Chinese President Jinping initiated one of China’s grandiose foreign policy initiatives in 2013. He emphasized on the reconstruction of Silk Road Economic Belt and a twenty-first century Maritime Silk Road (MSR), together referred as Belt and Road Initiative (BRI). The BRI presents opportunity for trade, investment, and jobs between China and Asian economies that will support increasing consumption, infrastructure development, political associations, and sustainable development in many parts of the world. This article examines the BRI project and its growth, specifically from the Asian perspective. The study is an endeavor to identify the impact of BRI on the growth of Asian economies along the BRI route (corridors). For achieving this objective, data has been obtained from various websites and the time period considered is between 2009 and 2016. The panel data regression has been used with controllable macroeconomic variables. The results based on multiple models indicate a significant impact of BRI on the economic growth of Asian Economies. Other macroeconomic variables, such as imports, political stability, and corruption, also have a significant impact on the economic growth of the Asian economies.

Foreign Direct Investment (FDI) is considered to be influenced not only by quantitative factors but also by qualitative factors. However, the present literature related to FDI focus more on quantitative factors rather than qualitative factors. One reason is that FDI is itself based on a quantitative benchmark (10% or more investment in equity). The qualitative factors that are related to FDI are governance, democracy, human development index etc. In the present study an endeavor is made to understand that how corruption influence FDI decision. FDI is taken in terms of percentage of GDP and Corruption is represented by Corruption Perception Index. The sample period of the study is from 1995 to 2014.

Determinants of Foreign Direct Investment has remained an exhaustive endeavour for the researchers and at times it becomes a Pollyanna for policy making. The present piece of research is an attempt to gauge the determinants of FDI for India and Sri Lanka. The plausible determinants are selected for empirical testing such as Market Size, Inflation, Trade Openness and Current Account Balance. Proxy variables are selected in case the determinant is not measured in itself. Augmented Dicky Fuller test (Dicky & Fuller, 1981) is used for checking stationary and for hypotheses testing Ordinary Least Squares Regression is used. JEL: C13, E22, F21, F23

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The present study intends to unwrap the influence of social media electronic word of mouth (eWOM) on revisit intention post-COVID-19 applying the theory of planned behavior (TPB). Two additional constructs, viz., eWOM and destination image, have been undertaken in the present study to enhance the robustness of the TPB model. An online questionnaire was employed to collect data, and the research relied upon 301 correct and useable responses. The survey's population includes potential tourists who intend to revisit India post-COVID-19. SPSS 20 and AMOS 22.0 were used to analyze the data. The posited model was validated using confirmatory factor analysis (CFA) and structural equation modeling (SEM). The findings indicate that all of the constructs under study, namely "electronic word of mouth (eWOM), destination image (DI), attitude (ATT), subjective norm (SN), and perceived behavioral control (PBC)," significantly and positively influence "tourists' revisit intention (RI)" post-COVID-19. These constructs explained approximately 71% (R2 = 0.709) of the variance in the revisit intention post-COVID-19. A number of theoretical and practical implications can be delineated to make recommendations to the ministry of tourism, tour and travel agencies, central and state government-owned tourism departments, marketers and promoters of travel destinations. The distinctiveness of the present study lies in the fact that it measures the influence of eWOM on revisit intention post-COVID-19 in the Indian context by incorporating destination image with the TPB model.