This study explores the relationship between GDP growth, unemployment rate, and labor force participation rate in the Gulf Cooperation Council (GCC) countries from 1990 to 2018. Furthermore, the study incorporates control factors such as government spending, trade openness, and energy use into the regression equation. We used panel dynamic ordinary least squares (DOLS) and Fully Modified Ordinary Least Squares (FMOLS) estimators to investigate the relationships between variables in this investigation. The econometric technique accounts for nonstationary, endogeneity bias and cross-sectional dependencies between country-year observations. Cointegration was found among GDP growth, unemployment rate, and labor force participation. Long-term, the unemployment rate has a statistically significant negative effect on economic growth in the GCC nations. Meanwhile, the labor force participation rate significantly influences economic expansion in the long term. The expansion of government expenditures and international trade reduces economic growth. Alternatively, it is discovered that energy consumption has a substantial and positive effect on economic expansion. Okun’s rule and the unidirectional causality from economic growth to unemployment indicate that the primary cause of unemployment in GCC nations is a failure to adequately expand their economies. When developing economic strategies to reduce unemployment, policymakers are particularly interested in determining whether or not economic development and the unemployment rate are cointegrated.
This study examines the challenges and needs faced by non-profit organisations (NPOs) in Colombia regarding the adopting of the International Financial Reporting Standards (IFRS) for small and medium enterprises (SMEs), particularly focusing on sections 3 and 4. Employing a mixed-method approach, the research combines qualitative and quantitative methods. Surveys were conducted with Colombia NPOs, official documents were analysed, and comparative case studies were performed. In-depth interviews and participant observation were also utilised to gain a comprehensive understanding of the obstacles and current practices within the Colombian context. The findings reveal that NPOs in Colombia encounter significant difficulties in adopting IFRS due to the complexity of the standards, lack of specialised resources, and the need for specific training. Internal challenges such as deficiencies in staff qualifications and training, resistance to change, and technological limitations were identified. Externally, ambiguities in the legal framework and donor requirements were highlighted. The case study illustrated that, while there are similarities between IFRS for SMEs and the IFR4NPO project, specific adaptations are essential to address the unique needs of NPOs. This research underscores the necessity of developing additional guidelines or modifying existing ones to enhance the interpretation and application of IFRS in Colombia NPOs. It is recommended to implement proactive strategies based on education and legislative reform to improve the transparency and comparability of financial information. Adopting a more tailored and supported accounting framework will facilitate a more relevant and sustainable implementation, benefiting Colombian NPOs in their resource management and accountability efforts.
This study conducts a systematic literature review to analyze the integration of artificial intelligence (AI) within business excellence frameworks. An analysis of the findings in the reviewed articles yielded five major themes: AI technologies and intelligent systems; impact of AI on business operations, strategies, and models; AI-driven decision-making in infrastructure and policy contexts; new forms of innovation and competitiveness; and the impact of AI on organizational performance and value creation in infrastructure projects. The findings provide a comprehensive understanding of how AI can be integrated into organizational excellence emerged frameworks to address challenges in infrastructure governance, and sustainable development. Key questions addressed include: how AI affects consumer behavior and marketing strategies. What AI’s capabilities for businesses, especially marketing and digital strategies? How can organizations address the drivers and barriers to help make better use of AI in these business operations? Should organizations even do anything with these insights? These questions and more will be tackled throughout this discussion. This paper attempts to derive a comprehensive conceptual framework from several fields of human resources, operational excellence, and digital transformation, that can help guide organizations and policymakers in embedding AI into infrastructure and development initiatives. This framework will help practitioners navigate the complexities of AI integration, ensuring profitability and sustainable growth in a highly competitive landscape. By bridging the gap between AI technologies and development-related policy initiatives, this research contributes to the advancement of infrastructure governance, public management, and sustainable development.
The significant climate change the planet has faced in recent decades has prompted global leaders, policymakers, business leaders, environmentalists, academics, and scientists from around the world to unite their efforts since 1987 around sustainable development. This development not only promotes economic sustainability but also environmental, social, and corporate sustainability, where clean production, responsible consumption, and sustainable infrastructures prevail. In this context, the present article aims to propose a development framework for sustainability in food sector SMEs, which includes Life Cycle Assessment (LCA) and the integration of Environmental, Social, and Governance (ESG) strategies as key elements to reduce CO2 emissions and improve operational efficiency. The methodology includes a comparative analysis of strategies implemented between 2019 and 2023, supported by quantitative data showing a 20% reduction in operating costs, a 10% increase in market share, and a 25% increase in productivity for companies that adopted clean technologies. This study offers a significant contribution to the field of corporate sustainability, providing a model that is adaptable and applicable across different regions, enhancing innovation and business resilience in a global context that requires collective efforts to achieve the sustainable development goals.
The purpose of this study is to investigate the relationship between the use of business intelligence applications in accounting, particularly in invoice handling, and the resultant disruption and technical challenges. Traditionally a manual process, accounting has fundamentally changed with the incorporation of BI technology that automates processes and allows for sophisticated data analysis. This study addresses the lack of understanding about the strategic implications and nuances of implementation. Data was collected from 467 accounting stakeholder surveys and analyzed quantitatively using correlational analysis. Multiple regression was utilized to investigate the effect of BI adoption, technical sophistication on operational and organizational performance enhancements. The results show a weak association between the use of BI tools and operational enhancements, indicating that the time for processing invoices has decreased. Challenges due to information privacy and bias were significant and negative on both operational and organizational performance. This study suggests that a successful implementation of a BI technology requires an integrated plan that focuses on strategic management, organizational learning, and sound policies This paper informs practitioners of how accounting is being transformed in the digital age, motivating accountants and policy makers to better understand accounting as it evolves with technology and for businesses to invest in concomitant advances.
The integration of digitalization and servitization has become a significant trend in transforming the manufacturing industry due to digital intelligence technology. This paper examines the impact of the integration of digitalization and servitization on the performance of manufacturing companies and how small-scale enterprises can promote digital transformation leading to servitization. The study involved surveying 331 manufacturing companies in China using a seven-point Likert scale questionnaire. Measurement scales were validated using confirmatory factor analysis and discriminant validity tests. Mediation analysis assessed digitalization’s impact on servitization and firm performance. The study’s findings emphasize the significant impact of digitalization and servitization on enterprises’ performance. Digitalization plays a crucial role in mediating this relationship. The study highlights three critical dimensions of digital variables, including digital technology, digital labor, and digital relationship resources, essential in enabling effective servitization. Manufacturing enterprises generally prefer aligning their technology investments and organizational changes within the digitalization framework to implement servitization successfully. The study suggests two integration strategies, namely conservative and aggressive. The finding emphasizes that the convergence of digitalization and servitization leads to a new manufacturing production mode called digital servitization.
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