E-learning has become an integral part of higher education, significantly influencing the teaching and learning landscape. This study investigates the impact of student characteristics such as gender, grade, and major on E-learning satisfaction. Utilizing Structural Equation Modeling (SEM) and collecting data through 527 valid questionnaires from Nanjing Normal University students, this research reveals the nuanced relationships between these variables and E-learning satisfaction. The findings indicate that gender, grade, and major significantly and positively impact student satisfaction with E-learning, highlighting the need for tailored E-learning resources to meet diverse student needs. The study underscores the importance of continuous improvement in E-learning resources and platforms to enhance student satisfaction. This research contributes to the understanding of effective E-learning strategies in higher education institutions.

This study examines the microeconomic determinants influencing remittance flows to Vietnam, considering factors such as gender (SEX), age (AGE), marital status (MS), income level (INC), educational level (EDU), financial status (FS), migration expenses (EXP), and foreign language proficiency (LAN). The study analyzes the impact of these factors on both the volume (REM_VL) and frequency of remittance flows (REM_FR), employing ordered logistic regression on survey data collected from Vietnamese migrants residing in Asia, Europe, the Americas, and Oceania. The estimations reveal that migrants’ income, age, educational level, and migration costs significantly positively influence remittance flows to Vietnam. Conversely, the financial status of migrants’ families in the home country negatively impacts these flows. Gender and migration costs primarily influence the frequency of remittance transfers, but they do not have a significant effect on the volume of remittances. Although foreign language proficiency was introduced as a novel variable of the models, it does not demonstrate any significant impact in this study. Furthermore, the survey data and regression estimates suggest that two primary motivations drive remittances to Vietnam: altruistic motives and implicit loan agreements. This research contributes to a deeper understanding of remittance e behavior, particularly in the context of Vietnam’s status as a major labor exporter. The findings provide valuable insights for policymakers and researchers seeking to optimize remittance flows and their impact on the Vietnamese economy. By understanding the complex interplay of factors influencing remittance behavior, policymakers can design effective strategies to support migrants and encourage increased remittance inflows, ultimately contributing to economic development and poverty reduction.

This research aimed to investigate the role of humanizing leadership in enhancing the effectiveness of change management strategies within organizations. Specifically, it focused on how humanizing leadership influences change outcomes and the extent to which organizational culture moderates this relationship. The study addressed critical questions regarding the impact of leadership behaviors, such as model vulnerability, emotional intelligence, open communication, and psychological safety on effective change management and employee performance. A quantitative approach was employed to provide a comprehensive analysis of the phenomena. Quantitative data were collected from a sample of 325 employees through surveys that measured perceptions of Humanizing leadership behaviors, organizational culture, and change outcomes. Data was analyzed by IBM SPSS 26.0. The findings revealed that humanizing leadership behaviors significantly enhances the success of change initiatives, primarily through improved employee engagement and reduced resistance. Organizational culture was found to play a moderating role, amplifying the positive effects of empathetic and inclusive leadership practices. The study provides actionable recommendations for organizational leaders and managers to foster a culture that supports humanizing leadership. By adopting leadership strategies that emphasize vulnerability, empathy, and inclusivity, organizations can enhance their adaptability and resilience against the backdrop of continuous change. These findings are particularly valuable for enhancing managerial practices and informing policy within corporate settings.

This study explored the relationships between green market orientation and competitive advantage, with a particular focus on the mediating role of green sustainable innovation. The research utilized a structured questionnaire to gather data from managers involved in environmental protection and professionals working in the manufacturing sectors of computers, electronics, optical products, and electrical equipment. The survey targeted respondents from key regions in Saudi Arabia, including Riyadh, Qassim, and the Eastern Province, resulting in a total of 273 responses. The collected data were analyzed using structural equation modeling (SEM), a robust statistical technique that allows for the examination of complex relationships between variables. The findings confirmed a mediational model where green sustainable innovation—comprising both green product and green process innovation—served as a critical intermediary linking green market orientation to competitive advantage. Furthermore, the study validated direct effects of green market orientation on both green sustainable innovation and competitive advantage. These results emphasize the dual pathways through which green market orientation influences business performance. The research concludes by offering actionable insights for Saudi managers, highlighting strategies to maximize profitability and competitiveness through the adoption and implementation of green sustainable innovation practices.

Among contemporary computational techniques, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are favoured because of their capacity to tackle non-linear modelling and complex stochastic datasets. Nondeterministic models involve some computational intricacies when deciphering real-life problems but always yield better outcomes. For the first time, this study utilized the ANN and ANFIS models for modelling power generation/electric power output (EPO) from databases generated in a combined cycle power plant (CCPP). The study presents a comparative study between ANNs and ANFIS to estimate the power output generation of a combined cycle power plant in Turkey. The inputs of the ANN and ANFIS models are ambient temperature (AT), ambient pressure (AP), relative humidity (RH), and exhaust vacuum (V), correlated with electric power output. Several models were developed to achieve the best architecture as the number of hidden neurons varied for the ANNs, while the training process was conducted for the ANFIS model. A comparison of the developed hybrid models was completed using statistical criteria such as the coefficient of determination (R²), mean average error (MAE), and average absolute deviation (AAD). The R² of 0.945, MAE of 3.001%, and AAD of 3.722% for the ANN model were compared to those of R² of 0.9499, MAE of 2.843% and AAD of 2.842% for the ANFIS model. Even though both ANN and ANFIS are relevant in estimating and predicting power production, the ANFIS model exhibits higher superiority compared to the ANN model in accurately estimating the EPO of the CCPP located in Turkey and its environment.

In the current context of multicultural collision, online information is impacting traditional gender values. To analyze the changes in gender role attitudes and gender awareness among Chinese Generation Z college students under the influence of various social factors, the study focuses on Generation Z college students and explores the impact of cultural, media, educational, and family factors on gender role attitudes and gender awareness among Chinese Generation Z college students through questionnaire surveys and quantitative analysis methods. The research results show that Generation Z college students exhibit extremely favorable gender perspectives, with the proportion of bisexual gender roles approaching 38%, surpassing the number of students with traditional understanding of single sex gender roles. At the same time, in school gender awareness education, research has found that the proportion of bisexual gender roles is the highest among students who accept open mindedness, at 46.6%. In family gender awareness education, students who receive parental gender awareness sharing education have the highest proportion of bisexual gender roles, accounting for 48.5%. Therefore, the current gender education for the new Generation of students in China needs to abandon traditional avoidance-based teaching methods and adopt an open and supportive attitude to guide students’ gender values.

Thailand and the EU started negotiating a free trade agreement (FTA) in 2005, but negotiations were subsequently suspended in 2014 after the country’s military coup. The significance of these negotiations are important because of the mutual benefit of achieving higher levels of trade and investment between the world’s largest single market and the second largest ASEAN economy. The Specific Factors (SF) model of production and trade is applied to identify potential winner and loser industries and factors of production in Thailand. The model identifies short-run loses for some labor inputs, return to capital, and output in agriculture and services. In the manufacturing and energy sectors, higher output will benefit some labor inputs and capital owners. Understanding the short-run impact of an FTA could allow policymakers in Thailand to reinforce the institutional infrastructure such as implementing trade adjustment assistance programs (TAA), to help re-train workers who may become unemployed due to free trade.

This study aims to analyze the effect of financial literacy and financial education on digital financial inclusion in Mexico. The analysis is carried out with 13,554 data from the National Survey of Financial Inclusion 2021, corresponding to Mexican adults who use digital financial services. The population under study comprises people over 18 years old, residing in Mexico, disaggregated by size of locality, and divided into six geographical regions. The dichotomous Probit model is used to estimate the effect of financial literacy and sociodemographic variables on digital financial inclusion. The results show that financial literacy and financial education have a marginal effect, of 0.94% and 4.42%, respectively, on digital financial services. Results also show that the marginal effect of financial literacy and financial education is greater on the use of mobile payments than on the acquisition of online accounts or apps and online credit. The results also show that gender, locality size, educational level, income and asset holding have a statistically significant relationship with the use of digital financial services. The findings confirm that financial literacy and financial education contribute to the digital financial inclusion of Mexicans, in this sense, providing financial education can especially benefit vulnerable population groups such as those living in rural areas and those with low income and low education levels.