326	0.045	0.527	2.359
2005	179	1434	0.045	0.503	2.402
2006	169	1255	0.045	0.429	2.471
2007	181	1612	0.049	0.511	2.348
2008	183	1739	0.052	0.535	2.297
2009	188	1654	0.047	0.513	2.384
2010	185	1660	0.049	0.530	2.415
2011	184	1745	0.052	0.548	2.342
2012	188	1751	0.050	0.521	2.382
2013	181	1768	0.054	0.542	2.274
2014	176	1730	0.056	0.529	2.265
2015	173	1637	0.055	0.512	2.27
2016	182	1632	0.050	0.468	2.365
2017	182	1647	0.050	0.506	2.331
2018	176	1679	0.055	0.523	2.338
2019	182	1666	0.051	0.472	2.338
2020	174	1530	0.051	0.488	2.357
2021	174	1593	0.053	0.485	2.313

).

In this study, trade flows between countries with effective trade (defined as trade volumes of $1 million or more) were selected to construct a network. In 2002, the trade network encompassed 160 countries and 1139 trade flows, representing approximately 97% of world trade; in 2012, this trade network expanded to include 188 countries and 1751 trade flows, accounting for about 95% of world trade; in 2021, it involved 174 countries and 1593 trade flows, reflecting over 98% of world trade; all the three time nodes effectively illustrate the global trade of cultural printed materials. The size of nodes indicates their weighted centrality, and the lines among nodes reflect the trade volumes. From 2002 to 2021, the global cultural printed material trade network has become gradually dense, with a gradual rise in network density. The connections among node countries (regions) in the network are gradually increasing. Throughout these three time nodes, the export trade flow between the United States and Canada has consistently ranked first, important trade flows have increased over time, such as China–the United States, and Poland–Germany in 2021 (Figure 2). The United States and Germany have maintained their position as the world’s largest exporters of cultural printed materials, significantly outpacing China and Poland. Within the global trade flow of all cultural printed materials, the exports of the United States to Canada, Poland to Germany, and the exports of China to the United States are the most important cultural printed material trade flows in the world. The United States, Germany, and China play pivotal roles in the supply of cultural printed materials. This is not only because of their substantial production capacities, which command a significant share of the global market, but also because of their strong commitment to the development of the cultural industry.

4.2. Spatial Linkage Characteristics

The global cultural printed material trade network exhibits a clear core–periphery structure: the United States–Canada has long occupied the core of this network, while Germany–Poland has emerged as a new core (Figure 3). The United States has maintained a stable core position within the network. From a regional point of view, Europe and the United States have dominated the global cultural printed material trade for an extended period, with the core status of the Asian region gradually improving. In 2002, the United States and Canada were classified as the first tier of the network and dominated the overall trade. The second tier comprised eight countries: the United Kingdom, Germany, France, Norway, Spain, Ireland, Belgium, Italy, the Czech Republic, Switzerland, and Austria. The third tier included 11 countries (regions), such as China and Hong Kong. The fourth tier encompassed 28 countries, including Russia and Sweden. The fifth tier consisted of 112 countries, including Guatemala and Slovenia. In 2012, the core positions of the United States and Canada remained robust, maintaining their status in the first tier of network. Germany, the United Kingdom, France, and several other nations were classified as sub-core countries in the second tier. China and Hong Kong advanced from semi-peripheral countries (regions) in the third tier in 2002 to sub-core countries in the second tier. Switzerland, Belgium, Italy, Spain, Singapore, and so on were in the third tier. By 2021, the network’s “two-pair core” structure had matured, with the United States–Canada and Germany–Poland forming the first tier as core countries. China, Hong Kong, the United Kingdom, and Mexico were recognized as the sub-core countries (regions) in the second tier (Figure 3).

4.3. Community Characteristics

The community detection algorithm is employed to segment the cultural printed material trade network into distinct communities, and the resolution is set at 1.2. The modular degree of the global cultural printed material trade network is measured using the weight of edges and the random detection algorithm, revealing a gradual dismantling of intercontinental trade barriers among various countries (regions).

In 2002, the modularity of the trade network was 0.363, which was divided into four network communities. Community I, led by the United States, has a total of 22 member countries (regions). It mainly consisted of the United States, Canada, Hong Kong (China), and some other nodes. Community II was the second largest society spearheaded by the United Kingdom, comprising 53 member states, accounting for 31.36%. Within the community, there were Asian countries such as Malaysia, Japan, and Singapore, alongside other countries like South Africa, Nigeria, and Australia. Community III was the largest community led by Germany, with 77 member states, accounting for 45.56% of the entire network. Within the community, most of the members were European countries, including France, The Netherlands, Belgium, Switzerland, Spain, and Austria as significant members. In 2012, the status of the three major communities was consolidated and continued to absorb and integrate. The modularity was 0.366, maintaining the division into four network communities. Community III, led by Germany, remained the largest with 75 member states, accounting for 39.68%. Community II, under the leadership of the United Kingdom, retained its position as the second largest community, comprising 58 member states, accounting for 30.69% of the entire network, including five new countries. Community I, led by the United States, expanded to include 36 member states, accounting for 19.05%. Based on nodes such as the United States, Canada, and Hong Kong (China), it also newly absorbed Asian countries such as Singapore, South Korea, and Thailand in 2012. In 2021, the community continued to integrate, forming two factions led by the United States and Germany. The modularity reached 0.375, with the network divided into four network communities. Throughout the process of evolution, community II continuously integrated with other communities, forming a community with the United States, China, and the United Kingdom as important nodes. In community I, the significance of Poland and The Netherlands increased, leading to the formation of a new community centered around Germany, Poland, and The Netherlands. France, Belgium, and Spain separated from the original community (Community III in 2012) and gradually transitioned into a new community (Figure 4).

4.4. Role of Countries

At the global level, the trade cooperation status index of countries is generally on an upward trajectory, and the trade cooperation status of emerging countries is rising.

At the intercontinental level, the European countries exhibit a high trade cooperation status index, while the Asian region has a significant increase in the trade cooperation status index. European countries generally maintain a strong position in the trade cooperation status index, particularly the United Kingdom, Germany, France, Italy, and Spain, underscoring Europe’s significant impact on global trade. In Asia, China’s trade status index has shown the most pronounced improvement, whereas Singapore and Japan have experienced a decline in their trade cooperation status index.

At the national level, the United Kingdom, Germany, France, and the United States are pivotal in trade cooperation, with China also demonstrating a marked enhancement in its trade cooperation status. The trade network cooperation index of the United Kingdom and Germany has remained in the top three positions at the three time nodes (

Table 3. The global cooperative status index of the Top 30 countries (regions).

Rank	Country (Region)	Year: 2002	Country (Region)	Year: 2012	Country (Region)	Year: 2021
1	UK	0.914	UK	0.883	UK	0.895
2	USA	0.819	USA	0.813	USA	0.831
3	France	0.646	Germany	0.703	Germany	0.809
4	Germany	0.600	France	0.672	France	0.723
5	Spain	0.394	China	0.580	China	0.623
6	Italy	0.358	The Netherlands	0.418	Italy	0.509
7	Guatemala	0.354	Spain	0.413	Spain	0.447
8	Jordan	0.347	Italy	0.401	The Netherlands	0.430
9	Iran	0.343	Hong Kong, China	0.394	Arabia	0.412
10	Malawi	0.343	Arabia	0.393	India	0.392
11	Serbia and Montenegro	0.342	Russia	0.362	Russia	0.390
12	Jamaica	0.342	Trinidad and Tobago	0.350	Switzerland	0.388
13	Qatar	0.336	Switzerland	0.348	Hong Kong, China	0.382
14	The Netherlands	0.326	Georgia	0.347	Poland	0.360
15	Singapore	0.324	India	0.341	Kazakhstan	0.351
16	Hong Kong, China	0.318	Namibia	0.339	Uzbekistan	0.347
17	Sweden	0.313	South Africa	0.334	Trinidad and Tobago	0.343
18	Japan	0.306	Japan	0.303	Iran	0.341
19	Denmark	0.305	Belgium	0.303	Belgium	0.334
20	Switzerland	0.301	Singapore	0.300	Canada	0.323
21	Russia	0.301	Australia	0.299	Malaysia	0.305
22	Belgium	0.277	Canada	0.299	Hungary	0.301
23	Austria	0.273	Malaysia	0.298	Denmark	0.294
24	Poland	0.273	the Czech Republic	0.294	Austria	0.292
25	Canada	0.269	Poland	0.291	Turkey	0.290
26	South Africa	0.267	Sweden	0.291	Romania	0.283
27	El Salvador	0.263	Denmark	0.287	South Africa	0.282
28	China	0.260	Mexico	0.282	Singapore	0.281
29	Hungary	0.248	Greece	0.282	Japan	0.279
30	Australia	0.246	Austria	0.281	Serbia	0.279

).

In conjunction with the previously proposed cooperation status evaluation model, this study utilizes the 2021 national (regional) cooperation index of the world’s Top 30 countries to compute the average values for the years 2002, 2012, and 2021, categorizing them based on the cooperating nations. Employing the K-means clustering analysis algorithm with a clustering coefficient set to 4, the trade cooperation status is delineated. The clustering ANOVA results indicate an F value of 143.840, with a significance level below 0.001, demonstrating a clear statistical significance.

Germany, France, the United States, China, and the United Kingdom are the core leaders of global cultural printed material trade cooperation. A review of cultural printed material exports in 2021 reveals that these countries accounted for approximately 12.77%, 4.62%, 11.14%, 11.68%, and 7.88% of the global market, respectively, which fully reflects the great importance these countries attach to the development of cultural trade in order to bolster the competitiveness of cultural products in the global market.

Malaysia, The Netherlands, Spain, and Italy are identified as sub-core leaders in the global cultural printed material trade cooperation. Malaysia benefits from its superior geographical location and cultural integration. Geographically, it is a hub connecting East Asia and South Asia, facilitating the cross-border exchange and trade of cultural products. At the same time, coupled with its cultural diversity background, cultural products have been given cultural internationalism and diversity, and contribute to the formation of the second-core leadership. The Netherlands, Spain, and Italy have rich cultural and creative industries and a multilingual cultural environment. The innovative design of the cultural industry and the advantages of multilingualism have contributed to the global influence of cultural printed materials, which not only adapt to the international market, but also broaden the potential audience.

Switzerland, Russia, India, and other countries are important partners of the global cultural printed material trade cooperation, while Kazakhstan and Uzbekistan are general collaborators (Figure 5).

5. Influencing Factors Dynamics

5.1. Model Construction

Based on the preceding assumption, this study covers 49 countries (regions) that accounted for 90% of the printing trade in 2021. The volume of the printing trade serves as the explained variable, while the explanatory variables include the gross domestic product (GDP), GDP growth rate (GDPgro), foreign direct investment (FDI), trade condition index (TCI), geographical distance (Dist), contiguity (Contig), colonial relationship (Col45), common language (Comlang), total population (TP) of 49 countries (regions), net migration (Netmig), political stability and non-violence index (PV), institutional composite ranking (ICR), Internet coverage (Cov), printing machine (Machine), base paper (Paper), and Ink (Ink). The QAP model is constructed using these variables. Taking 2002, 2012 and 2021 as time nodes, the QAP analysis of the global cultural printed material trade is carried out. The QAP model is as follows:

$$\begin{gathered} Y_t=f_t(GDP,GDPgro,FDI,TCI,Dist,Contig,Col45,Comlang,TP,Netmig,PV,ICR, \\ Cov,Machine,Paper,Ink) \end{gathered}$$

In this model, Y_t is the explained variable, which is the trade matrix of cultural printed material for year t, indicating the trade relationship between the selected countries. The three variables of a common language, colonial relationship, and contiguity are binary matrices: a value of 1 indicates that two countries share the same official language, have a colonial relationship (after 1945), or are adjacent, while a value of 0 indicates the opposite. The three variables of the printing machine, base paper, and ink in the industrial chain factors are the matrix constructed by the trade volume, and the remaining variables are the difference matrices. Furthermore, to avoid the influence caused by the inconsistency of various data variable units, the variable matrix constructed in this study was standardized in advance.

5.2. Correlation Analysis

The correlation analysis of the explained variables and explanatory variables is conducted to obtain the QAP correlation analysis results of the global printing trade network in 2000, 2012, and 2021 (

Table 4. Results of the QAP-related analyses.

Level-1 Variables	Level-2 Variables	2002		2012		2021
		Coefficient	p Value	Coefficient	p Value	Coefficient	p Value
Economic proximity	GDP	0.257	0.020	0.248	0.006	0.273	0.004
	GDPgro	−0.068	0.073	−0.104	0.004	−0.052	0.164
Political proximity	FDI	0.311	0.002	0.120	0.025	0.186	0.011
	TCI	0.028	0.232	0.037	0.185	0.063	0.041
Geographical proximity	Dist	−0.224	0.000	−0.233	0.000	−0.218	0.000
	Contig	0.426	0.000	0.490	0.000	0.455	0.000
Socio-cultural Relationship	Col45	0.423	0.000	0.279	0.003	0.192	0.015
	Comlang	0.240	0.000	0.225	0.000	0.197	0.000
	TP	−0.008	0.690	0.075	0.130	0.123	0.103
	Netmig	0.195	0.032	0.214	0.024	0.226	0.003
Institutional stability	PV	0.024	0.172	0.113	0.001	0.094	0.001
	ICR	0.073	0.006	0.074	0.004	0.031	0.105
Digital technology	Cov	0.081	0.001	−0.007	0.420	0.003	0.417
Industry chain	Machine	0.554	0.000	0.649	0.000	0.640	0.000
	Paper	0.516	0.000	0.560	0.000	0.540	0.000
	Ink	0.688	0.000	0.696	0.000	0.256	0.030

). In 2002, 3 out of the 16 s-level variables exhibited no significant correlation, while the remaining 13 explanatory variables were statistically significant; in 2012, 3 out of the 16 s-level variables exhibited no significant correlation, and the correlation analysis results of the remaining 13 explanatory variables indicated that they are statistically significant; by 2021, 4 out of the 16 s-level variables lacked a significant correlation, whereas the correlation analysis results of the remaining 12 explanatory variables demonstrated statistical significance.

5.3. Regression Results

The results of a correlation analysis show that the explained variable and the explanatory variable are independent and correlated. Building on this, a regression analysis was carried out, yielding the regression results. It should be noted that, in 2002 and 2012, because the correlation analysis of the trade condition index (TCI), political stability and non-violence index (PV), and total population (TP) were not significantly correlated with the cultural printed material trade matrix, these three variables were excluded from the regression analysis. In 2021, due to the insignificant correlation between the GDP growth rate (GDPgr), political stability and non-violence index (PV), institutional composite ranking (ICR), and total population (TP) and the cultural printed material trade matrix in the correlation analysis, the regression analysis is carried out after removing these four variables, and the regression results are obtained through calculation (

Table 5. Results of QAP regression analyses.

Year	Level-1 Variables	Level-2 Variables	Unstandardized Coefficient	Standardized Coefficient	Significance	Proportion as Large	Proportion as Small
2002		Intercept	−0.013	0.000	—	—	—
	Economic proximity	GDP	−0.059	−0.041	0.139	0.861	0.139
		GDPgro	−0.067	−0.018	0.228	0.772	0.228
	Political proximity	FDI	0.160	0.068	0.058	0.058	0.943
	Geographical proximity	Dist	−0.236	−0.044	0.015	0.986	0.015
		Contig	0.116	0.161	0.000	0.000	1.000
	Socio-cultural relationship	Col45	0.159	0.169	0.000	0.000	1.000
		Comlang	0.097	0.085	0.000	0.000	1.000
		Netmig	0.281	0.118	0.018	0.018	0.983
	Institutional stability	ICR	0.004	0.020	0.086	0.086	0.914
	Digital technology	Cov	0.002	0.012	0.196	0.196	0.805
	Industry chain	Machine	0.153	0.152	0.002	0.002	0.998
		Paper	0.171	0.160	0.000	0.000	1.000
		Ink	0.401	0.397	0.000	0.000	1.000
	Gof	R2	0.585
		Adj R2	0.582
2012		Intercept	−0.001	0.000	—	—	—
	Economic proximity	GDP	0.137	0.082	0.068	0.068	0.932
		GDPgro	−0.050	−0.011	0.321	0.680	0.321
	Political proximity	FDI	−0.043	−0.018	0.349	0.651	0.349
	Geographical proximity	Dist	−0.196	−0.040	0.060	0.941	0.060
		Contig	0.147	0.224	0.000	0.000	1.000
	Socio-cultural relationship	Col45	0.093	0.109	0.000	0.000	1.000
		Comlang	0.091	0.087	0.000	0.000	1.000
		Netmig	0.050	0.022	0.272	0.272	0.728
	Institutional stability	ICR	0.003	0.017	0.115	0.115	0.886
	Digital technology	Cov	0.003	0.022	0.119	0.119	0.881
	Industry chain	Machine	0.192	0.226	0.000	0.000	1.000
		Paper	0.099	0.106	0.000	0.000	1.000
		Ink	0.290	0.325	0.000	0.000	1.000
	Gof	R2	0.594
		Adj R2	0.592
2021		Intercept	−0.001	0.000	—	—	—
	Economic proximity	GDP	0.215	0.150	0.002	0.002	0.999
	Political proximity	FDI	−0.065	−0.023	0.230	0.770	0.230
		TCI	0.000	0.003	0.451	0.451	0.550
	Geographical proximity	Dist	−0.309	−0.063	0.005	0.996	0.005
		Contig	0.173	0.258	0.000	0.000	1.000
	Socio-cultural relationship	Col45	0.074	0.084	0.003	0.003	0.998
		Comlang	0.076	0.072	0.001	0.001	0.999
		Netmig	0.143	0.052	0.067	0.067	0.933
	Digital technology	Cov	0.005	0.032	0.030	0.030	0.971
	Industry chain	Machine	0.307	0.332	0.000	0.000	1.000
		Paper	0.149	0.158	0.000	0.000	1.000
		Ink	0.019	0.022	0.158	0.158	0.843
	Gof	R2	0.435
		Adj R2	0.432

). According to the fitting of the model, the statistical results of three years all passed the significance level test of 1%. This indicates that, when a linear relationship exists between explanatory variables such as the GDP, geographical distance, contiguity, common language, colonial relationship, and the trade volume of cultural printed materials, the aforementioned matrix data can account for over 40% of the variation in cultural trade volume, demonstrating a strong model fit. To make a more intuitive comparison, the influencing factors of the global cultural printed material trade network are categorized into primary influencing factors (standardized coefficient > 0.150), and secondary influencing factors (standardized coefficient < 0.150). In 2002, contiguity, a colonial relationship, ink trade, base paper trade, and printing machine trade were the primary factors influencing the global cultural printed material trade network, while the net foreign investment, geographical distance, common language, net migration, and trade condition index were the secondary influencing factors. In 2012, contiguity, ink trade, and printing machine trade were the primary factors affecting the global cultural printed material trade network, while GDP, geographical distance, a colonial relationship, a common language, and base paper trade were the secondary influencing factors. In 2021, the GDP, contiguity, printing machine trade, and base paper trade were the primary factors affecting the global cultural printed material trade network, while the geographical distance, colonial relationship, common language, net migration, and Internet coverage were the secondary influencing factors.

The regression coefficient of the economic development level transitioned from non-significant to positively significant, exhibiting a consistent upward trend. In terms of the level of economic development, the GDP had no significant correlation with the trade of cultural printed materials in 2002 (p = 0.139), but a significantly positive correlation between the GDP and the trade of cultural products in 2012 (Coef. = 0.082) and 2021 (Coef. = 0.150), with the regression standardization coefficient progressively increasing. Overall, the level of economic development of a country can provide a positive role in promoting the trade of cultural printed materials. Compared with 2012 (p = 0.068), the significance of the variable GDP in 2021 (p = 0.002) has increased, indicating that, at this stage, the economic development level of a country has enhanced its contribution to the development of the printing industry trade network. As time progresses, the level of economic development has amplified the degree of influence on the trade network. Therefore, research hypothesis 1 is validated.

The regression coefficient of the degree of national openness shifted from a positive significance to non-significance, suggesting a gradual diminishment of its role in the trade of cultural printed materials. In terms of the degree of a country’s openness, foreign direct investment and the terms of the trade index have no significant role in promoting the formation of the global cultural printed material trade network. The variable foreign direct investment exhibited a significant positive correlation with the trade network only in 2002, while the regression results in 2012 and 2021 were not significant. Therefore, research hypothesis 2 is rejected.

The regression coefficient of geographical distance and continuity gradually increase under geographical location factors. Geographical proximity emerges as a significant determinant in the formation of the global cultural printing trade network. In the three time nodes of 2002 (Coef. = 0.085), 2012 (Coef. = 0.087), and 2021 (Coef. = 0.072), there is a significant positive correlation between continuity and the cultural printed material trade, at the same time, while the geographical distance between trading countries exhibited a significant negative correlation. By acting on the cost of inter-country trade, geographical distance limits the frequency of bilateral trade contacts and has a notable diminishing effect on trade. This underscores the critical role of geographical proximity in the formation of cultural printed material trade networks; geographical proximity contributes towards reducing trade costs, strengthening communication links, and facilitating the smooth flow of cultural products between geographically adjacent countries. In short, geographical proximity mitigates the cost of trade between countries and has a significant consolidation and strengthening effect on promoting trade. Therefore, research hypothesis 3 is validated.

The regression coefficient of socio-cultural relations has shown a positive and significant trend, characterized by a wavelike increase. This indicates that the overall influence of social culture on the cultural printed material trade is increasingly important. A common language, colonial relationship, and net immigration are promoting the formation of the cultural printing trade network. The common language and colonial relationship of the three time nodes in 2002, 2012, and 2021 were significantly positively correlated with the trade network. A common language and colonial relationship can reflect the socio-cultural background of a country; a similar or the same socio-cultural background can reflect the development level of a country’s cultural industry to a certain extent. Speaking a common language between two countries can overcome the barriers or costs of communication; at the same time, it can reduce the risk of errors in the transmission of information, and it is also the carrier of the structure, characteristics, values, and world outlook of the form of cultural expression, conveying similar cultural concepts; the colonial relationship between the two countries can reflect the interaction of cultural development between the two countries, and they will be more familiar with and accept each other’s cultural products in the trade process, and will positively promote the development of related cultural printed material trade. From 2002 to 2021, the coefficient of the colonial relationship variable had decreased, suggesting that, as globalization progresses, the printing trade between nations (regions) is becoming less constrained by the colonial environment. While the variable of net migration demonstrated a significant positive correlation in 2002 and 2021, the regression result was not significant in 2012. Therefore, research hypothesis 4 is validated.

The regression coefficient of institutional stability has shifted from positively significant to non-significant, indicating that institutional stability has a diminishing influence on the trade of cultural printed materials. With the development of digital technology, the dissemination of cultural printed materials has undergone fundamental transformations; digital products are more easily disseminated through channels such as the Internet, and are not limited by institutional stability. Furthermore, globalization has brought countries closer together; the influence of institutional stability on the trade of cultural printed materials may be replaced by other factors. Therefore, research hypothesis 5 is rejected.

The regression coefficient of digital technology has transitioned from positively non-significant to significant and is becoming an “emerging force” to promote the formation of the cultural printed material trade network. This shift underscores the profound influence of information and communication technologies, particularly the Internet. The regression results of Internet coverage and the cultural printed material trade in 2002 and 2012 were not significant; by 2021, there was a statistically significant change, which indicates that, with the continuous improvement in the global scientific and technological development level, the coverage rate of the Internet in a country (region) has gradually influenced the development of its cultural trade. Internet platforms have gradually become key players in the trade process, changing the way cultural trade is produced and delivered. In particular, digital platforms have given rise to more possibilities in the trade in cultural products and created a more convenient trading environment for multiple market players. Digital technology, on the other hand, enable the storability of cultural services and provide strong support for the internationalization of the cultural printed material trade. Storing, transmitting, and trading the content of cultural services through digitization separates the service provider from the consumer, realizes the storability of cultural trade, alleviates geographical barriers, and facilitates the cross-border flow of cultural services. Therefore, research hypothesis 6 is validated.

The regression coefficient of the industrial chain has consistently remained positive and significant, exhibiting a wavelike upward trend. The printing machine, base paper, and ink trade are promoting the formation of the cultural printed material trade network. The printing machine and base paper of the three time nodes in 2002, 2012, and 2021 both showed a significant positive correlation; the ink trade was significantly positively correlated in 2002 and 2012, and the coefficient gradually diminished, becoming non-significant by 2021. The coordinated development of all links in the printing industry is one of the possible reasons why the upstream demand of the industrial chain is positively correlated. As the core elements of the upstream printing industry, the development of the printing machine, base paper, and ink are closely related to the production of cultural printed materials. The demand for these raw materials among trading partners is positively correlated, which may reflect the close coordinated development of the global printing industry chain to meet the needs of the entire printing value chain and promote the cross-border dissemination of technology and products. Therefore, research hypothesis 7 is validated.

6. Conclusions and Policy Implications

Cultural printed materials are the creative products that embody the characteristics of both the manufacturing and service industries. They serve as a medium for international trade and the dissemination of national images. With the popularization of Internet technology and digital media, the global printing industry is undergoing a profound transformation. The market share of the traditional printing industry is diminishing, while digital printing and culturally empowered industry pathways are reshaping the industrial landscape. In this context, the trade of cultural printed materials at the national level presents new global patterns. The analysis presented in this paper leads to the following conclusions:

Firstly, concerning the overall scale of cultural printed material trade, the trade volume is influenced by the broader international economic landscape and is closely tied to international economic and cultural events.

Secondly, from the perspective of the global cultural printed material trade network, the network exhibits a robust connectivity and a continuous rise in hierarchical levels. Poland, Germany, and China have become the new core nodes in the trade network and have become important countries in shaping the trade pattern. The global cultural printed material trade network has a significant core–periphery hierarchy, with developed countries in Europe and the United States residing at the core, and emerging industrial countries such as China, India, South Korea, and Turkey successively becoming the new core nodes. Germany, France, and Belgium play a prominent role as intermediary bridges, while the “circle of friends” of cultural printed material trade has an expanding effect, and China is more likely to form close ties with Southeast Asia, Northern Europe, and Central and Eastern European countries.

Thirdly, the formation of the cultural printed material trade network is primarily influenced by the industrial chain and geographical proximity. This also represents our contribution to the literature. The level of economic development and the degree of national openness significantly and positively contribute to the formation of the printing trade network. Socio-cultural factors, such as a common language and colonial relationship, also positively facilitate the formation of the printing trade network. Digital technology is emerging as a “new force” driving the formation of the cultural printed material trade network.

Our findings bring several policy implications. Firstly, fully leveraging the advantages of geographical proximity, trade partners with a location advantage can help reduce transportation costs and enhance communication, thereby promoting the circulation of cultural products in the international market. Consequently, it is essential that we consider the geographical location when selecting trade partners to promote sustainable socio-economic development. Secondly, we must consider promoting the coordinated development of the industrial chain to enhance global competitiveness. The coordinated development between the upstream and downstream segments of the industrial chain plays a critical role in the global trade of cultural printed materials. The production of cultural printed materials requires the coordination of multiple stages, including printing equipment, base paper, and ink. The integrity and efficiency of the industrial chain are crucial for facilitating trade circulation. Therefore, various countries should further strengthen cooperation and development along the industrial chain, promote green supply chain management, and realize ecological sustainability. Thirdly, we must consider leveraging the driving force of digital technology to shape the global production network of the printing industry while promoting the cultural printing sector towards a more eco-friendly and sustainable direction. Digital technology not only significantly enhances the efficiency and precision of production processes, enabling cultural printing enterprises to precisely manage resource utilization, effectively reduce waste, and guide the industry towards a more environmentally friendly direction, but also propels the printing industry towards greater globalization and increased digitization [54]. This will facilitate seamless connections in the global market, driving a deepening of the global production chain of the printing industry, ultimately promoting global knowledge dissemination and diffusion, thereby offering support and safeguards for the long-term prosperity and sustainable development of the cultural printing industry. For policymakers, this means that, in the future, there is a need to increase the investment in and use of digital technology to improve the productivity and product quality of enterprises.