Author Date

2021-06-18

Degree Name

BA

Department

Political Science

College

Family, Home, and Social Sciences

Defense Date

2021-06-08

Publication Date

2021-06-18

First Faculty Advisor

Dr. Dan Nielson

First Faculty Reader

Dr. Jay Goodliffe

Second Faculty Reader

Dr. Scott Sanders

Honors Coordinator

Dr. Ethan Busby

Keywords

tourism, politics, travel, corruption, regime type, political violence

Abstract

Hard currency earned from travel and tourism feeds an important share of currency reserves in many countries and is often a key source of income, but how do political factors influence travelers’ decisions to visit and spend money in destination countries? In this paper, I argue that political factors such as regime type, political violence, and corruption can override traditional tourism attractors in determining potential visitors’ professed likelihood of traveling to hypothetical vacation destinations. In addition, I expect that political factors will hold less weight in determining self-reported likelihood of traveling when proper nouns are used to describe country profiles instead of hypothetical profiles. In a conjoint design, participants sampled from Amazon’s Mechanical Turk are randomly exposed to details for hypothetical countries and for actual destinations revealing actual country names. The vignettes that contain the actual country names will randomly reveal actual countries’ political features compared to controls in which political and governance features are omitted. The conjoint design also randomly exposes participants to additional factors such as geographic location, attractiveness of the tourist destination, crime rates, disease prevalence, and COVID-19 health risks. Participants are asked a series of outcome questions measuring their willingness to travel to the country, the perceived safety of the country, and how much money they would be willing to spend to vacation at the chosen destination. Population marginal means are estimated for the conjoint design based on a basket of high-tourism countries’ attributes. I find that corruption is a stronger predictor of travel propensity than nearly any other attribute in the conjoint profile and that political factors produce some of the strongest effects compared to other country features. I also find that in both Thailand’s and Egypt’s vignette profiles, the presence of political factors decreases interest in travel, perceived level of safety, and how much money respondents would be willing to spend to vacation at the chosen destination.

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