The tourism industry plays a vital role in global economic growth, employment, and poverty reduction. However, the COVID-19 pandemic severely impacted this industry due to lockdowns, border closures, and social distancing measures. While some regions show optimism for tourism recovery, uncertainties persist due to economic slowdown and geopolitical tensions. China, with its extensive quarantine measures, faced particular challenges. Recovering the tourism sector requires significant efforts from both the industry and governments. Governments worldwide employed various fiscal and monetary policies, including traveler subsidies and financial support to tourism companies, to stimulate demand. In China, domestic tourism revenue dropped substantially in 2020, highlighting the urgent need for government support. Digital travel vouchers emerged as an innovative approach to incentivize travel and boost private consumption, leveraging China's ubiquitous smartphone-based digital transactions. This paper investigates the extent to which these vouchers contributed to the recovery of domestic tourism in China, utilizing data-mining technology to analyze passenger flows across 306 cities over 16 months. The study also explores regional spillover effects, considering the localized nature of pandemic policies and the potential for shorter-distance travel post-pandemic. The contributions of this paper include the creation of a unique dataset using web-crawling, the examination of the effectiveness of digital travel vouchers considering their characteristics, and the investigation of regional spillover effects using a spatial regression model. This research offers valuable insights for policymakers on effectively utilizing digital platforms for policy implementation and provides valuable evidence for other nations navigating similar challenges in a rapidly evolving digital economy.

The tourism market can be analyzed using classical economic theory, examining demand and supply. Government intervention is crucial during market turmoil, as seen during the pandemic. The COVID-19 pandemic caused an unprecedented crisis in the tourism industry, necessitating robust policy support. Strategies to combat the crisis involve managing the crisis, stimulating recovery, and making ex-ante preparations. On the demand side, the downturn stems from economic consequences and risk perceptions, with heightened health risks contributing to reduced demand. The Theory of Planned Behavior (TPB) model highlights the role of perception in influencing travel intentions. Government-issued vouchers, historically used to stimulate consumer spending, have generally shown positive results, particularly for low-income groups. Research on travel vouchers indicates their potential to stimulate demand. However, the effectiveness varies depending on design and characteristics. Unlike previous studies on paper vouchers, this paper focuses on the digital vouchers issued in the post-COVID era in China. The rapid development of digitalization in China has changed the travel and tourism landscape, making digital travel vouchers more attractive due to their ease of use and information advantages. Existing research on government digital vouchers post-COVID-19 mainly evaluates their effectiveness within individual cities. This study addresses the gap by examining the spatial spillover effects of these vouchers, considering regional imbalances in tourism destinations and infrastructure, the tendency for shorter-distance travel post-pandemic, and the localization trend in the tourism sector. Digital vouchers' characteristics transcend administrative geographical boundaries, potentially generating spatial spillovers.

This study uses a web-crawling tool to gather daily tourist inflow data from the Baidu Migration website, which is linked to Baidu Map, a leading navigation service provider in China. Monthly data from September 2020 to December 2021 for 306 cities were collected, yielding over 1.4 million data points. The Baidu Migration index, while an index rather than a precise measure, provides a reliable proxy for passenger flows, facilitating dynamic examination and comparisons across cities. Information on digital travel vouchers was manually collected from official and third-party websites using Baidu search engine. A total of 171 issuances were identified, providing information on volume, time frames, and issuing platforms. Control variables included city-level characteristics like population, GDP, public facilities, fixed-asset investment, environmental sanitation, high-speed railway lines, and the number of confirmed COVID-19 cases. The study employed a Poisson Pseudo-maximum Likelihood (PPML) model to address heteroscedasticity and zero flows in the analysis of the impact of digital travel vouchers on tourist inflows. A staggered difference-in-differences (DID) model examined the effects of issuing digital travel vouchers, comparing cities that issued vouchers to those that did not. An extended model incorporated interaction terms to analyze the influence of issuing platforms (larger platforms vs. WeChat Mini Apps), issuing frequency, and internet penetration. Finally, a spatial Durbin Model with a geographical adjacency matrix and a nested weight matrix (combining geographical distance and GDP per capita difference) was used to explore the spatial spillover effects of digital travel vouchers.

Descriptive statistics show that cities issuing digital travel vouchers had higher average tourist inflows and higher average annual GDP, suggesting that economically advantaged areas were more likely to implement such policies. The correlation matrix revealed high correlations between issuance value, publicity, and availability. The baseline PPML and DID models showed that issuing digital travel vouchers significantly increased tourist inflows. The extended model revealed that using larger platforms, increased frequency of issuance (though potentially diminishing returns with value), and higher internet penetration enhanced the effectiveness of vouchers. The heterogeneity analysis showed that well-known tourist cities saw amplified effects of voucher campaigns, and wider digital finance coverage significantly increased tourist inflows. While the depth of digital finance usage did not have a direct effect, the interaction with voucher value was positive and significant. Moran's I test confirmed significant spatial autocorrelation in tourist inflows. The spatial Durbin Model, using both geographical adjacency and nested weight matrices, confirmed significant spatial spillover effects: the issuance of vouchers in one city positively affected tourist inflows in neighboring cities. Robustness checks, including using publicity and availability as alternative measures, parallel trend and placebo tests, matched DID, CSDID, and IV-2SLS and IV-GMM regressions, consistently supported the positive impact of digital travel vouchers. The parallel trend test showed no significant difference in tourist inflows between treatment and control groups before voucher issuance, but significant differences afterward. The placebo test confirmed that the observed effects were not due to chance.

The findings strongly support the hypothesis that digital travel vouchers can effectively stimulate domestic tourism in China during the pandemic recovery. The results align with the Theory of Planned Behavior (TPB), suggesting that vouchers influence tourists' behavioral intentions and actual travel decisions. The characteristics of the vouchers, especially the platform used and issuance frequency, significantly impact their effectiveness. The spatial spillover effect highlights the interconnectedness of regional tourism economies and the importance of coordinated policy interventions. The findings contribute to the existing literature by providing quantitative evidence on the effectiveness of digital travel vouchers and their spatial spillover effects, enriching the understanding of tourism stimulus policies in the context of digital transformation and the post-pandemic recovery.

This study demonstrates the significant positive impact of digital travel vouchers on boosting domestic tourism in China during the COVID-19 pandemic recovery. The findings highlight the importance of considering the platform choice, issuance frequency, and digital inclusiveness when designing voucher programs. The significant spatial spillover effect emphasizes the need for regional coordination in policy design. Future research could explore alternative data sources to refine the analysis, investigate the specific mechanisms behind the observed effects, and compare the effectiveness of digital travel vouchers across different countries and contexts. Furthermore, research exploring the long-term impacts of these policies on tourism sustainability and regional development would be beneficial.

This study uses travel inflows as a proxy for tourist inflows, potentially introducing bias. While robustness checks were performed, future research could employ alternative data sources for improved accuracy. The study lacks precise information on voucher utilization due to data privacy regulations, limiting the analysis of operational efficacy. The study’s scope is limited to China, and cross-country comparisons could enrich the findings. The characterization of city features could also be further developed.