This research explores the dynamic intersection of sustainable design, cultural heritage, and community enterprise, focusing on the innovative utilization of post-harvest sugar cane leaves in bamboo basketry production from various provinces in Thailand. This study aims to investigate how design anthropology principles can enhance community enterprises’ resilience and sustainability by employing a qualitative case study approach. Findings reveal that while traditional bamboo basketry reflects the region’s rich cultural heritage, a shift towards sustainable practices offers environmental benefits and economic opportunities. Design anthropology informs the development of culturally relevant products, fostering market competitiveness and preserving traditional craftsmanship. Moreover, government policies play a pivotal role in supporting or hindering the growth of community enterprises, with soft power initiatives holding promise for promoting cultural heritage and sustainability. Collaboration between policymakers, design anthropologists, and local stakeholders is essential for developing inclusive policies that empower communities and foster sustainable development. Overall, integrating sustainable design practices and cultural insights holds significant potential for enhancing the resilience and effectiveness of community enterprises, ensuring a prosperous and sustainable future for both the industry and the communities it serves. This study is a testament that design anthropology provides a powerful framework for addressing complex social and environmental issues through the lenses of culture and design.

The study aims to examine the labor market challenges and motivational factors for employee retention through the example of a small machinery company in Hungary. In recent years, Hungary’s labor market has faced significant difficulties, particularly due to the COVID-19 pandemic, which resulted in temporary unemployment followed by labor shortages. The research aims to identify the motivational, welfare, and financial factors that contribute to employee retention. Due to the small sample size, we did not investigate the relationships concerning loyalty, commitment, and performance. The research methods included comprehensive data collection at a machinery company employing 24 people located near the Austrian-Hungarian border. During the data collection, we conducted a questionnaire survey that included questions related to benefits, performance, commitment, and loyalty. The collected data were processed by calculating weighted averages and differences. The results indicate that flexible working hours and easy accessibility to the workplace are of utmost importance to employees. There is also a significant demand for performance-based pay and diverse, flexible benefit packages. Employees require both formal and informal professional recognition, such as praise and awards. The research has practical significance for both organizational management and employee well-being. Understanding employee opinions and implementing measures based on these can have four primary effects: improvement in employee performance, reduction in turnover, increase in organizational commitment, and enhancement of the company’s positive perception.

The present study focuses on improving Cognitive Radio Networks (CRNs) based on applying machine learning to spectrum sensing in remote learning scenarios. Remote education requires connection dependability and continuity that can be affected by the scarcity of the amount of usable spectrum and suboptimal spectrum usage. The solution for the proposed problem utilizes deep learning approaches, namely CNN and LSTM networks, to enhance the spectrum detection probability (92% detection accuracy) and consequently reduce the number of false alarms (5% false alarm rate) to maximize spectrum utilization efficiency. By developing the cooperative spectrum sensing where many users share their data, the system makes detection more reliable and energy-saving (achieving 92% energy efficiency) which is crucial for sustaining stable connections in educational scenarios. This approach addresses critical challenges in remote education by ensuring scalability across diverse network conditions and maintaining performance on resource-constrained devices like tablets and IoT sensors. Combining CRNs with new technologies like IoT and 5G improves their capabilities and allows these networks to meet the constantly changing loads of distant educational systems. This approach presents another prospect to spectrum management dilemmas in that education delivery needs are met optimally from any STI irrespective of the availability of resources in the locale. The results show that together with machine learning, CRNs can be considered a viable path to improving the networks' performance in the context of remote learning and advancing the future of education in the digital environment. This work also focuses on how machine learning has enabled the enhancement of CRNs for education and provides robust solutions that can meet the increasing needs of online learning.

This study investigates the role of Chat-GPT with augmented reality applications in enhancing tourism experiences in Thailand, focusing on behavioral intentions and innovation adoption to reduce stress in the tourism industry. The research addresses two key objectives: identifying factors driving consumers' behavioral intentions to adopt AR apps and evaluating the robustness of a modified innovation framework for analyzing these intentions. A conceptual model integrating innovativeness, attitudes, perceived enjoyment, and revisit intentions was developed and tested using Structural Equation Modeling with data from 430 Thai tourists who have one to three years of mobile application experience. The findings highlight that service and technology innovation significantly influence perceived enjoyment and attitude, which in turn mediate the impact on behavioral intention to adopt augmented reality applications. At a significance level of p < 0.001, perceived enjoyment and attitude were identified as critical determinants of BI, underscoring the importance of intrinsic user experiences. Tourists are more likely to adopt augmented reality technologies based on personal perceptions and enjoyment rather than external recommendations. This research provides actionable insights for stakeholders in the tourism technology ecosystem, including technology providers, marketers, and policymakers. By emphasizing the interplay of social, emotional, and hedonic factors in shaping user attitudes, the study introduces a robust framework for advancing augmented reality applications in tourism. The findings underscore the importance of user-centric design to drive technology adoption and offer strategic guidance for developers and entrepreneurs aiming to enhance tourism experiences through innovative augmented reality solutions.

This study examines the determinants of audit quality and their impact on detecting financial statement fraud at public accounting firms member of OAI Solusi Manajemen Nusantara in Indonesia. Using a quantitative approach, data was collected through a structured questionnaire distributed to auditors and staff. Key findings highlight the significant influence of auditor independence, professional proficiency, and supervision actions on conducting effective audits, thereby enhancing fraud detection capabilities. The research identifies challenges such as the focus on Indonesian firms and potentially limiting broader applicability. Recommendations include enhancing auditor training, adopting stringent audit procedures and technology, and ensuring adherence to auditing standards to improve audit quality and uphold financial reporting integrity. This study underscores the critical role of audit quality in preventing and detecting financial statement fraud, suggesting avenues for future research to explore additional influencing factors.

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.