Forecasting Tourist Decisions Regarding Zoo Attendance Using Weather and Climate References

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Analytics

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Creator

Perkins, David Richard, IV
- Affiliation: College of Arts and Sciences, Department of Geography

Abstract

Tourism climatology studies relationships among people, business, weather, and climate within the tourism industry. This research tests these interfaces in the southeast United States at the North Carolina Zoo and Zoo Atlanta. Historical weather data are paired with zoo attendance. Weather variables include observed variables of temperature, humidity, cloud cover, and wind speed; derived variables of wind chill and heat index; and biometeorological index variables of Physiologically Equivalent Temperature (PET), Standard Effective Temperature (SET), and Predicted Mean Vote (PMV). Three analyses are used: correlation, multiple regression, and probabilistic. Correlation analysis compares direct relationships between weather variables and attendance. Multiple regression analysis combines standard variables in predictive models. Probabilistic analysis studies seasonal scale climate-attendance relationships. Results indicate weather influences on zoo attendances change by season, social influences, and geography of the zoo. Complex composite weather variables improve attendance predictability as they provide better assessments of how humans sense outdoor environments.

Date of publication