This study systematically analyzes the factors that affect consumers’ green purchase intention. Through a comprehensive literature review, the influencing factors of consumers’ green purchase intention are organized into three categories: cognitive factors, consumer individual characteristics, and social factors. Next, a meta-analysis of 54 empirical papers was conducted using Comprehensive Meta-Analysis 3.0 software to quantitatively assess these relationships. The results revealed that green perceived value, attitude, and green trust have a significant positive influence on green purchase intention. Perceived behavior control, perceived consumer effectiveness, and subjective norm also has a strong positive impact on green purchase intention. Collectivism has a positive effect on green purchase intention. Green perceived risk has a significant negative impact on green purchase intention. The study’s findings provide references for enterprises engaged in green product diffusion and organizations responsible for environmental protection.

The growing popularity of social commerce may transform the purchase behaviour of consumers. It is the need of time to investigate the factors that impact the consumers’ purchase intention in the social commerce environment, especially in a developing country like Pakistan. The study is a drive to investigate the factors influencing the purchase intentions of consumers in social commerce. By employing social learning theory, this study proposed a theoretical model to explore the factors affecting consumers’ purchase intention and decision making. A structured questionnaire-based survey was conducted for data collection, and 232 valid responses were analysed using structural equation modelling (SEM) to validate the proposed research model. The results of the study concluded that social commerce constructs in the form of learning from forums and communities, learning from ratings and reviews, and learning from social advertisements were significant predictors of social support constructs. Furthermore, social support constructs such as emotional and informational support significantly contribute to predicting consumer’s purchase intentions in social networking sites. In addition, this study revealed that special focus was needed to build social commerce constructs and social support by the managers of social commerce sites to attain consumers’ purchase intention.

China and Pakistan signed a free trade agreement in 2006. In this study, the impact of the China–Pakistan Free Trade Agreement (CPFTA) on trade of agricultural products is explored by using the gravity model. Two Panel data sets, one for agricultural exports of China and one for agricultural exports of Pakistan were used. This contains data for agricultural exports and other macro-economic factors of China and Pakistan with 110 partner countries from 2001 to 2014. The Poisson Pseudo Maximum-Likelihood (PPML) technique of the gravity model was employed to analyze this data. The results suggest that CPFTA had a strong trade creation effect on agricultural exports of Pakistan. It helped provide an exponential increase in the agricultural exports of Pakistan to China. However, CPFTA was not found very effective for Chinese agricultural exports to Pakistan. This study contributes to the literature by determining the potential effects of the CPFTA on agricultural trade. Policy makers will find the results of this study useful because they point out impact of a bilateral trade agreement on trade of agricultural products.

This study investigates the potential impact of China’s Belt and Road Initiative (BRI) on its agricultural exports. A gravity model was formulated to find the determinants of China’s agricultural exports. This model uses two measures of distance: Model 1A uses the great-circle measure of distance and Model 1B uses the existing real distance used between China and its trade partners. The determinants of both models are then used to simulate China’s pre-CPEC export potential in agricultural products. The results of Model 1B are then simulated, using the proposed real distance values to calculate China’s post-CPEC agricultural export potential. The findings for pre-CPEC exports show that a strong potential for agricultural exports exists for African, Middle Eastern, and other countries. The findings for post-CPEC trade show that there will be a tremendous increase in the export potential for African and Middle Eastern countries that can be attributed to BRI.