Rising fuel prices can affect driver behavior and thus the number of accidents, which is a key road safety issue. The aim of this paper was to assess and quantify the relationship between fuel prices (FP) and the number of road accidents in Europe. Content analysis of statistics from the countries was used to collect data, which were examined using Ramsey resets and Poisson distributions and then processed using negative binomial regression (NB), cluster analysis and visualization using contour plots. The results show that in Germany and Poland there is a statistically significant low negative correlation between fuel price and the number of traffic accidents, while in the Czech Republic and Denmark the relationship is weaker and statistically insignificant. In Iceland, no significant correlation was found. The contribution of this paper is to provide important insights that can be used in the development of transport policies and regulations to improve road safety. The main limitations include the difficulty of data collection, as many countries do not publish detailed statistics, and the low number of accidents in Iceland, which makes it impossible to perform a robust analysis for this country and may cause generalization of the results.
Purpose: This study empirically investigates the effect of big data analytics (BDA) on project success (PS). Additionally, in this study, the investigation includes an examination of how intellectual capital (IC) and (KS) act as mediators in the correlation between BDA and KS. Lastly, a connection between entrepreneurial leadership (EL) and BDA is also explored. Design/Methodology- Using a sample of 422 senior-level employees from the IT sector in Peru. The partial least squares structural equation modeling technique tested the hypothesized relationships. Findings- According to the findings, the relationship between BDA and PS is mediated by structural capital (SC) and relational capital (RC), and BDA demonstrates a positive and noteworthy correlation with PS. Furthermore, EL is positively associated with BDA in a significant manner. Practical implications- The finding of this study reinforce the corporate experience of BDA and suggest how senior levels of the IT sector can promote SC, RC, and EL. Originality/Value- This study is one of the first to consider big data analytics as an important antecedent of project success. With little or no research on the interrelationship of big data analytics, intellectual capital and knowledge sharing the study contributes by investigating the mediating role of intellectual capital and knowledge sharing on the relationship between big data analytics and project success.
Business intelligence is crucial for businesses, from start-ups to multinationals. Examining the role and efficacy of business intelligence (BI) technologies in gathering, processing, and evaluating data to assist responsible management practices and decision-making is crucial in the modern age, especially for educational institutions. This study investigates the impact of Business Intelligence (BI) tools on Knowledge Management (KM) stages and their subsequent influence on Responsible Business Practices Outcomes in the educational sector of the United Arab Emirates. Using a quantitative research design, the study collected data from 406 faculty and staff members across various UAE universities via a structured survey. It analyzed the data using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results revealed a significant positive relationship between the use of BI Tools and the implementation of KM Stages, indicating that the utilization of BI tools is instrumental in enhancing knowledge management processes. However, the direct effect of BI Tools’ usage on responsible business practices’ outcomes was insignificant, suggesting the need for a mediating factor. KM Stages Implementation emerged as a significant mediator, indicating that the benefits of BI tools on responsible business practices are realized through their influence on KM processes. Moderation analyses showed that Institutional Culture, Training, and Expertise significantly moderated the relationship between BI Tools Usage and KM stage implementation, while Support from Management did not have a significant moderating effect. These findings highlight the importance of fostering an enabling institutional culture and investing in training and expertise to leverage the full potential of BI tools in promoting responsible business practices in educational settings. The study contributes to the literature on technology adoption in education and provides practical implications for educational administrators and policymakers seeking to integrate BI tools into their institutional practices.
The purpose of this study is to investigate the correlation between sponsorship and the performance and development of early career athletes transitioning from junior level to professional sports, because this issue has not been fully explored in the Czech Republic. The reason is the almost absolute absence of financial or material support for such early-career athletes, when their transition from junior categories and the entire junior category is almost always exclusively financed and supported by their parents and families. We also emphasise the absolute absence of legislative provisions that would give supporters of such athletes at least a tax or other advantage. The research is based on research of Cardenas (2023), Hong and Fraser (2023) and Moolman and Shuttleworth (2023) and aims to assess how financial and material support provided by sponsors can enhance an athlete’s performance and long-term career trajectory. A mixed method approach was adopted, combining quantitative analysis through surveys and performance data with qualitative interviews. Data from 173 early career athletes from various disciplines were analysed using t-tests and ANOVA statistical methods to assess financial stability, access to better training, and community participation. Results indicate that sponsorship significantly contributes to better performance metrics, with sponsored athletes showing a 20% improvement in competition results compared to nonsponsored athletes. Furthermore, sponsorship financial support improved training opportunities and access to elite facilities, which was shown to increase athletes’ performance by 15%. However, some challenges related to sponsorship obligations, such as marketing commitments, were highlighted by athletes, underscoring the pressures that sponsorship can introduce. The implications of this study suggest that effective sponsorship strategies can play a vital role in an athlete’s career development, offering not only financial stability but also opportunities for personal branding and increased community engagement. Another implication is a possible consideration for legislators in the context of preparing a legislative framework enabling tax or other benefits for companies and organisations sponsoring or supporting these young athletes. More research is recommended to explore the long-term impact of sponsorship on athlete mental health and career sustainability, as well as the differences in sponsorship effects across various sports disciplines.
This paper aims to contribute with a literature review on the use of AI for cleaner production throughout industries in the consideration of AI’s advantage within the environment, economy, and society. The survey report based on the analysis of research papers from the recent literature from leading database sources such as Scopus, the Web of Science, IEEE Xplore, Science Direct, Springer Link, and Google Scholar identifies the strategic strengths of AI in optimizing the resources, minimizing the carbon footprint and eradicating wastage with the help of machined learning, neural networks and predictive analytics. AI integration presents vast aspects of environmental gains, including such enhancements as a marked reduction concerning the energy and materials consumed along with enhanced ways of handling the resulting waste. On the economic aspect, AI enhances the processes that lead to better efficiency and lower costs in the market on the other hand, on the social aspect, the application of any AI influences how people are utilized as workers/clients in the community. The following are some of the limitations towards AI adoption as proposed by the review of related literature; The best things that come with AI are yet accompanied by some disadvantages; there are implementation costs, data privacy, as well as system integration that may be a major disadvantage. The review envisages that with the continuation of the AI development in the following years, the optic is going to be the accentuation on the enhancement of the process of feeding the data in real-time mode, IoT connections, and the implementation of the proper ethical approaches toward the AI launching for all segments of the society. The conclusions provide precise suggestions to the people working in the industry to adopt the AI advancements appropriately and at the same time, encourage the lawmakers to create favorable legal environments to enable the ethical uses of AI. This review therefore calls for more targeted partnerships between the academia, industry, and government to harness the full potential of AI for sustainable industrial practices worldwide.
This research article explores the intricate relationship between cultural impacts and leadership styles in social science management. It emphasizes the importance of cultural-informed decision-making, highlighting its role in fostering inclusive managerial choices. The study also delves into how diverse leadership styles enhance team dynamics and collaboration, contributing to an innovative work environment. While recognizing the potential benefits, challenges like miscommunications are acknowledged, with recommendations for leadership development programs. The research underscores the significance of leadership flexibility in managing diverse teams. In conclusion, the article emphasizes the positive impact of cultural awareness on decision-making, collaboration, and innovation in social science management.
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