This paper focuses on studying the impact of institutional distance between home and host countries on the entry mode choice of multinational enterprises (MNEs). Based on theories of transaction costs and institutional theory, we predict the trend of choosing investment forms of wholly-owned enterprises (WOEs) and joint venture enterprises (JVEs) in the agricultural sector of Vietnam in the context of free trade agreement implementation. The data of 364 MNEs from 22 different nations that directly invested in the agricultural sector of Vietnam in the period 1996–2019 were extracted from Worldwide Governance Indicators (WGI), which is provided by World Bank. An empirical investigation has employed logistic regression. The results show a positive relationship between institutional distance with regard to rule of law and regulatory quality and WOE choice. Furthermore, the entry mode choices of MNEs in Vietnam’s agricultural sector are also noticeably influenced by the implementation of freedom trade agreements (FTAs).

Artificial Intelligence (AI) has become a pivotal force in transforming the retail industry, particularly in the online shopping environment. This study investigates the impact of various AI applications—such as personalized recommendations, chatbots, predictive analytics, and social media engagement—on consumer buying behaviors. Employing a quantitative research design, data was collected from 760 respondents through a structured online survey. The snowball sampling technique facilitated the recruitment of participants, focusing on diverse demographics and their interactions with AI technologies in online retail. The findings reveal that AI-driven personalization significantly enhances consumer purchase intentions and satisfaction. Multiple regression analysis shows that AI personalization (β = 0.35, p < 0.001) has the most substantial impact on purchase intention, followed by chatbot effectiveness (β = 0.25, p < 0.001), predictive analytics (β = 0.20, p < 0.001), and social media engagement (β = 0.15, p < 0.01). Similarly, AI personalization (β = 0.30, p < 0.001), predictive analytics (β = 0.25, p < 0.001), and chatbot effectiveness (β = 0.20, p < 0.001) significantly influence consumer satisfaction. The hierarchical regression analysis underscores the importance of ethical considerations, showing that ethical and transparent use of AI increases consumer trust and engagement. Model 1 explains 45% of the variance in consumer behavior (R² = 0.45, F = 154.75, p < 0.001), while Model 2, incorporating ethical concerns, explains an additional 10% (R² = 0.55, F = 98.25, p < 0.001). This study highlights the necessity for retailers to leverage AI technologies ethically and effectively to gain a competitive edge, improve customer satisfaction, and drive long-term success. Future research should explore the long-term impacts of AI on consumer behavior and the integration of emerging technologies such as augmented reality and the Internet of Things (IoT) in retail.

Cybercrime poses a growing threat to individuals, businesses, and governments in the digital age. This research aims to conduct a comprehensive study of the legal frameworks developed by international organizations to combat cybercrime, providing a comparative analysis of their approaches and highlighting strengths, weaknesses, and areas for improvement. The study employs a qualitative research methodology, utilizing a doctrinal approach to examine primary and secondary legal sources for data analysis. The results reveal the ongoing efforts of the United Nations and other international bodies to establish a unified approach to combating cybercrime through conventions on Cybercrime. The research emphasizes the importance of harmonizing laws, fostering international cooperation, and adapting to evolving cyber threats while maintaining a balance between security and individual rights. Recommendations include strengthening legal frameworks, enhancing public-private partnerships, and investing in capacity building and technical assistance for developing countries. The study concludes by highlighting the critical importance of comprehensive and harmonized cybercrime legislation in the global fight against cybercrime and calls for continued efforts to address the challenges posed by this ever-evolving threat.

In June 2023, the European Union (EU) enacted the Regulation on Deforestation-Free Products (EUDR), which requires agricultural products to enter and leave its territory free from deforestation. The regulations apply to seven commodities: cattle, cocoa, coffee, oil palm, rubber, soya, wood, and their derivate products grown or raised on land subject to deforestation or forest degradation will be banned from entering the EU market. EUDR will have a significant impact on Vietnam’s Exports of Agricultural Products. Coffee, rubber, wood, and wood products are the main industries in Vietnam affected by this regulation, as the country exports a substantial portion of these products to EU markets. This article examines the impacts of the European Union Deforestation Regulation on Vietnam’s coffee supply chains, discusses possible unintended effects on coffee farmers and farming households, and explores strategies to mitigate these negative impacts while highlighting specific challenges that may arise. The results of this study contribute to a better understanding and management of Vietnam’s agricultural exports, particularly in the coffee sector. Additionally, the article gives some recommendations for improving Vietnam’s laws and policies on deforestation-free products.

The complex interactions of industrial Policy, structural transformation, economic growth, and competitive strategy within regional industries are examined in this research. Using a dynamic capabilities framework, the study examines the mediating roles of organizational innovation and adaptability in the link between competitiveness and macroeconomic variables. A two-way fixed effects model is used in this study to examine the influence of structural transformation (ST) on Industrial Policy (IP). Using regional data covering the years 2010 to 2022, the research undertaken in this paper explores the dynamics of the Indonesian economy by empirically assessing the consequences of structural change on industrial Policy. In order to establish a comprehensive model that clarifies the mechanisms through which industrial policies and structural shifts impact the development of dynamic capabilities, ultimately influencing competitiveness strategies, this research draws on a large amount of empirical data and integrates insights from seminal works. Our research adds to our knowledge of strategic management in regional industries by providing detailed information on how economic development and policy interventions influence businesses’ ability to adapt and gain a competitive edge. In addition to advancing scholarly discourse, this study offers business executives and politicians valuable insights for managing the intricacies of global economic processes.

Academic integrity has been at the centre of the discussion of the adoption of Chat GPT by academics in their research. This study explored how academic integrity mitigates the desire to use ChatGPT in academic tasks by EFL Pre-service teachers, in consideration of the time factor, perceived peer influence, academic self-effectiveness, and self-esteem. The study utilized web-based questionnaires to elicit data from 300 EFL Pre-service teachers across educational fields drawn from different schools across the world. Analysis was conducted using relevant statistical measures to test the projected four hypotheses. The findings provide evidence in support of Hypothesis 1, with a statistically significant path coefficient (β) of 0.442, a t-value of 3.728, and a p-value of 0.000. The hypothesis acceptance implies that when academic integrity improves, the impact of the time-saving aspect of the use of ChatGPT Across educational fields study decreases. This suggests that EFL Pre-service teachers who have a firm dedication to academic honesty are less influenced by the tempting appeal of ChatGPT’s time-saving features, highlighting the ethical factors that influence their decision-making. The data also provide support for Hypothesis 2, indicating a substantial inverse relationship with a path coefficient (β) of 0.369, a t-value of 5.629, and a p-value of 0.001. These findings indicate that stronger adherence to academic integrity is linked to a diminished effect of colleagues on the choice to use ChatGPT in Academic tasks. The results suggest that a firm dedication to academic honesty serves as a protective barrier against exogenous pressures or influences from colleagues when it comes to embracing cutting-edge technology. However, in general, these findings revealed there was a negative association between academically related factors (e.g., time factor, sense of peer pressure, language study self-confidence, and academic language competence), as well as an attitude toward adoption of ChatGPT and commitment towards academic integrity.