Using the Resource Advantage Theory approach, this research aims to examine the gap between entrepreneurial opportunities and marketing performance, with market-based innovation capability acting as a mediating variable. The data collection method used non-probability sampling with a purposive sampling technique. The data that was eligible to be processed were 250 respondents. Hypothesis testing was used using the AMOS application. The research results show that market-based innovation capability can improve marketing performance as a mediating variable. In addition, market penetration strength can also improve marketing performance. As a strategic variable, market-based innovation capability (MBIC) converts entrepreneurial opportunities into competitive advantages relevant to market needs. In addition, business actors become more adaptive and responsive to market dynamics, increasing competitiveness sustainably. MBIC, rooted in the Resource Advantage Theory of competition, contributes to developing market-based innovation strategies in the UMKM sector.

This study investigates the career expectations of individuals in Thailand’s emerging economy, emphasizing the critical factors that shape these expectations within the context of a rapidly evolving labour market in the digital era. A quantitative approach was employed, collecting data from 1230 Thai respondents through convenience sampling, utilizing a structured survey as the primary research instrument. Data analysis involved the use of percentages, means and logistic regression to provide a comprehensive understanding of the findings. The results indicate that factors such as gender, age, monthly income, professional identity, values, culture and technology usage (including devices like laptops, social media platforms, home internet access and usage hours) significantly influence career expectations. Understanding these influential factors is crucial for developing targeted strategies to enhance career satisfaction, preparedness and overall competitiveness in an increasingly globalized and digital economy. By addressing the unique needs and aspirations of the Thai workforce, particularly in this digital age, stakeholders can cultivate a more responsive and adaptive professional environment, ultimately contributing to national economic growth in the digital era.

This study explores the impact of digital economy engagement and digital adoption on the entrepreneurship performance of Small and Medium Enterprises (SMEs) in Malaysia, with a specific focus on the PG Mall platform. Through an analysis of SMEs’ involvement in digital activities such as e-commerce, digital marketing, and data analytics, the research identifies key factors that enhance business performance. The main objective of this paper is to examines the mediating role of government policies in supporting digital adoption and fostering a conducive environment for digital entrepreneurship. This paper employed a quantitative method to examine the impact of digital economy engagement and digital adoption on the entrepreneurship performance of Small and Medium Enterprises (SMEs) in Malaysia, with a focus on the PG Mall platform. Through data analysis, this research assessed several hypotheses related to the relationship between digital engagement, adoption, and business performance. The findings revealed that the majority of the hypotheses were supported, confirming the positive influence of digital economy engagement and digital adoption on various aspects of entrepreneurship performance. Based on these findings, this paper also proposes a conceptual framework that highlights the elements of digital economy engagement and digital adoption that contribute to SME performance. This framework serves as a valuable guideline for government policymakers, practitioners, and scholars in shaping strategies to foster digital entrepreneurship. It underscores the importance of supportive government policies, such as financial incentives and training, in facilitating the digital transformation of SMEs. By providing a structured approach to understanding the role of digital tools in enhancing business outcomes, the framework offers a foundation for future research and policy development aimed at promoting digital entrepreneurship in an evolving economic landscape.

The quality of indoor classroom conditions influences the well-being of its occupants, students and teachers. Especially the temperature, outside acceptable limits, can increase the risk of discomfort, illness, stress behaviors and cognitive processes. Assuming the importance of this, in this quantitative observational study, we investigated the relationship between two environmental variables, temperature and humidity, and students’ basic emotions. Data were collected over four weeks in a secondary school in Spain, with environmental variables recorded every 10 minutes using a monitoring kit installed in the classroom, and students’ emotions categorized using Emotion Recognition Technology (ERT). The results suggest that high recorded temperatures and humidity levels are associated with emotional responses among students. While linear regression models indicate that temperature and humidity may influence students’ emotional experiences in the classroom, the explanatory power of these models may be limited, suggesting that other factors could contribute to the observed variability in emotions. The implications and limitations of these findings for classroom conditions and student emotional well-being are discussed. Recognizing the influence of environmental conditions and monitoring them is a step toward establishing smart classrooms.

In agriculture, crop yield and quality are critical for global food supply and human survival. Challenges such as plant leaf diseases necessitate a fast, automatic, economical, and accurate method. This paper utilizes deep learning, transfer learning, and specific feature learning modules (CBAM, Inception-ResNet) for their outstanding performance in image processing and classification. The ResNet model, pretrained on ImageNet, serves as the cornerstone, with introduced feature learning modules in our IRCResNet model. Experimental results show our model achieves an average prediction accuracy of 96.8574% on public datasets, thoroughly validating our approach and significantly enhancing plant leaf disease identification.

The study aims to explore the impact of examination-oriented education on Chinese English learners and the importance of cultural intelligence in second language acquisition. Through a questionnaire administered to postgraduate students majoring in English in China, the research discovered that the emphasis on test scores and strategies in China’s higher English education system has led to a neglect of cultural backgrounds and cross-cultural communication. The findings underscore the necessity for reforms in English teaching within Chinese higher education to cultivate students’ intercultural intelligence and enhance their readiness for international careers in the era of globalization.