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.

International logistics supply chain is an important guarantee to support the country to build a new development pattern, this paper aims to propose a new strategy to promote the development of international logistics supply chain through the case study of Ningbo City. On the basis of supply chain theory and international logistics theory, this paper constructs SWOT model to study the case of Ningbo City, and draws the following conclusions: The international logistics supply chain of Ningbo city has the advantages of superior geographical location, perfect logistics infrastructure and strong port resources, and the disadvantages of low logistics informatization level and logistics management mode to be optimized. At the same time, it faces the opportunities of “One Belt and One Road” initiative and the competitive threat of other logistics centers. Adopting strategies such as policy support, strengthening logistics informatization construction and optimizing logistics management mode can ensure the stable development of foreign trade, which is conducive to accelerating the construction of a new development pattern and modern economic system in which domestic and foreign cycles promote each other.

This study aims at predicting the interrelationship between among Chat GPT with its six dimensions, tourist’s satisfaction and Chat GPT usage intention as perceived by tourist, and as well as to examine the moderating effect of traditional tour operator services on the relationships between all the variables. Data were collected from 624 tourists. The study hypotheses were tested and the direct and indirect effects between variables were examined using the PLS-SEM. The SEM results showed that Chat GPT’s six dimensions have a positive and significant direct impact on tourist’s satisfaction, and emphasis the moderating role of Traditional Tour Operator Services “TTOS” on the relationship between GPT’s six dimensions and “TS”, and on the relationship between ‘TS” and Chat GPT usage intention. These findings yield valuable insights for everyone interested in the use of IT in the tourism industry, and provide effective strategies for optimizing the use of technological applications by traditional tour operators.

An extensive assessment index system was developed to evaluate the integration of industry and education in higher vocational education. The system was designed using panel data collected from 31 provinces in China between 2016 and 2022. The study utilized the entropy approach and coupled coordination degree model to examine the temporal and spatial changes in the level of growth of the integration of industry and education in higher vocational education, as well as the factors that impact it. In order to examine how the integration of industry and education in higher vocational education develops over time and space, as well as the factors that affect it, we utilized spatial phasic analysis, Tobit regression model, and Dagum’s Gini coefficient. The study’s findings suggest that between 2016 and 2022, the integration of industry and education in higher vocational education showed a consistent improvement in overall development. Nevertheless, there are still significant regional differences, with certain areas showing limited levels of integration, while the bulk of regions are either in a state of low integration with high clustering or low integration with low clustering. Most locations showed either a “low-high” or “low-low” level of agglomeration, indicating a significant degree of spatial concentration, with a clear trend of higher concentration in the east and lower concentration in the west. The progress of industrial structure and the degree of regional economic development have a substantial impact on the amount of integration of industry and education in higher vocational education. There is a notable increase in the amount of integration between industry and education in higher vocational education, which has a favorable effect. Conversely, the local employment rate has a substantial negative effect on this integration. Moreover, the direct influence of industrial structure optimization is restricted. The Gini coefficient of the development level of integration of industry and education in higher vocational education exhibits a slight rising trend. Simultaneously, there is a varying increase in the Gini coefficient inside the group and a decrease in the Gini coefficient between the groups. The disparities in the level of integration between Industry and Education in the provincial area primarily stem from inter-group variations across the locations. To promote the integration of industry and education in higher vocational education, it is recommended to strengthen policy support and resource allocation, address regional disparities, improve professional configuration, and increase investment in scientific and technological innovation and talent development.

In rural areas, land use activities around primary arterial roads influence the road section’s traffic characteristics. Regulations dictate the design of primary arterial roads to accommodate high speeds. Hence, there is a mix of traffic between high-speed vehicles and vulnerable road users (pedestrians, bicycles, and motorcycles) around the land. As a result, researchers have identified several arterial roads in Indonesia as accident-prone areas. Therefore, to improve the road user’s safety on primary arterial roads, it is necessary to develop models of the influence of various factors on road traffic accidents. This research uses binary logistic regression analysis. The independent variables are carelessness, disorderliness, high speed, horizontal alignment, road width, clear zone, road shoulder width, signs, markings, and land use. Meanwhile, the dependent variable is the frequency of accidents, where the frequency of accidents consists of multi-accident vehicles (MAV) and single-accident vehicles (SAV). This study collects data for a traffic accident prediction model based on collision frequency in accident-prone areas. The results, road shoulder width, and road sign factor all have an impact on the frequency of traffic accidents. According to a realistic risk analysis, MAV and SAV have no risk difference. After validation, this model shows a confidence level of 92%. This demonstrates that the model generates estimations that accurately reflect reality and are applicable to a wider population. This research has the potential to assist engineers in improving road safety on primary arterial roads. In addition, the model can help the government measure the impact of implemented policies and engage the public in traffic accident prevention efforts.

The study’s objective is to identify the challenges and limitations faced by the current vocational education system in preparing graduates in the era of the industrial revolution in the evolving job market in Tangerang, Indonesia. The study primarily examines vocational high schools and adopts a quantitative and quasi-experimental research approach, using control groups to conduct pre- and posttests. The experimental group experiences demonstrations, whereas the control group receives explanations. Instructors employ a blend of demonstration and explanation techniques to explain equipment operation before allowing students to engage in vocational training. The study, led by students in various engineering fields, evaluates technical competencies, work ethics, and foundational knowledge using tests and observations. Job preparation is assessed using the minimal completeness criteria (MCC), which focuses on the importance of proper knowledge, attitudes, and skills. The results indicate that vocational teachers have the potential to play a pivotal role in introducing cutting-edge, technology-based teaching methods, therefore enabling students to make well-informed decisions about their careers. This research enhances vocational education by incorporating practical skills and attitudes with academic knowledge, effectively addressing the changing requirements of the work market.