This study aims to analyse the impact of Brexit on London’s housing market, exploring socio-economic and regional disparities. By examining property transaction data from 2012 to 2022, the research seeks to understand how Brexit has influenced real housing prices across different boroughs of London. The methodology involves aggregating transaction data from the Her Majesty (HM) Price Paid database and normalizing prices using the Consumer Price Index (CPI) to obtain real price variations. These data were segmented into three distinct periods: pre-Brexit (2012–2016), post-plebiscite Brexit (2016–2019), and post-implementation Brexit (2020–2022). Spatial analysis was conducted using the software Quantum Geographic Information System (QGIS), transforming point data (postcodes) into polygonal data (wards) for better visualization and comparison. The findings reveal significant socio-economic impacts, with traditionally affluent areas such as Westminster, Kensington, and Chelsea experiencing notable declines in real housing prices. Conversely, certain outer boroughs like Newham and Barnet showed resilience, with positive real price variations despite decreased sales. This geographical disparity underscores the uneven distribution of Brexit’s economic consequences, highlighting the critical role of localized economic policies and development projects in mitigating adverse effects. The results confirm existing literature on the polarization and regional inequalities exacerbated by Brexit while providing new insights into the complex interplay of local and global factors affecting housing markets. The findings emphasize the need for targeted policy interventions to address the diverse challenges posed by Brexit, ensuring both affluent and disadvantaged areas receive adequate support. This research is crucial for informing public policy, urban planning, and housing market strategies in a post-Brexit context, promoting equitable and sustainable development across London.
Entrepreneurial self-efficacy has a predictive effect on entrepreneurial performance. The lithium-ion battery industry is the cornerstone of the emergency of the four emerging industries of “new energy”, “new materials”, “new technology” and “high-end manufacturing”. In the past, scholars have not considered the characteristics of entrepreneurs in their research on improving Chinese lithium-ion battery new venture growth. The personal characteristics of entrepreneurs have not received widespread attention from scholars. This article will start with the characteristics of entrepreneurs themselves and explore the path that entrepreneurs’ characteristics affect Chinese lithium battery new venture growth. This article builds a structural equation model to empirically analyze the relationship among variables. The data analysis results show that entrepreneurial self-efficacy significantly promotes the growth of new startups and entrepreneurial resilience plays a mediating role between the two. It cannot be concluded that entrepreneurial passion plays a positive moderation role between entrepreneurial self-efficacy and entrepreneurial resilience. Entrepreneurial passion also does not play a positive moderation effect between entrepreneurial self-efficacy and new venture growth. However, entrepreneurial passion plays a positive moderating role in the influence of entrepreneurial resilience on new venture growth. The findings of the study are beneficial for practitioners of Chinese lithium battery enterprises and will allow their strategies to promote sustainable new venture growth.
In the intricate realm of contractual law, the condition precluding action serves as a critical safeguard, ensuring that specific legitimate interests are protected within contracts and wills. This research examines this condition’s validity when based on a legitimate motive and for a reasonable duration. The study highlights a case involving an owner who violates this condition by engaging in acts such as sale or gift, raising important questions regarding the legal penalties associated with such violations. The primary objective of this research is to provide a comprehensive understanding of the legal consequences of breaching preventive clauses and to analyze how Egyptian, French, and Palestinian laws protect the interests of the stakeholders involved. The methodology adopted in this study is comparative in nature, involving a thorough analysis of the legal texts from Egyptian, French, and Palestinian laws. This involves a review of legal scholars’ opinions and relevant judicial rulings to highlight the differences in penalties and applications associated with preventive clauses. The findings reveal that both Egyptian and French laws advocate for the invalidity of actions carried out in violation of these preventive conditions. However, there is a divergence among scholars regarding the nature of this invalidity, with some arguing for absolute invalidity while others suggest relative invalidity. Conversely, the Palestinian legal framework prescribes specific penalties, indicating a variance in legislative approaches. The research concludes that the current legislative treatment of preventive conditions is insufficient and requires reform to ensure effective legal protection for affected parties. This leads to policy implications emphasizing the need to strengthen legal frameworks and enhance the clarity of legislative intentions in formulating laws related to preventive clauses. By doing so, the study aims to facilitate the achievement of legitimate interests for parties involved and ensure the enforcement of preventive conditions in a manner that upholds contractual integrity.
The main goal of the article is to formalize the key business models of marketing of modern companies and substantiate the key stages, types and trends of development. The relevance and need to pay significant attention to the marketing digital business model when organizing a business is substantiated. Using structural and logical analysis and criticism of scientific research, the essence, advantages and disadvantages are determined, the main blocks, stages and key elements of the structure of business models of modern companies are argued. It has been proven that marketing digital business models serve as a logical and visual plan for organizing all business processes of companies from production, marketing, sales and logistics to building a hierarchy of profitability. The key development trends are substantiated and the most popular business models of business organization in modern conditions are structured on the basis of scientific generalization, structural and logical analysis and mathematical modeling. Practical significance is characterized by the fact that the marketing business models of world-class companies are generalized and structured, taking into account their specifics and characteristics. Practical recommendations and key stages of building a company’s business model and its implementation into reality have been formed to achieve strategic business goals.
Under the developing trend of artificial intelligence (AI) technology gradually penetrating all aspects of society, the traditional language education industry is also greatly affected [1]. AI technology has had a positive impact on college English teaching, but it also presents challenges and negative impacts. On the positive side, AI technology can provide personalized learning experiences, real-time feedback, and autonomous learning opportunities, and so on. However, it may also lead to a lack of communication between students and humans, resulting in a decline in students’ interpersonal skills, and cause students’ dependence on online learning resources as well as possible risks to student data privacy and security, and other negative impacts. To address these challenges, teachers can adopt the following countermeasures: improving teachers’ skills in the use of AI technology incorporated in the classroom, offering personalized instruction to reduce students’ dependence on AI technologies, emphasizing the cultivation of students’ humanistic literacy and interpersonal communication ability. Additionally, colleges and technology providers should strengthen data security and privacy protection to ensure the safety and confidentiality of student data. By implementing comprehensive measures, we can maximize the advantages of AI technology in college English teaching while overcoming potential issues and challenges.
This article discusses one of the problems of using digital technologies, namely the complexity of assessing the effectiveness of their implementation. Since the use of digital twins at the enterprises of the fuel and energy complex (FEC) has recently become relevant, the authors have chosen the digital twins technology for consideration in this article. For the successful implementation of digital technologies, the authors propose a system of evaluation indicators that will measure the effectiveness of Digital Twins implementation and determine the benefits obtained. The advantages of digital twins include improved management and monitoring, optimization of production processes, prediction of equipment failures, as well as reduced maintenance costs and increased overall efficiency of FEC systems. As a methodological basis for the study, authors use the system of balanced indicators proposed by R. Kaplan and D. Norton, which served as the basis for the development of a set of performance indicators of the fuel and energy complex enterprise with the introduction of digital twins. As a result of the study, a list of indicators for monitoring the effectiveness of digital twins implementation was determined. The study identifies performance indicators for digital twin implementation, with future research aimed at quantitative assessments. The enterprise can implement a digital twin system with a WACC of 10.99%, payback period of 8.06 years, IRR exceeding the discount rate by 9.07%, a 3.5% reduction in harmful emissions, and a 2.5% efficiency increase.
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