Search results

The study aims to identify the status quo of artificial intelligence in entrepreneurship education with a view to identifying potential research gaps, especially in the adoption of certain intelligent technologies and pedagogical designs applied in this domain.

A scoping review was conducted using six inclusive and exclusive criteria agreed upon by the author team. The collected studies, which focused on the adoption of AI in entrepreneurship education, were analysed by the team with regards to various aspects including the definition of intelligent technology, research question, educational purpose, research method, sample size, research quality and publication. The results of this analysis were presented in tables and figures.

Educators introduced big data and algorithms of machine learning in entrepreneurship education. Big data analytics use multimodal data to improve the effectiveness of entrepreneurship education and spot entrepreneurial opportunities. Entrepreneurial analytics analysis entrepreneurial projects with low costs and high effectiveness. Machine learning releases educators’ burdens and improves the accuracy of the assessment. However, AI in entrepreneurship education needs more sophisticated pedagogical designs in diagnosis, prediction, intervention, prevention and recommendation, combined with specific entrepreneurial learning content and entrepreneurial procedure, obeying entrepreneurial pedagogy.

This study holds significant implications as it can shift the focus of entrepreneurs and educators towards the educational potential of artificial intelligence, prompting them to consider the ways in which it can be used effectively. By providing valuable insights, the study can stimulate further research and exploration, potentially opening up new avenues for the application of artificial intelligence in entrepreneurship education.

This paper aims to examine the extent to which these reforms address the limitations of Saudi Arabia’s previous investment framework. Long viewed as a hostile environment in which to do business, the Saudi Government has enacted a broad sweep of measures aimed at restoring investor confidence in central aspects of the country’s evolving private law framework.

This paper offers a timely assessment of the raft of foreign investment reforms, both legislative and regulatory, that have been introduced in Saudi Arabia over the last decade.

The paper will proceed by outlining the perceived failings of the old investment regime before going on to reforms.

It will consider the remaining obstacles to the flow of foreign investment in Saudi Arabia in the context of the dual forces that have historically defined the Kingdom’s ambivalent investment law regime.

Most research on sustainable tourism has been devoted to understanding the determinants of tourists' sustainable behavior on a unidimensional construct, overlooking the importance of behavioral costs in sustainable travel behavior. To shed light on this issue, this study aims to quantitatively differentiate sustainable travel behaviors based on behavioral costs and to examine the impact of psychological factors on both low-cost and high-cost sustainable travel behaviors.

A survey of 470 tourists used Rasch analysis to measure the behavioral costs associated with sustainable travel behavior and partial least squares structural equation modeling (PLS-SEM) to test hypotheses.

The results indicate that the value-identity-personal norm model explains more variance in low-cost sustainable travel behaviors than in high-cost sustainable travel behaviors. This supports the central tenet of the low-cost hypothesis and also suggests that values and self-identity factors have a stronger influence on low-cost sustainable travel behavior. However, personal norms have a stronger influence on high-cost behaviors.

This research highlights the importance for tourism and destination managers to distinguish between different categories of sustainable travel behavior and to analyze their determinants separately. This allows for the development of tailored messages for specific groups of tourists based on the psychological drivers of sustainable travel behavior.

This study provides insights into the determinants of sustainable travel behaviors with different behavioral costs and highlights the importance of analyzing different categories of behaviors separately.