The smallest administrative unit of the sixth national census-township (town) is selected as the basic unit, the population spatial distribution characteristics at the township (town) level in karst mountainous areas of northwest Guangxi are analyzed by using Lorenz curve and spatial correlation analysis method, and the influence intensity of natural factors on regional population spatial distribution is detected by using geographic detector method. The results show that: 1. the spatial distribution of population at the township (town) level has the characteristics of imbalance, showing generally significant positive correlation and certain aggregation; 2. There are significant differences in the impact of the spatial distribution of various natural factors on the population distribution. For the towns without karst distribution in the northwest and central south of the study area, the population density increases with the increase of factors conducive to human residence, but the average population density is only 79 people/km². In the towns with karst distribution in the East and south, the spatial distribution of population density and natural factors is not a simple increase or decrease relationship, but fluctuates with the change of karst distribution area. 3. The factor detection results of the geographic detector show that the altitude has the greatest impact on the spatial distribution of population. The interactive detection results show that the impact intensity of any two natural factors after superposition and interaction presents nonlinear enhancement and two factor enhancement. It can be seen that the karst mountain area in northwest Guangxi is similar to other areas. Altitude is one of the main factors affecting the spatial distribution of population, but the river network density and unique geological landform of karst mountain area have a strong catalytic effect on the spatial distribution of population. The superposition and interaction with other factors can further strengthen the impact on population distribution.

Low-cost housing homeownership funding for junior staffers is challenging in private sector organisations, especially in developing countries. Motivating private sector investment in junior staffers’ homeownership via a developed expanded corporate social responsibility (ECSR) may promote achieving Sustainable Development Goal 11 (SDG 11). Therefore, the study investigates the role of the ECSR framework in improving Nigeria’s private sector junior staffers’ homeownership and achieving SDG 11. Data were collected via face-to-face interviews with selected participants in six of Nigeria’s geo-political zones. The study adopted thematic analysis to analyse the collected data. Six variables emerged from the 18 re-clustered sub-variables. This includes institutionalising ECSR in low-income homeownership, housing finance for junior staffers’ homeownership, and housing incentives and stakeholders’ participation for low-income earners. The research employed six variables and 18 sub-variables to develop the improved private sector’s junior staffers’ homeownership via ECSR and achieving SDG 11 (sustainable cities and communities) and their targets. The research presents a novel approach by attempting to integrate SDG 11 with Corporate Social Housing, an extension of corporate social responsibility, especially to align the SDGs with evolving perspectives on Expanded Corporate Social Responsibility in Nigeria.

Entering the era of knowledge economy, various academic researches are blossoming under the social environment of double creation, but looking at the disputes of intellectual property cases in recent years, most of them happen in the college students group, the reasons for this phenomenon can be summarized as the blurring of the intellectual property education program, the system is too traditional and conservative, and the teaching concept is thin and so on. In view of this phenomenon, the author proposes to cultivate the intellectual property education of university students in the mode of "three constructions", so as to stimulate the vigor of social innovation and provide theoretical support for the scientific and technological research of university students.

This study explores the interactions between inflation and stock market. We carried out a bibliometric analysis with R package to highlight the worldwide research trends in the field, covering the period of three crises (financial, health crisis and war of Ukraine). Next, using monthly data for the period from 1 March 2020 to 31 August 2023 and based on a vector autoregressive model, impulse response and variance decomposition are performed to explore the dynamic relationships between inflation and Greek stock market. The results reveal the existence of high volatility in Athens’ stock market during COVID-19 pandemic, owning to a shock of the inflation. Regarding the period of Ukrainian war, the study verified the Fama’s hypothesis that there is a negative relationship between inflation and stock returns. The findings have significant implications for investors and policy makers.

This study examined the role of cryptocurrencies in tourism and their acceptance across EU regions, with particular attention to the digital transformation precipitated by the COVID-19 pandemic. The analysis focuses on the relationship between cryptocurrency acceptance points and the intensity of tourism, highlighting that the acceptance of cryptocurrencies is significantly correlated with tourism services. The literature review highlighted that Web 3.0, especially blockchain technology and decentralized applications, opens new possibilities in tourism, including secure and transparent transactions, and more personalized travel experiences. The research investigated cryptocurrency acceptance points and the intensity of tourism within the EU. The study illuminates that the acceptance of cryptocurrencies significantly correlates with tourism services. The data and methodology demonstrated the analysis methods for examining the relationship between cryptocurrency acceptance points and tourism intensity, including the use of clustering neural networks and Eurostat data utilization. The results showed a positive correlation between the number of cryptocurrency acceptance points and tourism intensity in the EU, affirming the research hypothesis. According to the regression analysis results, each additional cryptocurrency acceptance point is associated with an increase in tourism intensity. The significance of the research lies in highlighting the growing role of digital payment solutions, especially cryptocurrencies, in tourism, and their potential impacts on the EU economy. The analysis supports that the intertwining of tourism and digital financial technologies opens new opportunities in the sector for both providers and tourists.