Date of Award
Summer 2025
Document Type
Dissertation
Degree Name
Doctor of Business Administration (DBA)
Committee Chair
Anthony Negbenebor
Abstract
Google Trends is a publicly available aggregate search data portal that allows researchers to capture and review search interests. This dissertation analyzes real-time behavioral shifts resulting from tourism policy changes in Venice, Italy using Google Trends data. This work contributes to the current literature in DiD modeling, by using information-seeking behavior that is ahead of observable, lagged, outcomes. Through the integration of recent DiD advancements, this work further extends DiD applications in tourism econometrics, and a case-example of real-world tourism policy assessment. This dissertation highlights changes in search behavior immediately following policy implementation. Additionally, this work highlights Google Trends as an effective tool for real-time evaluation on policy impacts. Furthermore, this dissertation concludes that advanced DiD modeling provided greater opportunities to explore the data for economic implications than canonical DiD approaches used in contemporary policy analysis.
Recommended Citation
Scott, Aaron Bradley, "Analyzing Real-time Behavioral Shifts in Response to Tourism Policy Using Google Trends Data and Advanced Difference-in-Differences (DiD) Methods" (2025). Doctor of Business Administration Dissertations. 12.
https://digitalcommons.gardner-webb.edu/business-dissertations/12
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License