From click to Cargo: The role of digitalization, cross-border e-commerce, and logistics in deepening the China-Africa trade

Borojo, Dinkneh Gebre; Weimin, Huang Article From click to Cargo: The role of digitalization, cross-border e-commerce, and logistics in deepening the China-Africa trade Economies Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Borojo, Dinkneh Gebre; Weimin, Huang (2025) : From click to Cargo: The role of digitalization, cross-border e-commerce, and logistics in deepening the China-Africa trade, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 13, Iss. 6, pp. 1-33, https://doi.org/10.3390/economies13060171 This Version is available at: https://hdl.handle.net/10419/329451 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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From Click to Cargo: The Role of Digitalization, Cross-Border E-Commerce, and Logistics in Deepening the China–Africa Trade. Economies,13(6), 171. https://doi.org/ 10.3390/economies13060171 Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). Article From Click to Cargo: The Role of Digitalization, Cross-Border E-Commerce, and Logistics in Deepening the China–Africa Trade Dinkneh Gebre Borojo * and Huang Weimin * Yiyang Vocational and Technical College, Yiyang 413049, China *Correspondence: [email protected] (D.G.B.); [email protected] (H.W.) Abstract: Enhancing digital connectivity, advancing cross-border e-commerce (CE), and optimizing logistics performance (LP) are fundamental pillars for boosting trade flows between trading partners. However, the multifaceted impacts of digitalization, CE, and LP on China–Africa (C-A) trade remain underexplored. Therefore, employing the gravity model, this study examines the impacts of digitalization, CE, and LP on C-A trade using data on Chinese trade flow to 53 African countries from 2007 to 2023. Further analysis is conducted by accounting for African countries’ income, population, resources, and institutional heterogeneity. We also control for the impact of digitalization and logistics performance distance between China and African countries on C-A trade. The findings provide evidence that the digitalization of African countries and China significantly enhances C-A trade. Moreover, CE and LP improvements in China positively affect C-A trade, revealing that promoting the sustainable development of CE and LP can lead to increased trade integration between China and African countries. Furthermore, the effects of digitalization, CE, and LP on C-A trade are influenced by heterogeneity in the income level, population size, and institutional performance of African countries, revealing more beneficial effects in middle-income countries, more populated countries, and countries with better institutional quality. Policy suggestions are forwarded based on the findings. Keywords: digitalization; cross-border e-commerce; logistics performance; China–Africa trade; gravity model 1. Introduction China has emerged as Africa’s largest trading partner, surpassing the continent’s traditional trade allies (M. Miao et al.,2020;Usman & Tang,2024;Shao et al.,2025). Although trade relations between Africa and China date back many years, the past two decades have witnessed unprecedented growth in their trade exchanges (M. Miao et al., 2020). Trade between China and Africa has expanded at the most rapid pace since 2000 (M. Miao et al.,2020). More specifically, the speed and scale of China–Africa (C-A) trade growth have outpaced those of the United States (US) and most of the European Union (EU) economies, reshaping the continent’s economic landscape. The volume of C-A trade outpaced US–Africa (US-A) trade and is approaching surpassing Africa’s trade with the EU member countries (Figure 1). Consequently, the C-A trade relationship has achieved a remarkable compound annual growth rate of 24.7% over this period, exceeding USD 260 billion in total bilateral trade. More specifically, Chinese exports to Africa registered USD 172.45 billion, imports to African countries registered USD 89.77 billion, and total trade exceeded USD 261 billion in 2023 (Figure A1). Moreover, China has progressively Economies 2025,13, 171 https://doi.org/10.3390/economies13060171 Economies 2025,13, 171 2 of 33 established trade relationships with over 50 African nations and regions, formalizing bilateral trade agreements with more than 40 countries (Ya & Pei,2022). - 50.00 100.00 150.00 200.00 250.00 300.00 350.00 400.00 450.00 Total trade Trade in blTrade USD) Year C-A EU-A US-A Figure 1. Comparison of C-A trade with major trade partners (US and EU). Source: Authors’ computation using data from the China–Africa Research Initiative and EUROSTAT. While Africa’s exports to China remain largely dominated by raw commodities, the composition of these exports is undergoing a notable shift. For instance, China’s oil imports from Africa are decreasing as the country increasingly sources crude oil from Gulf Cooperation Council states, Russia, and other Asian nations. Additionally, a growing trend that could significantly influence the A-C trade dynamic is the rising export of semi-processed agricultural products from African countries (Usman & Tang,2024). Moreover, existing studies argued that C-A trade dynamics and increased growth of C-A trade are explained by resources, institutional, geographical, economic size, and other socio-economic determinants (Ya & Pei,2022;Gold & Rasiah,2022;Landry,2024). However, the dynamics of C-A trade flow can also be determined by recent technological developments such as digitalization, cross-border e-commerce (CE) development, and trading countries’ logistics performance (LP). Therefore, C-A trade flow can be explained by these variables, as international trade is mainly reliant on the variables that facilitate trade and lower trade costs, including communication technology, e-commerce, and LP (Bugarˇci´c et al.,2020). Empirical research contended that the increase and adoption of digital technologies (hereafter digitalization) is one of the most vital technological transformations in history, impacting economic activities worldwide (Labhard & Lehtimäki,2022). It refers to applying digital technologies, including mobile phones, laptops, computers, and other digital devices, across various domains such as economic and commercial activities, financial and banking operations, public administration, and service delivery (Kere & Zongo,2023). Therefore, the rapid advancement of information and communication technology (ICT) and the progression of digitalization have significantly influenced trade relationships between countries, promoting access to foreign markets (Bellucci et al.,2023;Herman & Oliver,2023). Furthermore, as a specific form of digitalization, CE has been a significant development trend in international trade. CE refers to cross-border logistics transactions involving multiple parties from different customs regions facilitated through e-commerce platforms and represents a contemporary model of international trade (Ai et al.,2016;Peji´c-Bach, 2021). Global CE transactions have experienced significant growth in recent years (Li & Li, Economies 2025,13, 171 3 of 33 2024). The shift toward borderless trade will also have a significant impact on global trade patterns (Y. Chen et al.,2022). Thus, with the continuous development of digitalization, trade between countries has grown closer and contributed to the development of countries (Y. Chen et al.,2022). From a practical standpoint, digitalization is advancing rapidly in China and Africa, with Africa making remarkable progress over the past decade. Hundreds of millions have gained internet access and embraced digital services like mobile payments (WB,2024). This transformation began with the introduction of M-PESA in Kenya in 2007 (Kere & Zongo,2023) and has been fueled by widespread smartphone adoption, which reached 64% in 2021, alongside other mixed technologies (Kere & Zongo,2023). These advancements significantly bolster digitalization and facilitate trade flows. Internet usage in Africa has also risen dramatically, from less than 0.1% in 2005 to 40% in 2022 (ITU,2022), positively influencing China–Africa trade. Consequently, digitalization is recognized as a catalyst for economic growth and a significant opportunity for African trade (Kere & Zongo,2023). China, the world’s largest e-commerce market, has seen annual transaction growth of 32% (H. Wang & Liu,2022;C. Wang,2021), playing a vital role in expanding foreign trade (Mou et al.,2019;Holslag,2017). From 2012 to 2023, China’s CE market grew from 2.1 trillion to CNY 16.8 trillion (K. Chen et al.,2024). Advances in Internet and information technology have enabled businesses to access global markets, driving economic and trade integration (Lee & Shen,2020). Platforms like Kilimall, Alibaba, JD.com, and Kikuu are transforming China–Africa trade, providing African suppliers access to a vast market. Notably, sales of African products, including Kenyan black tea and Ethiopian coffee, surged by 409% and 143% during Chinese shopping festivals in 2022 (Usman & Tang,2024). Empirically, several research works addressed the effects of digitalization on the trade performance of countries (López González et al.,2023;Herman & Oliver,2023;Bellucci et al.,2023;Añón Higón & Bonvin,2024;Yin & Choi,2024;Fan,2021) and CE on the trade performance of a group of countries or individual countries (Xing,2018;Liang et al.,2021; Yin & Choi,2023;He,2024;H. Wu et al.,2024). However, empirical studies focusing on the role of digitalization and CE in C-A trade are scarce. Consequently, the precise impact of digitalization and CE on C-A trade remains largely unexplored despite their critical importance for promoting trade flow. Furthermore, LP is crucial for supporting trade growth and is a primary determinant of a country’s economic development (Cui et al.,2022;Bhukiya & Patel,2023). LP reflects a country’s connectivity to international logistics networks by evaluating the overall logistics conditions, which represent the average of six sub-dimensions (Chakamera & Pisa,2021; Song & Lee,2022). It is used to analyze variations between countries regarding logistics costs and the quality of infrastructure for both overland and maritime transport (Martí et al.,2014). Thus, enhancements in LP contribute to promoting trade openness and the reduction in trade costs (Barakat et al.,2023;Jayathilaka et al.,2022). Conversely, inadequate logistics infrastructure can significantly hinder global trade integration (Gani,2017). From a theoretical standpoint, highly efficient logistics services reduce trade costs, promote product movement, and ensure product safety and delivery speed (Jayathilaka et al.,2022). Consistent with the theoretical underpinnings from empirical research prospects, several studies have been conducted on the effects of LP on trade flow (Jayathilaka et al.,2022; Barakat et al.,2023;Bugarˇci´c et al.,2020;Górecka et al.,2022;Mishrif et al.,2024;W. Wang et al.,2024;Cui et al.,2022;Bhukiya & Patel,2023) and found that promoting LP positively influences trade flow among countries. However, there is limited empirical literature on the C-A trade and LP nexus, so this study investigates the impact of LP on C-A trade. Moreover, the impact of digitalization, CE, and LP on C-A trade performance can be shaped by factors such as income heterogeneity, demographics, and resources, as well Economies 2025,13, 171 4 of 33 as the institutional quality of African countries. The impacts of these factors vary with diverse income levels, governance, and population sizes of trading countries (Labhard & Lehtimäki,2022;Yin & Choi,2024). Therefore, demographic shifts, income variation, resources, and governance heterogeneity influence trade patterns, as population growth in partner countries boosts demand for imports, shaping the role of digitalization, CE, and LP in trade. Therefore, this research addresses the following questions, drawing upon the aforementioned analytical discourse, theoretical base, and practical insights. First, what are the roles of digitalization in China and trade partner African countries in C-A trade? Second, what are the impacts of CE dynamics in China on C-A trade? Third, what are the roles of the LP of China and the trade destination of African countries in C-A trade? Finally, how does the heterogeneity in income, demographics, resources, and institutional quality of trade partner countries affect C-A trade? Based on these guiding research questions, this study aims to examine the complex impact of digitalization, CE, and LP on trade between China and 53 African countries for the periods between 2007 and 2023, applying the robust techniques of random effect (RE), Hausman–Tylor (H-T), and the Poisson pseudo maximum likelihood (PPML) strategies. Moreover, the analysis is repeated, controlling for income, population, resources, and institutional heterogeneity. Further analysis is conducted to incorporate the effects of digitalization and LP distance between China and African countries on C-A trade. Our findings demonstrate that digitalization, CE, and LP consistently positively influence C-A trade. Moreover, these outcomes differ subject to income, governance, and demographic heterogeneity among African countries. We focus on the role of digitalization, CE, and LP on C-A trade for the following reasons. First, the C-A trade pattern differs from Africa’s trade with its conventional trade partners, such as the US and EU economies. China’s engagement with Africa is characterized by a focus on infrastructure development and resource-driven partnerships, differing from the colonial legacies and development aid frameworks that historically shaped Africa’s trade with the US and EU. Moreover, compared to other trade allies of Africa, China’s trade with Africa has a pronounced upward trajectory and is more dynamic. C-A trade has experienced the most rapid growth compared to the US-A and EU-A trade (Figure 1). Furthermore, the EU remains Africa’s largest traditional trade partner, and China is closing the gap quickly due to the increasing two-way trade flow. US-A trade is declining and obtaining a more limited role in recent African trade growth trends compared to C-A trade (see Figure 1). Second, a distinctive feature of China–Africa trade is its strong foundation in south– south cooperation, reinforced by China’s Belt and Road Initiative (BRI) and the Digital Silk Road. These strategic initiatives have significantly enhanced connectivity and trade flows, integrating Africa more deeply into emerging global value chains (Asante,2018;Y. Wu et al.,2024). This unique partnership has driven substantial growth in two-way trade, propelled by a surge in Chinese private investment and the implementation of diverse projects, including export diversification efforts and expansive infrastructure programs, particularly under the framework of the BRI (Asante,2018;Y. Wu et al.,2024). Third, China’s technology level is closer to that of African countries than that of Western countries and traditional trade allies (Xu et al.,2016), and its economic model and foreign policy framework attract most developing economies. Unlike others, China’s model of cooperation emphasizes economic development over politics (Zhang & Huang, 2023). As a result, China’s policy approach is more attractive to African leaders than that of other countries, particularly Western countries, leading to increased economic cooperation (Huang & Cao,2023). Economies 2025,13, 171 5 of 33 Fourth, the C-A trade relationship is accompanied by investments in economic and trade cooperation zones, as China has successfully established a total of 25 economic and trade cooperation zones across 16 African nations, with investment flows and financial aid supporting infrastructure development (Bo et al.,2024). Trade flow, complemented by investment, financial aid, and contracted projects, can differ from Africa’s trade with others in terms of its efficiency and flow (W. Chen et al.,2024). Finally, unlike other conventional trade partners, digital transformation plays a crucial role in China’s innovation model and transformation, including trade flows (Hardi et al., 2024). Rapidly expanding digital infrastructure is enhancing supply chain efficiency and making CE more streamlined. China, the world’s largest e-commerce market (H. Wang & Liu,2022), plays a vital role in expanding foreign trade by leveraging its advanced digital infrastructure and extensive online platforms. Similarly, Internet usage in Africa has also risen dramatically (ITU,2022), which can affect C-A trade dynamics. Therefore, this study makes several valuable contributions to the existing literature and the current academic understanding of the multifaceted connection between digitalization, CE, LP, and trade performance in C-A trade. First, our research highlights the role of digitalization in China and trade destination African countries as a key component of factors affecting C-A trade. Subsequently, this study is the first attempt to assess the role of digitalization in C-A trade, which is an underexplored area in the context of trade flow between China and Africa. Second, this study synthesizes the roles of CE in C-A trade, offering fresh insights into the collective influence of e-commerce on China’s exports to African countries. Thus, our study extends this perspective by explicitly linking CE to trade performance in the C-A trade context. Third, it serves as a valuable addition to theoretical research and empirical works on the logistics trade nexus by examining the impact of LP on C-A trade. Therefore, this provides a comprehensive understanding of how LP facilitates trade flows between China and Africa, which is unexplored in the prior empirical works. Fourth, complementing the existing literature, this study’s results seem to provide further evidence of the important role of heterogeneity of governance, income, demographic, and resource aspects of African countries in the roles of digitalization, CE, and LP in C-A trade. Therefore, the findings of this study can serve as a reference for countries with different income, demographic, resources, and institutional levels to develop tailored trade development strategies to promote digitalization, CE, and LP. Finally, robust trade gravity model specification approaches such as H-T and PPML strategies are applied to control for endogeneity concerns, heterogeneity, and zero-valued observations concerns in C-A trade data. Therefore, this paper serves as a primary step in examining the effects of digitalization, CE, and LP on C-A trade across the aforementioned dimensions. Collectively, these elements of the research provide fresh insights into the complex interplay between trade, digitalization, CE, and LP within the context of C-A trade dynamics. These findings are especially valuable for policymakers and business leaders seeking to understand and navigate the challenges and opportunities emerging from China’s changing trade landscape and the evolving pattern of C-A trade. The structure of the paper is as follows: Section 2reviews the relevant literature; Section 3outlines the theoretical framework of model construction, data, and method of analysis; Section 4presents the findings and results; and Section 5provides discussions and policy implications. Economies 2025,13, 171 6 of 33 2. Literature Review 2.1. Digital Connectivity, CE, and Trade Flow Adopting and advancing digital technology can lower both fixed and variable costs in trade, thereby fostering trade growth (Fan,2021). The theoretical relationship between digital connectivity, CE, and trade flow is typically carried out from the standpoint of trade costs. It can reduce the cost of trade through several mechanisms. First, digitalization diminishes the need for physical proximity and in-person interactions in business relationships. Second, digitalization leads to lower communication costs, with automatic translation tools helping to bridge language gaps and further reduce these costs (Bellucci et al.,2023). Third, digital technologies enhance trade efficiency by improving logistics and customs processes. For instance, tracking systems and the automation of airport and port operations shorten transit times, while digitalized customs procedures minimize the time goods spend at borders and reduce administrative costs (Bellucci et al.,2023). Additionally, the rise of e-payments and e-commerce platforms has lowered the costs of business transactions, especially when acquiring products from abroad (Bellucci et al.,2023). Similarly, Freund and Weinhold (2004) provided a foundation for the theoretical relationship between trade and digitalization, arguing that internet access has a positive influence on trade flows. Based on these theoretical foundations, several empirical studies have examined the impact of digitalization on trade costs and trade flows, utilizing various digitalization measures. For example, using data from 37 countries, Rubínová and Sebti (2021) found that ICT, proxied by the proportion of the population with mobile phone subscriptions and the share of the population with access to the Internet, significantly reduces trade costs across trade partners. Aligned with the findings of Herman and Oliver (2023), López González et al. (2023) and Rubínová and Sebti (2021) provided reliable evidence that digitalization and the increasing share of the population using the Internet for business boost trade flow. Additionally, Bellucci et al. (2023) investigated the impact of digitalization, measured by the amount of active mobile broadband subscriptions per capita, on a comprehensive measure of costs of trade. Their findings suggest that advancements in digitalization can lower trade costs through various channels, including improved access to information, reduced transaction costs, less reliance on business travel, more efficient customs and logistics processes, and enhanced communication capabilities. Moreover, Rodríguez-Crespo and Martínez-Zarzoso (2019) analyzed the role of the Internet on trade flow using bilateral goods export data from 120 countries. The findings showed that utilizing the Internet promotes bilateral goods exports. Likewise, Fan (2021) analyzed the impact of digital economy development in importing countries on China’s exports. The findings indicate that developing a digital economy in importing countries can substantially mitigate China’s export efficiency losses and enhance the overall efficiency of its export trade. This effect is particularly pronounced in China’s exports to lowand middle-income countries. Besides using Spanish manufacturing firms, Añón Higón and Bonvin (2024) examined the effects of digitalization on enterprises’ participation in export and import activities. The results suggest that firms’ digitalization positively impacts their likelihood of engaging in both exporting and importing activities, either directly or by enhancing productivity. Additionally, some studies have linked digital connectivity with service trade. For example, a study by Kong et al. (2024) examined the role of digital technology in service exports and found that digital technology significantly promotes service exports. Also, applying the gravity model, Yin and Choi (2024) analyzed the role of digitalization in the trade of services and goods in the G-20 countries. The results revealed that digitalization exerts a more substantial positive impact on trade in services than in goods. Economies 2025,13, 171 7 of 33 Regarding African countries, applying the gravity model, Sawadogo and Wandaogo (2020) analyzed the impact of mobile money service adoption on trade among 48 African countries. Their findings indicate that countries adopting mobile money services experience a significant increase in the share of goods trade as a percentage of GDP. Similarly, Abendin et al. (2022) explored the role of digitalization in Africa’s trade, with a specific focus on intra-ECOWAS trade. Using data from ECOWAS countries spanning their study, they demonstrate that digitalization has a positive and significant effect on bilateral trade within the ECOWAS region. Enhanced digitalization of the economy notably boosts trade among ECOWAS member states. Additionally, Kere and Zongo (2023) investigated the impact of digitalization on intra-African trade for 48 African countries. The results indicate that the use of ICT, particularly the Internet, has a positive and significant impact on exports. Additionally, the introduction of mobile payment services in Sub-Saharan African countries stimulates product exports. Furthermore, as consumer demand in the international market becomes increasingly diversified and the Internet continues to evolve rapidly, the numerous advantages of CE as an emerging trade model have become increasingly evident (C. Wang,2021). Several studies have assessed the influences of CE on the trade performance of various economies. For example, Xing (2018) assessed the impact of the Internet and e-commerce adoption on trade flows among 21 developing and 30 OECD countries. The findings indicated that better access to modern ICT and the adoption of e-commerce stimulate trade flows. Similarly, Gregory et al. (2019) argued that e-commerce is crucial in reducing information asymmetry during trade processes, enabling the optimal allocation of resources across countries. As China is at the forefront of e-commerce technology, several studies have focused on the effects of CE on Chinese trade with various countries. For example, Y. Miao et al. (2019) highlighted that CE plays a significant role in the Belt and Road (B&R) initiative. Special CE policies have encouraged Chinese enterprises to expand their product exports to international markets. Liang et al. (2021) investigated the role of CE transactions between China and countries along the RBI as the core of the study using the GMM method and provided evidence that marine and land transport infrastructure have the most decisive impact on trade. Moreover, C. Wang et al. (2021) investigated the effects of international electronic commerce on the export trade in China. The findings indicated that international e-commerce development has significantly promoted China’s export trade expansion. Additionally, Yin and Choi (2023) investigated the roles of China’s CE in its exports to B&R countries and found that CE has a more substantial positive impact on trade in services than on goods. Also, He (2024) explored the dynamic interaction between e-commerce and China’s export growth, and the findings highlighted the substantial role of e-commerce in trade performance. H. Wu et al. (2024) analyzed the link between China’s CE, trade digitization, and enterprise export resilience. They found that the progression of CE can improve enterprise export resilience. Additionally, the role of digitalization and CE on countries’ trade performance can be affected by several factors. For example, appropriate governance policies lead to transparent institutions supporting digital connectivity and CE activities and lowering the risks of participating in digital connectivity and e-commerce (OECD,2019). In contrast, weak institutional quality and policy frameworks underpinned by inefficient regulatory and legal enforcement can adversely affect economic activity (Doh et al.,2017) and supplement the risks of digitalization and e-commerce (Jean et al.,2020). This suggests that the growth benefits of digitalization are likely to be more substantial in environments where institutions and governance are of high quality (Labhard & Lehtimäki,2022). Similarly, the effects of digitalization and CE will be subject to income heterogeneity. In this regard, Yin and Choi (2024) argued that the role of digitalization is income-dependent; Economies 2025,13, 171 8 of 33 high-income economies tend to positively impact services trade. Also, Kong et al. (2024) found that the trade impact of digital technology is more pronounced in developed countries. Likewise, the demographic structure can affect the pattern of trade between economies through the market change in demand for goods and services (Tao et al.,2021). The large population increase in trade partner countries can increase the demand for the import of goods and services. It can influence the role of digitalization and CE on trade flow. Therefore, the following hypotheses are developed. Hypothesis 1 (H1). Digitalization in China and its trade destination countries has a positive but heterogeneous impact on C-A trade. Hypothesis 2 (H2). CE development in China has positive and varied impacts on C-A trade. 2.2. LP and Trade Flow LP is a vital instrument for driving trade growth and serves as a critical determinant of a country’s economic development (Cui et al.,2022). Theoretically, LP is conceptualized as capital resources and technology that lower the cost of logistics services, promoting trade flow among countries. LP significantly promotes international trade (Bhukiya & Patel, 2023). Indeed, the volume of goods traded between two countries is primarily determined by the availability and quality of logistics services and other factors in exporting and importing countries. Therefore, the quality and efficiency of logistics services can matter for trade flow among countries, as a weak logistics infrastructure and operational processes can be a significant obstacle to trade integration (Gani,2017). Based on the aforementioned theoretical underpinnings, Gani (2017) explored the effect of LP on trade flow. The findings implied that LP is positively correlated with both exports and imports. Besides using the gravity model, Bugarˇci´c et al. (2020) investigated the effects of LP on trade flow in some European countries and the Western Balkans, and the findings indicated that logistics has a positive impact on bilateral trade between countries. Moreover, Jayathilaka et al. (2022) examined the impacts of LP on trade and indicated that LP positively promotes trade flow. Likewise, Górecka et al. (2022) investigated the impacts of LP on the trade of energy products in EU countries and found that LP positively affects the export of energy products. Additionally, Barakat et al. (2023) investigated the role of LP in trade openness in European countries. The results showed that the LP significantly affects trade performance. Also, Lu et al. (2024) used the meta-analysis to integrate the impact of LP on trade. The findings show that promoting logistics development, especially in the B&R countries, has a meaningful impact on trade. Furthermore, a recent study by Mishrif et al. (2024) assessed the role of logistics and supply chains in both international and domestic trade within a developing country. The results proved that developing countries should enhance logistics and promote supply chain infrastructure to enhance trading activities. Additionally, using the gravity model, W. Wang et al. (2024) analyzed the impact of LP in countries participating in the BRI on China’s trade. Their empirical findings indicate that enhancing the LP of countries along the B&R route significantly boosts China’s trade volume with these nations. Moreover, the effects of LP on trade flow can be affected by the economic size of African countries, including differences in income level and demographic heterogeneity. This argument is valid, as the impact of LP varies across countries with diverse income levels and population sizes (Fan & Yu,2015). For instance, Kumari and Bharti (2021) explored the role of country size in the relationship between trade and LP, focusing on population size differences. Their findings revealed that the effect of LP on trade volume is most pronounced in medium-sized countries. Economies 2025,13, 171 15 of 33 effect on China–Africa trade, implying that economic expansion in both China and trade partner African countries positively influences trade flow between African countries and China. Therefore, economic transformation and advancement positively contribute to C-A trade, among others (Omonijo & Zhang,2025). Similarly, the coefficients of institutional quality of China and African countries are positive and statistically significant, implying that improving governance performance indicated by the aggregate index in both China and trade partner African countries enhances trade flow between China and Africa. Also, the WTO membership of China and its trade destination, African countries, has a significant positive effect on the C-A trade. In contrast, the effect of physical distance between China and its trade partners in Africa on C-A trade is statistically significant and negative, indicating that greater physical distance hinders trade flows between China and African countries. Moreover, diplomatic disagreements negatively affect trade flows between China and African countries. The findings are consistent with Visser’s (2019) findings that diplomatic representation significantly influences the trade performance of countries. Regarding variables of our interest, digitalization in both China and its trade destination, African countries, positively influences C-A trade performance. More specifically, a percent increase in the digitalization index in China and African countries increases C-A trade by 0.603% and 0.423%, respectively. The results aligned with Hypothesis 1 (H1). These findings are logical, as they support the view that improvements in digital technology enhance trade flows among countries. The results support the findings of Kere and Zongo (2023), Yin and Choi (2024), Sawadogo and Wandaogo (2020), and Abendin et al. (2022), which provide evidence that an increase in digitalization among countries leads to a significant rise in trade among trading partner countries. Likewise, China’s CE coefficient is positive and statistically significant, implying that an increase in China’s CE trade robustly enhances C-A trade. The coefficient implies that a percent improvement in CE trade increases C-A trade by 0.393% (Table 1). The results support Hypothesis 2 (H2), articulating a positive link between CE and C-A trade. These findings are logical and justified, as promoting CE supports firms in avoiding high competition in their local markets and opening opportunities to access foreign markets (Guo et al.,2018). Furthermore, China’s LP coefficient is positive and robustly significant at a substantial level of significance, implying that the LP of China positively impacts the C-A trade. Notably, the corresponding coefficients of the LP of China display the anticipated signs and are consistent with Hypothesis 3 (H3). Therefore, availability and improvement in the quality of logistics performance of trading countries matter for promoting trade flow. The findings are congruent with the findings of Bugarˇci´c et al. (2020) and W. Wang et al. (2024) in the case of trade flow of Central and Eastern European countries and the Western Balkans and Chinese trade with the B&R initiative countries, respectively. Furthermore, the benchmark analysis is repeated using the H-T model to control for endogeneity concerns, which is an appropriate alternative to the RE model to run a gravity model. In the H-T method, we treated digitalization indicators, CE, and LP indicators as endogenous variables, as the associations between digital technology and trade will be endogenous because of the potential existence of reverse causality (Yin & Choi,2023). The results are reported in Table 2below. The results generally align with the baseline findings, with only minor variations in the magnitude and significance of some estimates. Digitalization of China and trade partner countries in Africa has a robust positive effect on C-A trade. Additionally, the effects of China’s CE have a positive influence on trade flows between China and African countries. Finally, the LP of China has a positive effect on C-A trade. Economies 2025,13, 171 16 of 33 Table 2. The effects of digitalization, CE, and LP on C-A trade. Variables (I) (II) (III) (IV) (V) lnGDPCijt 1.308 *** (0.231) 1.317 *** (0.157) 1.380 *** (0.225) 1.557 *** (0.165) 1.796 *** (0.070) lnDDij −0.252 ** (0.108) −0.182 * (0.105) −0.234 ** (0.108) −0.193 * (0.102) −0.097 (0.098) lnDijt −0.013 (0.077) 0.053 (0.079) −0.020 (0.077) −0.033 (0.077) −0.031 (0.080) lnIQjt 0.254 ** (0.102) 0.148 (0.111) 0.247 ** (0.102) 0.228 ** (0.100) 0.163 (0.109) WTOij 1.254 ** (0.602) 1.047 * (0.619) 1.229 ** (0.606) 1.177 * (0.613) 1.391 ** (0.647) lnDGit 0.379 ** (0.165) lnDGjt 0.385 *** (0.114) lnCEit 0.120 ** (0.059) lnLPit 0.686 * (0.396) lnLPjt 0.035 (0.083) _cons 25.428 ** (9.866) 19.477 ** (9.547) 23.456 ** (9.725) 17.785 ** (8.831) 10.814 (8.814) Obs. 714 714 714 714 714 Note: *** significance at 1%, ** significance at 5%, * significance at 10%; standard errors are reported in parentheses; time-fixed effects are controlled; irepresents the exporting country (China), and jdepicts trade partner African countries. 4.3. Robustness Analysis 4.3.1. Heteroscedasticity Issue Another important issue that should be considered in gravity model specification is heterogeneity and zero-valued observations concerns. A practical approach to addressing zero trade flows is to estimate the gravity model in its multiplicative form rather than the logarithmic form. Additionally, the presence of heteroscedasticity in the original nonlinear gravity model specification arises from the assumption of a multiplicative error term, which requires the adoption of an alternative estimation method. Silva and Tenreyro (2006) suggest an easy solution for handling concerns related to heteroscedasticity using PPML. Thus, we repeat the exercises using the PPML method to run the gravity specification of the impacts of digitalization, CE, and LP on C-A trade performance. It can solve heterogeneity and zero values in the C-A trade data. The results are given in Table 3. The findings are congruent with those presented in Tables 1and 2. The effects of digitalization of origin and destination are robustly positive, strengthening the baseline results. Likewise, the coefficient of CE of origin is significant at a 1% level of significance. Also, the LP of trade origin and destination African countries is strongly positive. 4.3.2. Further Robustness Analysis Moreover, we excluded African countries with the highest trade volume with China. More specifically, Angola, South Africa, Nigeria, and Egypt have been excluded to assess sensitivity to outliers (see Figure A2). The outcomes are presented in Table A4 in Appendix A. The findings are consistent with the baseline results in Table 1. Moreover, we utilized time series data for LP, employing data interpolation in the baseline analysis. To check the sensitivity of the results, we repeated the analysis using Economies 2025,13, 171 17 of 33 data with intervals instead of data pooled over consecutive years because data for LP are available for 2007, 2010, 2012, 2014, 2016, 2018, and 2023. The results are presented in Table A5 in Appendix Aand are not significantly different from the baseline results. Table 3. The role of digitalization, CE, and LP on C-A trade. Variables (I) (II) (III) (IV) (V) Control variables Yes Yes Yes Yes lnDGit 1.100 *** (0.217) lnDGjt 0.782 ** (0.206) lnCEit 0.732 *** (0.152) lnLPit 2.774 *** (0.565) lnLPjt 0.335 ** (0.146) Obs. 714 656 714 714 676 R2 0.954 0.951 0.953 0.948 0.852 Ramsey (p-value) 0.293 0.495 0.428 0.188 0.540 Note: *** significance at 1%, ** significance at 5%; country-pair clustered standard errors are reported in parentheses; countries and time-fixed effects are controlled; irepresents the exporting country (China), and jdepicts trade partner African countries. Ramsey is the test for model specification. 4.4. Heterogeneity Analysis 4.4.1. The Role of Income and Demographic Heterogeneity We re-examined the role of digitalization, CE, and LP on C-A trade on the notion that their impact on C-A trade flow may vary depending on the economic size of African countries, including variations in income levels and demographic heterogeneity. Hence, the sample of African countries is categorized as middle-income and low-income economies based on their income level following WB countries’ classifications (see Appendix B). 2 Besides, highly populated and less populated African countries are separately treated to examine the role of demographic variation in the effects of digitalization, CE, and LP on C-A trade (see Appendix B). The results are reported in Tables 4and 5, respectively. Table 4. The role of income heterogeneity. Panel A: Middle-Income African Countries Variables (I) (II) (III) (IV) (V) Control variables Yes Yes Yes Yes lnDGit 0.547 ** (0.249) lnDGjt 0.633 *** (0.229) lnCEit 0.353 ** (0.174) lnLPit 1.355 ** (0.647) lnLPjt −0.006 (0.109) Obs. 392 392 419 419 391 R2 0.601 0.535 0.590 0.590 0.574 Economies 2025,13, 171 18 of 33 Table 4. Cont. Panel B: Low-Income African Countries Control variables Yes Yes Yes Yes Yes lnDGit 0.824 (0.996) lnDGjt 0.275 * (0.142) lnCEit −0.904 (0.717) lnLPit 0.473 (0.787) lnLPjt 0.089 (0.126) Obs. 295 264 295 295 285 R2 0.646 0.643 0.647 0.608 0.610 Note: *** significance at 1%, ** significance at 5%, * significance at 10%; standard errors are reported in parentheses; time-fixed effects are controlled; irepresents the exporting country (China), and jdepicts trade partner African countries. Table 5. The role of population heterogeneity. Panel A: C-A Trade (Highly Populated African Countries) Variables I II III IV V Control variables Yes Yes Yes Yes Yes lnDGit 0.960 ** (0.490) lnDGjt 0.547 *** (0.241) lnCEit 0.627 *** (0.169) lnLPit 0.701 (0.816) lnLPjt 0.423 *** (0.149) Obs. 271 250 271 435 375 R2 0.566 0.564 0.600 0.588 0.500 Panel B: C-A trade (Less-populated African countries) Control variables Yes Yes Yes Yes Yes lnDGit 0.473 *** (0.182) lnDGjt 0.371 *** (0.131) lnCEit 0.100 (0.066) lnLPit 0.959 *** (0.463) lnLPjt −0.106 (0.108) Obs. 443 406 443 443 360 Wald test 0.540 0.543 0.542 0.505 0.530 Note: *** significance at 1%, ** significance at 5%; standard errors are reported in parentheses; time-fixed effects are controlled; irepresents the exporting country (China), and jdepicts trade partner African countries. The results show that the effects of digitalization in China and African countries, CE of China, and LP index of China on LC are robustly positive at substantial levels for middle- Economies 2025,13, 171 19 of 33 income African countries (Table 4). However, except for China’s digitalization level, the rest of the target variables are insignificant for African countries with low incomes. Moreover, the effects of digitalization, CE, and LP on C-A trade are population size dependent, having a higher magnitude of the coefficients of each target variable for African countries with a high population size compared to less populated African countries (Table 5). Hence, the findings are consistent with the hypotheses postulated. 4.4.2. The Role of IQ and Resources Heterogeneity The study further considers the institutional and resource heterogeneity of sample African countries to investigate the role of digitalization, CE, and LP on C-A trade flow on the proposition that effective governance supports digitalization and CE activities. Additionally, African countries exhibit significant heterogeneity in terms of resources, and variations in these resources can impact the effects of digitalization, CE, and LP on C-A trade dynamics. The IMF classifies a country as ‘resource-rich’ when exports of non-renewable natural resources, such as oil, minerals, and metals, comprise more than 25% of the country’s total export value. Based on these backgrounds, we re-evaluate the effects of digitalization, CE, and LP on C-A trade, dividing countries into countries with weak institutional quality (below the average) and strong institutional quality (greater than the sample average) and based on their value of resources export. The results are presented in Tables 6and 7. Table 6. The effects of IQ heterogeneity. Panel A: African Countries with IQ Greater than the Average Variables I II III IV V Control variables Yes Yes Yes Yes lnDGit 1.143 *** (0.316) lnDGjt 0.349 *** (0.175) lnCEit 0.764 ** (0.221) lnLPit 2.896 *** (0.824) lnLPjt 0.033 (0.111) Obs. 426 410 426 714 398 R2 0.589 0.582 0.568 0.589 0.565 Panel B: African Countries with IQ Less than the Average Control variables Yes Yes Yes Yes Yes lnDGit 0.435 (0.275) lnDGjt 0.627 *** (0.185) lnCEit 0.280 (0.191) lnLPit 1.075 (0.715) lnLPjt −0.016 (0.137) Obs. 288 246 288 288 278 R2 0.633 0.661 0.632 0.632 0.631 Note: *** significance at 1%, ** significance at 5%; standard errors are reported in parentheses; time-fixed effects are controlled; irepresents the exporting country (China), and jdepicts trade partner African countries. Economies 2025,13, 171 20 of 33 Table 7. The influence of resource heterogeneity. Panel A: Resource-Rich African Countries Variables II II III IV V Control variables Yes Yes Yes Yes Yes lnDGit 0.728 *** (0.261) lnDGjt 0.617 *** (0.173) lnCEit 0.485 *** (0.183) lnLPit 1.839 *** (0.681) lnLPjt 0.074 (0.127) Obs. 435 392 435 435 375 R2 0.589 0.595 0.588 0.588 0.500 Panel B: Non-Resource African Countries Control variables Yes Yes Yes Yes Yes lnDGit 1.377 *** (0.378) lnDGjt 0.262 (0.176) lnCEit 0.901 *** (0.265) lnLPit 3.443 *** (0.989) lnLPjt 0.109 (0.112) Obs. 279 264 279 279 231 R2 0.683 0.668 0.680 0.681 0.641 Note: *** significance at 1%, standard errors are reported in parentheses; time-fixed effects are controlled; i represents the exporting country (China), and jdepicts trade partner African countries. The findings implied that the effects of digitalization in China and African countries, CE of China, and the LP indicator of China have a robust positive effect on C-A trade for African countries with IQ greater than the average quality of institutions (Table 6). Conversely, except for the digitalization level of China, all target variables are insignificant when African countries with institutions with a quality less than the average are considered. Therefore, the findings imply that the effects of digitalization, CE, and LP are subject to the level of institutional quality of trade destination countries. Moreover, there is no significant variation in the effects of digitalization, CE, and LP on C-A trade when resource heterogeneity is considered, except for slight variations in the magnitude and level of significance of the variables (Table 7). 4.5. The Role of Digitalization and LP Distance The distance between two countries is much greater than the distance between geographies; it can be due to technological differences (Bellucci et al.,2023). Thus, differences in digital connectivity and logistics innovation among trading partners may indirectly affect trade between countries. Moreover, relatively better connectivity in one of the trade partners does not reduce trade costs with a poorly connected partner, which can be justified in the case of C-A trade, as China is relatively better than African countries in terms of digitalization and LP. China stands 19th in the LP rank of 2023 among world countries, Economies 2025,13, 171 21 of 33 and African countries stand significantly lower compared to China, except South Africa, which is ranked 19th. Therefore, we repeat our analysis controlling for digital connectivity and LP differences between China and trade destination African countries. The results are reported in Table 8below. Table 8. The role of digitalization and LP distance on C-A trade. Variables I II Control variables Yes Yes Digital_distanceijt −0.302 ** (0.147) LP_distanceijt −0.055 (0.087) Obs. 656 606 R2 0.557 0.529 Note: ** significance at 5%; standard errors are reported in parentheses; time-fixed effects are controlled; i represents the exporting country (China), and jdepicts trade partner African countries. The findings implied that the digitalization distance between China and African countries negatively and significantly affects C-A trade. Therefore, the results show that the difference between digitalization levels in the sample African trading partners and China can promote C-A trade, whereas a higher difference in digitalization between China and African countries negatively affects trade flow between countries. 5. Discussions and Theoretical and Practical Implications 5.1. Discussions Among key pillars to promote trade flow among trading partners are scaling up digital connectivity, development in e-commerce, and logistics and supply chain improvements in the countries. Given the fast growth of trade between China and African countries, as well as the demographic, income, institutional performance, and resource heterogeneity within African countries, this study examines the impacts of the digitalization of China and trade partner African countries, the CE of China, and the LP of China and African countries on C-A trade, taking data from Chinese trade to 53 African countries for the periods 2007 to 2023. Several econometric approaches are applied. The findings of this study reveal a positive association between digitalization in trade partner African countries and China, suggesting that a higher degree of investment in digitalization in both trade origin and destination countries is ultimately more beneficial to promoting C-A trade. These findings can be loosely explained by the fact that the application and development of digital technology can reduce costs in trade and promote trade growth. Moreover, the findings underscore that CE improvement in China positively influenced its trade relations with African countries. Therefore, the findings provide evidence that better access to modern digital technology and the adoption of e-commerce applications stimulate bilateral trade flows between China and Africa. Theoretically, the findings are aligned with the theoretical justification that improving the digitalization level of trade origin and destination countries serves as a transformative force in reducing trade costs through diverse channels. For example, it decreases the need for physical proximity and in-person interactions in commercial activities, fostering greater flexibility. Furthermore, digital innovations significantly cut communication costs, with tools like automated translation services bridging language divides and easing the financial and logistical challenges of cross-border communication. Additionally, digital technologies revolutionize the efficiency of goods trade by optimizing logistics and customs procedures. Advanced tracking systems and automated operations at ports and airports reduce tran- Economies 2025,13, 171 22 of 33 sit times, while digitalized customs processes minimize border delays and bureaucratic hurdles. Likewise, the rise of electronic payment systems and e-commerce platforms has simplified transactions, enabling cost-effective procurement from international suppliers (Bellucci et al.,2023). Additionally, the study’s findings align with the digitalization-trade empirical literature, such as Kere and Zongo (2023), Bellucci et al. (2023), Herman and Oliver (2023), López González et al. (2023), Rubínová and Sebti (2021), and Abendin et al. (2022), which argued that improving digital technology significantly reduces trade costs across trade partners and boosts international trade among countries. Similarly, the findings of this study are supported by some empirical works on the link between CE and trade flow. More specifically, the findings are congruent with the results of Yin and Choi (2023), C. Wang et al. (2021), He (2024), and H. Wu et al. (2024) in the case of China and Xing (2018) in the case of OECD and some developing countries. From a practical perspective, the findings of this study are justified, as improving digitalization in African countries and China can play a crucial role in guaranteeing the cut of trade costs and the promotion of trade flow. More specifically, the findings of this study are justifiable as digitalization is advancing rapidly in China and Africa. For instance, over the past decade, Africa has achieved significant progress, with millions gaining internet access and adopting digital services like mobile payments (WB,2024). Since 2007, initiatives such as Kenya’s M-PESA have driven the use of ICT, mobile money, and digital payments (Kere & Zongo,2023). Smartphone penetration reached 64% in 2021, and internet users rose from 0.1% in 2005 to 40% in 2022 (ITU,2022). Moreover, China, the world’s largest e-commerce market, has seen transactions grow 32% annually, fostering foreign trade and global market access (H. Wang & Liu,2022;Mou et al.,2019). Between 2012 and 2023, its CE scale surged to CNY 16.8 trillion (K. Chen et al.,2024). Platforms like Kilimall, Tmall, JD.com, and Kikuu are now enabling African suppliers to reach Chinese consumers, boosting sales of products such as Kenyan tea and Ethiopian coffee (Usman & Tang,2024). Therefore, the findings support the notion that information and transaction costs in goods flows are the most significant factors after transport costs. They reshape the economics of cross-border business by reducing the costs associated with communications and transactions across borders (WTO,2018). Furthermore, the findings provide evidence that the LP of China is an important determinant of C-A trade. It positively influences the C-A trade at a substantial level. Therefore, the improving quality and efficiency of logistics services matter for trade flow between China and African countries, as a weak LP and operational processes can be a significant obstacle to trade integration (Gani,2017). The results provided evidence that developing countries should develop logistics and supply chain infrastructure to enhance trading and commercial activities. The findings are consistent and in line with the justification that logistics technology offers a competitive edge by enhancing a country’s economic efficiency in managing product movement and storage with greater effectiveness. This outcome is expected to contribute to understanding the potential effects of LP on C-A trade dynamics, as logistics costs are also crucial to the trade of goods and services, representing 11% of overall trade costs (WTO,2018). It improves delivery capabilities and provides increased visibility throughout the global supply chain (Shikur,2022). Therefore, the findings provide insights that it is crucial to enhance LP in order to promote trade integration, implying that improving LP is one of the effective approaches for emerging economies to enhance economic activities (Yeo et al.,2020). Economies 2025,13, 171 23 of 33 However, the results implied that the role of LP of African countries in C-A trade is negligible. It can be argued that even though logistic infrastructure has improved significantly across some African countries (Kuteyi & Winkler,2022), the continent still lags in terms of LP compared to other regions of the world. Most African countries are facing trade challenges due to weak LP. Except for South Africa, the top-ranked African country that is placed 19th globally, other African nations rank much lower. Many of these countries face cumbersome and inefficient customs clearing procedures that add to costs, along with poorly maintained road networks that cause severe traffic congestion at ports and further delays, increasing the overall cost of trade (Kuteyi & Winkler,2022). The findings of the heterogeneity analysis further implied that the effects of digitalization, CE, and LP on C-A trade are heterogeneous and subject to income and demographic variation. The findings provide evidence that the effects of digitalization, CE, and LP on C-A trade depend on the economic size of African countries, having a more robust effect in middle-income African countries and African countries with higher population sizes. These results can be aligned with the justification of Fan and Yu (2015) and Kumari and Bharti (2021), who found the influence of country size on the trade-LP relationship by considering population size and found that LP’s effectiveness in boosting trade growth is higher in medium-income countries. Moreover, the findings implied that the effects of digitalization, CE, and LP on C-A trade are conditional on differences in the heterogeneity of institutional quality in African countries. The findings are logical because effective governance policies foster transparent institutions that enhance digital connectivity and CE activities while reducing the risks associated with digital connectivity and e-commerce participation (OECD,2019). Conversely, poor institutional quality and weak policy frameworks, characterized by ineffective legal and regulatory enforcement, can hinder economic activities and exacerbate the risks associated with digital connectivity and e-commerce (Jean et al.,2020;Doh et al.,2017). This suggests that the growth benefits of digitalization and CE are likely to be more pronounced when institutions and governance are robust (Labhard & Lehtimäki,2022). Additionally, strong institutions play a crucial role in improving logistics and streamlining policies related to border and customs clearance (Portugal-Perez & Wilson,2009), positively influencing the role of LP in the C-A trade. 5.2. Theoretical Contributions This study makes significant theoretical contributions to understanding the dynamics of C-A trade by investigating the interaction of digitalization, CE, and LP while accounting for African countries’ heterogeneity in income, demographics, institutional frameworks, and resource endowments. Therefore, the findings of this study bridge the gap in the existing literature and contribute to the theoretical framework by demonstrating how digitalization, CE, and LP serve as transformative tools that reduce trade costs and facilitate market access among developing countries. Digital technology, such as CE platforms and ICT technology, allows trading countries to better exploit their comparative advantage by accessing global markets more efficiently, optimizing production processes, and matching suppliers with the demand for the goods and services they produce, aligned with comparative advantage theory. Additionally, the research findings contribute to global value chain theory by showing how CE and LP enable deeper trade integration of China and African economies. Therefore, by incorporating these modern trade determinants, the research refines existing theories and provides a robust framework to explain evolving trade patterns, particularly in developing and emerging market contexts. Economies 2025,13, 171 24 of 33 Moreover, by integrating the heterogeneity of trade partner countries, the study enriches theories on international trade, offering a more nuanced understanding of trade dynamics under varying economic, demographic, and institutional conditions. The theoretical contribution of the results is to provide a comprehensive framework that integrates digitalization, CB, and LP with socio-economic factors and the absorptive capacity of trading partner African countries, enhancing our understanding of C-A trade dynamics and offering theoretical insights tailored to diverse domestic contexts of African countries. To sum up, this study offers a novel framework to evaluate how digital technological advancements, CE, and efficient LP reduce trade costs, enhance market access, and optimize supply chain management, promoting trade flow among trading countries subject to their socio-economic contexts. 5.3. Practical Implications The outcomes of this research offer valuable insights for governments and policymakers in China and African countries and underscore practical policies and strategies for progressing sustainable digital innovation, CE, and LP to promote C-A trade. First, the findings of the study highlight the critical role of digitalization of China and its trade partner African countries in improving C-A trade performance, suggesting the need for robust digital infrastructure, including mobile and broadband penetration, high-speed Internet, and secure digital platforms in both trade origin and destination countries. Therefore, governments and policymakers in China and African countries should collaborate on initiatives to develop shared digital ecosystems aligned with the Digital Silk Road Initiative, which aims to foster digital connectivity, enhance digital infrastructure, and promote CE across countries. Second, despite notable advancements in digital technology across African countries, digital connectivity and ICT infrastructure in many parts of Africa remain noticeably underdeveloped compared to global standards and China. This disparity reflects a significant digital divide, with a large portion of the African population having limited access to even basic telephone services, while urban areas are saturated with high-speed Internet and advanced digital telecommunications systems (Kuteyi & Winkler,2022). Hence, Africa’s digitalization requires a holistic approach combining investments, skills, policies, and partnerships. Therefore, governments should prioritize policies to expand digital infrastructure, promote affordable mobile Internet, enhance digital literacy through educational programs, and encourage investment in telecommunications and digital services to boost C-A trade. Third, the findings implied that China’s CE significantly and positively influences C-A trade, implying that promoting CE can significantly reduce barriers to trade flow and enhance trade participation. Therefore, governments and policymakers should develop vital policies and strategies to promote investment in scalable e-commerce platforms that connect African suppliers with Chinese buyers. In this regard, policymakers should incentivize partnerships between Chinese fintech firms and local African payment service providers. For instance, integrating Chinese digital finance platforms like Alipay or WeChat Pay with widely used African mobile money systems can simplify payments for CE transactions and promote C-A trade. 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