In the context of globalization and integration of world markets, import operations occupy an important place in the activities of enterprises, forming a significant part of their economic processes. Effective management of these operations requires accurate and timely accounting and high-quality auditing, which becomes especially relevant in modern conditions. The study of methodological features of accounting and auditing of import operations is a relevant and timely area that helps improve the quality of financial reporting and management decisions. The purpose of the study is to analyze the problems and prospects of methodological features of accounting and audit of import operations, as well as to develop recommendations for their improvement. The study examined the main methodological approaches, existing problems and challenges, and proposed solutions aimed at increasing the efficiency and reliability of accounting and auditing in a global economy. The improvement of methodological approaches to the accounting and auditing of import operations will improve the accuracy and reliability of financial reporting, reduce the risks of non-compliance with regulatory requirements, as well as improve management decision-making and the overall financial stability of companies. The development and implementation of effective accounting and auditing methods that comply with international standards and best practices will minimize financial risks and increase the competitiveness of enterprises in the global market. A study of the problems and prospects of methodological features of accounting and auditing of import operations has revealed a number of key issues that require attention and solutions. The main challenges are the complexity and diversity of regulatory requirements, currency fluctuations, the diversity of imported goods and services, difficulties in assessing and recognizing imported goods, and the lack of qualified specialists.
Purpose: This research examines the intricate interplay between Business Intelligence (BI), Big Data Analytics (BDA), and Artificial Intelligence (AI) within the realm of Supply Chain Management (SCM). While the integration of these technologies has promised improved operational efficiency and decision-making capabilities, concerns about complexities and potential overreliance on technology persist. The study aims to provide insights into achieving a balance between data-driven insights and qualitative factors in SCM for sustained competitiveness. Design/methodology/approach: The research executed interviews with ten Arab Gulf-based consulting firms. These companies’ ability to successfully complete BI projects is well recognised. Findings: Through examining the interplay of human judgement and data-driven strategies, addressing integration challenges, and understanding the risks of excessive data reliance, the research enhances comprehension of the modern SCM landscape. It underscores BI’s foundational role, the necessity of balanced human input, and the significance of customer-centric strategies for lasting competitive advantage and relationships. Practical implications: The research provided information for organizations seeking to effectively navigate the complexities of integrating data-driven technologies in SCM. The research is a foundation for future studies to delve deeper into quantitative measurement methodologies and effective data security strategies in the SCM context. Originality: The research highlights the value of integrating BI, BDA, and AI in SCM for improved efficiency, cost reduction, and customer satisfaction, emphasising the need for a balanced approach that combines data-driven insights, human judgement, and customer-centric strategies to maintain competitiveness.
During crisis events, the government implements many policies to control the development of the crisis and stimulate the economy damaged by the crisis. The government plays a very important role during the crisis. The stock market is a reflection of a country’s economic situation. This article takes the Chinese government policies during the COVID-19 crisis as the research object and analyzes the impact of government policies on the CSI300 index. The following conclusion is drawn: not all government restrictions will cause a decline in stock market prices, among which the Wuhan lockdown policy has promoted the rise of the CSI300 index. The two stimulus policies implemented by the Chinese government are both conducive to the rise of CSI300 index. During the COVID-19 crisis, investors holding high assets, high leverage, and low profitability companies will be significantly negatively affected after the government implements restrictive policies. After the government implements stimulus policies, investors holding high asset and high leverage companies will suffer losses. Investors who hold low asset, low leverage, and high profitability companies will have profits. And this article also finds that the size of company assets is an important driving factor for abnormal returns.
The development of the personal innovative competences in workers is of capital importance for the competitiveness of organizations, where the ability of the employees must respond in an innovative way to diverse situations that arise in specific contexts. Considering this, the question arises: How do innovative employees' competences affect the sustainable development of Micro, Small and Medium Enterprises (MSMEs)? Therefore, the objective of this work is to present a multi-criteria method based on the Analytic Network Process (ANP), to relate innovative personal competences and the sustainable development of MSMEs. An instrument was applied to groups of experts from 31 Ecuadorian fruit-exporting MSMEs, to develop a multi-criteria decisional network that allowed identifying the innovative personal abilities that have the greatest impact on the sustainable development of these organizations. The results demonstrate the relevance of the elements of innovative personal competencies, with a cumulative participation of 39.15%, Sustainable Export Development with 32.18% and Improvements with 28.66%. It also presents three types of analysis: i) Global to establish the weight of each variable; ii) Influences, to establish solid cause-effect relationships between the variables and iii) Integrated. The most relevant innovative personal competences for sustainable development and improvements for exporting SMEs are teamwork, critical thinking, and creativity within the international context.
This study provides a comparative analysis of Environmental, Social, and Governance (ESG) ratings methodologies and explores the potential of eXtensible Business Reporting Language (XBRL) to enhance transparency and comparability in ESG reporting. Evaluating ratings from different agencies, the research identifies significant methodological inconsistencies that lead to conflicting information for investors and stakeholders. Statistical tests and adjusted rating scales confirm substantial divergence in ESG scores, primarily due to differing data categories and indicators used by rating firms. Using a sample of 265 European companies, the study demonstrates that individual ESG agencies report markedly different ratings for the same firms, which can mislead stakeholders. It proposes that XBRL based reporting can mitigate these inconsistencies by providing a standardized framework for data collection and reporting. XBRL enables accurate and efficient data collection, reducing human error and enhancing the transparency of ESG reports. The findings advocate for integrating XBRL in ESG reporting to achieve higher levels of comparability and reliability. The study calls for greater regulatory oversight and the adoption of standardized taxonomies in ESG reporting to ensure consistent and comparable data across sectors and jurisdictions. Despite challenges like the lack of a standardized taxonomy and inconsistent adoption, the research contends that XBRL can significantly improve the reliability of ESG ratings. In conclusion, this study suggests that standardizing ESG data through XBRL could provide a viable solution to the unreliability of current ESG rating scales, supporting sustainable business practices and informed decision making by investors.
The fifth-generation technology standard (5G) is the cellular technology standard of this decade and its adoption leaves room for research and disclosure of new insights. 5G demands specific skillsets for the workforce to cope with its unprecedented use cases. The rapid progress of technology in various industries necessitates a constant effort from workers to acquire the latest skills demanded by the tech sector. The successful implementation of 5G hinges on the presence of competent individuals who can propel its progress. Most of the existing works related to 5G explore this technology from a multitude of applied and industrial viewpoints, but very few of them take a rigorous look at the 5G competencies associated with talent development. A competency model will help shape the required educational and training activities for preparing the 5G workforce, thereby improving workforce planning and performance in industrial settings. This study has opted to utilize the Fuzzy Delphi Method (FDM) to investigate and evaluate the perspectives of a group of experts, with the aim of proposing a 5G competency model. Based on the findings of this study, a model consisting of 46 elements under three categories is presented for utilization by any contingent of 5G. This competency model identifies, assesses, and introduces the necessary competencies, knowledge, and attributes for effective performance in a 5G-related job role in an industrial environment, guiding hiring, training, and development. Companies and academic institutions may utilize the suggested competency model in the real world to create job descriptions for 5G positions and to develop curriculum based on competencies. Such a model can be extended beyond the scope of 5G and lay the foundation of future wireless cellular network competency models, such as 6G competency models, by being refined and revised.
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