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.

Using data from 31 provinces, municipalities, and autonomous regions in mainland China from 2006 to 2019, we employ a double difference (DID) model and a spatial double difference (SDID) model to estimate the impact of the High-speed Railway (HSR) on the income gap between urban and rural residents, as well as its spatial spillover effects. Our research reveals several key findings. Firstly, the introduction of high-speed railways helps to narrow the income gap between urban and rural residents within local areas, but its spatial effects can lead to an increase in the income gap in neighboring provinces. Secondly, from a spatial perspective, intermediate variables such as industrial structure, education, science and technology, and foreign trade can also contribute to balancing the income gap between urban and rural residents, although the impact of population mobility is not significant. Thirdly, further analysis of the spatial effects demonstrates that education plays a significant role in balancing the income gap both within the local province and neighboring provinces. Additionally, adjustments in industrial structure, advancements in science and technology, and foreign trade have stronger spillover effects in reducing the income gap among neighboring provinces compared to their impact at a local level.

This study focuses on the problems of imperfect internal control effectiveness, insufficient information transparency, and plummeting stock prices. The study selects the data of non-financial main board listed companies in China’s Shanghai and Shenzhen A-shares from 2012 to 2021 as a sample, and adopts an empirical research methodology, which reveals that the effectiveness of internal control is negatively related to the trend of share price crash, and efficient internal control is positively related to the transparency of corporate information environment. The findings suggest the impact of internal control on the risk of stock price crash at the individual stock level and provide empirical support for listed companies to manage their risks. This study has practical value in guiding listed companies to strengthen internal control, improve information transparency, mitigate the risk of stock price crashes, and provide a decision-making basis for the healthy and stable development of the capital market.

This study seeks to explore the uses, behaviors and perceptions of university students regarding mobile phones to help elucidate whether there is a relationship between the use of mobiles and the academic performance of university students. A quantitative approach based on an ad hoc questionnaire, applied before the pandemic, was used to gather evidence in this regard, which revealed the uses and educational visions of mobile phones in a convenience sample of 314 university students from nine different degree courses in two Spanish universities. Three major conclusions are formulated as part of future lines of development. First, although there is frequent use of mobile phones, the image of the mobile as a learning resource in the university classroom does not reach one-third of students. Second, although this study does not determine the causal relationship, there is a statistically significant negative relationship between average grades achieved and hours of dedication to the mobile phone. Finally, students who are unable to spend more than one hour without checking their phone obtain a significantly lower average mark than those who can stay more than one hour without checking their phone.

The policy to accelerate the design of the Detailed Spatial Plan regulation document (RDTR) is a strategic step to enhance ease of doing business and promote sustainable development in Indonesia. Targeting 2036 RDTR sites nationwide, the initiative relies on various policy interventions and technical approaches. However, as of 8 January 2024, only 399 RDTRs (19.59%) were enacted after four years of implementation. This underperformance suggests the need to examine factors influencing the process, including issues at each stage of the RDTR design business process. While often overlooked due to its perceived irrelevance to the core substance of planning, analyzing the process is crucial to addressing operational and procedural challenges. This research identifies critical issues arising from the preparation to the enactment stage of RDTR regulations and proposes necessary policy changes. Using an explanatory approach, the study employs methods such as Analytic Hierarchy Process (AHP), post-review analysis, stakeholder analysis, business process evaluation, and scenario planning. Results show several impediments, including challenges related to commitment, technical and substantive issues, managerial coordination, policy frameworks, ICT support, and data availability. These findings serve as inputs for the development of business process improvement scenarios and reengineering schemes based on Business Process Management principles.

Industrial zones require careful and meticulous planning because industry can have a major impact on the surrounding environment. The research location is the northern part of West Java Province which is a gold triangle area named Rebana Triangle Area. The purpose of this study is to measure the weight of the research variables in determining industrial zones from the results of fuzzy analytical hierarchy process (F-AHP) analysis, assessing the location of industrial zones in the research area based on important variables in determining industrial zones. The result of this study is the weight of the research variables in determining the industrial zone from the results of the fuzzy analytical hierarchy process (F-AHP) analysis obtained is the availability of electrical infrastructure with an influence weight of 15.00%. The second most influential factor is the availability of telecommunications infrastructure with an effect of 13.02%, the distance of land to roads and access of 11.76%, land use of 11.21%, distance of land to public facilities of 9.99%, labour cost work is 9.60%, the distance of land to the river is 8.19%, the price of land is 7.97%, the slope is 6.79%, and the type of soil is 6.43%. This GIS analysis model can be a reference model for the government in determining the potential of industrial zones in other regions in Indonesia. A total of 4822.41 Ha or the equivalent of 3.50% of the total area of 6 (six) regencies/cities research areas which are very suitable to be used as industrial zones. The district that has the largest area of potential industrial zone is Majalengka, while Cirebon does not have a location that has the potential for industrial zone locations. Based on the results of the analysis of 10 (ten) variables for determining industrial zones from expert opinion, a draft policy proposal for the government can be proposed, among others. These 10 (ten) variables are variables that are expected to be mandatory variables in planning and determining the location of potential industrial areas.