The growing attention paid to industrial tourism can be seen as one of the major trends in cultural tourism and marketing and has given currency to the proposition that customer experience of industrial tourism acts as a direct personal source of information about their perceptions of companies visited and is essential for customer relationship management of companies. This study applies the service theater theory and proposes a model to explore the structural relationships among theatrical elements of industrial tourism (including setting, performance, and actor), the dimensions of customer experience (enjoyment, learning, and escape), and customers’ behavior intentions. A survey of 500 industrial tourists in a transparent factory in the health food industry was conducted in Zhuhai, Guangdong, China. The results of structural equation modeling indicate that two theatrical factors (setting and performance) relate positively to all dimensions of customer experiences. In contrast, the theatrical factor “actor” only relates positively to the learning experience. Furthermore, all dimensions of customer experience, in turn, positively affect customers’ behavioral intentions. This study will be helpful for corporate managers and tourism organizers who aim to develop and implement marketing strategies based on the service theatre theory to improve their services.

A method for studying the resilience of energy and socio-ecological systems is considered; it integrates approaches developed at the International Institute of Applied Systems Analysis and the Melentyev Institute of Energy Systems (MESI) of the Siberian Branch of the Russian Academy of Sciences. The article discusses in detail the methods of using intelligent information technologies, in particular semantic technologies and knowledge engineering (cognitive probabilistic modeling), which the authors propose to use in assessing the risks of natural and man-made threats to the resilience of the energy sector and social and ecological systems. More attention is paid to the study and adaptation of the integral indicator of quality of life, which makes it possible to combine these interdisciplinary studies.

In China, ideological and political education is currently the hot direction of teaching reform in various colleges and universities, yet the development of appropriate teaching evaluation methods needs to catch up. This study addresses the pressing need for a preliminary investigation into the complex relationships among ideological and political education, the students’ learning satisfaction and teaching quality. This research examines the influence of teaching and ideological and political education quality on students’ satisfactions by designing a set of scales, collecting about 3800 questionnaires. Utilizing Structural Equation Modeling (SEM) and qualitative interviews, this study reveals that the teaching quality directly affects students’ learning satisfaction and ideological and political education. Notably, ideological and political education can also affect students’ learning satisfaction. The findings underscore the importance of including ideological and political education assessments in evaluating courses. This research contributes to the ongoing dialogue on effective teaching evaluation methods in the context of evolving educational practices.

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.

 Beach protection is vital to reduce the damage to shorelines and coastal areas; one of the artificial protections that can be utilized is the tetrapod. However, much damage occurred when using a traditional tetrapod due to the lack of stability coefficient (K_D). Therefore, this research aims to increase the stability coefficient by providing minor modifications to the cape of the tetrapod, such as round-caped or cube-caped. The modification seeks to hold the drag force from the wave and offer a good interlocking in between the tetrapod. This research applied physical model test research using a breakwater model made from the proposed innovative tetrapod with numerous variations in dimensions and layers simulated with several scenarios. The analysis was carried out by graphing the relationship between the parameters of the measurement results and the relationship between dimensionless parameters, such as wave steepness H/gT2, and other essential parameters, such as the K_D stability number and the level of damage in %. The result shows that the modified and innovative tetrapod has a more excellent K_D value than the conventional tetrapod. In addition, the innovative tetrapod with the cube-shaped has a recommended K_D value greater than the round shape. This means that for the modified tetrapod structure and the same level of security, the required weight of the tetrapod with the cube cap will be lighter than the tetrapod with the round cap. These findings have significant practical implications for coastal protection and engineering, potentially leading to more efficient and cost-effective solutions.

This study delves into the evolving landscape of smart city development in Kazakhstan, a domain gaining increasing relevance in the context of urban modernization and digital transformation. The research is anchored in the quest to understand how specific technological factors influence the formation of smart cities within the region. To this end, the study adopts a Spatial Autoregressive Model (SAR) as its core analytical tool, leveraging data on server density, cloud service usage, and electronic invoicing practices across various Kazakhstani cities. The crux of the research revolves around assessing the impact of these selected technological variables on the smart city development process. The SAR model’s application facilitates a nuanced understanding of the spatial dynamics at play, offering insights into how these factors vary in influence across different urban areas. A key finding of this investigation is the significant positive correlation between the adoption of electronic invoicing and smart city development, a result that stands in contrast to the relatively insignificant impact of server density and cloud service usage. The conclusion drawn from these findings underscores the pivotal role of digital administrative processes, particularly electronic invoicing, in driving the smart city agenda in Kazakhstan. This insight not only contributes to the academic discourse on smart cities but also holds practical implications for policymakers and urban planners. It suggests a strategic shift towards prioritizing digital administrative innovations over mere infrastructural or technological upgrades. The study’s outcomes are poised to guide future smart city initiatives in Kazakhstan and offer a reference point for similar emerging economies embarking on their smart city journeys.