This study examines the influence of motivational (utilitarian and hedonic) and IS vulnerability factors (user and provider) on guests’ behavioural intentions toward smart hotels. Data were collected from 240 Indian hotel guests through online surveys. The findings revealed that efficiency, perceived control, enjoyment, and customised services significantly improved perceived benefits; user and provider vulnerabilities significantly influenced information privacy concerns. Moreover, perceived benefits positively affected guests’ intentions to stay at smart hotels whereas concerns regarding information privacy negatively affected behavioural intentions, although this impact was not statistically significant. The study delivers insightful information that hotel managers can use to leverage smart technologies to enhance guests’ experiences. Addressing guests’ privacy concerns and enhancing their familiarity with technological innovations, can help maximise their adoption and effective use of these technologies in hospitality settings.
This study examines key determinants of trust in AI-powered advertising, focusing on perceived usefulness, AI familiarity, perceived risk, perceived ease of use, and ad transparency. Grounded in the Technology Acceptance Model (TAM) and Social Exchange Theory (SET), the study proposes a conceptual model, assessing both direct effects on trust and indirect effects via consumer engagement and emotional response. The model was tested, using Structural Equation Modelling (SEM) on data from a diverse sample of digital consumers, allowing simultaneous analysis of direct and mediated relationships. Findings revealed that perceived usefulness, AI familiarity, perceived ease of use, and ad transparency did positively influence trust while perceived risk exercised negative effect. Consumer engagement mediated the relationship between perceived usefulness and trust whereas emotional response mediated the link between ad transparency and trust. The study advances theoretical understanding of trust formation in AI advertising and offers practical insights for marketers, seeking to build trust through transparency and engagement. Future research may extend this framework across varied digital contexts.
Grounded in the transformational and self-determination theory, this study examined crossnational and gender perspectives on leadership styles and self-directed learning (SDL), among university students in Malaysia and Indonesia. As the workforce is becoming more challenging and diverse, future leaders are expected to build on their character and leadership and become more self-driven and self-disciplined. Based on quota sampling, data were collected among 421 students in Malaysia and Indonesia. Inferential analyses were performed to identify any significant differences in the mean scores of different leadership styles and self-directed learning across gender and countries. The findings indicated that Malaysian students scored significantly higher than their Indonesian peers, on both people orientation and transformational leadership. An analysis of gender revealed that the national context did play a more significant role in shaping leadership qualities than gender itself. Comparisons between males and females within the same country showed no significant differences, aligning with past research which suggests that gender gaps in higher education in Asia are less pronounced when leadership opportunities are equally provided. However, Malaysian females did demonstrate a notable advantage over their Indonesian counterparts in transformational leadership. These findings underscore practical implications for higher education leadership programmes in diverse settings.
This article proposes to explore the factors driving India’s increasing need for renewable energy by analyzing financial instruments, investment trends, and governmental initiatives. Through an examination of data from official government records, trustworthy sources, and climate policy initiatives, it assesses India’s renewable energy capacity and carbon emissions. Regression analysis was used to identify the relationships between key factors, including investments, green bond values, and loan disbursements with the expansion of renewable energy efficiency. The findings revealed strong positive correlation between renewable energy investments and capacity expansion. Green bonds did not show significant influence on renewable energy growth. However, annual loans for renewable energy projects are strongly correlated with capacity growth. These findings pave the way for sustained investment, financial support, and policy mechanisms in driving renewable energy efficiency in India. It highlights the crucial role of direct investments and financial support, offering a footing for strategic decision-making and informed policymaking in the renewable energy sector.
In the modern business world, the mobile payment applications have become an integral part of digital payments. This is due to their convenience, speed and accessibility. The present study was carried out to identify the various factors that influence the people to adopt mobile payment applications. The study was based on the conceptual model of Technology Acceptance Model (TAM). The TAM suggests that people would accept a technology, based on factors like “Perceived ease of use” and “Perceived usefulness”. The model also has other variables such as “awareness”, “perceived trust”, “social influence” and “facilitating conditions”. In this study, purposive sampling method was used and data were collected from 380 respondents, using a Google Form. The present study used PLS-SEM for the data analysis. The findings revealed that factors like awareness, perceived ease of use, perceived trust, social influence and perceived usefulness significantly influenced the adoption intention of mobile payment applications. But at the same time, the facilitating conditions did not have significant positive impact on users’ adoption intention.
