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The purpose of this paper is to investigate the impact of foreign capital shifts on economic activities and asset prices in South Korea.

The authors in this paper apply the Bayesian threshold vector autoregressive (TVAR) model to estimate the regimes of large and low inflows of foreign capital. Then, structural impulse-response analysis is used to check whether the responses of the variables differ across the estimated regimes. The model is estimated using quarterly data of foreign capital inflows, gross domestic product (GDP), consumer price index, credit to the private non-financial sector, real effective exchange rate (REER), stock returns and house prices.

The main findings suggest that large inflows of gross foreign capital, foreign direct investments (FDI) and foreign portfolio investments (FPI) are ineffective to boost economic growth, but large inflows of other foreign investments (OFIs) significantly contribute to GDP. The decreases in the foreign capital inflows are associated with larger depreciation of REER. The large inflows of gross foreign capital, FDI and OFIs are associated with further expansion of credit supply to private non-financial sectors.

The policy implications of foreign capital inflows are of particular importance to all the emerging markets alike. However, the empirical analysis is limited to the case of South Korea due to various reasons. The experience with international capital inflows among emerging markets is heterogeneous. Therefore, it would be better to take each case of emerging market individually. In addition, TVAR analysis requires a long data sample, which unfortunately is not available for most of the emerging markets.

The foreign capital inflows are shown to be procyclical and notoriously volatile in many studies. Nevertheless, this topic has commonly been studied using linear VAR models, which do not properly deal with the cyclical characteristics of foreign capital inflows. This study attempts to resolve these methodological limitations by examining a non-linear VAR model that is capable of capturing the structural breaks associated with the cyclical behaviors of foreign capital inflows.

The purpose of the research is to gain an understanding about how stock market investors impact various behavioural personality traits in various consumer groups with differing levels of motivation and capacity to absorb emerging stock market data.

The research has used structural equation modelling (SEM) to test the validity of the theoretical model.

The current paper is the first study that uses stock market data from an emerging economy to examine the relationship between stock market investment and different behavioural patterns such as stock market attachment, trust, satisfaction and loyalty. The authors observe the presence of direct positive relationships between stock market investment and different behavioural personality traits. Moreover, the authors also observe that stock market attachment can be seen as an intermediary variable between stock investment involvement and satisfaction. The empirical findings also suggest the presence of indirect relationships between stock investment involvement and satisfaction and between stock market attachment and loyalty. The authors find that the indirect relationship between stock market attachment and loyalty occurs when the level of satisfaction is higher. Therefore, satisfaction appears to facilitate the relationship between stock market attachment and loyalty.

One major limitation of the study is data availability. More specifically, the study was conducted with customers of eight different banks in the province of Eskisehir, Turkey. From the 250 questionnaires distributed, 173 were returned, yielding a response rate of 69.2%.

By identifying the trait characteristics of segments of stock market participants relative to their propensity to invest in stocks, it is possible to tailor messages that influence people to invest for the long term.

The paper deploys stock market data from an emerging economy to investigate the relationship between stock market investment and different surface traits such as stock market attachment, trust, satisfaction and loyalty. To the best of the authors' knowledge the current paper is the first such study.

Nowadays, the main problem of industries is the issue of environmental pollution. The green supply chain (GSC) is one of the processes that can be effective to consider this issue and its practices in all working processes in every organizations, so that the concept of GSC has been emerged with the acceleration of the government regulations and rules to achieve environmental standards and the increasing demands of consumers to supply green products. Therefore, the organizations should move toward the development of environmental activities in today’s turbulent world. In other words, the current organizations should consider making their supply chain more agile and green to survive in the competition arena or in other words, they should consider making agile the GSC. The necessity of considering this issue needs to identify the evaluating indicators of the agility of the GSC. This study aims to consider this issue.

With reviewing the research literature and having survey with the experts, totally 7 criteria and 37 sub-criteria were identified as the evaluating indicators of the agility of the GSC. The results from collecting research data and using the confirmatory-factor analysis suggest the suitability of the above-mentioned indicators.

The idea of the GSC is to remove or minimize the greenhouse, chemical/hazardous gases and waste throughout the supply chain. On one hand, the agility of the supply chain as an operational capability in quick response to the uncertain and turbulent markers not only improves the performance of the company but also leads to cost decrease and increase of the professional capabilities. Therefore, the organizations should step toward the development of the environmental activities in the today’s turbulent world. The importance of the issue of agility and considering the environment in the supply chain double the necessity of identification of the factors of agility of the GSC.

The present research considers the identification of the evaluating indicators of the agility of the GSC in industries.