Despite extensive research on Chinese international students in North America, there is a lack of studies that compare students’ choices between the United States (U.S.) and Canada. In this study, we conducted in-depth, semi-structured interviews with 55 Chinese international undergraduate students in two case institutions in the U.S. and Canada. Drawing on the Push-Pull model and the Purchase Intention model, our study explains how the intense Chinese education system under Gaokao (National College Entrance Examinations) pushes students to pursue higher education abroad. The findings also reveal factors that attract Chinese students to foreign countries and institutions, such as the superior position of the U.S. ( 高大上 gaodashang ), the welcoming culture in Canada ( 包容 baorong ), and the institutional reputation ( 名气 mingqi ). Theoretical contributions and recommendations for scholarship and practice are provided in the article.

This study explored the employees’ perception of followership and its evolution in business transformation, given the case of the Hyundai Motor Group (HMG). Using a case study approach for explorative research, we conducted informal conversations and in-depth interviews with twenty participants to solicit employees’ and stakeholders’ perceptions of followership and its cultural formation through interpersonal relationships. Drawing on Kelley’s followership typology, we found three characteristics in participants’ followership perceptions: Ill-sa-bul-lan (extraordinarily well-organized), speed, and devotion. To explore the cultural formation of followership between leaders and followers, which is under-explored in Kelley’s theory, we adopted alternative theories (i.e., responsible leadership and implicit followership) to analyze the interpersonal relationship during the business transformation. Consequently, we found that the HMG followership, shaped by the relationships between leaders and followers within the Korean cultural context, evolved to facilitate successful business transformation. Initiated by top management, new and diverse elements from outside spurred the drive for business transformation and instigated changes in organizational culture, including perceptions of followership. This evolution of followership, in turn, reinforced the business transformation, creating a virtuous cycle. This study offers valuable insights into the dynamics of followership and its impact on organizational performance, providing a foundation for further empirical research in this underexplored area of followership.

This study aimed to examine the growth of social enterprises, their operational diversity and impact, and their characteristics from the stakeholders’ perspective focusing on the diversity and influence of social enterprises in the Republic of Korea. Based on data from periodical reports, newspaper articles, and the existing academic literature, this study provides insights into the diversity and influence of social enterprises in Korea. This study suggests that the growth of Korean social enterprises is rooted in extensive government support, including financial subsidies, tax benefits, and technological innovation incentives. We found that the landscape includes officially recognized social enterprises and other entities that, while not formally certified, fulfill similar roles by embodying social values within diverse institutional frameworks. These enterprises have diversified to engage various social issues, from job creation for marginalized groups to environmental sustainability and community development. Effective stakeholder engagement fostered diversity and inclusiveness within these organizations. A limitation of this study is the use of secondary sources. Future research should use more diverse data collection methods and examine a broader range of social enterprises, including non-certified ones. This study contributes to the discourse on social enterprise by highlighting the trajectory of social enterprise development, the critical role of government support, and the importance of stakeholder engagement to promote diversity. It also provides insights into the diversity and role of social enterprises in Korea and their potential to address socio-economic issues.

Using stochastics in stock market analysis is widely accepted for index estimation and ultra-high-frequency trading. However, previous studies linking index estimation to actual trading without applying low-frequency trading are limited. This study applied William%R to the existing research and used fixed parameters to remove noise from stochastics. We propose contributing to stock market stakeholders by finding an easy-to-apply algorithmic trading methodology for individual and pension fund investors. The algorithm constructed two oscillators with fixed parameters to identify when to enter and exit the index and achieved good results against the benchmark. We tested two ETFs, SPY (S&P 500) and EWY (MSCI Korea), from 2010 to 2022. Over the 12-year study period, our model showed it can outperform the benchmark index, having a high hit ratio of over 80%, a maximum drawdown in the low single digits, and a trading frequency of 1.5 trades per year. The results of our empirical research show that this methodology simplifies the process for investors to effectively implement market timing strategies in their investment decisions.

Recent research in algorithmic trading has primarily focused on ultra-high-frequency strategies and index estimation. In response to the need for a low-frequency, real-world trading model, we developed an enhanced algorithm that builds on existing models with high hit ratios and low maximum drawdowns. We utilized established price indicators, including the stochastic oscillator and Williams %R, while introducing a volume factor to improve the model’s robustness and performance. The refined algorithm achieved superior returns while maintaining its high hit ratio and low maximum drawdown. Specifically, we leveraged 2X and 3X signals, incorporating volume data, the 52-week average, standard deviation, and other variables. The dataset comprised SPY ETF price and volume data spanning from 2010 to 2023, over 13 years. Our enhanced algorithmic model outperformed both the benchmark and previous iterations, achieving a hit rate of over 90%, a maximum drawdown of less than 1%, an average of 1.5 trades per year, a total return of 519.3%, and an annualized return (AnnR) of 15.1%. This analysis demonstrates that the model’s simplicity, ease of use, and interpretability provide valuable tools for investors, although it is important to note that past performance does not guarantee future returns.

Chonsei, a Korean housing lease system, enables landlords to acquire direct housing purchase funds without mortgages and offers tenants a cost-effective rental option. However, public concerns have arisen about potential landlord defaults, causing financial distress for tenants. This study examined the risk of non-return of the Chonsei deposit and developed a default prediction model using Chonsei contract data from the Korea Housing and Urban Guarantee Corporation. Starting with the components from Merton’s bond pricing model, we included variables that reflect contract-specific factors, macroeconomic conditions, and the Korean Chonsei practices. The findings revealed that higher house price volatility, elevated debt-to-house value, and risk-free interest rates positively correlate with non-return risk. Meanwhile, certain factors, such as longer remaining maturity, favorable macroeconomic conditions, and rising market Chonsei price trends, demonstrated negative correlations with non-return risk. Consequently, a logistic regression-based default prediction model, with eight risk factors that predict the deposit non-return, was suggested. By identifying risk factors and predicting the non-return risk of deposits, this study contributes to an informed policy decision in planning and practicing Chonsei contracts in the Korean housing market.