Restaurants have been one of the most negatively affected by the COVID-19 global pandemic. Governments and many restaurant-goers considered dining out as a non-essential activity (Dube et al., 2020). The pandemic has consequently forced both the restaurants and the customers to alter their service process and dining habits. On the restaurant side, increasing proximity between diners and other tables have been recommended/enforced (Kim et al., 2020). Also, diners have been made aware of the different preventive measures to help protect themselves from potentially contracting COVID-19 when dining at a restaurant (Hu et al., 2021). In protecting customers and their business, restaurants need to provide an environment where diners feel safe. That is, diners' preferences toward health safety measures at restaurants should be explored. In assessing preferences, this project designed a series of choice experiments. including discrete choice experiment, as well as best-worst scaling experiments. Attributes associated with health safety measures included seating area, proximity of tables, staff protective equipment, preventive measures, staff-guest interaction, payment methods, and meal price. The data was collected among U.S. restaurant-goers online using a survey-based stated choice experiment design (Rose & Bliemer, 2009). Data analysis utilized discrete choice modeling methods.
Data was collected from 665 respondents, and results indicate that the defined safety measures significantly influence choices. Specifically, the study samples prefer seating area situated outdoor than indoor and an increased distance from another group of diners. Further, restaurant staffs wearing protective equipment (e.g., masks, protective gear) is preferred relative to serving restaurant customers without any protective equipment. Customers further prefer temperature check and sanitization of dining areas compared to no preventive measures in restaurants. Diners also reported a preference toward self-service technology as means of interaction between staff and guests, as well as mobile payment as opposed to cash. Result of this research indicate that the implementation of health safety measures in restaurants may provide diners with a safety environment, and therefore generate demand. Thus, in generating demand for restaurants, food and beverage establishments should consider implementing health safety measures.

The novel coronavirus-19 pandemic, also known as the COVID-19 pandemic, has continued to affect the global economy in consequential ways as the effects of the virus continue to put companies and industries at risk. The service sector is being faced with unique difficulties caused by severe demand shortages fueled by lost income and uncertainty about the future, particularly for the hospitality and tourism industries due to less traveling (Boone et al., 2020, pp. 39-40). Due to the sudden demand-side shortages, it is especially important for managers to understand the perspectives of those customers in order to best adapt to the changing environment in the hospitality industry.
This empirical study extracts the latent topics from a large training set of tens of thousands of online reviews that were scraped from Agoda.com regarding accommodations in South Korea. In order to analyze qualitative information from text at scale, text mining techniques can be utilized, specifically topic models. Latent Dirichlet allocation (LDA) was first proposed by Blei et al. (2003) as a stochastic, hierarchical Bayesian topic model that learns the latent topics in a corpora of text and assigns probabilities to documents (e.g., reviews) based on the probabilities that those documents contain the topics. LDA has been used by several studies to analyze online reviews of accommodations in order to gain insight into customer experience and decision making processes (Guo et al., 2017; Sutherland et al., 2020; Sutherland and Kiatkawsin, 2020; Zhang, 2019a, 2019b). This study also utilizes latent Dirichlet allocation to evaluate customers eWOM over time.
Using latent Dirichlet allocation, the extracted topics are utilized to evaluate a testing subset of data ranging from pre-COVID-19 to post-COVID-19 reviews. Changes in the importance of topics are detected and analyzed to establish how the COVID-19 pandemic has impact on the topics of discussion in customer online reviews in a Topics Over Time (ToT) approach. The results show that there is a statistically significant increase in the online reviews regarding comments about some accommodation characteristics (e.g., quality of facilities) while there is a significant decrease in other areas of interest.

Recently, urban tourism-oriented travel has become a trend After becoming FIT(Foreign Independent Tour), tourists mainly used smartphones to feel the convenience, and tourists made decisions and interacted through information collection using smart tourism technology. However, the recent 2019 COVID-19 pandemic has caused an unprecedented socio-economic upheaval in societies around the world In Korea, as the COVID-19 pandemic has spread since January 2020, all corona 19 has affected many aspects of society and affects all individuals (Bae & Chang, 2020). Accordingly, the demand for untact tourism has also increased in the tourism field, and the trend is changing.
Even at the COVID-19 pandemic, people started untact travel rather than face-to-face travel to minimize the risk of COVID-19 and quench their thirst for travel (Bae & Chang, 2020). COVID-19 has created a threat to tourists' freedom to choose tourist destinations. Accordingly, visitors who have visited smart tourist cities using smart tourism technology in the past are no longer able to travel due to COVID-19 and are solving their desire to travel through untact tourism using social media Now, as untact tourism has become established due to the threat of COVID-19 risk perception, tourists will inevitably feel somewhat uncomfortable. Therefore, how the COVID-19 pandemic affects the change in choosing a smart tourist city has become significant and a problem that needs to be considered In addition, a large number of studies have been conducted on smart tourism technology (e.g., Chung et al., 2015; Huang, et al., 2017; Jeong & Shin, 2019; Lee et al., 2018; Pai et al., 2020). However, there is not yet a sufficient number of studies on COVID-19 and smart tourism technology together. Accordingly, this study is expected to be appropriate and timely to the current situation.
Therefore, the research model of this study is as follows. Accordingly, first of all, this study attempts to examine whether tourists' perceptions of smart tourism technology and social media before and after COVID-19 outbreak continue to influence the intention to revisit smart tourist cities. Second, this study aims to investigate whether the perception of risk for COVID-19 threatens tourists' freedom of choice, affecting the intention to revisit smart tourist cities. In addition, this study intends to propose an MGB(Model of Goal-directed Behavior) model as the overall framework of this study by integrating the perception of the threat of freedom of choice according to the perception of COVID-19 risk in the process of forming the intention of visitors to smart tourist cities.