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This paper aims to seek the optimal proportion of female executives in corporate management teams, and to analyze the threshold effect of the proportion of female executives on the enterprise market value and enterprise management performance by using a panel threshold regression model. The purpose of this paper is to obtain the optimal interval, during which female executives exert positive effects on enterprise market value and enterprise management performance.

Based on the data of listed companies in SSE from 2003 to 2012, this paper conducts theoretical and empirical analysis by using a panel threshold regression model.

This paper proves that the proportion of female executives has a threshold effect on the enterprise market value and enterprise management performance. The results show that the proportion of female executives has an optimal interval. In other words, during the 53.8-68.4 percent interval, the proportion of female executives exerts the least negative effect on the enterprise market value and the most positive effect on the enterprise management performance.

In this paper, the non-linear relationship between female executives, enterprise market value and enterprise management performance has been verified, and the optimization interval of the female executives’ proportion has been figured out as well.

This paper summarizes the severity of global warming, collaboration and endeavor within international government and the trend of international development for “energy-saving and emission reduction.” The Chinese government is enduring high pressure under the environment of “global warming” and “energy-saving and emission reduction” and it has made a policy for “energy-saving and emission reduction.” Based on this, we analyzed the possibility and feasibility for our logistics to “energy-saving and emission reduction,” then propose some solutions for our logistics industry to development and “energy-saving and emission reduction.”

This study aims to examine the unemployment hysteresis effects from the perspective of the heterogeneity of genders within Asian countries.

The authors use the annual unemployment rate dataset of 12 Asian countries ranging from 1991–2020. Traditional unit root tests are initially employed to investigate the unemployment hysteresis effect. Considering the structural break and cross-section dependence problems, the sequential panel selection method (SPSM) and the Kapetanios–Snell–Shin (KSS) panel unit root test with Fourier functions have proven to be more applicable.

The empirical results indicate that the unemployment rate is stationary in most Asian regions for both females and males, which confirms the mean reversion process of the natural unemployment hypothesis. This suggests that these countries' unemployment rates are flexible to quickly revert to its long-run equilibrium determined by the labor markets. However, only the female unemployment rate in Pakistan and Nepal and adult female unemployment rates in these two economies present non-stationary series. In line with the unemployment hysteresis effect, it means shocks will leave a permanent impact on their labor market.

On the one hand, in most of the Asian countries, it can be inferred that the trade-off between inflation and unemployment is temporary because the natural unemployment hypothesis holds. Therefore, policymakers may consider using monetary policy as a tool to control inflation and stimulate growth during a recession. Such policy measures should not have a long-run impact on unemployment or cause a permanent shift in the natural unemployment rate. On the other hand, the government should implement active labor protective programs such as education or training schemes, job search assistance programs and maternity protection, especially for female adults, to reduce the negative shocks in the economic downturn, which is beneficial for them away from being long-term unemployed. It is also necessary to improve the labor unions to reduce the discrimination between female and male labors.

This paper innovatively concentrates on the heterogeneity performances between genders about the unemployment hysteresis effect within Asian countries. Furthermore, taking into account the age-specific characteristics, the youth and adult unemployment rates have been investigated. Additionally, the approximation of bootstrap distribution and the advanced panel KSS unit root test with a Fourier function are employed. Thereby, targeted policies for the government can be applied to reduce the discrimination and negative shocks on female adults in the labor market.

Given the critical role of user-generated content (UGC) in e-commerce, exploring various aspects of UGC can aid in understanding user purchase intention and commodity recommendation. Therefore, this study investigates the impact of UGC on purchase decisions and proposes new recommendation models based on sentiment analysis, which are verified in Douban, one of the most popular UGC websites in China.

After verifying the relationship between various factors and product sales, this study proposes two models, collaborative filtering recommendation model based on sentiment (SCF) and hidden factors topics recommendation model based on sentiment (SHFT), by combining traditional collaborative filtering model (CF) and hidden factors topics model (HFT) with sentiment analysis.

The results indicate that sentiment significantly influences purchase intention. Furthermore, the proposed sentiment-based recommendation models outperform traditional CF and HFT in terms of mean absolute error (MAE) and root mean square error (RMSE). Moreover, the two models yield different outcomes for various product categories, providing actionable insights for organizers to implement more precise recommendation strategies.

The findings of this study advocate the incorporation of UGC sentimental factors into websites to heighten recommendation accuracy. Additionally, different recommendation strategies can be employed for different products types.

This study introduces a novel perspective to the recommendation algorithm field. It not only validates the impact of UGC sentiment on purchase intention but also evaluates the proposed models with real-world data. The study provides valuable insights for managerial decision-making aimed at enhancing recommendation systems.