The role of technology in stimulating economic growth needs to be reexamined considering current heightened economic conditions of Asian developing Economies. This study conducts a comparative analysis of technology proxied by R&D expenditures alongside macroeconomic variables crucial for economic growth. Monthly time-series data from 1990 to 2019 were analyzed using a vector error correction model (VECM), revealing a significant impact of technology on the economic growth of India, Pakistan, and the Philippines. However, in the cases of Indonesia, Malaysia, Thailand, and Bangladesh, macroeconomic indicators were found more crucial to their economic growth. Results of Granger causality underlined the relationship of R&D expenditures and macroeconomic variables with GDP growth rates. Sensitivity analyses endorsed robustness of the results which highlighted the significance and originality of this study in economic growth aligned with sustainable development goals (SDGs) for developing countries.

This study explores the critical role of the retail sector in the global economy and the importance of working capital management within retail businesses. Recognizing retail’s influence beyond just income generation, the research examines its impact on economic stability, job creation, and national GDP, and how it links industries such as manufacturing and logistics. Employing a blended-methods approach, the study integrates quantitative analysis using AMOS software with qualitative insights from interviews with financial managers and retail experts. Key focus areas include cash flow management, market demand, and supplier relationship management in the context of working capital management. Findings highlight the necessity of effective working capital management in maintaining financial stability, optimizing shareholder wealth, and ensuring long-term business viability in the retail sector. Strategies for enhancing profitability, such as improving supplier relationships and adapting to market demands, are identified. This research contributes to understanding the economic impact of the retail sector and the intricacies of working capital management. It offers insights for policymakers, retail managers, and academics, emphasizing the need for supportive retail industry measures and effective financial management practices. The study fills a gap in literature and sets a foundation for future research in this critical area of economic studies and retail management.

The Intellectual Property (IP) chapter of the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) is recognized for its extensive coverage, encompassing a broad range of innovation areas such as patents, trademarks, geographical indications, and copyright. This chapter sets a new global benchmark for IP protection, posing significant challenges to the existing legal frameworks of member countries and necessitating rapid adaptation, particularly for developing members like Vietnam, Malaysia, and Mexico. These nations have undertaken comprehensive revisions to their IP laws to align with the international standards established by the CPTPP. Despite their unique national contexts, the legal amendments reflect distinct strategies and methodologies in meeting international standards. This paper conducts a qualitative analysis of Vietnam, Malaysia, and Mexico, comparing their law amendment strategies, contents, and techniques across three dimensions. It highlights the distinctive characteristics and impacts of their legal revisions, offering valuable insights for other prospective developing members within the CPTPP framework on the practice of IP law reform.

The financial services industry is experiencing a swift adoption of artificial intelligence (AI) and machine learning for a variety of applications. These technologies can be employed by both public and private sector entities to ensure adherence to regulatory requirements, monitor activities, evaluate data accuracy, and identify instances of fraudulent behavior. The utilization of artificial intelligence (AI) and machine learning (ML) has the potential to provide novel and unforeseen manifestations of interconnectivity within financial markets and institutions. This can be represented by the adoption of previously disparate data sources by diverse institutions. The researchers employed convenience sampling as the sampling method. The form was filled out over the period spanning from July 2023 to February 2024, and it was designed to be both anonymous and accessible through online and offline platforms. To assess the reliability and validity of the measurement scales and evaluate the structural model, we employed Partial Least Squares (PLS) for model validation. Specifically, we have used the software package Smart-PLS 3 with a bootstrapping of 5000 samples to estimate the significance of the parameters. The results indicate a positive and direct connection between artificial intelligence (AI) and either financial services or financial institutions. On the contrary, machine learning (ML) exhibits a strong and positive association among financial services and financial institutions. Similarly, there exists a positive and direct connection between AI and investors, as well as between ML and investors.

This article aims to examine the impact of fiscal decentralization on the performance of local government expenditure in Vietnam. By using a dataset including 63 provinces from 2012 to 2021, the research shows the more expenditure-based fiscal decentralization occurs, the better is the performance of local expenditure. Moreover, the level of provincial literacy and the size of the private sector have positive impacts on the local expenditure index, while the opposite effect can be seen in the case of the ratios of local citizens to total citizens of the country. Besides this, the study also provides some recommendations which are strictly related to the mechanism of fiscal decentralization to improve local expenditure performance of Vietnamese provinces, such as more effective decentralization of budget expenditures to local government, improving the vertical budget imbalance at local budget level, increasing local government budget autonomy, and establishing stronger mechanisms to control public spending.