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This study examines the impact of entrepreneurship education on the social entrepreneurship intentions of undergraduate students with a focus on the mediating effects of individual capital, such as human, social and cultural capital.

This study adopted a quantitative approach with data collected from 392 third- and fourth-year students studying at a private university in Vietnam through a self-administered survey. The data were analysed using partial least squares structural equation modelling.

The results show that entrepreneurship education positively impacts the social entrepreneurship intentions of undergraduate students. Furthermore, this study reveals that social and cultural capital serve as mediators in this relationship, whereas the mediating role of human capital was not supported.

The study findings highlight the crucial role of higher education institutions in promoting and implementing formal entrepreneurship education. It also emphasises the importance of supporting enhancement of students' individual capital through social and cultural activities to foster their intentions to engage in social entrepreneurship.

This study adds to the current literature on social entrepreneurship intentions by highlighting the significance of entrepreneurship education provided by universities and the roles of individual capital, such as social and cultural capital, in mediating the impact of entrepreneurship education on social entrepreneurship intentions.

While the adoption of accounting information systems (AIS) is crucial in developing countries owing to the rapidly changing business environment, the emerging factors in its successful implementation continue to be inconsistent. This systematic literature review (SLR) aims to understand the emerging factors of underlying successful AIS implementation, with a specific focus on developing countries.

A total of 70 empirical studies from 2017 to 2024 were analysed using an SLR technique. Studies including the search term “accounting information systems” OR “AIS” AND “developing countries” in their titles, keywords or abstracts were retrieved from five digital databases. The articles were analysed and synthesised using thematic analysis.

The findings revealed six key themes: (1) AIS literacy, (2) automation in AIS, (3) cloud-based AIS, (4) cultural factors, (5) environmental factors and (6) mobile accessibility and 25 subthemes.

A comprehensive understanding of these gaps will enable academics, policymakers and AIS professionals to make well-informed decisions and enhance the efficacy and efficiency of AIS operations.

The thematic analysis highlights the theoretical gaps and exposes areas where the connection between factors may be inadequate to indicate future study avenues.

This study aims to investigate the interconnectedness of sustainability-linked and AI-based cryptocurrencies returns and volatility over five years (2018–2024). It aims to uncover the dynamic relationships between these two sectors under various market conditions, providing insights into their behavior and influence within the broader cryptocurrency market.

The research employs a Time-Varying Parameter Vector Autoregression (TVP-VAR) model to analyze key cryptocurrencies associated with AI and sustainability. This approach is complemented by a quantile-based perspective, allowing for an in-depth examination of return and volatility spillovers across different market conditions. Thus, facilitating an understanding of the intricate dynamics between sustainability-linked and AI-based cryptocurrencies.

The findings reveal distinct market dynamics with the Sustainable sector consistently acting as a net transmitter, while the AI sector predominantly as a net receiver, indicating its reactive nature. In bearish markets, both sectors display high interconnectedness, with the Sustainable sector shaping dynamics. In bullish markets, the Sustainable sector maintains influence, while the AI sector adopts a more proactive role, influencing the market more than in bearish conditions. Post-Chat GPT 3 the Sustainable sector decreases influence, becoming a net receiver in bullish markets. In contrast, the AI sector strengthens as a net transmitter, signaling growing investor confidence and prominence.

This study explores the interconnectedness of sustainability-linked and AI-based cryptocurrencies through a TVP-VAR model and a quantile-based analysis. It provides insights into how these sectors interact and influence each other across different market conditions, especially highlighting the significant shifts in dynamics following the advent of advanced technologies like Chat GPT 3. This contributes to a deeper understanding of the evolving landscape of the cryptocurrency market in the context of sustainability and AI.

As emerging e-course providers after the COVID-19 crisis, universities (UNI) policymakers in the Mekong Delta region (MDR) have faced difficulties owing to limited clues about what factors improve student retention and recruitment. This study aims to determine important factors (IF) for student satisfaction with e-course adoption (e-satisfaction) for student retention and recruitment.

Survey data collected from 850 students of the target UNI were analyzed using the DT-fuzzy DEMATEL method. Input factor dimensions included course design, technical infrastructure, interaction, teacher-related and student-related factors. Decision Trees (DT) confirmed the final factors; fuzzy decision-making trial and evaluation laboratory (DEMATEL) was used to establish the cause-effect relationships among these factors.

DT-fuzzy DEMATEL method can identify satisfied and dissatisfied students (accuracy = 94.95%) and determine IFs successfully. The most IFs included new and useful knowledge/information provided, various effective teaching methods and motivation to read provided learning materials.

Although e-satisfaction has been the focus of theories and practices, e-satisfaction in an emerging region like MDR has been studied here for the first time. Most IFs can be used as predictors for e-satisfaction and serve as a primary reference for UNIs’ policymakers. Several practical suggestions were also provided for the sustainable and long-term development of e-programs.

The emergence of consumerism has led to regulatory measures being integrated into business practices, but the influence of consumers in developing countries remains limited, resulting in businesses being less responsive. The digital retail landscape is undergoing a transformative revolution, driven by Industrial Revolution (IR) 4.0 technological advancements such as artificial intelligence (AI), wearables, virtual reality (VR), augmented reality (AR), and blockchain technology. This development focuses on convenience, personalisation, and emotional connections. Companies are adapting to modern consumer behaviour through various strategies, including online shopping, mobile commerce, data analytics, technology integration, user reviews, and contactless payments. The COVID-19 pandemic has accelerated this seismic shift in the retail industry, and online retail is expected to continue to grow post-pandemic, driven by these technologies. AI enhances the customer experience, wearables provide interactive engagement, VR offers immersive shopping, AR merges online and physical shopping, and blockchain ensures secure transactions in the emerging metaverse. As retail converges with the metaverse, the potential for borderless and personalised shopping experiences is enormous. Advances in VR technology could lead to interconnected virtual spaces that seamlessly connect physical and digital retail, providing immersive and personalised shopping experiences. However, challenges such as cost, learning curves, digital security, legal ambiguity, data privacy, financial risk, and ethical considerations need to be addressed through vigilant and informed consumer engagement in this evolving digital landscape.

This study aims to integrate the Social Cognitive Career Theory with the Theory of Planned Behavior to unravel the intricate dynamics of how engaging with ChatGPT affects individuals’ digital entrepreneurial intention, underlying the serial mediation mechanism of the cognitive and reasoned career process.

This research use a cross-sectional design, drawing on a sample of 604 higher education students from six universities in Vietnam. Multiple regression analyses were conducted to test the formulated hypotheses after assessing the reliability and validity of scales through Cronbach’s alpha and confirmatory factor analysis.

The results indicate that ChatGPT adoption significantly increases perceived AI competencies, entrepreneurial opportunity recognition and digital entrepreneurial self-efficacy. Digital entrepreneurial self-efficacy was found to have a positive impact on attitudes toward digital entrepreneurship, which, in turn, fosters digital entrepreneurial intention. ChatGPT adoption thus poses serial indirect impacts on digital entrepreneurial intention through the sequential pathways of enhanced digital entrepreneurial self-efficacy and positive attitudes.

This study’s findings provide valuable recommendations for entrepreneurs, higher education institutions and policymakers.

This research contributes to the entrepreneurship literature by integrating two prominent theoretical frameworks to elucidate how ChatGPT adoption impacts digital entrepreneurial intentions. The serial mediation model expands that understanding of the complex cognitive and reasoned processes involved, providing a novel perspective on the role of AI in entrepreneurship.

This study aims to develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were examined. In addition, automated smoothing and replenishment rules can alleviate supply chain bullwhip effects. This study aims to understand the current artificial intelligence (AI) implementation practice in alleviating bullwhip effects in supply chain management. This study aimed to develop a system for writing reviews using a systematic approach.

The methodology for the present study consists of three parts: Part 1 deals with the systematic review process. In Part 2, the study applies social network analysis (SNA) to the fourth phase of the systematic review process. In Part 3, the author discusses developing research clusters to analyse the research state more granularly. Systematic literature reviews synthesize scientific evidence through repeatable, transparent and rigorous procedures. By using this approach, you can better interpret and understand the data. The author used two databases (EBSCO and World of Science) for unbiased analysis. In addition, systematic reviews follow preferred reporting items for systematic reviews and meta-analyses.

The study uses UCINET6 software to analyse the data. The study found that specific topics received high centrality (more attention) from scholars when it came to the study topic. Contrary to this, others experienced low centrality scores when using NETDRAW visualization graphs and dynamic capability clusters. Comprehensive analyses are used for the study’s comparison of clusters.

This study used a journal publication as the only source of information. Peer-reviewed journal papers were eliminated for their lack of rigorousness in evaluating the state of practice. This paper discusses the bullwhip effect of digital technology on supply chain management. Considering the increasing use of “AI” in their publications, other publications dealing with sensor integration could also have been excluded. To discuss the top five and bottom five topics, the author used magazines and tables.

The study explores the practical implications of smoothing the bullwhip effect through AI systems, collaboration, leadership and digital skills. Artificial intelligence is rapidly becoming a preferred tool in the supply chain, so management must understand the opportunities and challenges associated with its implementation. Furthermore, managers should consider how AI can influence supply chain collaboration concerning trust and forecasting to smooth the bullwhip effect.

Digital leadership and addressing the digital skills gap are also essential for the success of AI systems. According to the framework, it is necessary to balance AI performance and accountability. As a result of the framework and structured management approach, the author can examine the implications of AI along the supply chain.

The study uses a systematic literature review based on SNA to analyse how AI can alleviate the bullwhip effects of supply chain disruption and identify the focused and the most important AI topics related to the bullwhip phenomena. SNA uses qualitative and quantitative methodologies to identify research trends, strengths, gaps and future directions for research. Salient topics for reviewing papers were identified. Centrality metrics were used to analyse the contemporary topic’s importance, including degree, betweenness and eigenvector centrality. ABEF is presented in the study.

This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.

Artificial intelligence (AI) is a significant trend in digital technology that is revolutionizing the field of global business and internationalization. Based on institutional theory and resource-based view, this study examines the intricate relationship between AI capabilities and export performance, taking into account the different province market development within a country and cultural distance.

This study gathered data from the websites of privately owned Chinese exporters and complemented it with a survey in 2023. In conducting the survey, we employed a simple random-sampling approach to select 1,500 exporters in China, with a focus on economic development indicators, particularly GDP contribution. We received 1,000 surveys, but only 749 were valid due to missing data. The study’s comprehensive coverage of regions ensured the inclusion of potential variations and subnational disparities within the country. This study conducted ordinary least squares (OLS) regression, and standardized variables before entering into the regressions.

The results demonstrate that AI capabilities have a significant positive impact on export performance. In addition, the influence of AI capabilities on export performance varies depending on the home-country and host-country institutional environment. The relationship between AI capabilities and export performance is strengthened by larger cultural distance, while province market development within a country has a negative moderating effect on this relationship. In less developed markets, the AI capabilities can drive significantly export performance. In developed markets with more advanced institutional development, the significance of AI capabilities in reducing transaction costs diminishes due to established institutions and market structures. AI capabilities serve as an intermediary institutional mechanism that connects the institutional context of the home country with the cultural environment of the host country.

While the impact of AI on international business and internationalization performance is a growing area of study, further exploration of the moderating factors that influence this relationship is needed. Organizations operating in diverse global markets are profoundly shaped by institutional contexts in their operational environments. This research addresses the relatively unexplored role of institutional factors within the home country (provincial market development) and host country (cultural distance) in moderating the effects of AI capabilities on export performance. This study illuminates the intricate dynamics underlying the relationship between AI capabilities and export performance, with a specific focus on province-level market development and cultural distance. Employing institutional theory as the overarching framework, this research sheds light on how AI serves as an intermediary institutional mechanism, bridging the gaps related to cultural differences and varying market development levels. In doing so, it contributes to academia by advancing our understanding of how AI is shaping internationalization dynamics and the interaction between AI capabilities and institutional factors. Additionally, it offers insights for business managers and policymakers to make informed strategic decisions regarding AI capabilities.

This study clarifies the history and significance of cryptocurrencies. It explores the underlying decentralisation and trustlessness concepts that set these digital assets apart from conventional fiat currencies. It clarifies how blockchain technology functions as the core component of decentralised money. The mechanics of mining, its function in creating and validating Bitcoin transactions, and the emergence of substitute consensus mechanisms to solve environmental issues are all covered in this study. An in-depth analysis of blockchain technology covers its advantages, such as immutability and transparency, as well as its architecture and consensus processes. This study continues with a focus on the future by examining the development of decentralised finance (DeFi) and showcasing numerous DeFi applications, including yield farming, lending protocols, and decentralised exchanges (DEXs). As a result of the development of cryptocurrencies and blockchain technology, DeFi has become possible, ushering in a new era of financial independence and inclusivity. This study emphasises the significance of striking a balance between innovation and suitable regulatory measures as the globe embraces this revolution in order to enable the proper integration of DeFi into the global financial environment. The revolutionary potential of DeFi, particularly in increasing financial inclusion and empowerment for marginalised groups globally, is one of the major themes discussed. To negotiate legal frameworks while maintaining DeFi's decentralised nature, this study looks at the regulatory problems that come with this potential.