Purpose: AI improves the operational efficiency of hotels while fostering green human resource management. The study explores the effects of AI and green human resource management on low-carbon behavior, employee performance, and overall sustainability performance. Design/methodology/approach: Employing the PLS-SEM model to enhance comprehension of how AI and green human resource management influence low carbon behavior, employee performance, and sustainability performance. An anonymous survey comprising 46 questions was carried out with 1,256 managers from different hotels in Vietnam. Findings: The results demonstrate that AI has a beneficial impact on both employee performance and sustainability performance, with green human resource management and low-carbon behavior serving as mediators in the connection between AI and sustainability performance. Furthermore, AI also plays a positive role in enhancing sustainability performance, where green human resource management and employee performance act as mediators in this relationship. Practical implications: AI fosters GHRM, thereby increasing employee commitment to environmental issues and enhancing sustainable performance in hotels across Vietnam through the use of advanced data management systems. Additionally, the research emphasizes the importance of incorporating AI into employee operations to effectively encourage environmental conservation and sustainable growth within the hospitality industry. Originality/value: This research emphasizes the considerable influence of AI as a catalyst for both green human resource management and sustainability performance. A principal conclusion of the research is that the advantages linked to sustainability performance and employee performance, which stem from AI, are mainly realized through green human resource management practices and low-carbon behaviors.

Purpose: AI and digital innovation (DI) enhance the operational efficiency of hotels while simultaneously fostering green innovation (GI). This dual benefit provides hotels with a competitive edge, enabling them to pursue more sustainable practices that align with the growing emphasis on environmental protection among consumers. This paper seeks to examine the influence of AI and DI on GI, sustainable performance (SP) and competitive advantage (CA). Design/methodology/approach: Employing path modeling through the partial least squares structural equation modeling (PLS-SEM) technique to enhance understanding of the effects of artificial intelligence and digital innovation. An anonymous survey consisting of 34 questions was administered to 668 participants from various hotels in Vietnam. Findings: The findings indicate that artificial intelligence positively influences both DI and GI, with DI serving as a mediator in the connection between AI and GI. Additionally, AI contributes positively to SP and CA, with digital and GI playing mediating roles in this relationship. Practical implications: AI and digital innovation enhance green innovation and sustainability in Vietnamese hotels through smart data and energy management. Furthermore, it underscores the necessity of combining these two forms of innovation to effectively promote environmental protection and sustainable development within the hospitality sector. Originality/value: This research highlights the significant impact of AI as a driving force for both digital and environmental innovation. A key finding of the study is that the advantages related to SP and the competitive edge derived from AI are primarily attained through initiatives in green and DI.

Drawing on the Knowledge-Based View, this study examines the impact of intellectual capital components, including human capital, social capital, and organizational capital, on innovation performance and competitive advantage among SMEs in Vietnam. Using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach, this study focuses on answering two questions: (1) Do the components of intellectual capital significantly influence innovation performance? (2) Does innovation performance mediate the relationship between components of intellectual capital and competitive advantage? Data were collected through a structured survey administered to a sample of 274 respondents from SMEs in Vietnam. The results reveal that all three dimensions of intellectual capital have a direct and statistically significant influence on both innovation performance and competitive advantage, with human capital playing the most critical role in driving these outcomes. Additionally, innovation performance is found to mediate the relationship between human capital, social capital, and competitive advantage. Based on these findings, the study provides relevant discussions and practical implications.

AI plays a pivotal role in facilitating green servant leadership and green human resource management by enabling data-driven decision-making, optimizing resource allocation, and fostering a culture of sustainability. This study investigates the effects of AI and green servant leadership on green human resource management, employee green innovation behaviors, and hotels' environmental performance. PLS-SEM was employed to examine AI's effects on environmental performance and the relationships among green servant leadership, green human resource management, and employee green innovation behaviors. An anonymous questionnaire comprising 35 items was administered to 923 managers and employees from hotels across Vietnam. Findings from the standardized model reveal that AI exerts the most significant influence on green service leadership (β = 0.579). Additionally, AI positively influences green human resource management and employee green innovation behaviors, with green servant leadership acting as a mediator. Furthermore, AI enhances environmental performance through the sequential mediating roles of green servant leadership and employee green innovation behaviors. This study provides valuable insights into integrating AI with green servant leadership to enhance green human resource management, foster employee green innovation behaviors, and improve environmental performance in hotels. This study extends the Resource-Based View (RBV) and Social Learning Theory (SLT) by integrating both perspectives into a unified research framework. The findings provide practical guidance for hotels to optimize resource utilization, promote environmentally sustainable practices, and improve environmental performance, thereby supporting long-term sustainable development.

This study examines how dynamic capabilities and artificial intelligence (AI) capabilities shape innovation, competitive advantage, and business performance (BP) in Vietnamese small and medium-sized enterprises (SMEs). Drawing on the dynamic capabilities view, survey data from 1,512 managers in 301 SMEs were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings show that exploitative capability enhances both innovation capability and competitive advantage, while exploratory capability directly improves competitive advantage but does not significantly affect innovation capability. Innovation capability positively influences BP both directly and indirectly through competitive advantage. AI capability emerges as a key organizational capability: it strongly predicts innovation capability, improves BP, and strengthens the relationship between innovation capability and competitive advantage. The study contributes by distinguishing between exploitation and exploration, positioning AI capability beyond technology adoption, and demonstrating how AI helps SMEs convert innovation into competitive advantage.