As a classical trade model, the gravity model plays an important role in the trade policy-making process. However, the effect of physical distance fails to capture the effects of globalization and even ignores the multilateral resistance of trade. Here, we propose a general model describing the effective distance of trade according to multilateral trade paths information and the structure of the trade flow network. Quantifying effective trade distance aims to identify the hidden resistance information from trade networks data, and then describe trade barriers. The results show that flow distance, hybrid by multi-path constraint, and international trade network contribute to the forecasting of trade flows. Meanwhile, we also analyze the role of flow distance in international trade from two perspectives of network science and econometric model. At the econometric model level, flow distance can collapse to the predicting results of geographic distance in the proper time lagging variable, which can also reflect that flow distance contains geographical factors. At the international trade network level, community structure detection by flow distances and flow space embedding instructed that the formation of international trade networks is the tradeoff of international specialization in the trade value chain and geographical aggregation. The methodology and results can be generalized to the study of all kinds of product trade systems.

China’s ‘Market for Technology’ policy has attracted much interest over the past decade. In light of a relative emphasis on the spillover effects of joint ventures, this study examines the transferring effects of Multinationals’ (MNCs) outbound open innovation in such a context. A survey of 2071 research and development (R&D) contract transactions between Chinese entities and MNCs indicates both internal factors (e.g. organisational capabilities) and external factors (e.g. the role of Intellectual Property protection) affect the transferring effects, which reformulate the focus of the Policy from the relational dimension of ‘Government vs. MNCs’ to the transactional dimension of ‘Domestic entities vs. MNCs’. We thus conclude that MNCs’ active initiative in the involvement of technology transfer and the success of domestic transaction partners combine to contribute to the technology progress within China’s ‘Market for Technology’ policy.

Will high-speed rail improve air quality, or make it worse? We use data of 270 cities in China from 2000 to 2018 to study the impact of high-speed rail (HSR) on air pollution. Based on the difference-in-difference (DID) model, the regression results show that high-speed rail has reduced air pollution. But the results also show geographic differences. In underdeveloped areas, HSR will increase urban air pollution. The main mechanism is that HSR has affected the industrialization level and the entry of polluting enterprises. Especially in underdeveloped cities, HSR will increase industrial output and attract more polluting companies, which is not conducive to environmental governance.

Detailed micro-level data of enterprises between 2000 and 2007 are adopted to study the influence of quality of imports on quality of similar exports in general trade and processing trade. Results indicate that quality of competitive imports in general trade exerts a significant and stable promoting effect on quality of similar exports, but in processing trade bears an inverted U-shaped relationship. The competitive imports with higher quality gradient exert a more promoting effect on quality of similar exports. The competitive imports with higher quality from a certain exporter exert a higher promoting effect on similar exports of Chinese enterprises to the country. The innovation-driven quality improvement of competitive imports in general trade significantly improves quality of similar exports. Furthermore, the quality of competitive imports exerts the highest promoting impact on quality of exports in the monopoly and labor-intensive industries, while it exerts a small effect on those in the capital-intensive industries.

This study investigates the relationship between openness and pollutant emission intensity across 286 Chinese cities from 1990 to 2019, aiming to evaluate the potential environmental benefits of open economy strategies. The findings indicate that enhanced urban openness significantly lowers pollutant emission intensity. To ensure the robustness of our findings, we make an innovative attempt to employ high-speed rail connection and motorway density as instrumental variables to address potential endogeneity issues, corroborating the reliability of the results through various robustness tests. Moreover, we also find the heterogeneous effects of urban openness on pollution emissions, highlighting the moderating influences of trade complexity, urbanization level, and environmental regulatory intensity. Lastly, the study elucidates the mechanisms through which urban openness diminishes pollution emissions, namely fostering green innovation capacity and enhancing public environmental awareness. This research makes theoretical contributions on understanding the nexus between open economies and environmental protection while offering practical insights to inform governmental environmental policy formulation.