Big Data for Big Insights: Quantifying the Adverse Effect of Air Pollution on the Tourism Industry in China

Abstract

Adverse meteorological conditions and air pollution resulting from human activities, such as extreme weather and smog, adversely affect the global tourism industry. However, such impacts are difficult to quantify. This study strives to quantify the adverse impact of air pollution on foreign tourists’ revisiting behaviors to China by analyzing large numbers of TripAdvisor reviews. The study first identifies travelers affected by air pollution through analyzing their reviews. It then employs propensity score matching technique to detect a matching group of travelers with identical characteristics who did not report air-pollution-related issues in reviews. By estimating their respective likelihoods of revisiting, our results indicate that travelers who encountered air pollution during their trips are 92.857% less likely to revisit a specific city and 93.421% less likely to revisit China. Our study enriches the tourism literature by quantifying the adverse impact of air pollution on a country’s inbound tourism using big data.

Air Pollution and Its Potential Consequences for Tourism and Career Development from Students’ Perspective: A Case Study of the Gdańsk Agglomeration in Poland

“…Understandably, tourists can also feel the negative effects of breathing polluted air, and because tourist trips are rarely mandatory (except for business trips), people who are aware of this may consider the condition of air quality as one of the factors determining attractiveness of a particular destination influencing their final decision to choose it as a place of potential visit [17]. Therefore, air pollution emerges as a vital problem in the tourism industry [13,15,18,19,[43][44][45][46][47][48][49][50][51][52][53][54][55][56], decreasing the quality of tourist experience, which is fatal to the development of tourism destinations in the long run [16]. It is underlined that countries and cities with poor air quality may lose their attractiveness, and consequently, tourists who fear for their own health may start to avoid them [15].…”

A typology of quantitative approaches to discovery in tourism and hospitality research

“…To avoid relying on self-report measures, researchers can use proxy measures (abbreviated as "P"). Proxy measures are depicted in the second row of the typology in Figure 1; they can be used to indirectly measure latent variables (e.g., emotions inferred from skin conductance and facial electromyography data; Li et al, 2018) or actual behaviours (e.g., revisit behaviour inferred from online reviews; Fan et al, 2022). A rich array of psychophysiological measures such as eye tracking or skin conductance can function as proxy measures, and they are increasingly being used to push the boundaries of discovery (e.g., Li et al, 2018.…”

Big Data in China Tourism Research: A Systematic Review of Publications from English Journals

“…Thus, these reviews are valid cues of visitors' experiences in numerous settings, including restaurants (Jia, 2020), hotels (Luo et al, 2021;Ying et al, 2020), and destinations (Li, Tung, et al, 2017). Most studies have sought to discover factors that shape the tourist experience, including attributes related to climate (Liu et al, 2021), the environment (Fan et al, 2021;Zhang, Yang, et al, 2020), racial discrimination , tourists' cultural backgrounds (Jia, 2020;Schuckert et al, 2015;Ying et al, 2020), hotels (Liu et al, 2017;Luo et al, 2021), and destination attributes (Li, Tung, et al, 2017). For example, Ying et al (2020) explored Chinese tourists' preferred characteristics and desired services for accommodation based on review data from Ctrip.com and TripAdvisor for hotels in six major tourist cities.…”