This article advocates for a fundamental shift in England’s legal approach to professional negligence, particularly within the domains of accounting and audit. English law should move away from its intricate and unclear case law surrounding professional negligence towards a clearly defined test for professional misconduct. Drawing upon a comparative analysis with the legal framework in the United States, where auditors are not shielded from liability under the law, the article highlights the need for a more consistent and accountable legal landscape in England. One of the main aspects that necessitates change is the proximity test, as set out in the Caparo case, which currently prevents auditors from being held liable for negligence to investors (as third parties)—despite investors relying on auditors for their professional skill to audit accounts. As investors rely on audited accounts when making financial decisions, a well-defined test for professional negligence should align English law with international standards and empower victims to seek compensation from the auditors themselves and/or the auditors’ professional indemnity insurance. Such a change would enhance trust and transparency in the financial domain.

With the advancement of the green economy, the labor market is experiencing the emergence of new employment forms, positions, and competencies. This arises from the special relationship between the green job market and the transforming energy sector. On the other hand, the energy sector’s influence on the green labor market and the creation of green jobs is particularly significant. It is because, the energy sector is one of the fundamental foundations of any country’s economy and impacts its other sectors. Key components of this influence include green employment and green self-employment. The purpose of this study is to identify elements of the green labor market within the context of the green economy and the energy sector. The methodology employs a hybrid literature review, combining a systematic literature review facilitated by the use of VOSviewer software. Exploring the Scopus database enabled the identification of keywords directly related to the green economy and the energy sector. Within these identified keywords, elements of the green labor market were searched. The main result is the empirical identification of the crucial term ‘green skills,’ which links elements of the green labor market, as presented in bibliometric maps. The research results indicate a gap in the form of insufficient discussion on green self-employment within the energy sector. Aspects of green jobs and elements of the green labor market are prominently featured in current research. However, there is a notable gap in the literature regarding green self-employment, presenting promising avenues for further research.

Low levels of financial literacy cause people to have lower savings rates, higher transaction costs, larger debts and the loans acquisition with higher interest rates, therefore it becomes relevant to analyze the determinants of financial literacy. The aim of this research is to identify whether there is an association between the financial literacy level and sociodemographic characteristics. The Mexican Petroleum Company (Pemex) employees is the population analyzed. Pemex is the state-owned oil and natural gas producer, transporter, refiner and marketer in Mexico. A non-probabilistic convenience sampling was performed and 404 responses were obtained. The analysis of data was carried out with the Bayesian method. The results show that there is an association between Pemex employees’ level of financial literacy and their level of education, income, age and type of retirement saving. No association was found between their level of financial literacy and gender, marital status and whether or not they have children.

This study aims to identify the impact of inheritance literacy, inheritance socialization, inheritance stress, and peer influence on the inheritance behaviors among FELDA communities in Malaysia. Inheritance literacy pertains to individuals’ comprehension of wealth transfer and estate planning, while peer influencer evaluates friends’ impact on inheritance attitudes; inheritance socialization explores family interactions’ role in shaping inheritance attitudes, and inheritance stress measures emotional strain in inheritance matters, with inheritance behaviors encompassing asset management and wealth transfer decisions for future generations by individuals and families. Understanding inheritance behaviors is crucial, as it helps individuals depict their inheritance knowledge and attitudes toward FELDA inheritance better, fostering a more favorable inheritance attitude. Through self-administered survey questionnaires, data related to FELDA communities are obtained using convenience sampling from 413 respondents. This study applies Partial Least Squares Structural Equation Modeling (PLS-SEM) technique to test the research hypotheses. The present study’s outcome confirms that two determinants, which are inheritance literacy and inheritance socialization significantly influence the inheritance behavior of FELDA communities. However, inheritance stress and peer influence determinants have statistically insignificant influence inheritance behavior. This study’s theoretical framework enriches the discussions on wealth management and financial behavior by refining and expanding upon existing financial behavior theories to incorporate inheritance-specific behaviors. The present study is exclusive in its effort to ascertain the relative importance of both inheritance behavior and the FELDA communities. This paper will assist the government, inheritance service providers, and policymakers in offering innovative economic schemes and designing policies that may enhance the inheritance behavior wellbeing of FELDA communities. This article also provides a roadmap to guide future research in this area.

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.

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.

The recent crisis-filled period has placed a significant burden on various businesses, including in the tourism sector. As a result, the concept of resilience, the flexible ability to resist, has become more and more tangible. This study aims to update the quantitative organizational resilience assessment scale of Orchiston, Prayag and Brown. The paper analyses a sample of 87 tourism service providers managing attractions, and factor analysis was carried out to identify the factors in order to be able to measure the resilience of tourism service providers. Four factors could be identified: Leadership and Organization, Strategy, Independence, and Internal Identity. These identified factors and the included 14 items mean the key contribution, as a new, updated assessment system.

This study focuses on the environmental cost accounting and economic benefit optimization of China’s FAW Hongqi New Energy Vehicle manufacturing enterprise under uncertain conditions, within the context of the emission permit system This study calculates the pollution situation throughout the manufacturing and production process of FAW Hongqi new energy vehicles, and constructs a multi-level environmental cost evaluation system for FAW Hongqi new energy vehicle manufacturing projects. Through the interval fuzzy model of FAW Hongqi new energy vehicle manufacturing projects, the maximum economic benefits of the enterprise are simulated. The research results indicate that the pollution emissions of enterprises are mainly concentrated in the three processes of welding, painting, and final assembly. Enterprises use their own exhaust gas and wastewater treatment devices to meet the standards for pollution emissions. At the same time, solid waste generated during the automobile manufacturing process is handed over to third-party companies for treatment. Secondly, based on the accounting results of enterprise pollution source intensity and a multi-layer environmental cost evaluation system, the environmental costs of enterprises are accounted for, and the environmental costs are represented in interval form to reduce uncertainty in the accounting process. According to the accounting results of enterprise environmental costs, the main environmental costs of enterprises are environmental remediation costs caused by normal pollution discharge and purchase costs of environmental protection facilities. Pollutant emission taxes and routine environmental monitoring costs are relatively low. Enterprises can adopt more scientific solutions from the aspects of environmental remediation and environmental protection facilities to reduce environmental costs. After optimization by the fuzzy interval uncertainty optimization model, the economic benefits of the FAW Hongqi new energy vehicle manufacturing project were [101,254.71, 6278.5413] million yuan. Compared with the interval uncertainty optimization model, the lower bound of economic benefits increased by 57.68%, and the upper bound decreased by 12.08%, shortening the results of the economic benefits interval. Clarify the current environmental pollution situation of FAW Hongqi’s new energy vehicle manufacturing enterprise, provide data support for sustainable development of the enterprise, and provide reasonable decision-making space for enterprise decision-makers.