Patent-Based Analysis of China’s Emergency Logistics Industry Convergence

Abstract

Technology and innovation have promoted industry convergence and brought new opportunities for industrial development, and a degree of convergence exists in the emergency logistics industry. The purpose of this study is to explore the convergence of the emergency logistics industry and the change in convergence degree among related industries, so as to find a solution to the lack of robustness of the emergency logistics system. This study measures the technical relationship between industries and analyzes the overall trend of emergency logistics industry convergence using the consistency between patent co-classification analysis and patent categories and technical fields. The dominance index and relative strength index are used to assess the strength of industry nodes and the convergence of the emergency logistics industry. Social network analysis is used to investigate the industries and technical fields that are important in the convergence industry. The findings indicate that there is significant convergence between the technical fields of the emergency logistics industry. Twelve industries are actively involved in the emergency logistics industry convergence, and nine industry pairs have strong convergence relationships between them. The information industry is critical to the convergence of the emergency logistics industry. Industry convergence is assisting in the coordinated growth of the emergency logistics sector, lowering informational barriers between sectors, and boosting the system’s resilience. This study contributes theoretical significance to the development of the emergency logistics industry and enriches the emergency logistics industry’s research system.

1. Introduction

A special logistics activity for the emergency protection of materials, personnel, and capital needs in response to serious natural disasters, sudden public health events, public safety events, military conflicts, and other emergencies is referred to as emergency logistics. At times of public health emergencies, it takes on the task of gathering, distributing, and transporting emergency supplies. Public health emergencies, such as the COVID-19 outbreak crisis, have, however, become more common in recent years. The emergency logistics system has been made less resilient [1,2] as a result of some issues that have come to light throughout this process, such as poor response capacity, uneven dispatching, and insufficient transportation capacity [3,4,5]. To effectively solve this problem, people from all walks of life are actively looking for new approaches [6]. Among these, industrial convergence in the technical field has a greater impact on the emergency logistics system.

Industry convergence is the blurring of boundaries between two or more industries, and it is a phenomenon that can facilitate paradigm shifts [7]. With technological change and innovation, the boundaries between industries are becoming blurred, different technologies and markets are integrating, and industries are beginning to interconnect [8]. Industrial convergence can create new business opportunities as well as value chains for businesses, thereby promoting economic growth. Clear industry boundaries can effectively promote the development of industry convergence.

In the emergency logistics industry, industrial convergence in the technical field plays an important role. With the demand and innovation of the emergency logistics industry, we find that the traditional boundary between emergency logistics and other fields has been blurred and a new technology paradigm has emerged. For example, the application of blockchain in emergency logistics. Blockchain-distributed bookkeeping technology is conducive to the centralized coordination of resources such as people, vehicles, goods, fields, and roads, the efficient deployment of logistics operations in all links, and the realization of integrated organization and operation of the whole chain of material support. It can greatly improve the operation’s efficiency and avoid delays, imbalances, and even fractures in the emergency logistics supply chain. This technological convergence results in the convergence of emergency logistics industries and the restructuring of industrial structures. The development of information and communication technology is accelerating industry convergence [9,10], for example, through the unmanned, zero-touch intelligent sorting and distribution technology in the emergency logistics system and the early warning monitoring of emergencies, etc. The integration of technologies is used to effectively alleviate the problem of emergency supply chain breakage and enhance the resilience of the emergency logistics system. In the convergence of the emergency logistics industry, Huang Xing and others built a cooperative symbiotic relationship between the government and emergency materials’ storage enterprises with the help of population symbiosis theory to solve the problem of how the government chooses emergency materials’ storage enterprises [11]. Zhang Haibo and others used the econometric analysis method of policy documents to make a quantitative analysis of the joint articles of departments promulgated at the state council level during the emergency management of public health events and studied the changes in the cooperation network between government departments in the emergency management of public health events [12]. Su Taoyong and others studied the coupling between the manufacturing and logistics industries from the perspective of industrial symbiosis [13]. Costa et al. used a multi-criteria decision-aid approach to address the selection of hospital aid vessels under COVID-19 [14]. However, few scholars have studied the convergence of emergency logistics industries, including how it has evolved. As a result, previous research makes it difficult for us to understand the relationship between emergency logistics industries. No scholars have fully answered how to measure the convergence of the emergency logistics industry before, making it difficult for us to understand the level of the emergency logistics industry. To compensate for previous research shortcomings, this study will use IPC co-classification analysis of patent data to study and quantify the evolution of emergency logistics industry convergence. This study also investigates what industries and technical fields play a key role in the convergence of emergency logistics industries in order to deeply analyze the relationship between emergency logistics industries and discover ways to improve the resilience of emergency logistics systems.

Patent data are important data sources in related research fields because it reflects the trend of knowledge accumulation and technological progress and is widely used in technology research [15]. Wang used patent information to analyze the development of blockchain [16]. Qiu used patent semantics and citation analysis to predict the development trend of technology and took the robot field as an example to carry out research. It is found that surgical robots and mobile robots are gradually becoming popular themes of research, along with the deep study of artificial intelligence and biomedical engineering [17]. In the field of emergency logistics, intelligent distribution technology, warehousing and logistics automation technology, and early warning and monitoring technology span many fields, forming a unique intelligent system and a new technical paradigm. The emergence of a new technology paradigm has had a significant impact on industrial convergence, particularly during the COVID-19 epidemic, when the convergence and development of technologies driven by the demand and innovation of emergency industries became more apparent and technology drove industrial convergence. In this study, IPC co-classification analysis is used as the most effective measure of technology-driven industrial interconnection [18]. The reason for adopting the IPC classification method is that the IPC system has stronger technical differentiation abilities. IPC subclasses are deep and extensive enough to specify different technical fields and cover similar technologies [19,20]. Then, all the patent data related to emergency logistics in China from 2010 to 2020 are used to study the convergence development of the emergency logistics industry in China and the regional distribution trend of the convergence development of the emergency logistics industry in China. Finally, from a macro perspective, once can analyze the industries that play a key role in the convergence of the emergency logistics industry, and from a micro perspective, once can analyze the technical fields that play a key role in the convergence of the emergency logistics industry. This study deepens people’s understanding of the convergence of the emergency logistics industry through the analysis of time–change trends. At the same time, it is hoped that the research on the regional distribution trend can provide scientific support for the improvement of regional emergency logistics resilience. Furthermore, in order to improve the resilience of the emergency logistics system, it investigates the important factors that help improve the toughness of the system from both macro- and micro-perspectives. This study also enriches the research system in emergency logistics.

The remainder of the paper is organized as follows: The second section summarizes the literature review on industrial convergence. The third section proposes research methods. The fourth section introduces the data that were used in this study. The fifth section discusses the empirical findings. The sixth section is a summary of the entire research.

2. Literature Review

2.1. Industrial Convergence Background

With the development of the Internet era, its business scope is expanding day by day, which has changed the operating boundaries of major industries in the past. Since the 21st century, the speed innovation and iterative evolution of information and communications technology (ICT) has been accelerating, and new technologies such as information, biology, new energy, and new materials have shown a significant trend of cross-fertilization, which is regarded as an important symbol of the new round of technological revolution and industrial change [21]. Industrial convergence is the internet integration of all industrial resources, allowing for the interconnection of industrial R&D, manufacturing, commodity trading, product circulation, and financing, as well as promoting cross-border integration of industrial resources, improving manufacturing efficiency within the industry, and optimizing resource allocation. The deep integration of traditional industries with the Internet can penetrate deeply into the operation links and nodes of the industrial chain in the form of digitalization and networking, reshaping the industrial chain process, which is conducive to improving the efficiency of production operations and saving resources and costs.

Relying on big data, artificial intelligence, and blockchain technology, industrial convergence has flourished. Many scholars have studied industrial convergence through the integration of technical fields [22]. For example, with the development of 3D printing technology, new markets will be created through the convergence of 3D printing [23]. Integrating the traditional design industry with the 3D printing industry enables the formulation of the production direction for building a new industry ecosystem [24]. However, there are still many problems in the process of implementing convergence. After industrial convergence, large-scale and high-quality business demand will be a new challenge for the future development of industrial convergence. How to allocate multi-task and multi-business resources has become a key issue that needs attention. Song C and others put forward a fully distributed optimal control solution, RSPE-DOCS, to solve the problem of real-time service in the shared resource pool to improve the optimal resource allocation of equipment nodes, which realized the information exchange strategy and distributed optimization method between nodes and ensured that the optimal resource allocation scheme was found in the convergence process [25]. The future of industrial convergence is to realize the convergence of everything. Converged machines and business processes will communicate with each other to optimize production and realize more efficient and sustainable large-scale manufacturing. However, the sharing of resources and the opening of processes will lead to a crisis of trust. Preuveneers, D. and colleagues proposed a distributed trust model and middleware for collaborative and decentralized access control in order to ensure data transparency, integrity, authenticity, and authorization, and demonstrated that a private blockchain can cross the trust boundary of industrially convergent manufacturing enterprises [26]. Industrial convergence has received a lot of attention as technology has advanced. However, few scholars have investigated the evolution of emergency logistics industrial convergence, and this study will do so.

2.2. Measurement of Industry Convergence

When measuring the degree of industry convergence, several data metrics can be used. Convergence is frequently measured using research paper data such as co-citation, co-word, or co-authorship when the convergence in question is in the knowledge domain. When there is a technical convergence, patent data, such as co-citation or co-classification data, are primarily used [27,28]. Breschi proposed a correlation coefficient based on the cosine index between the technical input structure vectors to measure the level of industrial convergence between the supply and demand sides [29]. Furthermore, market convergences are measured by the company’s product characteristics or market activity data. Chao Lu and colleagues, for example, used the Herfindahl–Hirschman index (IIIII) and input–output analysis to investigate the degree of convergence between Beijing’s cultural and financial industries [30]. Wan Xing and colleagues used the input–output table cross-entropy updating technology to measure the industrial convergence of China’s communication technology industry, concluding that some departments were highly complementary, the supply-side convergence dominated the industrial convergence, and the demand-side convergence remained stable [31]. Some scholars have investigated the convergence of services and Industry 4.0 from the standpoint of business innovation [32], as well as the degree of convergence between industries with interconnected industries and potential industries, such as diffusion parameters [33]. For this study, the earlier research techniques serve as a kind of reference. Patent data that can reflect the development of the technology track are chosen as the study data in order to examine the convergence of emergency logistics sector technology. The research methodology is the IPC classification approach with strong technical distinction capabilities.

3. Research Method

3.1. Constructing the Relation Matrix by IPC Co-Classification

When patent classification data are combined with industry-matching data, we can find the symbiotic relationship between technology categories in emergency logistics industry convergence and industry categories in patents. Firstly, the technical relationship between emergency logistics industries is constructed using IPC co-classification. It is analyzed using the IPC’s first four digits (for example, H04N). Each patent contains several IPCs. Several IPCs in each patent are divided into the corresponding WIPO technical fields using a comparison table of 35 WIPO technical fields and IPC classification numbers. IPC and technical fields have a one-to-one correspondence. Through the corresponding relationship, the technical relationship matrix between emergency logistics industries can be constructed. The relationship matrix provides an effective basis for analyzing the convergence of the emergency logistics industry.

3.2. Social Network Analysis

According to the relationship between the technical fields contained in the same patent, the technical relationship matrix is formed, and the ecological network of the emergency logistics industry is formed through the technical relationship matrix. Using Gephi software, visualize the industrial ecological network. In this study, an industry ecological network at both macro and micro levels was established. The nodes and connections in the macro-industry ecological network represent the industries and their technical relationships, which will be used to analyze the overall trend of technology-driven industrial convergence in the emergency logistics industry. The nodes and connections of the micro-industry ecological network represent a single technical field and their relationships, which will be used to determine the key technical fields that drive industrial convergence in the field of emergency logistics.

3.3. Determine the Index to Measure the Convergence of the Emergency Logistics Industry

The passenger flow organization coefficient is used in this study to depict the nodal strengths of industries as well as the degree of convergence between industries [34]. The dominance index $C_i$ and the relative strength index $P_{ij}$ are used to determine their importance. In the emergency logistics industry, the non-vector undirected index dominance index $C_{i }$ (Equation (1)) is used to assess the importance of industries with industry convergence. The sum of industries that converge with industry i is divided by the average number of industries that converge with all industries other than industry i. In the emergency logistics industry, the relative strength index $P_{ij}$ (Equation (2)) is used to assess the degree of convergence of two industry pairs. It is calculated by dividing the number of convergences between two industries by the total number of convergences in emergency logistics.

$$C_i=\frac{D_i}{\left({{\displaystyle \sum }}_{j=1}^J{D}_j/J\right)}\hspace{1em}\hspace{1em}(i\ne j)$$

(1)

$$P_{ij}=\frac{d_{ij}}{{{\displaystyle \sum }}_{i=1}^I{{\displaystyle \sum }}_{j=1}^J{d}_{ij}}\hspace{1em}\hspace{1em}(i\ne j)$$

(2)

where $D_i$ is the number of industries that have convergences with industry I, and $d_{ij}$ is the number of convergences that occur between industry i and industry j, where i ≠ j. For industries that actively participate in the convergence of the emergency logistics industry, the potential degree index $C_i$ is greater than 1. The importance of these industries in this convergence is greater than the average level of other industries. $P_{ij}$ of all industry pairs adds up to 1. The convergence between each industry pair ranges from 0 to 1. The lower the value of $P_{ij}$, the lower the convergence between the industries, implying that this industry pair is less important in the emergency logistics industry’s convergence. The greater the value of $P_{ij}$, the greater the convergence between the industries, implying that this industry pair is more important in the convergence of the emergency logistics industry. Because the initial measurement value of $P_{ij}$ is small and difficult to observe for comparison, it is uniformly adjusted to 1000 times the original.

4. Data Sources and Processing

The search terms were chosen in accordance with the literature review and national emergency system planning for China’s “14th Five-Year Plan.” The study’s search terms included “emergency logistics”, “safety production”, “emergency rescue”, “public safety”, “disaster prevention and mitigation” and “emergency events”. Secondary search keywords are IPC numbers corresponding to several major industries such as transportation, distribution processing, packaging, warehousing, loading and unloading, distribution, and information processing in the reference relationship table between the International Patent Classification and the Industrial Classification of the National Economy. The State Intellectual Property Office of China’s patent database was searched for emergency logistics-related patents. With the exception of invalid data and unprivileged and in-process patents, a total of 7069 patents were used for this study’s analysis.

According to the table comparing WIPO’s 35 technical fields to IPC classification numbers, more than 700 IPC subcategories in 7069 patents corresponded to the 35 technology fields, linking the technology to the industry. Patents are categorized as inter-industry convergence, intra-industry convergence, or not convergence using a co-classification methodology. When the patent contains different IPC subclasses from different industries, it is considered an “inter-industry convergence” between two different technical fields. Intra-industry convergence occurs when a patent contains different IPC subclasses but belongs to the same industry. A patent is not considered convergent if it contains only one IPC subclass.

Creating industry ecological networks with co-categorized information.

Table 1. Industry relationship matrix.

Industry	1	2	3	……	33	34	35
1	0	157	65	……	2	41	95
2	157	0	128	……	17	19	186
3	65	128	0	……	0	8	47
……	……	……	……	……	……	……	……
33	2	17	0	……	0	2	20
34	41	19	8	……	2	0	35
35	95	186	47	……	20	35	0

depicts the relationship matrix between industries. With 35 industries as nodes and industry connections as edges. The number of technical fields contained in the industries is indicated by the size and color of the nodes. The more technical fields there are in the industry, the larger the node and the darker the color of the node. The edges signify how closely related the industries are to one another. The stronger the link between two industries, the thicker the edge.

5. Discussion

5.1. General Trends in the Tonvergence of the Emergency Logistics Industry

5.1.1. Regional Distribution Trends

The comparative analysis of the degree of industry convergence using the region as the main classification can assist in understanding the information on emergency logistics industry convergence in different regions and further exploring the distribution of convergence in the emergency logistics industry in different regions. Figure 1a depicts the distribution of industry convergence degrees in each region. Beijing, Guangdong, Jiangsu, Zhejiang, Shandong, Sichuan, Shanghai, Anhui, Hubei, and Chongqing are the regions with the ten highest convergence degrees in the emergency logistics business, as shown in Figure 1b. Economically developed regions along the eastern seaboard have a higher degree of convergence in emergency logistics industries. Strong economic support enables them to obtain adequate research funding. The convergence of the emergency logistics industry is also high in the Sichuan Province, which is located in the central region. This could be because Sichuan is located in a mountainous region prone to earthquakes and other natural disasters, and the local government places a high value on emergency logistics research.

5.1.2. Time Development Trend

The number and percentage of industrial convergence and non-convergence patents issued according to time-based classification can provide insight into the evolution of industrial convergence in emergency logistics as time passes. Figure 2a depicts the number of issued emergency logistics industry (non-)convergence patents over time. Figure 2b depicts the evolution of the (non-)convergence share situation in the industry over time. Figure 2a shows that the total number of convergence and non-convergence patents increased between 2010 and 2015. There is no discernible distinction between the two. The expansion of the two has contributed to an increase in the total number of emergency logistics patents. Non-convergence patents began to decline in 2015. From 2015 to 2016, intra-industry and inter-industry convergence outpaced non-convergence. Due to the significant growth in inter-industry convergence in 2016, convergence began to grow significantly faster than non-convergence. As technology evolves, different technologies and markets merge, resulting in an increasing number of patents for industry convergence and fewer and fewer patents for non-industry convergence. The increase in industry convergence patents will inevitably affect the convergence of the emergency logistics industry.

Figure 2b shows that, from 2010 to 2020, the proportion of industry convergence was always greater than the proportion of non-convergence. In the emergency logistics industry, there is a high degree of industry convergence. From 2010 to 2015, the convergence ratio decreased. However, in the five years following 2015, the convergence ratio increased and approached 100%. The non-convergence ratio gradually decreased to zero. It demonstrates that, over time, the convergence between industries in the emergency logistics industry has become nearly as extensive. The activities of the emergency logistics business are rarely completed by a single industry. This also strengthens the information exchange between industries, promotes coordinated development between industries, and is conducive to the improvement of the resilience of emergency logistics systems.

Figure 2b also shows that the ratio of convergence to non-convergence shows an opposite trend around 2015. To better investigate the convergence of the emergency logistics industry, the patent data collected from 2010 to 2020 were divided into two stages for analysis: 2010 to 2015 and 2015 to 2020, resulting in more accurate and effective results. Figure 3a,b depicts the industrial ecological networks of the two stages.

According to the industrial ecological network diagram from 2010 to 2015, there were industries involved in convergence during this time period. There are few convergences among industries, and the degree of convergence is low. On the other hand, the industrial ecological network map from 2015 to 2020 reveals that there are numerous industries with significant intra-industry convergences, including 12 (control), 6 (computer technology), 32 (transportation systems), 25 (processing), 35 (transportation systems), 2 (audiovisual technology), and 1 (motors, equipment, and energy). Strong inter-industry relationships exist between industries 6–12 (computer technology–control), 4–12 (digital communications–control), 3–4 (telecommunications–digital communications), 2–12 (audiovisual technology–control), and 6–7 (computer technology–IT management methodologies). The comparison also demonstrates that the convergence of the emergency logistics industry did not develop prior to 2015 and that the convergence of the emergency logistics industry occurred primarily after 2015. The convergence of the emergency logistics industry has changed dramatically over time. Convergence has grown rapidly in recent years, owing in part to the direction of national policies and the advancement of information technology. Convergence between industries has increased, and industry boundaries have blurred, promoting the development of emergency logistics industry convergence.

5.2. Analysis of Node Strength and Convergence in the Emergency Logistics Industry

5.2.1. Industry Node Strength

Table 2. Nodal strength.

NO.	Industry	Node Strength
1	12 (control)	5.99
2	6 (computer technology)	4.45
3	4 (digital communication)	4.16
4	2 (Audiovisual technology)	3.70
5	7 (IT management methods)	2.28
6	3 (telecommunications)	2.15
7	32 (transportation systems)	1.89
8	35 (civil engineering)	1.85
9	1 (electrical machinery, equipment, energy)	1.58
10	10 (measurement)	1.31
11	25 (processing)	1.25
12	31 (mechanical components)	1.24
13	24 (environmental technology)	0.86
……	……	……
35	18 (food chemistry)	0

shows the strength of industry nodes. The emergency logistics industry has 12 nodes that are converging with an intensity greater than 1. Due to their importance being higher than the average of all other businesses, these 12 industries are thought to play a more significant part in the convergence. In total, 12 of the 35 industries are actively involved in the emergency logistics industry’s convergence. It is clear that there is a strong network of connections within the emergency logistics sector. The control industry patents with the highest node strength are mostly related to early warning systems, alarm systems, monitoring systems, and control systems. This is the stage of preparation in the emergency logistics system. The system’s early warning monitoring of emergency logistics is critical. It can detect risks and hazards in real time and improve disaster prevention and response capabilities. Aside from the control and transportation industries, which are critical to logistics, there is a wide range of cutting-edge technologies such as computers, digital, and communications. The rapid development of emerging technologies such as big data, artificial intelligence, and the Internet of Things has accelerated industry convergence. Information processing in emergency logistics has greatly benefited from advancements in fields such as digital communications. The effectiveness of emergency logistics has been considerably boosted by all of these industries.

5.2.2. Convergence Strength between Industries

Table 3. Convergence strengths between industries.

NO.	Industry Pair	Convergence Strength between Industries
1	6–7 (computer technology–information technology management methods)	29.37
2	6–12 (computer technology–control)	29.09
3	4–12 (digital communications–control)	28.78
4	3–4 (telecommunications–digital communications)	28.61
5	2–12 (audiovisual technology–control)	24.29
6	4–6 (digital communications–computer technology)	14.10
7	2–6 (audiovisual technology–computer technology)	13.51
8	7–12 (information technology management methods–control)	12.37
9	25–31 (processing–mechanical components)	10.78
…	……	……
595	31–34 (mechanical components–other consumer goods)	0

shows the degree of industry convergence. The industries that pair with convergence scores above 10 in the emergency logistics industry are those that are deemed to have a significant amount of relevance. There is a high level of convergence between industries, and industry pairs play a significant role in the convergence of the emergency logistics industry.

The five industry pairs 6–7 (computer technology–IT management methods), 6–12 (computer technology–control), 4–12 (digital communications–control), 3–4 (telecommunications–digital communications), and 2–12 (audiovisual technology–control) have a degree of convergence of 20 or more. In addition, 12 (control) is closely related to 6 (computer technology), 4 (digital communication), and 2 (communication) (audiovisual technology). Converging the most with other industries in the convergence process, 12 (control) plays a more important role in the development of the emergency logistics industry, with which numerous industries related to emerging technologies are converged. Emergency early warning monitoring is becoming more intelligent as emerging technologies such as big data, artificial intelligence, and the Internet of Things mature. The convergence of the control industry and many emerging technology industries is being quickly integrated to enable more accurate and real-time prevention, monitoring, and emergency rescue work. It plays a crucial part in the system of emergency logistics. Recent years have seen an acceleration in the field of information processing in logistics systems due to the rapid development of innovative technologies. Timely and effective information processing will improve the efficiency of the emergency logistics response phase and reduce the losses caused by unexpected situations as much as possible. The rapid development of emerging technologies is also driving the rapid development of industrial convergence and accelerating industry convergence.

5.3. Identification of the Key Roles in the Convergence of the Emergency Logistics Industry

At the micro level, the industry ecological network identifies the core technology areas driving industrial convergence. This study examines the industry ecological network situation of each technology area from a micro perspective to investigate the technology areas that play a key role in industrial convergence. As shown in Figure 4, the micro-industry ecological network is built using IPC subcategories as nodes and the technological relationships between IPC subcategories as edges. The number of patents in IPC subclasses is indicated by node size and color. The strength of links between technology sectors is reflected in the thickness of the edges.

The H04N (image communication) and G08B (signaling device or calling device, command sending device, alarm device) technology areas are located at the network’s heart and are critical to the emergency logistics industry. H04N and G08B are in the audiovisual technology and control industries, which are actively involved in convergence and have stronger convergence with several industries. Between 2010 and 2015, the control and transportation system industries were heavily involved in the convergence. Many new technologies and information technology industries have emerged since 2015. Control and transportation systems are still very important to them as regards creating a technologically driven convergence. The role of technology and information processing in the development of emergency logistics is becoming increasingly important. In the event of an emergency, it is common for emergency storage, procurement, transportation, distribution, and other links to be uncoordinated, for enterprises to be disconnected, and for the entire emergency supply chain’s information to be opaque, resulting in an imbalance between supply and demand for materials and other issues. These issues will also contribute to the emergency logistics system’s lack of resilience, resulting in long response times, low rescue efficiency, and high rescue costs, among other issues. These are the issues that must be addressed as soon as possible in the development of emergency logistics. In the face of these challenges, the solid foundation of facilities and the quick response of information technology work together to aid in the efficient dispatch and distribution of emergency logistics.

6. Conclusions

Although patent data have been widely used in related technical research [35], their application in the field of emergency logistics systems remains limited. This study examines the evolution of emergency logistics system technology and employs patent data to supplement related research on the emergency logistics industry’s convergence. This study employs co-categorization analysis to assess the convergence of the emergency logistics industry from a patent standpoint. Although co-classification analysis has been widely used, it is still well-suited to this study’s analysis due to the IPC system’s strong technical distinction ability. The trend of emergency logistics industry convergence over time and regional distribution is analyzed using patent data, and the evolution of emergency logistics industry convergence is dissected using the emergency logistics macro-industry ecological network diagram. We discovered that there is a high degree of industrial convergence behavior in the emergency logistics industry and that convergence between industries became more frequent and closer after 2015, particularly in economically developed regions. We identified the industry and technology areas that play a key role in the convergence of the emergency logistics industry using empirical analysis. Twelve industries are actively involved in the emergency logistics industry convergence, and nine industries have strong convergence relationships with one another, including the control industry, the emerging technology industry, and the information industry, all of which play important roles in the emergency logistics industry convergence. The technology areas that play a key role in the convergence of the emergency logistics industry are H04N (image communication) and G08B (signaling device or call device, command and communication device, alarm device). The present research contributes to the theoretical system of emergency logistics industry convergence and broadens the scope of emergency logistics research [36].

This research has practical implications for the growth of the emergency logistics industry. Industrial convergence will promote the coordinated development of the emergency logistics industry, reduce information barriers between industries, aid in the improvement of the emergency logistics system’s resilience, and provide new growth points for economic development. In the future, we should: continue to expand the emergency logistics industry chain, build a perfect industrial ecosystem, and create more market development space [37]; encourage the comprehensive development of industries that have actively participated in convergence, including emerging industries such as computer technology and information technology; pay more attention to the convergence of these and other industries and expand the use of artificial intelligence, blockchain, cloud computing, digital twins, and other technologies in emergency logistics; and realize the automation, visualization, intelligence, and flexibility of an emergency logistics system. The growth of other industries that are crucial to the development of emergency logistics but have not actively participated in the convergence should also be aggressively encouraged. For example, how can other consumer goods industries integrate with other industries more effectively? As a result, the emergency logistics system will be strengthened, providing a strong guarantee for the country’s and people’s life and property safety, as well as promoting social stability. At the same time, it can deal with the dual pressures of economic downturn and epidemic prevention and control, enhancing economic vitality and promoting economic development.

There are also numerous flaws in our research that can be further investigated in the future. Firstly, the emergency logistics patents retrieved by the emergency logistics keywords used in this study are limited and may not include all patents; more comprehensive and accurate data to conduct related research may exist. Secondly, we can use other methods to assess the convergence of the emergency logistics industry, and more complicated methods may improve the research’s reliability. Finally, when measuring the strength of key nodes and the degree of industry convergence, we set a critical value, and differences in the critical value affect the research results.