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.

Lighting conditions in learning spaces can affect students’ emotions and influence their performance. This research seeks to verify the influence of classroom lighting on students’ academic performance under different conditions and measurement forms. The research method is based on the systematic review of research articles establishing case analyses characterizing lighting intensity and color temperature to determine ranges favorable to a higher level of attention and long-term memory. Also, this study shows relevant aspects of the cases representative of a sustainable solution and proposes a research model. The study found light intensity values between 350 and 1000 lux and color temperatures between 4000 and 5250 Kelvin that favor attention. Long-term memory reached the highest levels of measurement by analyzing different parameters sensitive to lighting conditions and questionnaires. In conclusion, it was demonstrated that an adequate light intensity and color temperature based on the greatest possible amount of natural light complemented with Light Emitting Diode (LED) light generates optimal lighting for the classroom, achieving energy efficiency in a sustainable solution and promoting student well-being and performance.

The article examines the issues of application and improvement of the methodology for evaluating industrial enterprises as recipients of state support within the framework of the implementation of industrial policy. The authors considered approaches to the content of industrial policy, investigated the factors influencing its efficiency, identified aspects of its imperfections that arise when applying an incomplete list of important parameters of economic development and ambiguity in the interpretation of previously applied estimates. The article presents proposals to improve the methodology for assessing potential recipients of state support based on the development of a comprehensive indicator for assessing enterprises (recipients of support), taking into account not only the classical parameters of the economic efficiency of industrial enterprises applying for state financial assistance, but also such aspects as the development of budgetary funds, belonging to priority sectors of the economy, characteristics of sustainable development and export and innovation potential. Combining the results of a comprehensive assessment of the recipient of state support with a map of the business demography of the territory allows making a decision not only about the fact of support and its efficiency, but also to predict the assessment of the life cycle of the enterprise and its subsequent development.

Rural tourism, which offers authentic cultural and nature-based experiences, is increasingly recognized as a vital tool for sustainable development. Ethiopia, with its rich rural landscapes and cultural heritage, holds immense potential for rural tourism, but the sector remains underdeveloped. This study assesses the facilitating conditions and challenges of rural tourism in Ethiopia using a mixed-methods approach. Results indicate that Ethiopia’s economic growth, improved rural infrastructure, large rural population, higher ethnic and religious diversity index, and 11 UNESCO World Heritage Sites provide strong foundations for rural tourism. However, significant challenges such as inadequate infrastructure, limited marketing, restricted access to financing, ethnic conflicts, environmental degradation, and insufficient stakeholder cooperation hinder its growth. To address these barriers, the study proposes a model encompassing strategic investments in infrastructure, enhancing marketing and promotion, access to finance initiatives, conflict resolution strategies, sustainable tourism practices, enhancing stakeholder coordination, and supportive policy frameworks. By employing these strategies, Ethiopia can harness the full potential of its rural tourism sector, contributing to economic development and community well-being while promoting cultural preservation and environmental sustainability. Also, the proposed model is highly applicable to other developing economies that share similar contexts. Besides, given the importance of the seven fundamental pillars of the model, it remains relevant across tourism types like coastal destinations.

This study sought an innovative quality management framework for Chinese Prefabricated Buildings (PB) projects. The framework combines TQM, QSP, Reconstruction Engineering, Six Sigma (6Σ), Quality Cost Management, and Quality Diagnosis Theories. A quantitative assessment of a representative sample of Chinese PB projects and advanced statistical analysis using Structural Equation Modeling supported the framework, indicating an excellent model fit (CFI = 0.92, TLI = 0.90, RMSEA = 0.06). The study significantly advances quality management and industrialized building techniques, but it also emphasizes the necessity for ongoing research, innovation, and information exchange to address the changing problems and opportunities in this dynamic area. In addition, this study’s findings and recommendations can help construction stakeholders improve quality performance, reduce construction workload and cost, minimize defects, boost customer satisfaction, boost productivity and efficiency in PB projects, and boost the Chinese construction industry’s growth and competitiveness.