In a globalized environment, a major shock or event can reverberate across tourism interdependent countries over time. This paper aims to empirically examine how economic policy uncertainty (EPU) emanating from a large country may influence inbound and outbound tourism in other countries. Using Global Vector Autoregressive (GVAR) model and two alternative measures of EPU, the study finds the modeled effects of EPU are dependent on the source of EPU measures, level of internationalization, and type of trade-weights used. Notably, the results show the “decline-rebound-overshoot” effect of EPU shock on tourism demand, and capture the link between capital flight and outbound travel from China in times of surge in EPU. This research highlights that GVAR is able to capture previously unobserved empirical insights because assessing the international impact of shocks such as economic crises, pandemics, and political instability necessitates accounting for cross-sectional interdependence in tourism flows between many countries.

This research aims to quantify the effect of air transport capacity on tourism demand by examining their long-term (cointegrating) relationship, accounting for cross-sectional dependence and endogeneity. Panel time series data from 2008Q1 to 2019Q4 for international tourist arrivals from 16 main origins to six Australian states are investigated. The study finds 1% increase in Available-Seat-Kilometers, seat capacity, or flight frequency can result in 0.4%–0.7% increase in tourist arrivals to Australia, adding to the body of evidence that shows a non-negligible aviation-led generative effect on tourism demand. The study finds ignoring cross-sectional dependence can result in significantly different, and potentially incorrect, coefficient estimates. Although using pre-COVID data, the results are useful in highlighting the likely aviation supply—tourism demand relations under reasonably well-performing market conditions. For greater tourism demand, findings call for more liberal international air services agreements, and direct/indirect air route development subsidies with minimum commitment of several years.

The increasing availability and affordability of RPA have led to a rapid expansion in their commercial demand. However, this growth has raised concerns due to rising RPA-involved safety incidents, which could negatively impact public acceptance. To address these concerns, this study empirically examines the factors influencing public acceptance of RPA operations. A survey was conducted to collect data on public acceptance across RPA operations within a popular hotspot—Sydney Harbour, Australia. Results reveal varied levels of public acceptance, with environmental monitoring receiving the highest support, followed by commercial filming. Several factors, including self-identified gender, previous RPA experience, and risk–benefit perceptions, significantly influence RPA acceptance. Trust in the RPA pilot is the strongest predictor of acceptance, while privacy risk is significantly more important than mid-air collision and ground impact safety risk. This study adds value by including all three risk types and factors identified in the literature within a single model, providing a statistically robust insight into the factors influencing public acceptance of RPA operations.