Economic globalization, the primary mechanism of globalization, has driven the flourishing of international tourism. However, little research has empirically revealed how it affects international tourism from a structural perspective. Based on network theory, this study applies network analysis and fixed-effects panel data estimation techniques to examine the impact of economic globalization on the structure of international tourism and the moderating role of uncertainty avoidance as an inertia factor in this relationship. The statistics are derived from panel data for 47 countries from 1995 to 2018. The empirical results indicate that there is a positive relationship between economic globalization and countries’ network prominence in both outbound and inbound tourism, and the effects vary under different degrees of uncertainty avoidance. This study offers insights and practical implications for policymakers, tourism marketers, and transnational tourism corporations to formulate tourism recovery strategies against the de-globalization caused by the COVID-19 pandemic.

This study investigates how voice characteristics (i.e., speech rate, loudness, pitch) affect interpretation purchases in digital interpretation platforms through the lenses of signaling theory and nonverbal communication. Based on auditory and transactional data from a leading digital interpretation platform in China, this study uses voice mining techniques to extract voice characteristics and examine their effects on interpretation purchases. Findings demonstrate the significant positive effects of speech rate and the significant inverted U-effects of loudness and pitch on interpretation purchases. This study thus extends tourism interpretation research focused on traditional forms to digital interpretation platforms and provides empirical evidence that nonverbal signals (voice characteristics) matter in tourism interpretation purchases. Findings also offer practical implications for tourism interpretation innovation and platform operation.