Research Resource Repository
- Tool
Tourist Experience Simulation Tool
Tourist Experience Simulation Tool is a Web-GIS system designed to help tourism practitioners monitor and simulate tourist experiences under varying environmental conditions. This tool allows users to input specific scenarios defined by air pollution levels (specifically PM2.5), weather conditions (temperature, sun, wind, and precipitation), and date types (e.g., weekends or holidays). Utilizing a predictive algorithm derived from the sentiment analysis of geotagged social media posts, the system calculates “experience scores” to visualize the spatial distribution of tourist satisfaction across the city. This platform enables stakeholders to conduct scenario analyses, such as predicting experience fluctuations during heavy pollution events, and offers features for benchmarking specific locations and recommending itineraries that mitigate the negative impacts of poor air quality
- Dataset
Restaurant Resilience Index
The Restaurant Resilience Index was developed to characterize the regional restaurant industry’s resilience to the COVID-19 pandemic across U.S. counties. Estimated from econometric results regarding daily restaurant demand, this index incorporates key moderating variables—specifically ethnicity, political ideology, dining habits (eat-in vs. off-premise), and restaurant diversity—that were found to influence the magnitude of demand decline caused by the pandemic and stay-at-home orders. By visualizing these data, potentially through tools like an ArcGIS dashboard, the index enables government entities and stakeholders to pinpoint geographically vulnerable areas and effectively allocate support resources, such as consumer voucher programs, to the hardest-hit local businesses.
Link to the Restaurant Resilience Index dashboard.
- Tool
Hotel Location Selection and Analysis Tool (HoLSAT)
Hotel Location Selection and Analysis Tool (HoLSAT) is a WebGIS-based spatial decision support system and simulation toolkit designed for hotel location assessment. In your study of Beijing hotels, we programmed a simulation toolkit that allows hotel investors to assess various determinants and calculate the probability of a hotel locating in a specific potential site based on estimated model coefficients. Furthermore, in our research on Los Angeles, you developed a location evaluation tool that utilizes a “fishnet” grid system to predict and simulate location preference scores for any site within the research area. This tool allows stakeholders to conduct scenario analyses, evaluating how different traveler portfolios or changes in location factors (such as new metro lines) would influence guest satisfaction with a hotel’s location. Additionally, our work on Hong Kong hotel preferences advocates for a Web-GIS platform that uses willingness-to-pay (WTP) estimates to demonstrate promising location sites for new market entrants
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