Introduction

Information technology (IT) has changed the form of international trade, and the emergence of cross-border e-commerce (CBEC) has reduced the impact of distance on cross-border trade (Kim et al., 2017). With the advance of globalization, many IS/IT investments are deployed in organizations located in different countries and world regions to serve cross-border e-commerce (Romano and Pick, 2012). The prosperity of CBEC has greatly facilitated people’s life; more than 71% of European consumers choose to buy goods from overseas through CBEC (Cbcommerce, 2021). According to Cross Border Commerce Europe’s Top 500 Cross-border Retail Sales Report, cross-border trade sales in Europe grew by a whopping 17% to 171 billion euros in 2021. Meanwhile, CBEC also boosts the global economy, especially in China. Therefore, the Chinese government attaches great importance to CBEC and has formulated relevant policies to promote its development (Ministry of Finance of the People’s Republic of China, 2013; Ma et al., 2018), such as the tax rebate policy launched by the Ministry of Finance, the Belt and Road Initiative, and the CBEC incubator platform of The State Council. Besides, the COVID-19 pandemic has also accelerated the development of CBEC (Tolstoy et al., 2022).

The prosperity of CBEC has aroused the attention of scholars in various fields. These studies (Miao et al., 2019; Anson et al., 2019; Tolstoy et al., 2022; Goldman et al. 2021) cover strategy analysis, supply-demand matching, consumer behavior, exchange rates, SMES specialized research, marketing, etc. Literature reviews are the most direct way to understand a given academic field. For example, Giuffrida et al. (2017) conducted the review in the field of Chinese cross-border B2C e-commerce. Liu et al. (2021b) reviewed 60 CBEC papers from 2001 to 2020 to reveal the macroscopic risks and challenges in Chinese CBEC development. In addition, the last-mile delivery efficiency in B2C e-commerce, the consumer-to-consumer (C2C) e-commerce, and the sustainable logistics for e-commerce are the other hot subfields reviewed by the CBEC scholars (Mangiaracina et al., 2019; Yuan et al., 2021; Cano et al., 2022). The paper sets of the above researches are all under 100, which show that it is difficult to review too many papers with the literature review method. Besides, the reliability of literature review methods depends on experts’ understanding of the field, the quality of literature selection, and the ability of systematic review, which also leads to a certain subjectivity of literature review results. In contrast, bibliometric methods can process the larger paper set and extract more objective theoretical results from the objective data. Unfortunately, there are few bibliometric studies in the field of CBEC. Therefore, it is necessary to adopt the bibliometric method to specially study CBEC, a hot spot of e-commerce field.

Main path analysis (MPA) and science mapping method (SciMAT) are widely used in the research to reveal the knowledge structure and the academic evolution objectively in the given field. The MPA method can extract the key knowledge development tracks from the citation information of a large number of papers, while the SciMAT analysis can identify the important academic themes in the different periods of the selected field and the related evolutionary relationships. An integrated analysis combining MPA and SciMAT could not only grasp the knowledge development backbone but also present more academic evolution details in the CBEC field.

The main contributions of this study can be summarized as follows: first, a comprehensive approach combining MPA and SciMAT is proposed to explore the knowledge evolution of the CBEC field, and it enriches the research methods in this field. Second, quantitative identification and analysis of the knowledge development in the CBEC field can deepen the understanding of relevant researchers in the field of CBEC and help the CBEC practitioners better grasp the direction of future development.

The remainder of this study is designed as follows: the next section introduces the research methods used in the paper; In the “Results” section, the study results and relevant analysis are presented; the “Discussion” section discusses the findings in depth; in the end, conclusions aiming at the CBEC knowledge evolution are provided in the “Conclusion” section.

Methodologies

The accuracy of the original data set directly affects the reliability of the research result. Web of Science (WoS) is a significant citation database that records more than 8800 core academic journals. In addition, the WoS database is commonly used to conduct bibliometric researches. Therefore, we choose the WoS database as the data source in this study.

We refer to the relevant studies (Giuffrida et al., 2017; Hazarika & Mousavi, 2021) to ascertain search strategy. The searching query contains three keywords related to CBEC as shown below: “cross-border,” “e-commerce,” and “international.” It is worth noting that the keyword “logistics” also appears frequently in the relevant researches, but the adoption of it would introduce lots of papers unrelated to CBEC. In order to ensure the reliability of the results, our subject keyword only uses the professional word “Electronic Commerce” and its abbreviation. “International”, as a substitute for “cross-border,” is also taken into our query. The search strategy based on these keywords confirmed as follows: TS= (“Cross-Border Electronic Commerce”) OR (TS= (“Cross-Border”) AND TS= (“Electronic Commerce”)) OR TS= (“Cross-Border E-Commerce”) OR (TS= (“Cross-Border”) AND TS= (“E-Commerce”)) OR TS= (“International Electronic Commerce”) OR (TS= (“International”) AND TS= (“Electronic Commerce”)) OR TS= (“International E-Commerce”) OR (TS= (“International”) AND TS= (“E-Commerce”)). The document type is set to article and review. The specific database is limited to SCI-Expanded and SSCI and is consisted with the papers before 2023/03/31. The final dataset which contains 805 papers was collected on April 8, 2023.

As shown in Fig. 1, the whole research process can be divided into three steps. After downloading the given dataset, we import the relevant data to Histcite. This software would create a citation network with the given citation information. Brysbaert and Smyth (2011) found that scholars tend to cite their previous researches, whose purpose is to improve academic influence of their studies. Liu et al. (2019) showed that removing self-citation can effectively eliminates the impact of redundant links on the network. Therefore, it is necessary to eliminate the self-citations in the citation network to make sure the reliability of this study method.

Fig. 1
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Flow chart of research

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Finally, three different main paths are extracted to analyze the development trajectory of the field of CBEC. Meanwhile, we apply SciMAT to identify the research themes of different periods and explore the evolution relationship among them.

In short, the research process can be sketched as follows: the academic knowledge flow in the field of CBEC is structured through the citation network, and then the knowledge development process in the field is extracted by combining MPA and science mapping methods, so as to analyze the micro development trajectory of knowledge and the direction of macro academic evolution in the field of CBEC.

Main path analysis method

Main path analysis was first proposed by Hummon and Dereian (1989) to trace the main knowledge flow of the DNA field. Nowadays, it is commonly used in the bibliometric field to explore the main knowledge evolution trajectory. Academic research often appears in the form of papers, and the relationships among them are citations. This gives us reason to believe that citation relationships can represent the knowledge transfers among different researches or scholars (Yu and Yan, 2021; Yu et al., 2023a). In a citation network, papers are represented by nodes and directed links (the direction of links is from citing papers to references) between nodes mean citation relations among different researches (Liu et al., 2013; Yu and Hong, 2022). In short, paper A cites paper B means that study A inherits the knowledge of study B and makes more contributions on this basis; the knowledge diffuses in the citation network until hitting the current researches.

According to the bibliometric method proposed by Hummon and Dereian (1989), MPA can be divided into three steps: first, structuring a network with the citation information; second, conducting the selected algorithm to weight links in the citation network; third, identifying and extracting main paths according to different search strategies.

More details about MPA process are shown as following: there are mainly four weighting indices used in MPA method. NPPC (Node Pair Projection Count), SPNP (Search Path Nodes Pair, and SPLC (Search Path Link Count) were proposed by Hummon and Dereian (1989). On this basis, Batagelj and Mrvar (1998) developed a new weighting algorithm that has a better calculation rate, i.e., the SPC (Search Path Count) index. Therefore, we adopt SPC algorithm to transform the citation network into a weighted one. A simple network is shown in Fig. 2a to show the process of SPC algorithm. There are two sources (A and B) and four sinks (I, J, K, and E) in the network. Traversing the entire network from all source nodes to all sink nodes, the value of SPC is the times links have been traversed. For example, the SPC value of link C-F is 4, because there are 4 paths are consisted of it, namely A-C-F-I, A-C-F-J, B-C-F-I, and S-C-F-J.

Fig. 2
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Different main paths based on a simple citation network

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After step 2, a weighted citation network is created. Different approaches can be adopted to extract the main path. The first main path searching algorithm is local main path search (Hummon and Dereian 1989). This search strategy starts from the source nodes and select the links with the highest SPC value for each pathfinding until it reaches sink nodes. As shown in Fig. 2b, the local main path of the simple network is B-D-G-H-J and B-D-G-H-K. Relevant scholars further developed global main path search and key-route main path search (Liu and Lu, 2012; Liu et al., 2013). Different from the local main path search, the global main path search algorithm extracts the path with the highest sum of weights in the whole network. As shown in Fig. 2c, A-C-G-H-J, B-C-G-H-J, A-C-G-H-K, and B-C-G-H-K are the paths that have the highest sum of weights. Both local main path search and global main path search might miss some key citation links. Key-route main path search can avoid this issue; it starts with the most important links and searches the path backwards and forwards. The key-route main path in Fig. 2d contains all the links with the highest weight, namely B-D, C-G, and G-H.

In short, the global main path can extract the development backbone of a given field from a macro perspective, the local MPA can reveal more development details from another perspective, and the key-route MPA ensures the existence of all key developments. Therefore, all these different MPA methods are combined in this study to make sure that a significant and comprehensive academic development process can be extracted from dataset.

Science mapping analysis method

Science mapping analysis can help relevant scholars comprehend the knowledge structure, academic evolution, and hot research directions of a given field macroscopically. SciMAT is an open-source science mapping analysis software; it can identify the key academic themes evolution among different periods in a given field (Cobo et al., 2011). SciMAT method can visualize the selected dataset as two kinds of scientific maps, i.e., the strategic diagram and the thematic evolution diagram. As shown in Fig. 3, two schematic diagrams are presented to introduce the function of SciMAT.

Fig. 3
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Schematic diagrams of SciMAT

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In Fig. 3a, the strategic diagram is shown to present the research themes extracted from the same period. The horizontal axis represents centrality; it is an indicator measuring the external association of themes, namely the significance of themes in the whole academic field. The vertical axis is marked with the other indicator, density, which represents the internal strength of identified themes. In other words, the academic themes with high density have better internal developments. Therefore, the whole academic field can be divided into four quadrants. The first quadrant is “motor themes”; the themes in this domain have both high centrality and density which means that the themes in this quadrant have both important roles and are well developed. The second quadrant, “Highly developed and isolated themes”, has high density but low centrality. The themes in this domain develop well but have less relationships with the external researches. The themes in the “Emerging or declining themes” quadrant are commonly emerging or dying. The last quadrant is “Basic and transversal themes”; the researches in this quadrant play an important role in the given academic field while are at a standstill. The academic themes with these characters often play a basic role.

Compared with the static strategic diagram, the evolution map explores the dynamic evolution relations among the themes of different periods. A simple evolution diagram is shown in Fig. 3b; the whole field is divided into two periods with a dotted line. The spheres in thematic evolution diagram represent different academic themes, and their sizes are proportional to the number or G-index of relevant papers. The links among the themes of different periods stand for the academic evolution relationships in the given field. The thicker the links are, the stronger the academic evolution relationships are. As shown in Fig. 3b, the solid line means that the academic themes at both ends are the similar, while the dashed line means that the different topics at both ends have the same factors.

In short, SciMAT can effectively extract and classify the key themes of different periods, and identify the evolution relationships between themes in different periods, so as to analyze the evolution process in the given field (Yu et al., 2023b).

Results

MPA would be combined with the SciMAT method in this study to explore the knowledge structure and trace the academic trajectory in the CBEC field. We hope that we can strengthen the understanding of relevant scholars and provide some enlightenment for future research based on our study results.

MPA research

In this section, three different main paths are analyzed to trace the significant knowledge development trajectory. The MPA results are shown as a path map which is consisted of nodes and directed links. The nodes present CBEC papers and the links mean the citation relationships. In addition, the source nodes are marked in green and the sink ones in blue.

Global main path analysis

As shown in Fig. 4, the global main path contains 17 papers. It can be divided into four parts which represent the research hotspots in different periods, i.e., CBEC National Policy Research, International Logistics Research, Consumer Behavior Research, and CBEC Supply Chain Research.

Fig. 4
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Global main path

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The early studies which marked with blue shadow in Fig. 4 focused on the impact of the Internet on international trade, usually policy studies at the national level. The first node paper (Freund and Weinhold, 2004) conducted an empirical study containing 56 countries about the impact of Internet technology on international trade, and they found that the Internet had a significant effect on international trade. Bojnec and Ferto (2009) narrowed their research scope to OECD member countries and studied the impact of internet level on bilateral manufacturing exports. Pastuszak (2008) and Gokmen (2012) focus on a specific country and propose policy opinions on e-commerce development in Poland and Turkey from the perspectives of “e-gaps” and e-commerce application respectively. At this stage, the papers mainly analyzed the development strategy of CBEC from the national perspective, but the overall trend was from macro multi-country research to micro country-specific research.

Subsequently, scholars paid more attention to the specific problems in the field of CBEC. International logistics, as the key link of CBEC, undoubtedly becomes a research hotspot in this field (the green shadow in Fig. 4). Wang et al. (2015) investigated the factors affecting international logistics performance with confirmatory factor analysis and structural equation modeling methods. Giuffrida et al. (2017) reviewed the current researches of logistics in the CBEC of the Greater China and identified a number of promising directions.

The other research hotspot in the CBEC field is consumer behavior research, which marked with the purple shadow in Fig. 4. Zhu et al. (2019) structured a three-stage model to evaluate the influence of product cognition level on the CBEC purchase intention. Based on the previous research, Mou et al. (2020) found that the product description does not have a direct impact on purchase intention but affects consumer purchase intention through the intermediary of product involvement. There is no doubt that the product cognition and description may affect consumer purchase intention. Therefore, Rui (2020) applied image recognition and deep learning methods to optimize the CBEC product classification system. Obviously, the application of IT in the field of cross-border trade has generated a large amount of product transaction data that can be analyzed, which is conducive to relevant scholars to analyze consumer behavior, so as to optimize product classification and strengthen consumers’ product cognition.

The supply chain theory originates from the integration of logistics system and advanced manufacturing industry (Yu and Ye, 2023), which becomes the current research frontiers in the CBEC field (the yellow shadow in Fig. 4). Liu et al. (2021a) explored the influencing factors of cross-border e-commerce supply chain resilience, which helps ensure the safe operation of cross-border e-commerce supply chain. The rest studies based on Liu et al. (2021a) focused on the supply chain optimization, the supply chain integration, the transportation mode selection, the technological innovation, the supply chain risk assessment, and the supply chain strategy analysis (Zhang et al., 2021; Zhou, 2021; Lu et al., 2022; Nie, 2022; Deng and Ouyang, 2022; Fang and Wang, 2021; He et al., 2022).

According to the global main path, the development trajectory of CBEC is clearly presented; CBEC originates from the application of IT in international trade. This can be seen as a subversive innovation of IT in the field of cross-border business. Alt and Zimmermann (2014) proposed that such technology-led business innovation is accompanied by the development of IT. Bawack et al. (2022) also affirmed the role of IS in promoting the development of e-commerce and emphasized the key position of AI technology in the current e-commerce field. Early papers focused on the policy studies at the national level. The subsequent research hotspot is CBEC logistics system, while the latest research paid more attention on the higher-level supply chain system. In addition, the consumer behavior research is another recent research hotspot. The relevant information of global main path papers is presented in Table 1.

Table 1 The information of papers in global main path
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Local MPA and key-route MPA

Compared with the global main path, there are some different findings in this section. Specifically, two other CBEC academic origins are identified by local MPA and key-route MPA.

The academic origin identified by the local MPA is the applicability of culture. Baack and Singh (2007) studied how culture applies to network communication in order to conceptualize its impact on internet marketing. Since cultural factors affect e-commerce behavior differently across regions, it is difficult to implement a localization and standardization strategy for CBEC. Based on an “adaptive strategy”, Alhorr et al. (2010) proposed that the CBEC localization and standardization should be approached with flexibility.

As shown in Fig. 5, the two researches (the nodes in yellow shadow) that differ from the ones of the global MPA in the local main path showed the other origin affecting the CBEC development. Based on the localization and standardization problems faced by CBEC, relevant scholars conducted researches. They believe that culture is an important factor affecting CBEC and emphasize that the performance of e-commerce in different cultural backgrounds should be considered, and the localization and standardization of CBEC should be solved based on the “adaptation strategy.”

Fig. 5
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Local main path

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The key-route MPA identifies a different origin path in the CBEC field, namely internet marketing research. Chao et al. (2003) analyzed the reasons why Asia-Pacific countries have made great achievements in economy and become the contemporary global marketing hegemons, emphasizing the significant influence of technological innovation, Internet, and e-commerce on Asian multinational enterprises. Wood (2004) studied the positive role of the Internet in marketing activities and proposes two development paths: state-led infrastructure development and enterprise-led entrepreneurship. Considering that the rat competition of global e-commerce strategic deployment, Samiee (2008) proposed that enterprises should formulate and implement the CBEC marketing strategies in line with the competitive environment. Jean and Sinkovics (2010) emphasized the role of IT in improving the relationship performance between enterprises in emerging countries and their international supply chain partners. While e-commerce brings opportunities to firms, it also comes with risks and challenges, especially for SMEs (small and medium enterprises). Pezderka and Sinkovics (2011) integrated traditional international risk theory and emerging e-commerce risk view to discuss the online-offline risk tradeoff in SME online internationalization decision. Interestingly, the research object of this stage still has a change from macro to micro, that is, from the early research on global marketing of Asia-Pacific countries to the CBEC marketing strategy of enterprises to the current SME cross-border e-commerce research.

The path (the five nodes marked with yellow in the grey shadow as shown in Fig. 6) different from the above two main paths in key-route main path emphasizes the influence of IT, especially the Internet, on international marketing. The CBEC scholars affirm the positive impact of technological innovation on global marketing and put forward the theory of marketing strategy and risk-decision based on firm in this context.

Fig.6
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Key-route main path

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In conclusion, the CBEC policy research and Internet marketing research together form the knowledge base of this field. The former includes strategic research from national perspective and cultural perspective. The latter is based on the application of the CBEC information technology to explore enterprise strategic direction. Current CBEC researches pay more attention on practical problems, mainly about consumer behavior research and supply chain optimization. In short, the development of CBEC shows a trend from macro theoretical analysis to micro applied research. The impact of IT on traditional cross-border business ecology has prompted relevant scholars to study universal CBEC theories, such as national CBEC development strategies and global marketing case studies of Asia-Pacific countries. With the development of CBEC field, the current scholars pay more attention to specific applied research at the enterprise level, such as supply chain management and consumer behavior research. Combining three different MPA results, a comprehensive CBEC academic development network is presented for us to grasp the main knowledge flow, identify the study hotspots of different periods, and forecast the future development path of the CBEC field.

Science mapping research

In this section, SciMAT is applied to explore the theme evolution of CBEC. According to the publication distribution of given dataset, from 1995 to 2018, the CBEC researches were in a stable and gentle development state. While from 2019 to 2023, the researches in this field increased sharply. Therefore, this paper divides the period from 1995 to 2018 into two periods equally, which serves as the basis for the development of this field. The period 2019–2023 is grouped into a sole period to identify current research frontiers. In short, the whole time-span is divided into three parts, namely 1995–2006, 2007–2018, and 2019–2023.

Analysis of strategic diagram

The co-occurrence method is used to identify the academic themes in the CBEC field. The keywords which are too common to extract useful information are eliminated in our study, such as “e-commerce,” “cross-border e-commerce,” “electronic-commerce,” “framework,” “performance,” and “management”. Meanwhile, the keywords that share the same meaning are identified as one keyword, for example, “supply chain” and “supply chains,” “logistics,” and “cross-border logistics”. In addition, the themes are marked with the g-index score which is proportional to the theme sphere size.

The first period (1995–2006)

As shown in Fig. 7, the strategic diagram in the first period contains five key research themes which are all located in the first and third quadrants: culture, innovation, market, internet, and information-technology.

Fig. 7
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The strategic diagram of period 1

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The theme market has the highest g-index score. As the most important research theme, it also has high centrality, which indicates that the market has a very important position in the period 1. In addition, the market has always been the focus of economic and management scholars. Therefore, this leads to the emergence of a large number of market studies on CBEC in the first stage, which mainly focus on the analysis of the impact of e-commerce on marketing.

The other two themes in the first quadrant are culture and innovation. The theme innovation has the highest centrality, this shows that the theme is at the core of the whole field, namely it is related to most of other themes. In the first period, researches in the innovation theme are divided into two parts: one is technical innovation and the other is marketing innovation under the background of CBEC. There is no doubt that the innovation research in the first period is promoted by Internet technology. Scholars devote themselves to upgrade and iteration of the traditional international trade mode through technological and corresponding marketing innovation. The density of the research theme culture is the highest. It means that the internal development of culture is flourishing. Compared with its significant density value, the centrality of culture is not too high which means that the studies on this theme are isolated comparatively.

There are two themes in the “Emerging or declining themes” quadrant, i.e., internet and information-technology. They are both emerging themes without doubt. IT is the driving force of CBEC; it contains computer technology, network technology, and communication technology. The Internet belongs to IT, but given that it is the direct factor that led to the creation of CBEC, we separate it as a sole theme to explore more evolution details. The first quadrant focuses more on the strategy research, while the third quadrant of emerging research focuses more on technology. This heralds a shift from theoretical analysis to technical application in the CBEC field.

The second period (2007–2018)

The second period contains eight academic themes, i.e., resource-based-view, word-of-mouth, culture, risk, big-data, online-shopping, innovation, and strategy (Fig. 8).

Fig. 8
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The strategic diagram of period 2

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The most significant theme in period 2 is big-data which is contained in the third quadrant. As an emerging academic theme, big-data has a well internal development and centrality comparatively. The rapid development of e-commerce generates a large amount of transaction and market data, which provides a prerequisite for the emergence of big data technology. Relevant scholars try to mine useful information to promote the development of CBEC by analyzing the huge e-commerce data. There is no doubt that the big-data technology is the main driving force of CBEC in the second period.

The development of research themes of the first quadrant in the period 1 experiences a slowdown in the period 2. Most of the strategic research themes in period 1, such as market, turn to a basic and transversal theme in period 2, namely strategy. So it is with Innovation, and they together lay the foundation of research in the field of CBEC to provide theoretical guidance for future researches. It is worth noting that although the density and the centrality of culture both declines, it is still an academic hotspot.

The themes of the first quadrant in period 2 are online-shopping, resource-based-view, and word-of-mouth. The theme having the best development is online-shopping, as the key link in the CBEC field; it has naturally attracted great attention from relevant scholars. Resource-based-view has the second highest density, which illustrates that the importance of resources is increasingly recognized by scholars and enterprises. At the same time, the strategic decision based on the resource perspective will also encourage enterprises to adopt e-commerce technology to acquire and allocate resources in the network era. The theme word-of-mouth is the other hotspot which has both high density and centrality in the first quadrant. This is due to the surge of trade in the e-commerce environment and the access to word-of-mouth data made possible by IT.

The other highly developed and isolated theme is named risk. It is very isolated, which means that the CBEC risk has raised attention of few scholars in the context of the rapid development of CBEC. But the risk research is still one of the academic hotspots in this period.

The third period (2019–2023)

The strategic diagram of period 3 is used to identify the CBEC themes of research front (as shown in Fig. 9). There are eight themes evenly distributed in different quadrants: competitive-advantage, purchase-intention, and product in quadrant 1; small and medium-size enterprise(SMES) in quadrant 2; decision theory and logistics in quadrant 3; and investment and internet in quadrant 4.

Fig. 9
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The strategic diagram of period 3

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The theme investment earns the highest g-index score in period 3. This marks the beginning of the maturity of the CBEC field. The influx of capital into the CBEC industry reflects the continuous positive development of the industry, which attracts the attention of a large number of scholars. In addition, the high centrality and low density of investment mean that it is a basic and transversal theme. Therefore, researches of investment would play a basic role to provide strategic guidance for the future development of CBEC. The other basic and transversal theme is internet. Combined with the themes of the previous period, it is clear that the foundation of the CBEC field has realized the transformation from market strategy-led to IT-led. In addition, internet has the highest centrality which means it has the densest external connections. There is no doubt that the internet technology has penetrated into every aspect of CBEC and been the most important cornerstone of this field.

There are three motor themes having both high density and centrality, namely competitive-advantage, purchase-intention, and product. Some useful information could be explored from them: first, the prosperity of CBEC is accompanied by risk, which is also the research purpose of relevant scholars, i.e., analyzing risk to gain competitive advantages and promote better development of CBEC; second, the purchase-intention and product verify the conclusion of MPA, i.e., the current research hotspot is the study of consumer behavior, which is attributed to the huge data acquisition of consumer behavior in the context of the Internet. How to optimize the product system to enhance the purchase intention of consumers has become the core issue in the field of CBEC.

The only isolated research theme is SMES. It indicates that under the background of the increasingly complete e-commerce system of large enterprises, the SMES with large number have become the hotspot in the CBEC field.

The “Emerging or declining themes” quadrant of period 3 contains the themes logistics and decision-theory. The logistics is undoubtedly the emerging theme which is the one promoted by big-data technology under the context of supply chain system; it is fundamentally different from the traditional research on logistics and transportation. The theme decision-theory in period 3 is declining; it means that big data technology is gradually replacing the traditional market-based decision theory to guide the development of the CBEC field.

Analysis of evolution map

Based on the academic themes identified with the strategic diagram, the evolution map analysis can further explore the evolution relationships and development process among these themes in the CBEC field dynamically. As shown in Fig. 10, the theme evolution map can be divided into five different thematic clusters: (1) Culture and risk; (2) Marketing innovation; (3) Technology innovation; (4) Market strategy; (5) Information technology.

Fig. 10
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Theme evolution map

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The themes of different periods show a trend from relative isolation to deep integration over time. According to the fusion trend of the theme, the whole theme evolution map can be divided into two parts: one is Business Marketing Research which consists of Marketing innovation and Culture and risk; the other three thematic clusters, Technology innovation, Market strategy, and Information technology, constitute another research direction, namely Technology-Driven CBEC Research. In short, although the various themes in the current CBEC field are closely linked, some research still focuses on marketing research, while most research focuses on the application of IT in the CBEC field.

The theme Culture is the origin of the thematic cluster Culture and risk marked with blue (as shown in Fig. 10). In the second period, the research popularity of Culture declined, but it evolved into another academic theme, namely Risk. This shows that cultural adaptation brings great risks to the field of CBEC, which has attracted the attention of relevant scholars. The theme Risk has a big impact on themes purchase-intention and SMEs in period 3; it emphasizes the current hot directions of the CBEC risk research. It is worth noting that both Culture and Risk have direct influence on the theme Decision-theory. This shows that cultural adaptation and risk have been the key factors influencing the decision-making behavior of the CBEC enterprises.

Innovation is a key academic theme in the first period. Its highest centrality means that innovation thinking is ubiquitous in the CBEC research field. The theme innovation developed in two thematic clusters in the subsequent periods, one is Marketing innovation which is marked in yellow and the other is technology innovation marked in purple (as shown in Fig. 10). Considering the evolution of the first development direction, innovation has the strongest contact with resource-based-view in period 2 and competitive-advantage in period 3. It means that the development of the CBEC field is conducive to the integration of global resources. In this context, it has become the consensus of relevant practitioners and scholars to adopt the resource-based view of resource allocation to obtain competitive advantages. Innovation has a significant influence on SMES in period 3. Considering Risk, the other theme having great influence on SMES, this indicates that coping with the CBEC risks through innovation has become an important way for SMEs. Given the availability of word-of-mouth data in the internet age, it is an integration innovation of marketing theory and IT in the CBEC field to improve the marketing level of relevant enterprises and enhance purchase intention by analyzing word-of-mouth data.

The other evolution direction is technology innovation. The development of IT has directly promoted technological innovation in the CBEC field. There is no doubt that the emerging theme of the second period, big-data, has been the technological base in the field of CBEC. The theme most affected by the big-data technology is the CBEC logistics. By analyzing the data of the entire supply chain system of CBEC to reasonably plan the path and flow, logistics performance can be effectively improved. In addition, big-data evolves into Investment, Product, and Internet in period 3. It is worth emphasizing that the Big-data-driven Internet of period 3 is different from that of period 1.

Themes Market is the origin of the thematic cluster market strategy (as shown in the green area of Fig. 10). Market research is ancient and sensitive; the emergence e-commerce has injected new vitality into the market research. Market researches under the background of CBEC developed into the knowledge foundation in period 2, namely the theme strategy. In the third period, the theme strategy mainly evolutes into two academic themes, namely Investment and Internet. It means that the CBEC investment is still decided by market; meanwhile, strategies from the market also affirm the role of Internet technology in the CBEC field.

The last thematic cluster marked with brown in Fig. 10 is Information-technology. According to the evolution trace of Information-technology, some interesting findings can be concluded. First, online-shopping, which evolved from information-technology and market, has impact on all academic themes of the thematic cluster Information-technology in period 3. This emphasizes the key role of online-shopping in the CBEC field, although it is not a hot academic theme in the current period. Second, the development of IT influences the CBEC strategy and thus the later academic themes.

From a macro perspective, the CBEC Business Marketing Research originates from the cultural-adaptive risk and resource-based view, and there are two current research hotspots: one is the competitive advantage of CBEC (based on cultural-adaptability and resource-based view) and the other one is consumer behavior research (based on CBEC risk research). Considering the technology-driven CBEC research, the main driving force of its development is Internet-based big data and market-based strategy, the current research focuses on Internet technology, product research, and logistics system.

Discussion

In the Internet era, the international trade mode based on IT, namely CBEC, has gradually replaced the traditional cross-border trade mode. The emergence of a large number of relevant studies makes it difficult for scholars to accurately grasp the development process of the CBEC field, identify important researches in this field, and explore relevant research hotspots. The purpose of this study is to review the important development process of the CBEC field through bibliometric method and dynamically identify the research hotspots in this field to provide reference and inspiration for the future researches. In this study, the MPA method is used to extract the main academic development trajectory, and science mapping analysis is applied to identify the key research themes and their dynamic evolution relationships.

Three different MPA methods are used synthetically to trace the path of knowledge evolution in the CBEC domain. The global MPA results show that the early CBEC researches focus on the internet influence and relevant strategies for international trade based on the national level, and subsequent researches pay more attention on the CBEC logistics system which reflects the importance of logistics system construction in this field. The research frontier which is driven by IT focuses on two directions: one is the researches of market-based consumer behavior; the other one is the research of supply chain system, which can be understood as the innovation and expansion of the traditional logistics system. The academic evolution of the CBEC field shows a development trend from macro research to micro research. The former is based on the global or national level to study the impact of Internet technology on business and trade to put forward strategic guidance. During this period, the integration of IT and international trade was in its infancy. The latter is more professional and has strong application. In addition, both market research and supply chain system construction are deeply integrated with IT. In short, the whole development track of CBEC reflects the integrated development process of IT and international trade.

The other two academic origins of CBEC, culture and marketing, are identified by the local MPA and the key-route MPA. Cultural differences are an important obstacle in the development of CBEC. Scholars have found that culture has adaptability in network communication and thus influences network marketing, while CBEC is bound to be affected by global cultural differences (Baack and Singh, 2007). Therefore, the concept of cultural compatibility theory was proposed to address the challenges of cultural differences in CBEC (Alhorr et al., 2010). The result from SciMAT also proves that improving cultural adaptability can bring competitive advantages to enterprises, which has become the current research hotspot.

The emergence of e-commerce has greatly promoted the economic development of all countries, especially the Asia-Pacific countries represented by China. Relevant scholars conducted research on this issue and concluded that technological innovation and the application of Internet technology can effectively improve the global marketing ability. Therefore, enterprises around the world accelerate the deployment of e-commerce strategies to enhance competitive advantages, such as global marketing capabilities, which also intensifies the global business competition. It thus led to the rise of risk researches of CBEC, especially the ones aiming at SMES.

According to MPA, some conclusions could be got as follow: first, the CBEC academic field has its roots in the impact of Internet information technology on international trade; this confirms the findings based on ecosystem theory, i.e., the impact of Internet technology and globalization marketing on traditional business ecology has prompted the birth of cross-border e-commerce (Xi et al., 2023; Wang et al. 2021). Besides, cultural adaptation and online marketing contribute to the early development of CBEC; second, logistics system and supply chain play an extremely important role in CBEC which can be confirmed not only in the early logistics construction of CBEC, but also in the current CBEC supply chain system optimization; third, purchase intention analysis and product classification study based on e-commerce platform have become hot topics in the CBEC field; fourth, there is an interesting finding that most of the early CBEC studies were in Europe and America, while the current studies are mainly in Asian region. We believe that this academic development process from Europe and America to Asia is continuous. CBEC originated from the early European and American scholars’ macro thinking on the development strategy of cross-border trade, which formed the research basis of this field and also influenced the development direction of specific applied research in the future. For example, Early European and American scholars studied the impact of distance on cross-border trade in the context of the Internet and found that the application of CBEC greatly reduced the impact of distance on cross-border trade (Bojnec and Ferto, 2009; Gomez-Herrera et al. 2014), while subsequent Asian studies focused on the optimization of CBEC logistics system to better weaken the adverse impact of distance on international trade. Last but not least, the earlier research methods were mostly case analysis and theoretical research, while the current researches, especially the ones related to the CBEC supply chain, generally adopt the decision theory. In addition, the most advanced information technologies widely applied in CBEC include the following: the blockchain technology (for cross-border supply chain system construction), the computer vision (for product classification), the machine learning method (for product classification and purchase intention analysis and prediction).

The academic themes with different characters can be identified with the strategic diagram analysis of SciMAT. Some useful information is explored as shown below: (1) the information technology has always promoted the development of the CBEC field. At present, the Internet technology with the highest centrality has become the core of this field, playing the most important fundamental role. (2) The competitive-advantage is the most important motor theme in period 3. We can conclude that the prosperous development of CBEC not only attracted the attention of capital, but also accompanied with competition and risk. How to avoid risk, make reasonable investment and gain competitive advantage has become the core goal of the current CBEC research. We believe that IT innovation, especially big-data based internet technology, will remain the optimal solution to achieve this core goal because such innovations in CBEC might be disruptive considering the fundamental role of the IT. (3) The purchase-intention with the second highest g-index score is another research hotspot which benefits from the application of big-data technology. However, this positive influence is not direct. Relevant scholars are committed to optimizing the product system of CBEC with the help of big data technology, so as to enhance consumers’ purchase intention, which is different from the traditional consumer behavior research.

According to the dynamic evolution process of the CBEC field presented in the theme evolution map, not only can we construct a knowledge development network in this field to deepen our understanding of the CBEC field, but we could also gain some insights from the evolution relations to guide future research. Some promising research directions are presented as follows:

  • CBEC culture adaptability research: both MPA and SciMAT results emphasize the role of culture. MPA finds that culture adaptability is one of the origins of the CBEC field, but the current researches rarely consider this important factor. Combining with the result of SciMAT that culture has great impact on the theme competitive-advantage, and themes internet and information-technology have evolution relationship with culture, we can conclude that how to combine IT and marketing innovation to improve the CBEC culture adaptability may be a study hotspot related to gaining competitive advantage.

  • CBEC supply chain structure and management: evidence from the MPA shows that both early logistics system construction and current integrated supply chain management play an extremely important role in the field of CBEC. Meanwhile, the relationship between Big-data and Logistics in SciMAT result shows that the big-data-based logistics has been a hot emerging theme in the CBEC field. Thus, how to build supply chain system based on big data technology and how to realize supply chain management under the cross-border background will become the hot research direction in the future.

  • Research on data-driven consumer behavior: the evidence from SciMAT shows that the theme big-data has evolution influence both on product and purchase-intentions. The researches in main path also verify the positive impact of big-data technology on consumer-behavior research. Therefore, it is promising to construct and optimize product system to enhance product description and cognition based on big-data technology, thus stimulating consumers’ purchase intention.

  • CBEC information technology based on big data: thanks to the big data technology of period 2, Internet technology can still maintain a prominent position in the current research. Meanwhile, there are a large number of applications of big-data technology in period 3. The MPA result also underlines the role of big-data application in consumer behavior and supply chain management. In this context, it is necessary to develop the CBEC application information technology based on big data.

Conclusion

Thanks to the development of IT, the form of international trade has undergone an essential change, and CBEC has greatly promoted the global economic development and trade connections. This has attracted lots of attention from scholars which leads to the appearance of abundant CBEC researches. These studies cover different aspects of the CBEC field, containing macro policy, micro consumer behavior, logistics and supply chain system, specialized research for SMES, etc. It is difficult to understand and grasp the knowledge structure in such a flourishing and complex academic field. We integrate the MPA and SciMAT methods to grasp the knowledge development of the CBEC field.

Combining three different MPA methods, main knowledge evolution trajectories of different perspectives are extracted to structure the comprehensive academic development path. The academic field of CBEC originates from the collision and integration of Internet technology and international trade. Compared with the earlier CBEC studies, the later CBEC studies were the product of the deep integration of cross-border trade and IT. Two other origins that have a significant impact on the development of CBEC are culture compatibility and online marketing. The research direction that occupies the most important position in the field of CBEC is logistics system, whether it is the early logistics system research or the current integrated supply chain system construction. The MPA results confirm the challenges of the current development in the CBEC field, for example, Ding et al. (2017) conducted a systematic review of CBEC academic field and concluded that culture, consumer behavior, laws, product and marketing, and especially logistics are the main obstacles to CBEC. This not only helps to predict future academic development, but also points the way for CBEC practitioners. For enterprises, they should pay more attention to the construction of CBEC supply chain system, the analysis to the big data of consumer behaviors, and the application of AI technologies in CBEC system (for instance, developing the new CBEC product classification system with image recognition and deep learning technologies). For relevant institutions, it is necessary to improve laws and regulations, optimize product and trade supervision, and improve management efficiency to further release the potential of CBEC (Liu et al., 2021b).

According to the result of science mapping analysis, the key academic themes of different periods are identified and their evolution relations are presented. Early research focuses on culture, market, and innovation, meanwhile emerging themes such as information-technology, internet, and online-shopping highly promote the development of CBEC. The identified research themes in the early stage verify the results concluded from MPA, i.e., the development of IT forces the transformation of international trade. The emergence of new cross-border trade forms had also aroused the exploration of relevant scholars, whose research focuses on cultural adaptation, technological innovation, Internet marketing, market, and related strategic analysis. In other words, these theme keywords of early period constitute the academic origins of the CBEC field. Subsequently, macro themes such as policy studies declined in popularity, but they became the fundamental theory guiding the development of the CBEC field. At present, the development of CBEC is in a mature stage with both risks and opportunities and driven by information-technology. Therefore, current research focuses on two broad directions, i.e., the business marketing research and the technology-driven CBEC research. According to the evolution relations of the CBEC field, the academic themes of the whole period can be divided in to five different theme clusters. Through the analysis of these clusters, we can explore more details of the academic evolution of CBEC to deepen our understanding of this field.

There is a limitation, the dataset source, existing in this study. We collect the citation information through WoS. It cannot contain all papers in the CBEC academic field. In the future, scholars could apply more databases to do relevant researches with larger data size. Besides, the natural language processing (NLP) method based on neural network, such as Latent Dirichlet Allocation (LDA), could be used to explore the development process and theme evolution of the CBEC field.