A Case Study of Tourism in North Carolina State Parks Using Google Trends

A Case Study of Tourism in North Carolina State Parks Using Google Trends

Aaron Bradley Scott
DOI: 10.4018/IJTHMDA.298703
Article PDF Download
Open access articles are freely available for download

Abstract

The purpose of this study is to examine available innovative technologies as a means to forecast visitors to the North Carolina State Park system. The research will use Google Trends as the innovative technology and using the data from Google search queries to measure relationship from searches to visitors. This examination will include literature review and data collection methods. Furthermore, the quantitative measures will include the Pearson Correlation Coefficient (Pearson) and Time-Series Linear Modeling (TSLM), which accounts for seasonal and trending values. The data from the state parks were provided by the Public Information Office of the North Carolina Division of Parks and Recreation. Additionally, the search query data was collected from Google Trends. Two locations within the Appalachian Mountains of western North Carolina were selected due to the exclusivity of the locations and to capture visit behavior in search queries. Those locations are Mount Mitchell State Park and Grandfather Mountain State Park.
Article Preview
Top

Introduction

Tourism is a service-focused industry that spurs economic activity. The industry is found to be reflective of economic growth (Tisdell, 2013). In 2018, tourism represented 7.8 million jobs in the American workforce and carried 2.8% of the country’s GDP (Franks & Osborne, 2019). The U.S. Bureau of Economic Analysis (2020) released the 2019 figures indicating higher growth for industries with real GDP recorded at 2.1%. Tourism carries wide-ranging subsectors with varying impact, bringing together cultures within developing or developed regions or countries (Uysal et al., 2016; Kozak & Kozak, 2015). While the calendar year of 2020 will be producing economic numbers marred by the coronavirus global pandemic, it is becoming clear that consumer behavior is changing how travel occurs (Uğur & Akbiyik, 2020).

Tourism, as an industry, relies on other consumption-based industries like transportation, accommodation, food and beverage, recreation, and more (Karuaihe et al., 2015). Both domestic and international tourism were brought into the forefront of economic academics due to the increased per capita income and reduction of transportation costs in western economics after WWII (Polo & Valle, 2015). The act of a consumer engaging in a travel and tourism activity impacts other industries either beneficially or negatively. Generally, positive impacts are discussed around growth activities to the local, state, and national economy. On the other hand, the negative impacts which are discussed among academics and stakeholders are income inequality (Assadzadeh & Yalghouzaghaj, 2015), over-dependency (Rezapouraghdam et al., 2018), carbon emissions (Akadiri et al., 2018) and more.

For the local economy to flourish as a tourist destination, it needs to create an environment for optimally efficient cooperation from politicians, business leaders, and community (Niҭӑ, 2014). Tourism has historically proven the adaptations of the industry and relevancy are possible in local economics (Rodriguez et al., 2020). An economic impact study at one of North Carolina’s state parks, Hanging Rock State Park, concluded visitors contributed $26.65 per person to the local economy (Bergstrom et al., 1990). While the economic impact relevancy thirty years later would not hold the same monetary value to local business leaders, it still provides research in how tourism assists and impacts other local industries within the economy. Economic impact studies are a vital tool for assisting the local business leaders in understanding what tourist find the most relevant within their visits and can assist in bettering those segments within their jurisdiction.

Google Trends is a platform that allows researchers across many fields to understand the popularity of search query topics, over time (West, 2020). The platform is accessible to the general public via the online web. Google records samples of search query data from users to measure on a normalized scale in a particular city, state, region, or country (Padhi & Pati, 2017). Google Trends (2020) measures the search volume on a scale from 0 to 100 and sets the highest volume at 100. Due to time being an infinite measure, Google Trends peak scale of 100 will be adjusted to the newest maximum peak and all other data will be adjusted per the scale (Google Trends, 2020). Both state park examples have recorded new peaks during the 2020 global coronavirus pandemic.

Complete Article List

Search this Journal:
Reset
Volume 7: 1 Issue (2024): Forthcoming, Available for Pre-Order
Volume 6: 1 Issue (2022)
Volume 5: 2 Issues (2021)
Volume 4: 2 Issues (2020)
Volume 3: 2 Issues (2019)
Volume 2: 2 Issues (2018)
Volume 1: 2 Issues (2017)
View Complete Journal Contents Listing