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Culture and network may be interacted according to their impact on international trade, in such a way that networks alleviate the negative effect of cultural dissimilarity. This study investigates the effect of network and culture on international trade, and a possible interaction between two effects. Empirical findings from the augmented gravity model using a bilateral data set of 34 OECD countries confirm the positive effect of cultural proximity and network on trade. More importantly, the findings also reveal an interaction effect in a way that networks, such as FDI, migration and internet, play a significant role in mitigating the deterrent effect of culture dissimilarity on international trade. The internet is found to have the strongest interaction effect, followed by FDI and migration.

Recently, decoupling between the US and China has emerged as an important issue in global economics. We propose an analytical framework for trade decoupling analysis, borrowing the idea from the production function in non-competitive input-output tables. Using that methodology, we analyze the mobile phone trade network subject to various measures imposed by the US. A scenario analysis is performed to compare the extent of decoupling after a trade war with worst-cases. In bilateral trade, China’s share of total US imports fell significantly in 2019 compared to 2017. However, China’s indirect exports to the US increased during the same period. A similar pattern is observed in the global trade network visualized via multidimensional scaling (MDS). China’s out-degree centrality decreased slightly, while Vietnam’s role expanded. Actual figures for 2019 show a decreased out-degree centrality for Chinese final good exports, but a much higher one in the scenarios. Also, China’s indirect exports to the US have increased. But China does not appear to play a key role in the network as assumed in the scenario. Throughout the study, intermediate goods were treated homogeneously, and further studies considering the heterogeneity of input-output linkages are needed.

This paper examines the network dynamics of the cross-border trades utilizing Social Network Analysis (SNA) based on data obtained from the WTO-OECD Trade in Value Added database from 2000-2011. The main results of this paper are as follows: regarding the top 10 in-degree centrality industries, industries in China, Germany, and the U.S. have emerged as the largest importers of foreign value added, implying that the global production network is dominated by two different types of industries. The first type includes processing and assembling functions in China and Germany. The other type of industry involves foreign value added largely for domestic final demand in the U.S. Secondly, there are also two types of brokerage roles. U.S. industries are operating in a liaison role, while Chinese and German industries are mostly operating as coordinator or gatekeeper. Thirdly, manufacturing industries in China and Germany which have emerged as higher in-degree centrality incur a large portion of their value added from the logistics industry. This suggests that those leading industries with the highest characteristics of hubness in the global production network cannot sustain their network status without efficient utilization of the logistics industry.

In recent years, the proliferation of free trade agreements (FTA) has led to rapid economic boons and political security among nations. This study investigates whether the percentage of expats or permanent foreign residents plays a role in deciding which countries to partner with in bi-lateral FTAs. Previously, the reasons for FTA formation were believed to be primarily based upon economic, geographic, and political reasons. However, through the use of social network analysis, a larger picture can be mapped which allows for a more comprehensive understanding of key players in the current state of FTA formation in relation to the immigrant network that they share between them. More specifically, through computerized social network analysis, centrality can be calculated to determine the key players and the most central immigrant populations. When analyzing both the immigrant centrality in relation to FTA centrality, it becomes evident that there is a high correlation between the two factors. Thus, the findings highlight that immigration trends can be used as a predictor of FTA formation. As a result, it emphasizes the weight of immigration policy on the formation of bi-lateral FTAs.

This editorial proposes three fundamental issues in the international economic field evoked by the US-China trade war. The first is the intensifying conflict between protectionism measures and the coherence with relevant global trade rules. The second is decoupling between the US and China and subsequent evolution in the global production network. The third is the digression in the trade flow between the US and China and the resulting change in innovative capabilities and manufacturing competitiveness among major industrial countries. This editorial also offers the long-term perspective of the current global trade war and how the world encounters repercussion of openness and protectionism as well as times of prosperity and uncertainty.

The purpose of this paper is to examine the influence of entrepreneurial orientation on the network and exhibitor’s performance. The entrepreneurial orientation is seen as a highly competitive factor for the company, which can foster its trade fair business.

A survey-based quantitative approach was adopted, including a questionnaire (n = 362) applied to companies participating in trade fairs. To arrive at results, the study developed structural equations modeling techniques, using SPSS 24 and AMOS 20 software.

The study demonstrates positive impacts of entrepreneurial orientation on network capability and consequent exhibitor’s non-sales performance and exhibitor’s sales performance. A conceptual model is presented.

The study was carried out mainly on Portuguese companies, restricting its generalization. In addition, the exhibitor’s performance was measured based on the exhibitors’ level of satisfaction and not on real sales results.

The study offers a process which the results highlight such as innovativeness, proactivity, risk-taking, competitiveness and autonomy (dimensions of entrepreneurial orientation) as a mix of important ingredients for the exhibitor’s networking. The networking promotes intangible results (non-sales performance) that can generate sales (sales performance).

The study is the first research to apply entrepreneurial orientation in the trade fair context and it also presents a relationship between non-sales performance and sales performance.

Using the Social Network Analysis(SNA) method, this paper examines inter-country relationships between countries that may be part of the New Silk Road. Based on bilateral-trade data from more than 70 countries, the paper provides a more vivid understanding of overall features and effects of the New Silk Road policy. According to the results, India, Turkey, and Russia have the highest degree centrality, indicating that the success of the New Silk Road policy depends mainly on the ability of the Chinese government to incorporate these countries. Among European countries, only Germany can be successfully incorporated into the New Silk Road network. In addition, Central Asian countries such as Kazakhstan and Uzbekistan show no potential as hubs in the network. Most importantly, China has a dominant position in the New Silk Road network. China's focal and dominating status is also supported by the fact that there is no change in the clustering coefficient in the network, which implies that the Chinese government has to absorb into the system those countries that are less likely to benefit from the policy.

This study aims to examine the degree to which a selection of home country factors affects the proclivity of firms to internationalise. The study also proposes and tests a conceptual model that fuses institutional and resource-based theories to improve our understanding of firm internationalisation.

The study uses cross-sectional, national-level secondary data from the 2018 Global Entrepreneurship Development Institute and World Economic Forum data sets on global entrepreneurship and competitiveness indices for 137 countries. The data is analysed using correlation and hierarchical regression analysis to test the hypotheses.

The results indicate that national income, institutions, trade openness and availability of risk capital positively influenced firm internationalisation, while home-country networking had an inverse effect. However, home country infrastructure had no statistically significant effect on firm internationalisation.

The findings highlight the importance of considering home country attributes in understanding the internationalisation of firms.

This study contributes to the body of knowledge by providing empirical evidence of the role of local factors on the internationalisation of entrepreneurial ventures. It also tests a novel conceptual model that integrates institutional and resource-based theories to explain the nuances of the internationalisation of business ventures globally.

This paper explores international trade of the Chinese manufacturing industries through the lenses of network analysis (NA) to visualise the world trade network of the Chinese economy, describe its topology and better explain the international organisation of Chinese manufacturing industries.

The authors built a dataset of 40,550 Chinese companies and their 107,026 subsidiaries in 118 countries from Orbis-BVD and used a NA to investigate the connection between China and other countries. In particular, the authors studied the connections between Chinese companies and their subsidiaries in order to build a network of Chinese industries.

The authors found that the network of Chinese companies is ramified but not wide and it can be divided into two clusters. Moreover, the relations between China and other peripheral countries are strongly mediated by a few leading locations (e.g. Hong Kong and the USA).

This paper contributes to the literature in several ways. First, the authors provide empirical evidence on the magnitude and ramifications of Chinese enterprises in the world. The existing studies generally focus on applying NA to sectoral insights (Mao and Yang, 2012; Shaikh et al., 2016; Zheng et al., 2016; Wanzenbö ck, 2018; Krichene et al., 2019), whereas in this work the authors take a comprehensive view of the entire Chinese manufacturing system. Second, this paper complements the existing literature identifying the difference between cluster levels in Chinese manufacturing (Wu and Jiang, 2011) by proposing a cluster centralisation method to analyse the international network of Chinese firms rather than just the national network. Finally, the results also shed light on the international trade relationship between China, Hong Kong and the USA.

This study analyzed Korea's relations table through network analysis. In particular, among the centralities, eigenvector centrality, PageRank centrality and degree were used. The author studied which network characteristics affected the value-added rate.

A network analysis method was used.

It is the inward relationship that affects the value-added ratio of Korea's industries and the outward relationship has less influence. In particular, the inward relationship not only acts as a cost but also has an effect on the rate of added value recently.

Since the three years of 2010, 2015 and 2019 are the target, the data are somewhat insufficient to generalize.

As for the value-added ratio of an industry, input is more important than output (sales). Therefore, where the input is received is very important.

It is possible to increase the understanding of the determinants of the value-added rate of Korean industries.

(1) It was clarified which side is inward or outward in determining the industry in Korea. (2) The relationship between PageRank, eigenvector centrality and degree was analyzed in Korean cases. (3) Input is a cost and acts to increase added value.