The effects of industry 4.0 on economic complexity and foreign trade performance: Selected countries from G20 and OECD

Industrial revolutions have developed as more advanced versions of the previous one. The transition from steam and water power to the use of electricity in industry, from there to semiconductors, personal computers, mainframe computers and digital transformation, and the last revolution, Industry 4.0, with concepts such as artificial intelligence, IoT (Internet of the Things), cloud computing and cyber security. It is a process of intertwining. Countries have begun to experience transformations in production and trade with the Industry 4.0 production model and to evolve towards a more complex structure in their economic structures. In this study, it is aimed to examine whether Industry 4.0 has an impact on the international trade performance and economic complexity levels of countries in the context of selected countries from the G20 and OECD, using data between 2003 and 2019. In addition, with the help of complex network analysis, rare elements, which are low complexity products, and industrial robots, which are high complexity products, were determined for the years 1986, 1995, 2000, 2010, 2013, 2018, 2019, 2020, 2021 and 2022 in the context of the specified countries. It is aimed to create network maps and explain the changes in the structures of the networks and statistical outputs such as ego network, hub and authority, self-vector centrality, core and peripheral countries within the framework of the determined research questions. In addition, it was aimed to determine whether the prominent countries are similar in terms of both products. In this context, 5 independent variables are included as Industry 4.0 indicators. As dependent variables, three different indexes of Economic Complexity/Complexity (Economic Complexity/Complexity Trade Index, Economic Complexity/Complexity Technology Index and Economic Complexity/Complexity Research Index) and for foreign trade performance (Growth in Exports (percent), Growth in Imports (percent), Export to GNP ratio and Import to GNP ratio) were selected. Thus, it is aimed to make suggestions to policy makers regarding Industry 4.0, Economic complexity and foreign trade performances. Accordingly, it has been observed that ICT exports positively affect the percentage growth in exports, the percentage growth in imports, and negatively affect the Economic Complexity/Complexity Trade Index and Economic Complexity/Complexity Technology Index. It has been observed that ICT imports negatively affect the share of exports in GNP and positively affect the Economic Complexity/Complexity Trade Index and Economic Complexity/Complexity Technology Index. It has been observed that internet use positively affects export growth, Economic Complexity/Complexity Trade Index and Economic Complexity/Complexity Technology Index. It has been observed that mobile phone use negatively affects the share of exports in GNP. It has been observed that carbon dioxide emissions negatively affect the share of exports in GNP, positively affect the Economic Complexity/Complexity Trade Index, and positively affect the Economic Complexity/Complexity Technology index. According to the complex network analysis, it has been observed that the rare earths trade network is evolving towards a complex structure and the number of countries that cannot establish connections is gradually decreasing. The industrial robots trade network has maintained its very complex structure throughout all periods, and it has been observed that the number of countries that cannot establish a connection is gradually decreasing. In both networks, increases and decreases were detected in statistical values such as ego network, hub and authority, eigen vector centrality and core and peripheral countries during negative and positive periods. In addition, it has been observed that the countries that stand out for both products are similar and the majority of these countries consist of G20 and OECD countries.