In this study, the entropy weight method, the α convergence model, the absolute β convergence model and the conditional β convergence model are used to evaluate the 31 provinces’ innovative potential in China from 2011 to 2022. It is found that the innovative potential in nationwide China and in various regions are all increasing year by year, and the innovative potential in the eastern region is obviously better than that in the central region and western region. No matter considering the influence of external factors or not, the gap of innovative potential among provinces in different regions will gradually expand over time, with the largest gap among provinces in the eastern region, followed by the central region and the smallest in the western region. The conclusion of this study is instructive to enhance the innovative potential of China and promote the balanced development of regional innovative potential in China.

Clustering technics, like k-means and its extended version, fuzzy c-means clustering (FCM) are useful tools for identifying typical behaviours based on various attitudes and responses to well-formulated questionnaires, such as among forensic populations. As more or less standard questionnaires for analyzing aggressive attitudes do exist in the literature, the application of these clustering methods seems to be rather straightforward. Especially, fuzzy clustering may lead to new recognitions, as human behaviour and communication are full of uncertainties, which often do not have a probabilistic nature. In this paper, the cluster analysis of a closed forensic (inmate) population will be presented. The goal of this study was by applying fuzzy c-means clustering to facilitate the wider possibilities of analysis of aggressive behaviour which is treated as a heterogeneous construct resulting in two main phenotypes, premeditated and impulsive aggression. Understanding motives of aggression helps reconstruct possible events, sequences of events and scenarios related to a certain crime, and ultimately, to prevent further crimes from happening.

In the process of forest recreation value development, there are some characteristics, such as large amount of investment capital, long financing recovery cycle and high potential risks, which lead to limited capital source and prominent financing risks. To achieve sustainable development, forest recreational value development enterprises must solve the financing dilemma, therefore, it is very urgent to identify the financing risk factors. The research constructed financing risk evaluation index system through WSR (Wuli-Shili-Renli) methodology (from affair law, matter principle and human art dimensions), taking S National Forest Park at Fujian Province as a case study, the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method were used for empirical analysis. The results showed that for the first level indicators, operational risk should be paid close attention to, followed by political risk and environmental risk. Among the secondary level indicators, policy changes, financing availability and market demand need attention, which are consistent with the result of field survey. Based on that, countermeasures were put forward such as the multiple collaborative linkage and effective internal control; reduction on operating costs and broaden financing channels; encouragement diversification of investment entities and improvement of financial and credit support; strengthening government credit supervision, optimizing financing risk evaluation, and building a smart tourism financing information platform, to reduce and control financing risks, then promote the development of forest recreation value projects.

The present study aims at analyzing the various factors influencing consumer attitudes towards the adoption of electric vehicles (EVs) in Saudi Arabia. The study evaluates consumer attitudes, their impact on shaping behaviours, and whether consumer intention mediates the relationship between consumer attitude and purchase behaviour towards EVs. This research employs a mixed-method approach, including literature review, surveys, and data analysis. It investigates EV adoption dimensions encompassing individual, social, economic, and environmental factors. Data collected from 397 current and potential EV owners in Saudi Arabia provide insights into their attitudes and behaviours. Survey findings indicate that in Saudi Arabia, safety rating, social influence, economic value, operating cost, and product variety significantly shape consumer attitudes and influence EV adoption. However, factors like range anxiety, charging infrastructure, environmental concern, and performance expectancy are less significant in affecting consumer attitudes toward EVs and their adoption. Investigating multiple dimensions and employing a mixed-method approach, the study enhances the existing knowledge of consumer attitudes toward EVs in the unique context of Saudi Arabia’s sustainable mobility transition. Policymakers and industry stakeholders can utilize these findings to expedite the shift to sustainable transportation in the Kingdom. This research also guides future investigations in this burgeoning field.

The study’s goal was to investigate the impact of e-learning determinants on student satisfaction and intention to use e-learning tools. The dependent and independent variables in this study were based on the technological acceptance model. The study examines three determinants, including usefulness, ease of use, and facilitating conditions, as independent variables, while student satisfaction and intention to use were used as dependent variables. Additionally, this study is unique by adding student satisfaction as a dependent variable and a mediator to examine the relationship between e-learning determinants and intention to use. A questionnaire was prepared and distributed to 324 undergraduate students from Jordan’s private universities on the basis of a convenience sample. The proposed hypotheses were investigated using the quantitative techniques of regression in SPSS and SEM in AMOS. The findings of this study revealed that student satisfaction and intention to use e-learning were positively impacted by e-learning determinants. It found that intention to use was positively impacted by student satisfaction. Furthermore, e-learning intention to use was found to be positively impacted by e-learning determinants via student satisfaction. Universities and other educational institutions are advised to identify the appropriate e-learning determinants that satisfy students’ demands and motivate them to use e-learning tools in light of the study’s findings. Private universities can accomplish their goals, stay ahead of the competition, and obtain a competitive advantage by properly understanding e-learning determinants, student satisfaction, and the application of successful e-learning solutions.