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.

This study aims to assess the efficacy of speech-to-text (STT) technology in improving the writing abilities of special education pupils in Saudi Arabia. A deliberate sample of 150 special education college students was selected, with participants randomly allocated to either an experimental group employing STT technology or a control group using traditional writing methods. The study utilized a comprehensive approach, which included standardized writing assessments, questionnaires, and statistical analyses such as t-tests, correlation, regression, ANOVA, and ANCOVA. The results demonstrate a substantial enhancement in writing skills among the experimental group utilizing Speech-to-Text (STT) technology. The findings contribute to the discussion on assistive technology in special education and offer practical recommendations for educators and policymakers.

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.

The worldwide COVID-19 pandemic has prompted significant transformations in several facets of human existence as it has disseminated over the globe, hence instigating extensive investigations into urban environments and public health. Recent research has investigated the correlation between cities, urban planning, and COVID-19. This signifies a shift in the urban planning paradigm. Resume focusing on and giving priority to health, particularly in relation to infectious diseases. This article seeks to elucidate the paradigm shift in cities and health as a result of due to the COVID-19 pandemic by employing a Systematic Literature Review. The research findings demonstrate a significant change in how health and cities are perceived due to the COVID-19 pandemic. This research also contributes novel insights into the significance of urban design that prioritises public health, particularly in relation to infectious diseases.

Decentralized cryptocurrencies, such as bitcoin, use peer-to-peer software protocol, disintermediating the traditional intermediaries that used to be banks and other financial intermediaries, effectuating cross-border transfer. In fact, by removing the requirement for a middleman, the technology has the potential to disrupt current financial transactions that rely on a trusted authority or intermediary operator. Traditional financial regulation, primarily based on the command-and-control approach, is ill-suited to regulating decentralized cryptocurrencies. The present paper aims to investigate the policy option most suitable for regulating decentralized cryptocurrencies. The study employs content analysis method to effectuate the purpose of the study. The paper argues that the combination of both direct and indirect regulatory approaches would be a feasible option for regulating decentralized cryptocurrencies. The absence of centralized authority and the borderless nature of decentralized cryptocurrencies would make them antithetical to centralized direct regulation. Therefore, the findings of the study suggest that regulators should focus on regulating intermediaries bridging the connection between the online world (crypto ecosystem) and the physical world (the point of converting crypto into fiat money). These intermediaries can work as passive actors or surrogate regulators who are indirectly responsible for implementing policy options on behalf of the central authority.

Purpose—In the business sector, reliable and timely data are crucial for business management to formulate a company’s strategy and enhance supply chain efficiency. The main goal of this study is to examine how strong brand strength affects shareholder value with a new Supplier Relationship Management System (SRMS) and to find the specific system qualities that are linked to SRMS adoption. This leads to higher brand strength and stronger shareholder value. Design/Methodology/Approach—This study employed a cross-sectional design with an explanatory survey as a deductive technique to form hypotheses. The primary method of data collection used a drop-off questionnaire that was self-administered to the UAE-based healthcare suppliers. Of the 787 questionnaires sent to the healthcare suppliers, 602 were usable, yielding a response rate of 76.5%. To analyze the data gathered, the study used Partial Least Squares Structural Equation modelling (PLS-SEM) and artificial neural network (ANN) techniques. Findings—The study’s data proved that SRMS adoption and brand strength positively affected and improved healthcare suppliers’ shareholder value. Additionally, it demonstrates that user satisfaction is the most significant predictor of SRMS adoption, while the results show that the mediating role of brand strength is the most significant predictor of shareholder value. The results demonstrated that internally derived constructs were better explained by the ANN technique than by the PLS-SEM approach. Originality/Value—This study demonstrates its practical value by offering decision-makers in the healthcare supplier industry a reference on what to avoid and what elements to take into account when creating plans and implementing strategies and policies.

An unprecedented demand for accurate information and action moved the industry toward RegTech where computing, big data, and social and mobile technologies could help achieve the demand. With the introduction and adoption of RegTech, regulatory changes were introduced in some countries. Enhanced regulatory changes to ease the barriers to market entry, data protection, and payment systems were also introduced to ensure a smooth transition into RegTech. However, regulatory changes fell short of comprehensiveness to address all the issues related to RegTech’s operation. This article is an attempt to devise a Privacy Model for RegTech so industries and regulators can protect the interests of various stakeholders. This model comprises four variables, and each variable consists of many items. The four variables are data protection, accountability, transparency, and organizational design. It is expected that the adoption of this Privacy Model will help industries and regulators embrace standards while being innovative in the development and use of RegTech.

The paper at hand analyses the principal-agent relationship, where comparative perspective between principals’ (municipalities) and agents’ (public utility providers) in the field of water and wastewater management is scrutinized. The goal of the paper is twofold: firstly, to present empirical results validating principal-agent relationships that emerged due to the reorganization process of public enterprises; secondly, to highlight the similarities and differences between the perspectives of principals and agents regarding motives, advantages and disadvantages, and price-setting in relation to the reorganization process. The empirical research is based on the primary data collected through two self-prepared and structured online questionnaires—one for municipalities, and the other for public utility providers. The results reveal similarities between public enterprises and municipalities in motivating factors for full municipal ownership. However, differences are seen among the advantages of the reorganization process. Price-setting by public utilities is recognized as a motivating mechanism for agents.