Purpose
The paper aims to find the preferences of different tourist type. Since, COVID-19 pandemic has brought the international hospitality industry to a standstill, there are some early signs of recovery. For this industry’s long-term recovery, the tourists’ changing preferences need to be analyzed. Moreover, with different types of tourists, a more nuanced and in-depth study is required to analyze the preferences of each tourist type.
Design/methodology/approach
The research focuses on the changing preferences of the tourist by comparatively analyzing the pre-COVID-19 and current COVID-19 phase. The study extracted online data from TripAdvisor and identified themes by applying Latent Dirichlet Allocation (LDA).
Findings
The study’s findings confirmed the change in preferences of the different types of tourists during the COVID-19 pandemic by performing thematic analysis. New themes emerged in the pandemic phase, providing more insights into tourists’ changing preferences in the current COVID-19 phase. The study also found that specific dominant themes in the pre-COVID-19 phase were replaced by new themes in the current COVID-19 phase.
Originality/value
To the best of the authors’ knowledge, this study is the first to compare the pre-COVID-19 and current COVID-19 phase themes to decipher the new themes that managers of the hotels should consider to win back tourists’ confidence during the pandemic. The unraveling of changing preferences of the different tourist types in the current COVID-19 pandemic is the novel contribution of the study.
The present paper is about the social media analytics. It is a new tool to analyze the behavior of the users who use social networking sites and other social sites like blogs, forums etc. Every organization uses this tool to analyze their customers. Even the government agencies are using these analytical tools to get the feedback of their newly launched missions and their policies. In this paper the sentiment analysis of Swachh Bharat Abhiyan is done with the help of tweets extracted from twitter. Tweets regarding Swachh Bharat Abhiyan are extracted with the help of an open source software R-studio. The geo-locations of tweets are also extracted in the software and the results are plotted on the map of India. The pattern of tweets are analyzed and the popularity of the mission is evaluated. The word cloud of the popular and the most used words is also formed in the R-studio software. With the overall analysis, the popularity of the mission is perceived according to the regions on the map of India, and the strategies can be applied to popularize the campaign in the lesser known regions of India.
There is a decline in revenue and occupancy rates in the hotels during the pandemic. For the sustainable and long-term recovery of the hotel industry, the guests need to be analyzed for their stay preferences. This study attempts to find the preferred attributes of the travelers visiting the Indian luxury hotels during the COVID-19 pandemic. The research investigated the post-visit experiences from the online reviews published by tourists on TripAdvisor.com. Thematic salience valence analysis and lexical salience valence analysis was used to identify the vital attributes of the hotel industry. The study revealed staff, location, food, hygiene, and rooms as the preferred hotel attributes, in which the coastal locations were highly considered for location based marketing of luxury hotels, and non-compliance of COVID-19 standards and complaints for upgradations in the rooms were the non-recommenders for the luxury hotels. The dashboard-based salience valence zone analysis was used to provide suggestions to the hotel authorities by revealing the significant and critical hotel attributes simultaneously for prompt handling of the issues during the COVID-19 pandemic.
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