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The implementation of "the Belt and Road" initiative has further enhanced China’s economic openness and attracted more foreign direct investment (FDI). However, China is characterized by unbalanced economic development and distribution of resources in different regions. Therefore, analyzing the impact of FDI on economic openness of 18 provinces along "the Belt and Road" and developing the economies of these provinces more specifically have become an important issue. This paper uses factor analysis and DEA-Malmquist model to construct the economic openness of 18 provinces. FDI proxied by 5 measurements are selected to evaluate the impact of foreign direct investment on each province’s economic openness by using spatial econometric model. Empirical results find that FDI has a positive impact on the economic openness of the provinces along "the Belt and Road", and the surrounding provinces also have a significant role in promoting the economic openness of a province. But FDI has different impact on different regions with East Region exhibiting the most significant effect. FDI enhances economic openness mainly through registered capital of foreign-invested enterprises and total import and export of foreign-invested enterprises.

Vulnerability refers to the ability of a country or a region to resist internal and external natural factors such as ecological environment, economy, and society during its development. Germany is a country with low overall vulnerability and distinct regional differences, so research on its regional vulnerability can be a representative case for developing countries, as it provides a comprehensive assessment of regional vulnerability via scientific methodology and at the same time proposes rational solutions. The research collects quarterly data of 16 states of Germany from 2000 to 2015. This study describes a series of features of the data and establishes a comprehensive assessment of regional vulnerability including 33 indicators. Combined with the multi-criteria decision analysis method (MCDM), the analytic hierarchy process (AHP) method and the entropy method are applied to calculate the weights. A linear weighted sum method is applied to obtain the regional vulnerability index of Germany. Afterwards, by performing regression tests, this study empirically assess the influencing factors of the regional vulnerability of Germany. Moreover, this study adopts the neural network training model and forecasts the regional vulnerability of Germany of 2016 to 2020. This study identifies the main factors that influence the regional vulnerability of Germany, and proposes policy implications on the overall regulation to reduce the vulnerability of different regions in Germany accordingly.

With the continuous development of globalization, China has been devoted to promoting the degree of openness. The implementation of “the Belt and Road” initiative brings huge development prospects for China’s OFDI. Utilizing a panel data set consisting of a total of 51 countries along the “the Belt and Road” from 2007 to 2016, this paper establishes an empirical model and examines the influencing factors of the location choice on China’s OFDI in “the Belt and Road” countries. This paper collects comprehensive country-level data of 51 countries along “the Belt and Road” with Python. The number of investment enterprises in the host country published by the Open Directory of Record Results of Overseas Investment Enterprises (Institutions) is used as the explanatory variable. This paper conducts Poisson’s regression to study the influencing factors of location choice. According to the empirical results, bilateral trade agreements can help reduce the difficulties that China may face with in investing and facilitate China to access the host country for investment. In addition, Chinese enterprises may invest in countries where the degree of governance is moderate based on the negative impact on China’s investment in “the Belt and Road” countries. Also, China may invest in countries where the natural resources are poor considering the degree of governance even though natural resources have a positive effect on investment. Furthermore, the level of infrastructure construction in the host country has a positive effect on China’s direct investment in countries along “the Belt and Road”. Besides, good political environment can attract Chinese enterprises to invest in countries along “the Belt and Road”.