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This study aims to assess the effects of risk perception and management subject satisfaction on consumers' online meal food safety self-protection behavior during the COVID-19 pandemic.

This study uses 742 questionnaires collected via a two-stage online survey conducted during the COVID-19 pandemic, between December 2021 and January 2022. The entropy method, descriptive statistics, ordered logit model, stepwise regression models, interaction terms and decentralization method were used in the quantitative analysis. Respondents’ written responses to self-protection behavior were categorized into five groups.

Less than half of consumers were aware that online food products carry the risk of SARS-COV-2 (44.48%). Between 30 and 40% of consumers took insufficient or no self-protection measures. Risk perception significantly and positively affected self-protection behavior during the COVID-19 pandemic. Consumers' management subject satisfaction has a positive moderating effect on risk perception, with the moderating effect of the satisfaction of online retailers being significant at the 5% level. Risk perception significantly and positively influences consumer self-protection behavior in provinces not affected by the pandemic.

The findings stress the benefits of synergistic interventions by consumers and management subject to food safety measures and the inclusion of tailored interventions during events threatening public health to effectively address food safety. The study offers valuable insights contributing to the improvement of public health outcomes, customer trust and service quality within the online food delivery industry.

The emergence of cryptocurrency has developed a new payment system that is changing how financial transactions happen in hospitality. Consumers/travelers have started experimenting with cryptocurrency payments in hotels and restaurants. However, extant research is lacking in understanding the consumer adoption intention of cryptocurrency payments. This study investigates the intention to use cryptocurrency payments in the hospitality industry.

The conceptual model in this study is based on the Behavioral Reasoning Theory, and it explores the motivating and deterring factors influencing the adoption of cryptocurrency payments in the hospitality industry. A quantitative survey was conducted among 1,080 consumers to examine and confirm the model, with data being analyzed through the Partial Least Squares Structural Equation Modeling (PLS-SEM) method.

The outcome of this work showed that the “reasons for” positively influence and “reasons against” negatively influence consumers’ attitudes and use intentions. Consumers’ values of openness to change positively influence the “reasons for” and do not influence the “reasons against” and attitude toward the use of cryptocurrency payments.

This work contributes to practice by providing insights to customers (users/payee), hospitality managers (investors) and organizations/firms (receiving crypto payments) as well as to financial firms and the government.

This research contributes to cryptocurrency payment adoption and behavioral finance literature. The research uniquely provides the adoption and inhibiting factors for cryptocurrency payment in an integrated framework in the hospitality sector.

User-generated content was explored to understand the public discourse surrounding the Vessel, a star architecture in New York. Through text analytics, the study aims to uncover topics, sentiments and themes in public opinion regarding this controversial building from social media data.

This study utilized a big data and text analytics approach, employing topic modeling with the BERTopic technique, sentiment analysis with roBERTa and thematic analysis on 10,259 Reddit comments pertaining to the Vessel.

The comments were grouped into 20 topics and seven themes, shedding light on discussions regarding the Vessel’s philosophy of existence, critiques of the architect’s approach, evaluations of project success or failure and considerations of the project’s future. Negative sentiments dominate the discourse, reflecting widespread criticism and skepticism towards the project.

The manual data collection method, due to API restrictions, precluded tracking evolving trends over time. Nevertheless, the study provides insights for architects, urban planners, policymakers and stakeholders involved in public space design and management, highlighting the importance of considering user feedback from social media platforms.

This study enriches our comprehension of how users perceive star architecture in the age of social media, focusing on hidden layers of discourse surrounding a controversial iconic building. By combining topic modeling and sentiment analysis, the study offers a novel approach to analyzing architectural public debates on social media platforms like Reddit.