Knowledge Structure of Emergency Logistics Research in China: An Analysis Based on Bibliometrics ()
1. Introduction
With the development of China’s economy and society, the frequency and level of emergencies have been increasing. The improvement of the emergency logistics system directly determines the emergency supplies support capability, and then affects the overall development of emergency work. Therefore, emergency logistics often plays a decisive role in the face of various emergencies, and has become one of the focuses of research in recent years. As of April 11, 2022, domestic and foreign scholars have conducted a lot of analysis and review of the literature in emergency logistics (Li, 2013; Chen, 2014; Wang, 2014; Wang et al., 2015b; Wang et al., 2021; Liu et al., 2020b; Zhao, 2020; Gao et al., 2009; Li & Lu, 2017; De Brier et al., 2020) .
However, most of the researches are still based on qualitative analysis, and only a few are carried out by quantitative methods such as bibliometrics. Different authors usually choose different time slicing, research topics and data sources when using bibliometric methods for research, among which the research topics differ the most. In terms of research topics, there are two literatures in Table 1
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Table 1. Literature statistics of emergency logistics research review field (12 articles).
that focus on domestic or foreign logistics partly involving emergency logistics (Yin & Chen, 2011; Lyu, 2017) . The three literatures mainly focus on emergency management, so they are related to emergency logistics relatively limited (Li, 2016; Li & Yang, 2020; Wang & Sheng, 2018) . The other five literatures focus on domestic or foreign emergency logistic: In the study of Liu & Li (2018) , there is no cluster analysis of keywords, and the research time line is short. Research on Zhou (2020) lacks the control of future research frontiers and trends. The clustering view analysis of Zhou & Zhang (2022) is relatively macro, which cannot realize specific analysis of different knowledge groups. Pei et al. (2022) do not carry out correlation analysis on research institutions. Li (2021) does not show a graph for visual analysis . Two foreign literature reviews the model optimization and large-scale disasters in emergency logistics (Caunhye et al., 2012; Jiang & Yuan, 2019) .
Therefore, this research uses CiteSpace 5.8.R3 visualization software to comprehensively analyze the research literature on emergency logistics from 2002 to 2022, and explores the development trend and hot frontiers of China’s emergency logistics research from multiple dimensions such as research time, research subject, research hotspot and research frontier. It provides some ideas and references for the follow-up researches.
2. Data Sources and Research Methods
2.1. Data Sources
The data in this study are from the CNKI. In order to comprehensively retrieve the published literature related to emergency logistics, reduce the influence of other disciplines on the analysis, so as to make the research data have a higher generality, the main topic is emergency logistics. A total of 2702 results were retrieved from January 1, 2002 to April 11, 2022, and were downloaded and saved as plain text. After format conversion on CiteSpace 5.8.R3, 2694 results were obtained in record-conversion, which is the final data of this study.
2.2. Research Methods
In this study, CiteSpace 5.8.R3 visualization software is used to set its parameters as follows: time slicing—January 2002 to April 2022—years per slice—one year— pruning consists of three ways: pathfinder, pruning sliced networks, pruning the merged networks. Visualization selects cluster view-static and shows merged network. Other settings remain unchanged. Node types are selected as author, institution and keyword in order to draw and analyze the visual knowledge graph.
3. Research Results and Analysis
3.1. Analysis of Annual Print Volume of Emergency Logistics
The change of the number of publications in a discipline field over time reveals the academic status and research activity in a certain period to some extent. In this study, Origin was used to make a dot plot for the annual number of posts and the cumulative number of posts, and the variation trend of them over time is shown in Figure 1.
From the perspective of time distribution, the annual number of posts and the cumulative number of posts can reflect the research heat of emergency logistics from 2002 to 2022 to a certain extent. The number of articles published in the direction of emergency logistics in China fluctuates little and tends to be stable on the whole. The number of articles published in 2008 and later years is larger than the previous years. The cumulative amount of articles published each year presents an upward trend, and the increase has increased significantly since 2008. The Wenchuan earthquake in 2008 reflected the situation of emergency logistics in China, which greatly exposed many problems in emergency management. It can be seen that 2008 is an important node for the development of China’s emergency logistics, and the research in this field has attracted more and more attention from scholars. The outbreak of the COVID-19 at the end of 2019 puts forward new requirements for the development of emergency logistics in China. Given that there are still many problems to be solved in this field, the research of emergency logistics still needs further attention from domestic scholars. This study predicts that the number of articles published in this field will show an upward trend, and the cumulative number of articles will increase again.
3.2. Subject Analysis of Emergency Logistics Research
3.2.1. Co-Occurrence Analysis of Core Authors
Visualization software CiteSpace 5.8.R3 is used to set Node Types as Author, and other settings remain unchanged. The knowledge graphs are shown in Figure 2 and Figure 3, and the top 10 prolific authors are listed in Table 2.
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Figure 1. Trend chart of annual and cumulative number of emergency logistics posts.
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Figure 2. Translated co-occurrence knowledge graph of core authors.
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Figure 3. Translated time-zone view of core author co-occurrence knowledge graph.
The top 3 authors are Jigang Wei, Changshi Liu and Zi Yan respectively. Among them, Jigang Wei published 90 articles, far ahead of other scholars, and the other scholars published more than 10 articles. The academic research group represented by them promotes the development of China’s emergency logistics. From the perspective of the cooperation among authors and the distribution of research teams, the cooperative relationship between authors in this field is relatively harmonious, with a certain number of research teams. However, the cooperation between authors is limited within the team and lacks of communication between teams. This will directly affect the quality and process of further development of this field, and there is still a large space for development in the future.
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Table 2. Core authors of emergency logistics research (TOP 10).
Through the time-zone view of the co-occurrence knowledge graph of the core authors, Figure 3 is obtained. We can clearly obtain the founders of the research of emergency logistics in China, such as Changshi Liu, etc., which lays a solid foundation for the development. At the same time, we can find that some up-and-comers in the current research, such as Yanbiao Sun, will be the backbone of the rapid development in the future. In addition, we can easily conclude the active period of emergency logistics research in China, such as the period from 2013 to 2015. However, in recent years, the research activity has slowed down, and it needs to be paid more attention by domestic scholars.
3.2.2. Co-Occurrence Analysis of Core Research Organization
Visualization software Citespace 5.8.R3 is used to set node types as institution, and other settings remain unchanged. The knowledge graph is shown in Figure 4, and the top 10 research institutions in the number of publications are listed in Table 3.
The top 3 research institutions in terms of publication volume are Industrial Economic Research Department of the Development Research Center of The State Council, School of Business Administration of Chongqing Technology and Business University, and School of Management Science and Engineering of Chongqing Technology and Business University, with publication volume of more than 40. Universities and research institutions, as the two major groups of research institutions, are the main body and important position of scientific research innovation, which helps to promote interdisciplinary integration and construction. From the perspective of cooperation between research institutions, most exchanges and cooperation only exist between different universities in the same province or city, or between different colleges in the same university, but there is still a lack of cross-regional cooperation between universities in different provinces and cities. This will make it difficult to form a regional academic community of emergency logistics, and thus restrict the development of this field.
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Figure 4. Translated co-occurrence knowledge graph of core institutions.
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Table 3. Core Institutions in the field of emergency logistics research (TOP 10).
3.3. Analysis of Hot Spots of Emergency Logistics Research
3.3.1. Co-Occurrence Analysis of Key Words in Emergency Logistics Research
Visualization software CiteSpace 5.8.R3 is used to set node types as keyword, and other settings remain unchanged. The knowledge graph is shown in Figure 5. The data are further processed by Excel, and keywords with the same meaning
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Figure 5. Translated co-occurrence knowledge graph of keyword.
are merged, such as “site selection” and “site selection model” are merged into “site selection”, etc. The top 20 keywords in frequency and centrality are obtained, as shown in Table 4 and Table 5.
It can be seen that the keywords with the highest frequency in Table 4 is emergency logistics, followed by emergency supplies, natural disasters, site selection model and emergency, etc. The research mainly focuses on such keywords. Keywords such as demand forecast, two-level planning, emergency distribution and COVID-19 are the research hotspots in recent years. High centrality keywords in Table 5 include emergency, emergency logistics and military logistics, etc. The highest centrality keywords are emergency, which is the source of research in the field of emergency logistics, mainly including emergency logistics, military logistics and emergency management three main subjects. In terms of research methods, it focuses on the use of models and methods such as robust optimization, ant colony algorithm, genetic algorithm and AHP. In terms of research direction, it mainly focuses on emergency supplies, demand forecast, management system, operation mode, evaluation model and supply chain, which reflects the significance of emergency logistics.
3.3.2. Cluster Analysis of Key Words in Emergency Logistics Research
On the basis of keyword co-occurrence, this study clustering keywords through LLR algorithm recommended by professor Chaomei Chen, a total of 92 clusters are obtained, in which Q (modularity) = 0.8817, S (silhouette) = 0.9781. The data show that the clustering structure of keywords is significant (Q > 0.3), and the clustering effect is convincing (S > 0.7). In this study, the first 5 large and representative clusters were selected to draw the knowledge graph, as shown in Figure 6. After reading the core literature, the 5 clusters were summarized into 5 research topics, and their expansion was analyzed in detail.
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Table 4. High-frequency keywords of emergency logistics (TOP 20).
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Table 5. High centrality keywords of emergency logistics (TOP 20).
1) Emergency logistics network and information construction
Primary construction stage: Emergency logistics has a low level of informatization and systematicness in China, and lacks a good information platform. Therefore, the construction of information system centered on logistics network collaboration system is one of the keys in the construction of emergency logistics (Wei, 2010) . In the study of urban emergency logistics network, Zhao (2007) focused on the interaction structure of urban emergency management and logistics network, so as to realize the sharing of information resources and emergency supplies. From the perspective of national security strategy, strengthening the informationization construction of emergency logistics is also the top priority to accelerate its construction (Wang, 2009) .
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Figure 6. Translated cluster knowledge graph of keyword.
Adjustment and optimization stage: The frequent occurrence of emergencies makes the evaluation of emergency logistics capability gradually put on the agenda (Deng et al., 2010) . Xu et al. (2015) constructed an evaluation index system for the reliability of emergency supply chain from the aspects of information system and network structure. In view of the evaluation of dynamic network topology structure under emergencies, Zhu et al. (2018) proposed an evaluation method for cascade failure resistance of emergency logistics network based on CI-TOPSIS fuzzy multi-criteria group strategy. In addition, taking the May 12 Wenchuan earthquake as the background, Zhou et al. (2020) optimized the design of the traditional initial post-earthquake rescue emergency logistics network in consideration of the facility interruption scenario. However, the outbreak has typical unstructured characteristics, such as fuzzy diffusion boundary and dynamic time-varying situation. Based on this, Liu et al. (2020a) constructed a kind of innovative decision-making framework model for dynamic adjustment and optimization of emergency logistics network, so as to make continuous adjustments according to the actual situation.
2) Emergency logistics model and system
Emergent or abnormal nature is a significant mark that distinguishes emergency logistics from general logistics, which requires that the emergency logistics supply chain must have reliability (Wang et al., 2005; Zheng, 2009) . In view of this, Ji & Zhu (2007) established an optimization model of emergency logistics resource distribution to respond to the requirements of rapid distribution in emergencies and solve the problem of shortage of anti-disaster materials. A scientific, reasonable and fully functional emergency logistics system is the basic guarantee for responding to emergencies, and also an important work for the Chinese government to comprehensively improve the ability and efficiency of emergency logistics management (Li et al., 2012) . In the rescue of emergency supplies in major emergencies, Zhizhu Lai et al. (2020) established a multi-objective finalization model and a robust optimization model for the location of emergency logistics center, and studied the site selection of emergency logistics center and the transportation of emergency supplies. In addition, emergency logistics is an important support to deal with public health emergencies. Based on blockchain application, Li et al. (2020b) explored and improved emergency logistics under emergencies. Combined with the COVID-19 epidemic, Jiang et al. (2020b) analyzed the problems in China’s emergency supplies support and established a GOVERNMENT-led BCM emergency supply chain system.
3) Emergency management system construction and improvement
Wenchuan earthquake emergency response reflected some deficiencies in China’s emergency response system, such as the lack of emergency logistics coordination management system (Jing & Song, 2009) . It shows that a scientific management system is the basis for the effective organization of emergency logistics. Cheng (2010) pointed out the defects and problems existing in the operation of the current natural disaster emergency logistics management system, and proposed key tasks and measures to improve its operational effectiveness. At the same time, to comprehensively improve the ability to prevent and respond to emergencies, the construction of emergency management system should rely on the support of the emergency industry, and accelerate the formation of a scientific and technological support system for national public safety and emergency management (Liu & Li, 2012) . In the era of extensive application of modern information technology and the Internet, the outbreak of COVID-19 has brought challenges and opportunities to international emergency procurement management, and also provided good experience and practical cases for comprehensive summary of national emergency procurement plans in the future (Meng, 2020) . Through information update from the perspective of grid management, Qu et al. (2022) established a multi-stage time-constrained response-timeliness location model for emergency supplies distribution, which is conducive to the development of actual rescue.
4) Emergency logistics site-path model
After studying the core literature, it is found that the researches of domestic scholars on this topic mostly focus on the construction of site-path model. Huang & Xie (2009) combined ant colony algorithm and radial basis neural network to establish a location decision model of food emergency distribution center. To solve the location-path problem of disaster reduction system, Zeng et al. (2010) established a LRP model aiming at minimizing the total cost. Li et al. (2013) established an optimization model of multi-objective site selection and multimodal transport for post-earthquake emergency supplies distribution, so as to minimize the total time of emergency supplies distribution and the total loss of unmet emergency supplies at the disaster-hit points. In view of the uncertainty of emergency supplies demand and time of transportation vehicles between demand points, Wang et al. (2015a) set up a minimum time and cost minimization of dual stochastic programming model under the certain emergency restrictions, and establishes Sun et al. (2019) establish an emergency facility site-path robust optimization model with the goal of minimizing the sum of the rescue time of material delivery to demand points. From the perspective of COVID-19 prevention and control, Li et al. (2020a) established an emergency response decision-making model including multi-level collaborative storage location and logistics distribution, in order to cope with the uncertainty and dynamic change of demand for emergency supplies in public health emergencies.
5) Emergency supplies support capability
In the early practice of dealing with all kinds of major unexpected public events, China has had certain ability to support emergency supplies, but it still reflects the status quo of the relatively backward construction of emergency logistics system (Wei & Zhang, 2009) . In this regard, Wang & Wang (2012) proposed a coordinated optimization scheduling scheme for multi-period emergency supplies in multi-epidemic areas, and constructed a multi-objective stochastic programming model for a class of emergency logistics network optimization. Wang et al. (2013) constructed a multi-objective emergency supplies point selection model under transport capacity constraints, aiming at the shortest supply time and minimum supply cost. Efficient delivery of relief materials is a key link in emergency rescue of major public emergencies (Ma et al., 2013; Huang et al., 2021) . In view of the robust uncertainty of disaster relief information in the process of emergency supplies distribution, Zhu et al. (2016) constructed a multi-stage and multi-objective robust optimization model for emergency supplies distribution, and proposed a robust control strategy on this basis. Liu et al. (2016) constructed a multi-objective fuzzy LRP optimization model based on opportunity constrained programming, so as to effectively solve the fuzzy location-path problem of post-earthquake emergency supplies distribution. In addition, Zhang & Ni (2020) constructed a dual-objective optimization model of efficiency and equity to achieve a fair and reasonable distribution of relief supplies on the basis of considering that relief supplies can be delivered separately (Table 6).
3.4. Frontier Analysis of Emergency Logistics Research
On the basis of keyword co-occurrence, the first 24 burst words are counted in this study, as shown in Table 7.
It can be concluded that the intensity and span of burst keywords are different. The keywords with the greatest intensity were robust optimization, and the keywords with the longest time span were robust optimization and logistics activity.
1) In 2002, emergency logistics was still in its infancy in China, and the research in this field was in the basic stage (Sheu, 2007) . The sudden outbreak of SARS in 2003 has gradually transformed China’s emergency logistics management system from single disaster response to comprehensive and coordinated emergency management. The keywords that burst around 2002 disappeared before 2010.
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Table 6. Main clusters of emergency logistics research.
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Table 7. Burst keywords in emergency logistics (TOP 24).
2) Since 2008, major emergencies such as the Wenchuan earthquake have highlighted the important role of emergency logistics. With the explosive development of the logistics industry, emergency logistics has begun to “turn defense into attack” and gradually move towards comprehensive emergency logistics management (Liu et al., 2020b) . In this stage, the keywords of the logistics industry, path selection, construction, natural disaster and so on suddenly burst and become new research hotspots (Yong et al., 2017) .
3) At the end of 2019, COVID-19 swept across the country, bringing great challenges to China’s emergency logistics, and exposing many problems, such as incomplete management system, insufficient information synchronization, etc., which led to sudden burst in keywords such as COVID-19, COVID-19 vaccine and intelligent logistics (Jiang et al., 2020a; Hou & Jiang, 2021) .
At present, China is in a period of high incidence of emergencies and the coexisting situation of COVID-19 still exists for a long time. The research on pandemic response and improving intelligent logistics system will become the research frontier and development trend in the field of emergency logistics, which has a promising future.
4. Conclusion and Future Work
This research reveals the current research hotspots and future trends of China’s emergency logistics based on bibliometrics, and the main contributions are in the following aspects: 1) The active researchers, leaders and research institutions in this field are presented, and provide references for future scientific research cooperation. 2) Five major research hotspots in this field are summarized: the emergency logistics network and information construction, the emergency logistics model and system, the emergency management system construction and improvement, the emergency logistics site-path model, the emergency supplies support capability. 3) The prediction of future research trends of this field is provided: pandemic response and improving the intelligent logistics system. All these have great reference significance for finding the research trendency and pointing the research directions for scholars who are or will be engaged in emergency logistics research.
However, due to technical limitations, CiteSpace tool cannot process the literature data from the CNKI and WOS databases simultaneously. Therefore, we only analyzed the literature data of China’s emergency logistics research from the CNKI, and our future work will be focused on the above aspects.
Acknowledgements
This paper is supported by the Special Funds for Student Innovation and Entrepreneurship Training Program (http://gjcxcy.bjtu.edu.cn/, 202110555088), Philosophy and Social Science Foundation Youth Project of Hunan Province of China (19YBQ093), Scientific research project of Education Department (http://www.cutech.edu.cn/, No.20C1625), Natural Science Foundation of Hunan Province of China (http://kjt.hunan.gov.cn/zxgz/zkjj/, No.2018JJ2336), Philosophy and Social Science Foundation of Hunan Province of China (18YBQ105), Youth talents support program of Hunan Province of China (http://www.hunan.gov.cn/, 2018HXQ03), Key scientific research project of Education Department (http://www.cutech.edu.cn/, No.20A443), Social Science Key Breeding Project of USC (https://jgxy.usc.edu.cn/, 2018XZX16), Doctoral scientific research foundation of USC (https://www.usc.edu.cn/, No.2013XQD27).