The purpose of this research is to estimate the differences in sales levels between businesses owned by individuals who self-identify as Indigenous (IE) and those who do not (NIE), as well as between males (ME) and females (WE), and how this intersection may affect their sales levels. To accomplish this, an Analysis of Variance (ANOVA) is used to compare the means between the groups analyzed, and Tukey’s Honestly Significant Differences (HSD) is used to determine the magnitude and direction of these differences. The results of the study show that indigenous-owned businesses have sales that are 26% lower than the general average, while women-owned businesses have sales that are 70.6% lower in the same comparison. In addition, businesses run by indigenous women have sales that are 93.5% lower on average. These findings suggest that the challenges faced by entrepreneurs reflect the structural inequalities observed in other areas of society and highlight the need for public and private policies focused on reducing these gaps.

With the continuous development of educational information technology, college English teaching is gradually transitioning to digital and informational. This article discusses and researches the application of educational information technology, the impact of educational information technology on student learning outcomes, changes and reasons in learning methods, and the construction of college English teaching staff under educational information technology. It is believed that conducting effective research on college English teaching under educational information technology will not only help improve the level of college English teaching, but also promote the development of educational informationization.

The advent of Artificial Intelligence (AI) has transformed Learning Management Systems (LMSs), enabled personalized adaptation and facilitated distance education. This study employs a bibliometric analysis based on PRISMA-2020 to examine the integration of AI in LMSs from an educational perspective. Despite the rapid progress observed in this field, the literature reveals gaps in the effectiveness and acceptance of virtual assistants in educational contexts. Therefore, the objective of this study is to examine research trends on the use of AI in LMSs. The results indicate a quadratic polynomial growth of 99.42%, with the years 2021 and 2015 representing the most significant growth. Thematic references include authors such as Li J and Cavus N, the journal Lecture Notes in Computer Science, and countries such as China and India. The thematic evolution can be observed from topics such as regression analysis to LMS and e-learning. The terms e-learning, ontology, and ant colony optimization are highlighted in the thematic clusters. A temporal analysis reveals that suggestions such as a Cartesian plane and a league table offer a detailed view of the evolution of key terms. This analysis reveals that emerging and growing words such as Learning Style and Learning Management Systems are worthy of further investigation. The development of a future research agenda emerges as a key need to address gaps.

This study aims to explore the design and application of a learning achievement evaluation model, in order to improve the quality of teaching in the field of education and promote student development. This article starts with the importance of constructing a learning effectiveness evaluation model, and then clarifies the basic concepts and related theories of learning effectiveness evaluation, providing theoretical support for subsequent model design. In the model design section of learning effectiveness evaluation, propose the model design principles, indicator selection, and construction process to ensure the accuracy and comparability of the evaluation model construction. In the application and evaluation section of the learning effectiveness evaluation model, the application and evaluation methods of the main models in practical teaching were explored. Finally, the issues that need to be noted in the design process of the evaluation model were proposed in order to design a more high-quality evaluation system and promote the improvement of education quality.

This study focuses on the problems of imperfect internal control effectiveness, insufficient information transparency, and plummeting stock prices. The study selects the data of non-financial main board listed companies in China’s Shanghai and Shenzhen A-shares from 2012 to 2021 as a sample, and adopts an empirical research methodology, which reveals that the effectiveness of internal control is negatively related to the trend of share price crash, and efficient internal control is positively related to the transparency of corporate information environment. The findings suggest the impact of internal control on the risk of stock price crash at the individual stock level and provide empirical support for listed companies to manage their risks. This study has practical value in guiding listed companies to strengthen internal control, improve information transparency, mitigate the risk of stock price crashes, and provide a decision-making basis for the healthy and stable development of the capital market.

Reusable bags have been introduced as an alternative to single-use plastic bags (SUPB). While beneficial, this alternative is economically and environmentally viable only if utilized multiple times. This study aims to identify the determinants influencing the use of reusable bags (RB) over single-use plastic bags (SUPB) within the framework of ecological impact reduction, employing the Theory of Planned Behavior (TPB). The focus is on understanding how attitudes (AT), subjective norms (SN), and perceived behavioral control (PBC) collectively guide consumers towards adopting reusable bags as a pro-environmental choice. The focus is on understanding how attitudes (AT), subjective norms (SN), and perceived behavioral control (PBC) collectively guide consumers towards the adoption of reusable bags as a pro-environmental choice. Data were collected through a survey administered to 814 consumers in Lahore, employing both regression analysis and Structural Equation Modeling (SEM) to assess the impact of AT, SN, and PBC on reusable bag consumption (RBC). The TPB framework underpins the hypothesis that these three psychological factors significantly influence the decision to use RBs. Both regression and SEM analyses demonstrated that AT, SN, and PBC positively affect RBC, with significant estimates indicating the strength of each predictor. Specifically, PBC emerged as the strongest predictor of RBC (PBC2, β = 0.533, p < 0.001), highlighting the paramount importance of control perceptions in influencing bag use. This was followed by AT (β = 0.211, p < 0.001) and SN (β = 0.173, p < 0.001), confirming the hypothesized positive relationships. The congruence of findings from both analytical approaches underlines the robustness of these techniques in validating the TPB within the context of sustainable consumer behaviors. The investigation corroborates the TPB’s applicability in predicting RBC, with a clear hierarchy of influence among the model’s constructs. PBC’s prominence underscores the necessity of enhancing consumers’ control over using RBs to foster sustainable consumption patterns. Practical implications include the development of policies and marketing strategies that target the identified determinants, especially emphasizing the critical role of PBC, to promote broader adoption of RBs and contribute to significant reductions in plastic waste.